Challenging the Culture of Stress: Evaluating a Brief, Theory-Driven Mental Health Help-Seeking Intervention for Undergraduate Engineering Students

Challenging the Culture of Stress: Evaluating a Brief, Theory-Driven Mental Health Help-Seeking Intervention for Undergraduate Engineering Students | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Challenging the Culture of Stress: Evaluating a Brief, Theory-Driven Mental Health Help-Seeking Intervention for Undergraduate Engineering Students Joshua Parrott, Hammer Joseph, Elahe Vahidi, Nayeon Kim, Sarah Wilson This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-8205457/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Engineering undergraduate students report high levels of mental health distress yet exhibit comparatively low rates of engagement with professional mental health services compared to students in other academic majors. These low help-seeking behaviors may be further compounded by the prevailing “culture of stress” within engineering, which emphasizes self-reliance, stoicism, and academic rigor. Therefore, this study examines the impact of a brief, 15-minute mental health and help-seeking training tailored for engineering students at a large Southeastern U.S. university. Grounded in the Integrated Behavioral Model of Mental Health Help Seeking (IBM-HS), the study evaluates whether the training influenced mental health help-seeking perceptions, including key determinants (e.g., mental health perceptions, knowledge, and skills), beliefs (e.g., prioritizing academics over mental health needs) and mechanisms (e.g., attitude, perceived norm, personal agency) that shape intentions to seek professional support. The study compares training and non-training groups from Fall 2023 ( n = 431) and Fall 2024 cohorts ( n = 132) using pre/post survey responses. Findings indicate statistically significant improvements in both perceived and objective knowledge of mental health resources, while help-seeking beliefs, mechanisms, and overall intention did not change significantly. Discussion of our results includes the training’s advantages (e.g., low-cost, scalable, and designed to be embedded into existing engineering curricula) and considerations for future research and practices. Overall, our findings highlight the potential for brief, discipline-specific interventions to improve mental health literacy in engineering education while underscoring the need for complementary approaches to shift deeper help-seeking attitudes and norms. Engineering students engineering education help seeking mental health mental health literacy integrated behavioral model intention attitude perceived norm knowledge Figures Figure 1 Figure 2 Figure 3 Figure 4 INTRODUCTION Mental health concerns and treatment use among undergraduate students have risen in recent years (Lipson et al., 2022 ; Sheldon et al., 2021 ; Watkins et al., 2011). Students can remain untreated due to their low mental health help-seeking intention; a meta-analysis found that only 41% of college students with mental health concerns considered seeking help, and just 28% followed through, citing barriers like self-reliance, time constraints, limited resource awareness, and low perceived need (Zhao et al., 2025 ). With low help seeking and poor adherence to treatment, mental health distress among college students can worsen over time, becoming chronic (Pedrelli et al., 2015 ) and negatively impacting student retention and academic performance (Mojtabai et al., 2015 ; Arria et al., 2013 ; Melnyk et al., 2015 ; Vitasari et al., 2011 ). Therefore, it is crucial to develop strategies to reduce barriers and promote timely access to mental health services for college students broadly (Doll et al., 2021 ). Within undergraduate engineering, students experience high levels of mental health distress yet demonstrate lower treatment utilization compared to peers in other disciplines (Whitwer et al., 2025 ). These mental health challenges can be exacerbated by academic norms (e.g., heavy academic workloads, sleep disturbances, normalization of stress) (Asghar et al., 2024 ; Akter et al., 2025; Jensen & Cross, 2021 ; Jensen et al., 2023 ), and cultural norms that emphasize rigor, stoicism, and grit (Godfrey & Parker, 2010 ; Kirn & Benson, 2018 ). Further, engineering students often prioritize academic obligations over wellbeing (Wright et al., 2023 ; Jensen et al., 2023 ). Therefore, to address this normalization of stress and reduced help seeking in engineering, we created a brief (15-minute) mental health training tailored specifically to engineering undergraduates, grounded in a theoretical model of mental health help seeking. Expanding on prior mental health help-seeking intervention research [ citation redacted for masked peer review ], this study implemented a college-wide intervention and evaluated its impact on engineering students’ mental health help-seeking perceptions across two cohorts (Fall 2023 and Spring 2024). This allowed us to answer the following research questions: How do we develop a mental health training intervention tailored toward the engineering undergraduate population? How does a discipline-tailored mental health intervention impact engineering students’ mental health help-seeking perceptions? To contextualize this study, the following section reviews additional research on mental health help-seeking and related interventions in engineering education. Mental Health and Help-seeking in Engineering Engineering students experience high levels of mental health distress (Whitwer et al., 2025 ). In a national sample, 44.4% of engineering students screened positive for current depressive and/or anxiety symptoms (Whitwer et al., 2025 ), with even higher rates observed among female, first-generation, and gender-expansive students in engineering (Vick et al., 2025; Hargis et al., 2021; Jensen & Cross, 2021 ). A 2023 systematic review of 34 studies examining the mental health and well-being of undergraduate engineering students identified stress as the most commonly reported mental health concern, followed by depression, anxiety, and post-traumatic stress disorder (Asghar et al., 2024 ). These concerns put engineering students at risk for attrition, with roughly 45% of students at research institutions either switching to a major unrelated to STEM (Science, Technology, Engineering, Mathematics) or not completing the four-year degree (Kraus et al., 2015). Research has also highlighted key barriers to promoting mental health in this population, including heavy academic workloads, sleep disturbances, and aspects of engineering culture itself (Asghar et al., 2024 ; Akter et al., 2025). Despite the large percentage of engineering students who screen positive for depression or anxiety, engineering students self-report depressive and anxiety symptoms at lower rates than students in other majors (Whitwer et al., 2025 ). This discrepancy may reflect a reduced recognition of mental health struggles among engineering students, potentially due to limited mental health literacy or reluctance to acknowledge distress (Whitwer et al., 2025 ). The literature provides important insights into engineering students’ mental health help-seeking beliefs, which are shaped by the internalization of dominant cultural norms within the discipline and are associated with reduced help-seeking. Students who endorse beliefs emphasizing competition and meritocracy in engineering report less favorable attitudes toward seeking treatment (Sánchez-Peña et al., 2023 ). Cultural norms related to masculinity and Whiteness embedded in engineering culture further discourage help-seeking, particularly among gender and racial minority groups (Sánchez-Peña et al., 2025 ). Similarly, culturally reinforced values such as self-reliance and efficiency may strengthen students’ preference for managing struggles independently rather than developing supportive networks (Wright et al., 2023 ; Sánchez‐Peña et al., 2025). Finally, the normalization and trivialization of mental health concerns within engineering programs (Beddoes & Danowitz, 2022) may lead students to prioritize academic success over self-care. As one student explained, “you have to prioritize the education and the work that goes towards it instead of … yourself … I think a lot of people think that it's just four years … They need to get through the school and then it'll be fine” (Wright et al., 2023 , p. 974). Additional barriers accounting for engineering students’ decreased likelihood of seeking help include concerns with a lack of appointment availability, and relying on informal support (e.g., peers) in lieu of professional support to cope with distress (Wright et al., 2023 ; Jensen et al., 2023 ). Both perceived and internalized help-seeking stigma (e.g., believing that others view help-seeking as a sign of weakness and endorsing those external views oneself, respectively) further undermine the willingness of engineering students to access care (Sánchez-Peña et al., 2023 ). This stigma may be reinforced by students rarely seeing their faculty openly modeling such help-seeking behaviors; the absence of professors who discuss or demonstrate help-seeking can make students feel that faculty do not understand or relate to their struggles (Busch et al., 2024 ). Students often perceive implicit messages from their professors and advisors suggesting that prioritizing mental health may not be supported within their academic environment (Ban et al., 2023 ). Other barriers including the perceived time requirements, opportunity costs associated with seeking help (Sánchez-Peña et al., 2023 ; Wright et al., 2023 ), and accessibility beliefs likely further discourage students to prioritize their mental health concerns. Even when students know resources exist, concerns about not finding a “good fit” with a provider (Beddoes & Danowitz, 2022; Wright et al., 2023 ) or believing the process would be too complicated or inaccessible (Jensen et al., 2023 ; Wright et al., 2023 ) act as barriers. Mental Health Help-Seeking Interventions in Engineering Within engineering, there has been an increase in interventions aimed at improving student mental health and well-being. A recent scoping review by Tait and colleagues (2023) examined 33 studies with interventions designed to support the mental health and wellbeing of engineering college students, involving over 4,000 engineering students from 10 countries. The review categorized these 33 interventions into psychological (14), physiological (5), and/or educational (15). Psychological interventions primarily involved mindfulness training, tutoring, social belonging interventions, and assessing social and/or professional support (Miller & Jenson, 2020; Walton et al., 2015 ; Grasty et al., 2021). Physiological interventions included structured breathing exercises and activities designed to promote body awareness including dance movement therapy (Rodríguez-Jiménez et al., 2022 ) and yogic breathing (Joshi & Kiran, 2020 ). Educational interventions focused on increasing awareness of stress reduction techniques, recognizing signs of mental health distress, and modifying teaching approaches (Abiade & Moliski, 2020; Su, 2016 ). Tait and colleagues (2023) found that mental wellness interventions in engineering education led to improvements in academic achievement, reductions in stress and anxiety, and additional benefits such as improved motivation, positive attitude, physical activity, physiological regulation, spiritual health, self-confidence, health awareness, and communication skills. The 33 studies included in Tait and colleagues’ (2023) scoping review primarily focused on reducing mental health distress among undergraduate engineering students through direct mental health support interventions. However, none of these studies primarily focused on improving engineering undergraduates’ mental health help-seeking perceptions. In fact, only one reported data regarding mental health help-seeking perceptions: Paul and colleagues ( 2020 ) integrated weekly 15- to 75-minute mental wellness modules (e.g., exam anxiety, how to access campus academic and mental health support services) and structured self-reflection activities into required first-year engineering coursework. Analysis of these reflections revealed that students generally appreciated the modules, perceived faculty as supportive, and showed increased engagement in help-seeking behaviors. They also expressed a preference for shorter modules (15–20 minutes) over longer seminars, appreciated the student peers presenting and sharing their own struggles (e.g., academic burnout, mental health), yet continued to view mental wellness as a lower priority compared to academics. Our review of the literature suggested that few published studies beyond the scope of this systematic review exist; one exception is Kalamatianos and colleagues’ (2025) implementation of a blended counseling intervention among undergraduate engineering students. Their five-week psychoeducational and positive psychology-based program effectively reduced symptoms of depression, anxiety, and stress within this population. In summary, there remains a dearth of literature on interventions designed to specifically influence mental health help-seeking perceptions within the engineering student population. Furthermore, extant engineering student mental health studies are often characterized by limitations including the frequent lack of (a) use of psychometrically-vetted measures, (b) grounding in theory, much less mental health help-seeking theory, (c) tailoring of intervention content to the culture of engineering education and engineering students’ lived experience, (d) brief interventions feasible to deliver at scale to the engineering student body, and/or (e) control groups and pre/post designs to mitigate threats to internal validity (e.g., testing and history effects). Therefore, there is a need for intervention research focused on improving engineering students’ mental health help-seeking perceptions that address these important limitations. Theoretical Framework This study was grounded in the Integrated Behavioral Model of Mental Health Help Seeking (IBM-HS), which provides a comprehensive framework for understanding psychological, social and environmental determinants of mental health help seeking and service utilization (Hammer, Vogel, et al., 2024 ). According to the IBM-HS, an individual’s intention to seek help serves as the most immediate predictor of their prospective help-seeking behavior (Hammer, Vogel, et al., 2024 ) and is shaped by the three help-seeking mechanisms of attitude, perceived norm, and personal agency. Attitude refers to an individual’s overall evaluation of seeking help as a good or bad thing and is informed by outcome beliefs (expected results of seeking help) and experiential beliefs (emotional response to the idea of seeking help). Perceived norm reflects the perceived social expectations around help seeking and includes both injunctive norm (influenced by beliefs about what others expect them to do) and descriptive norm (influenced by beliefs about whether others would seek help if in distress). Finally, personal agency refers to an individual’s evaluation of their capacity to seek help and their autonomy around the decision to seek help. Personal agency is shaped by logistical beliefs about likely facilitators or barriers to seeking help. For example, a logistical belief is that one must prioritize their academic success over their mental health, a theme that has been noted in existing engineering mental health literature (Wright et al., 2023 ; Hammer, Wright, et al., 2024 ). Underlying these beliefs are broader help-seeking determinants (Hammer, Vogel, et al., 2024 ). One such category of help-seeking determinant is called mental health perceptions, knowledge, and skills. This category includes both perceived and objective mental health literacy (e.g., ability to recognize signs of distress, knowledge of mental health resources and how to access them). Collectively, the help-seeking determinants not only inform the beliefs that shape mechanisms and intention but can also directly influence whether an individual follows through on their intention to seek care (Hammer, Vogel et al., 2024 ). Understanding these determinants, beliefs, and mechanisms provides a foundation for designing interventions that target the specific cognitive, affective, and structural barriers influencing help-seeking among engineering students. Current Study Grounded in the IBM-HS, our study aimed to address the limitations of previous research on engineering-specific mental health help-seeking interventions. Specifically, we implemented and assessed a 15-minute mental health presentation intervention designed specifically for engineering students that aimed to improve mental health literacy (help-seeking determinant), normalize the prioritization of mental health (help-seeking belief), improve help-seeking attitude, perceived norm, and personal agency (help-seeking mechanisms), and enhance help-seeking intention. Further, open-ended participant feedback regarding the presentations was also collected. Informed by Bloom’s Taxonomy of Learning (Bloom et al., 1956 ; Krathwohl et al., 1964 ), we expected this brief intervention to primarily strengthen engineering students’ foundational mental health literacy (e.g., knowledge of campus mental health resources, perceived ability to recognize signs of distress) because these outcomes align with the cognitive domain’s basic knowledge level. Given the short duration of the training, we did not anticipate substantial changes in broader help-seeking perceptions such as attitudes toward seeking professional help. This expectation is consistent with the larger literature: a meta-analysis of brief web-based mental health literacy interventions for youth conducted by Nazari and colleagues ( 2023 ) found significant improvements in objective knowledge but no significant changes in stigma or help-seeking attitudes, and a systematic review of classroom-based programs among high school and college students by Nazari and colleagues ( 2024 ) similarly showed consistent gains in mental health knowledge with only mixed or limited effects on attitudes or stigma. Together, these findings suggest that brief educational interventions can reliably enhance foundational mental health literacy, whereas shifting deeper-seated perceptions (e.g., mental health stigma or help-seeking intention) likely requires more intensive and sustained efforts. With this context in mind, our interdisciplinary team sought to conduct develop, implement, and evaluate an intervention explicitly designed to influence engineering students’ mental health help-seeking perceptions. Findings from this work are intended to inform future intervention development and testing within colleges of engineering nationwide. METHOD Training Delivery The mental health intervention was first delivered in Spring 2023 and then adapted for a second round of delivery in Spring 2024. Participants were undergraduate engineering students at the [ name of institution redacted for masked peer review ]. To identify courses for recruitment, department chairs were contacted during each fall semester to identify courses within their discipline that would: 1) reach all students across all academic years within the major, 2) limit the overlap of students across courses, and 3) be taught by faculty that would: support the integration of the training into their course, encourage a positive narrative around prioritizing student mental health, and represent the demographics of students within their program. After receiving a list of courses from each department chair, faculty were contacted by the research team’s graduate student members, informed about the training and an optional 15-minute post-training facilitated discussion, and asked to schedule a time for the integration of the training within their course during the spring semester. Both the department chair and associate dean for undergraduate education and student success were included in the email to illustrate administrative support for the training. In Spring 2023, 95% (57) of the 60 contacted faculty members agreed to the incorporation of the 15-minute training into their courses. 11 of the 57 faculty also agreed to the additional 15-minute post-training facilitated discussion. A total of 2,592 students were enrolled in courses in which the training was delivered, representing up to 93% of the 2,780 students enrolled in the College of Engineering at the time [ citation redacted for masked peer review] . In Spring 2024, 46 of the 70 contacted faculty agreed to incorporate the training, and 8 of the 46 faculty also agreed to the facilitated discussion. A total of 1,890 students were enrolled in courses in which the training was delivered, representing up to 67% of the 2,836 students enrolled in the College of Engineering ( citation redacted for masked peer review ). The training was delivered by graduate student research team members from the counseling psychology program at the university, in addition to the [ discipline to be added after review ] associate professor and [ discipline to be added after review ] assistant professor leading the research team. There were three graduate student presenters in 2023 and five presenters in 2024. Collectively, the presenters held a diverse range of identities across gender, race, and academic year, and were all trained in providing culturally responsive care and demonstrated effective public speaking skills. Training Description The 15-minute mental health trainings were developed based on the findings of empirical research on undergraduate engineering students’ mental health and help seeking, as highlighted in the prior literature review. The 2024 training was adapted from the previous year based on additional data collected by the research team, along with 2023 participant feedback and ideas from new research team members. University administrators engaged in mental health training and service delivery were consulted to ensure the training content was up-to-date and in accordance with university guidelines. The training was piloted with graduate and undergraduate engineering students to ensure the content met the needs of the engineering student body. To personalize the training to the engineering student context, mental health and help-seeking statistics from engineering students at the university were included, along with direct quotes from semi-structured interviews and focus groups our team had conducted with engineering students. Table 1 summarizes the training content for 2023 and 2024. Table 1 Content of the Engineering Student Mental Health Training for 2023 and 2024 Topic Key Content Covered 2023 2024 Prioritizing Mental Health Engineering students feel they do not have time to prioritize mental health and are less likely to seek help (Whitwer et al., 2025 ), (Wright et al., 2021), (Ban et al., 2022 ) Chronic stress linked to decreased burnout, academic performance, and increased mental health disorders (Wang et al., 2024 ) (Ban et al., 2022 ) ✓ ✓ Mental Health Resources Overview of campus resources related to mental health and wellness (Paul et al., 2020 ) Additional resources to support overall well-being (e.g., academic tutoring and accommodations, basic needs, financial support, etc.) (Ban et al., 2022 ) ✓ ✓ Recognizing/ Addressing Mental Distress Differentiating between normal stress and unhealthy distress and teaching mental health literacy (O’Sullivan, 2011 ; Shim et al., 2022 ) Tips for peer support (e.g., talking to someone experiencing distress and/or how to advocate for them) (Hyseni Duraku et al., 2023 ) ✓ ✓ Substance abuse Recognizing signs of substance abuse and its impact on academic performance (Paul et al., 2024 ) ✓ Practical Skills Overview of small independent habits to promote mental health/wellness (e.g., diet, exercise, self-care, prosocial relationships) (Ban et al., 2022 ) Community involvement can positively impact mental wellness (e.g., mentorship, student organizations) (Ban et al., 2022 ) ✓ For faculty that agreed to the optional 15-minute post-training facilitated discussion, the discussion was held immediately following the training presentation. Facilitators posed a series of questions (e.g., “What are some ways that you have seen or heard high levels of stressed being normalized in engineering?” “Which stressors are unique to engineering students?” “What is one thing you want to work on better prioritize your own mental health?”) and students were encouraged to discuss in a small group before reporting themes to the larger group. Quantitative Data Collection In 2023, survey data was collected after completion of the training for two independent sample groups: students who did not receive the training (“No Training”; n = 164), and students that did (“Training”; n = 267). In contrast, survey pretest and posttest data were each collected in 2024 from the Training group ( n = 64) and the No Training group ( n = 68). Table 2 provides demographic information for both 2023 groups and 2024 groups. To anonymously link student survey responses across time (Lippe et al., 2019 ), each student was asked to provide a subject-generated four-character identification code by answering the following four questions: 1) the first initial of your mother's name, 2) The number of older brothers you have, 3) the first letter of your middle name and 4) the number of the month in which you were born. In 2023, there was only a small number of linking codes ( n = 35) across the combined 2023 pre-test and post-test sample size. Consequently, we chose to discard any participants with matching linking codes, allowing for the treatment of the responses as independent Training (pre-test responses) and No Training (post-test responses) groups. In 2024, there was a sufficient number of linked codes ( n = 132) across the pre-test and post-test samples for the Training and No Training groups, so we were able to perform additional analysis to account for possible history effects. Online surveys were administered during the spring semesters of both academic years, collecting quantitative (i.e., perceived knowledge, objective knowledge, prioritization of mental health, intention, mechanisms) and qualitative (i.e., helpful aspects of training; aspects of training to be improved) data. After obtaining approval from the university’s Institutional Review Board (IRB; protocol number 86047), students were recruited via email and provided with all necessary information to ensure informed consent and voluntary participation at the start of the survey. Because training sessions were conducted across the 2023 and 2024 academic semesters, and students had the flexibility to complete the surveys at their convenience, the time elapsed between each training and corresponding survey completion varied both within and across the two academic years. Based on demographic data (Table 2 ), participants were representative of the engineering population at the university, with most being white, heterosexual male students. Eleven engineering majors were represented (e.g., mechanical, computer science, civil, chemical, electrical, mining, computer engineering, biomedical, biosystems). Across both years among training and no training groups, over a third of the students were freshmen or sophomores (35%), and a minority of students were international (2%), first-generation (14%), or transfer students (10%). Due to challenges with the linking code used for the 2023 survey data, there is limited demographic data for this population. That being said, the demographic distribution of students across each phase of the study was comparable. Table 2 Sociodemographic Characteristics of the Participants Sample Characteristics No Training 2023 (n = 164) Training 2023 (n = 267) No Training 2024 (n = 68) Training 2024 (n = 64) n % n % n % n % Gender Man 93 67.9% 56 66.7% 46 67.6% 34 53.1% Woman 42 30.7% 26 31.0% 19 27.9% 30 46.9% Gender Expansive 3 2.2% 2 2.4% 3 4.4% 0 0.0% Prefer Not to Answer 1 0.7% 0 0.0% 1 1.5% 0 0.0% No Answer Provided 27 183 0 0 Sexual Orientation Straight/Heterosexual 115 83.9% 76 90.5% 61 89.7% 59 92.2% LGBQ+ 20 14.6% 8 9.5% 7 10.3% 6 9.4% Prefer Not to Answer 2 1.5% 1 1.2% 1 1.5% 0 0.0% No Answer Provided 27 183 0 0 Race/Ethnicity White or Caucasian 109 79.6% 67 78.8% 54 79.4% 55 85.9% Asian or Asian American 12 8.8% 5 5.9% 7 10.3% 4 6.3% Latino/a/x/e or Hispanic 7 5.1% 6 7.1% 4 5.9% 3 4.7% Biracial/Multiracial 5 3.6% 5 5.9% 3 4.4% 4 6.3% Black/African American 5 3.6% 5 5.9% 1 1.5% 3 4.7% Arab or Arab American 3 2.2% 1 1.2% 0 0.0% 2 3.1% American Indian, Native American, or Alaskan Native 1 0.7% 2 2.4% 0 0.0% 1 1.6% Jewish 1 0.7% 2 2.4% 0 0.0% 0 0.0% Pacific Islander or Native Hawaiian 1 0.7% 0 0.0% 1 1.5% 0 0.0% Prefer Not to Answer 4 2.9% 1 1.2% 1 1.5% 0 0.0% No Answer Provided 27 182 0 0 Note . The percentages per category were calculated based on existing demographic data and did not include responses without data. Participants were given the option to select all that apply per category (i.e., Gender, Sexual Orientation, Race/Ethnicity). Gender Expansive included the following options: transgender, non-binary, gender queer, gender fluid, agender, and poly-gender. LGBQ + included the following options: gay, lesbian, bisexual, pansexual, asexual, and queer. Measures For both 2023 and 2024 studies, the measures used to assess students’ help-seeking perceptions and experience with the training are described below. Perceived Knowledge Respondents completed three items evaluating their perceived knowledge of mental health resources available to students at their university (i.e., “I know what mental health resources are available to students on this campus”), how to access these services (i.e., “I know how to access the available mental health resources on campus”), and their ability to recognize signs of mental health distress (i.e., “I know how to recognize signs of mental health distress”). Each item was rated on a six-point Likert scale from 1 (strongly disagree) to 6 (strongly agree). Objective Knowledge Respondents completed a 10-item multiple-choice quiz that evaluated their factual knowledge of available resources for students at the university and how to access them. These included resources for mental wellness, academic accommodation and tutoring, financial and basic needs, and survivors of sexual and gender-based violence. All resources were reviewed in the training. For six of the 10 items, respondents were given a hypothetical scenario (e.g., “supposed you are seeking financial assistance…”) and asked to choose the most appropriate university resource from a multiple-choice list. Two items asked about the specific purpose and location of the university’s main resource for mental health needs. The final two items were true/false questions regarding free mental health resources available to students at the university. For all 10 items, respondents also had the option to choose “I’m Not Sure”. Correct responses were coded as one, whereas incorrect or “I’m Not Sure” responses were coded as zero. An overall “percentage correct” score on the quiz was calculated for each respondent. Prioritization of Mental Health A single item was used to evaluate how much respondents agreed with the following statement regarding their own mental health prioritization: “During my time as an engineering student, I will need to prioritize my academic success over my mental health”. This item, which represents a logistical belief, was taken from a larger validated instrument aimed at identifying beliefs that impact mental health treatment access in undergraduate engineering students: The Undergraduate Engineering Mental Health Help-Seeking Instrument (UE-MH-HSI) (Hammer, Wright, et al., 2024 ). The item was rated on a six-point Likert scale from 1 (strongly disagree) to 6 (strongly agree). Help-Seeking Intention A single item was used to measure mental health help-seeking intention (i.e., “If I had a mental health concern, I would intend to seek help from a mental health professional in the next 3 months”). This item was measured on a six-point Likert scale from 1 (extremely unlikely) to 6 (extremely likely). This item was adapted from the Mental Health Help-Seeking Intention Scale (MHSIS; Hammer et al., 2018 ), which has demonstrated evidence of validity for use with engineering students and utilized in the UE-MH-HSI (Hammer, Wright, et al., 2024 ). Help-Seeking Mechanisms Respondents completed single-item measures of mental health help-seeking attitude, perceived norm, and personal agency. These single-item versions were adapted from the multiple-item measures of these constructs embedded in UE-MH-HSI (Hammer, Wright, et al. 2024 ): Attitude. Attitude was measured with a single item rated on a six-point Likert scale from 1(very bad) to 6 (very good) (i.e., “If I had a mental health concern, my seeking help from a mental health professional in the next 3 months would be…”). (Hammer, Wright, et al., 2024 ). Perceived Norm. Perceived Norm was measured with a single item rated on a six-point Likert scale from 1 (I should not) to 6 (I should) (i.e., “Most people who are important to me would think that ____ seek help from a mental health professional in the next 3 months”). This item focused on the injunctive element of perceived norm (Hammer, Wright, et al., 2024 ). Personal Agency. Personal Agency was measured with a single item rated on a six-point Likert scale from 1 (completely false) to 6 (completely true) (i.e., “I am confident that I could seek help from a mental health professional in the next 3 months”). This item focused on the capacity (i.e., degree of confidence) element of respondents’ self-efficacy (Hammer, Wright, et al., 2024 ). Qualitative Open-ended Questions Respondents completed two open-ended questions about their experience with the training regarding what they found most helpful (i.e., “What was helpful about the mental health presentation in your class?”) and how they felt it could be improved (i.e., “What could have been different (e.g., topics covered, presentation style) about the mental health presentation to make it more helpful to you?”). Data Cleaning & Analysis Across both years, responses that either lacked usable data or did not provide a four-character identification code were deleted. For 2023 data, identification codes for survey data from students with ( n = 267) and without ( n = 164) training were used to ensure that each group was independent (i.e., all codes were unique across both groups). In contrast, 2024 data were cleaned by linking pretest/posttest responses using unique codes; responses without matches or with conflicting information were excluded, and duplicates were deleted to ensure only linking pretest/posttest code matches remained. Additionally, no variables exceeded cutoffs of 3 and 10 for high univariate skewness and kurtosis values (Weston & Gore, 2006 ). Quantitative data was analyzed using IBM SPSS Statistics Software Version 29. For both the 2023 and 2024 data, independent sample t-tests were conducted comparing mean scores between the No Training and Training groups on all nine measures, Levene’s Test (p < .05) was used to measure equality of variances across the two independent groups (Gastwirth et al., 2009 ). Five of the nine variables were found to violate assumptions of homogeneity. In these cases, homogeneity was not assumed when determining significance. To avoid inflating the Type I error rate when conducting multiple independent-sample t‑tests, we applied a Bonferroni correction, dividing the conventional α = .05 by the number of comparative tests. This resulted in a more stringent significance threshold (i.e., p < .006), as recommended in prior literature (Armstrong, 2014 ). For both 2023 and 2024 analyses, we applied a Bonferroni correction to the following eight tests: perceived knowledge (three), help-seeking mechanisms (four), and objective knowledge (one). Because the simple comparison of the No Training and Training groups cannot account for potential history effects (events that influence mean scores on the dependent variable between pre-test and post-test measurements), we conducted a supplemental set of analyses to increase confidence in the validity of our results. Using the 2024 data, which measured study variables at both pre- and post-intervention, we conducted a series of Two-Way Repeated Measures Analyses of Variance (ANOVA). This analytical procedure can analyze two factors of interest (the within subject factor of time and the between subject factor of training) from the experimental (Training) and control (No Training) groups, as well as the time x training interaction (Schober & Vetter, 2018 ). Box’s Test of Equality of Covariance Matrices ( p < .05) was used to compare variation in the two multivariate samples. Four of the nine variables were found to violate Box’s Test. However, given the nearly equal sample size groups (Training n = 64; No Training n = 68), the test results are robust to these violations (Pituch & Stevens, 2015 ). Because we had already provided independent samples t-test evidence regarding potential differences between the No Training and Training groups, we focused on using Wilks’ Lambda to determine whether the interaction effect was significant, which would indicate that the rate of change for the mean score was significantly different from pre to post-intervention (time) between the experimental (Training) and control (No Training) groups. We anticipated that significant differences between the No Training and Training groups detected by the independent sample t-tests would be confirmed by the supplemental examination of the interaction effect for the corresponding Two-Way Repeated Measures ANOVA. Mauchly’s test on all nine variables indicated that the assumption of sphericity was met throughout, X 2 (0) = .0, p < .001, and therefore degrees of freedom did not need to be corrected using Greenhouse-Geisser (Blanca et al., 2023 ). Qualitative data from 2023 and 2024 regarding what respondents found helpful and what they felt could be improved was inductively coded through informal structured tabular thematic analysis (ST-TA). This approach is designed to analyze brief qualitative data (Robinson, 2022 ). After checking the level of coding agreement between two research members, eighteen codes were generated. The qualitative analysis helped provide additional insight into what worked well and what might be addressed to further enhance the effectiveness of the training. Use of Generative Artificial Intelligence Our team members utilized generative artificial intelligence (Gen AI), specifically ChatGPT (OpenAI, GPT-4), to support clarity and consistency in the wording and structure of this manuscript. Gen AI was used during the manuscript development and revision phases to suggest more concise phrasing, reword redundant or awkward phrasing, and improve tone alignment across sections. All content was reviewed and edited by the authors to ensure accuracy, appropriateness, and alignment with our intended meaning. No generative AI tools were used for data generation, analysis, or for producing original content beyond writing support and copyediting. We take full responsibility for the content of the publication. POSITIONALITY STATEMENT Our research team was composed of two tenured or tenure-track professors (both engineering and non-engineering), one postdoctoral researcher, and two counseling psychology graduate students, possessing a collective domain expertise in mental health help seeking and engineering education, with a mixture of inside and outsider status members to the engineering student population (Secules et al., 2021 ). We represent a range of social, cultural, and disciplinary perspectives, which were intentionally explored and discussed in relation to our motivations, research approach, and engagement with our target population, enhancing the overall quality and rigor of the study (Sochacka et al., 2018 ). Our team collectively affirms the belief that mental health support is a fundamental human right and that accessing professional resources can play a critical role in enhancing individual well-being. We recognize that engineering training environments can often implicitly socialize students to prioritize academic and professional productivity over their own mental health and self-care. Furthermore, we recognize the presence of intrapersonal, interpersonal, and systemic barriers that can hinder distressed undergraduate engineering students from both seeking and receiving consistent and effective access to mental health services. Our eight graduate student presenters also collectively reflected a broad range of social identities (e.g., race/ethnicity, gender, sexual orientation, academic year) which strengthened the relevance and relatability of the trainings for diverse student audiences. The inclusion of this positionality statement aligns with recent calls within engineering education research to promote transparency regarding the influences that shape the research process, particularly within quantitative studies (Hampton et al., 2021 ). RESULTS Impact of Training on Perceived Knowledge Between 2023 and 2024, the 15-minute mental health training was delivered in courses with a total of nearly 4,500 students enrolled. We examined the impact of the brief mental health training on perceived knowledge, help-seeking beliefs and mechanisms, and help-seeking intention across students in the Training and No Training groups. In both years of the training, students in the Training groups reported higher perceived knowledge than the No Training groups across all three perceived knowledge items (Table 3 and Fig. 2). Specifically, compared to students in the No Training groups, the students who received the training had greater perceived knowledge related to (a) knowing what mental health resources are available to students on campus, (b) how to access these resources, and (c) how to recognize signs of mental health distress. Most students at least slightly agreed that they were knowledgeable regarding these three items. However, while approximately 45% of students in the No Training groups reported that they at least slightly agreed (i.e., reporting a score of 4 or higher on the six-point Likert scale) with the statement that, “I know what mental health resources are available to students in campus.” This is compared to approximately 80% of the students in the Training groups, indicating a noticeable increase in perceived knowledge of resources. This difference was similar for the other two knowledge items. In addition, the 2024 perceived knowledge scores were trending higher across both groups compared to the 2023 scores for both groups, suggesting that 2024 respondents started at a higher perceived knowledge baseline compared to the prior year. Table 3 Effect of Training on Perceived Knowledge Items Groups M SD df T p I know what mental health resources are available to students on this campus 2023 No Training 4.09 1.40 292.65 -6.37 < 0.001 2023 Training 4.91 1.14 2024 No Training 4.41 1.26 107.99 4.54 < 0.001 2024 Training 5.22 0.72 I know how to access the available mental health resources on campus 2023 No Training 3.79 1.50 285.46 -6.33 < 0.001 2023 Training 4.66 1.18 2024 No Training 4.15 1.31 123.11 3.89 < 0.001 2024 Training 4.92 0.97 I know how to recognize signs of mental health distress 2023 No Training 4.52 1.24 302.75 -2.96 0.003 2023 Training 4.86 1.06 2024 No Training 4.40 1.24 123.89 3.19 0.002 2024 Training 5.00 0.93 Note. Sample sizes for each independent group from both years were as follows: 2023 No Training, n = 164; 2023 Training, n = 267; 2024 No Training, n = 68; 2024 Training, n = 64. Figure 2. Effect of Training on Perceived Knowledge Note : An asterisk (*) indicates a significant difference between independent groups within years ( p < .05). Impact of Training on Objective Knowledge Across both years, students in the Training groups demonstrated better objective knowledge of available resources at the university and how to access them (about 20% more accurate in their responses) than the students in the No Training groups (Table 4 and Fig. 3). In 2023, 68% of students in the Training group achieved a passing score (i.e., 60% or higher), compared to just 25% in the No Training group. In 2024, this pattern persisted, with 84% of students in the Training group passing compared to 49% of the No Training group. Consistent with perceived knowledge outcomes, students in both groups showed improved objective knowledge scores from 2023 to 2024. To better understand the objective knowledge results, we examined scores for the individual objective knowledge items. Students in both the Training and No Training groups performed poorly when tested on their objective knowledge of their university’s main mental health intake unit (“You are concerned about a classmate’s mental health. Who do you tell?”), with approximately 28% of respondents answering correctly across years. Similarly, respondents performed poorly (approximately 13% correct) when tested on their objective knowledge of the university’s resource for interpersonal violence education and prevention (“You need support related to gender or sexual based violence. Where do you go?”). However, students in the Training groups across both years performed notably well on two true/false items assessing awareness of free mental health services available to students (“True or False: students get access to free counseling at the Counseling Center.”, “True or False: students get access to free counseling through Talkspace”) with approximately 90% accuracy across both items compared to 66% accuracy in the No Training groups. Similarly, students in the Training groups across both years performed well on the item assessing knowledge of the appropriate resource for basic housing and financial security needs on campus (“You need help related to housing or financial insecurity. Where do you go?”), with approximately 82% accuracy, compared to 59% accuracy in the No Training groups across both years. Table 4 Effect of Training in Objective Knowledge Items Groups M SD df T p Average Score of 10-Item Quiz 2023 No Training 39.13% 0.22 349.33 9.68 < 0.001 2023 Training 62.70% 0.25 2024 No Training 50.45% 0.24 124.86 5.53 < 0.001 2024 Training 71.75% 0.19 Note. Sample sizes for each independent group from both years were as follows: 2023 No Training, n = 164; 2023 Training, n = 267; 2024 No Training, n = 68; 2024 Training, n = 64. Figure 3. Effect of Training on Objective Knowledge Note An asterisk (*) indicates a significant difference between independent groups within years ( p < .05). Impact of Training on Prioritization of Mental Health and Help-Seeking Intention Across both years, students in the Training and No Training groups reported similar levels of agreement with the belief that they would need to prioritize their academic success over their mental health (Prioritization) and that they would intend to seek help if they had a mental health concern (Intention) (Table 5 and Fig. 3). Across both years and groups, an average of approximately 84% of students reported at least slightly agreeing with the statement that they would need to prioritize their academic success over their mental health during their time as an engineering student. Likewise, only about 49% of students reported that they would be at least slightly likely to seek help from a mental health professional if they were struggling with their mental health. This highlights the low prioritization of mental health and help seeking within the engineering student population. Table 5 Effect of Training on Prioritization of Mental Health and Help-Seeking Intention Items Groups M SD df T p Priority 2023 No Training 4.60 1.46 429.00 0.36 0.72 2023 Training 4.65 1.39 2024 No Training 4.81 1.34 130.00 -1.87 0.06 2024 Training 4.38 1.32 Intention 2023 No Training 3.43 1.70 265.20 0.75 0.46 2023 Training 3.30 1.43 2024 No Training 3.24 1.51 127.00 1.97 0.05 2024 Training 3.76 1.49 Note. Sample sizes for each independent group from both years were as follows: 2023 No Training, n = 164; 2023 Training, n = 267; 2024 No Training, n = 68; 2024 Training, n = 64. Impact of Training on Help-Seeking Mechanisms Across both years, students in the Training and No Training groups reported similar levels of agreement with the idea that their seeking help would be a good thing (attitude), most people important to them would think they should seek help (perceived norm), and they are confident they could seek help if they wanted to (personal agency) (Table 6 and Fig. 5 ). For all three help-seeking mechanisms, the average student in each group across both years indicated uncertainty (i.e., response averages around three and four, which are in the middle of the six-point response scale) about their perceptions toward seeking professional help. In other words, the average student thought that their seeking help would be neither a good nor bad thing (attitude), felt that most of the important people in their lives would neither approve nor disapprove of their seeking help (perceived norm), and were undecided uncertainty about their ability to seek help (personal agency). Table 6 Independent T-Test Outcome on Help-Seeking Perceptions in 2023 and 2024 Items Groups M SD df T p Attitude 2023 No Training 3.85 1.38 355.00 0.36 0.72 2023 Training 3.90 1.37 2024 No Training 3.82 1.28 127.00 1.52 0.13 2024 Training 4.16 1.26 Perceived Norm 2023 No Training 4.10 1.56 352.00 -0.03 0.98 2023 Training 4.09 1.58 2024 No Training 3.97 1.64 127.00 -0.12 0.90 2024 Training 3.94 1.55 Personal Agency 2023 No Training 3.96 1.55 353.00 0.04 0.97 2023 Training 3.97 1.43 2024 No Training 4.19 1.45 127.00 0.80 0.43 2024 Training 4.39 1.29 Note . Sample sizes for each independent group from both years were as follows: 2023 No Training ( n = 164), 2023 Training" ( n = 267), "2024 No Training ( n = 68), 2024 Training” ( n = 64). Repeated Measures ANOVA (2024) Our Two-Way Repeated Measures ANOVA analyses across our 2024 No Training and Training groups corroborated our independent t-test sample results, with two of the four previously significant items no longer showing significant interaction effects. Of the four significant direct effects found from the 2024 independent t-tests (i.e., the three perceived knowledge items and the one objective knowledge item), two of the three variables (“I know how to access mental health resources on campus”, “I know how to recognize signs of mental health distress”, ) did not demonstrate a significant interaction effect during the corresponding Two-Way Repeated Measures ANOVA. This indicates that, when accounting for both within-subject changes over time and between-group differences, these two items did not show evidence that the training had a significantly different effect when compared to students without the training. Descriptive statistics for these specific items indicated that baseline pre-intervention scores for students in the 2024 Training group were higher than those in the 2024 No Training group. This reduced the available range for score increases on the 6-point Likert scale (i.e., a potential ceiling effect), which may have limited the ability to detect a significant interaction effect from pre- to post-intervention. It should also be noted that one of these two non-significant items was non-significant due to our conservative use of Bonferroni correction (i.e., the p of .01 for the item was not below the Bonferroni-adjusted p threshold of .006). In summary, in two of the four cases, these supplemental Two-Way Repeated Measures ANOVA analyses supported significant findings of the independent sample t-tests results (See Table 7 below for the Repeated Measures ANOVA interaction effects). Table 7 Repeated Measures ANOVA Interaction Effects Outcome for 2024 Items Groups M SD Time*Training Sum of Squares df Mean Square F p I know what mental health resources are available to students on this campus No Training - Pre 4.21 1.41 9.21 1 9.21 11.18 < 0.001 No Training - Post 4.41 1.26 Training - Pre 4.27 1.37 Training - Post 5.22 0.72 I know how to access the available mental health resources on campus No Training - Pre 3.96 1.52 7.71 1 7.71 7.38 0.01 No Training - Post 4.15 1.31 Training - Pre 4.05 1.43 Training - Post 4.92 0.97 I know how to recognize signs of mental health distress No Training - Pre 4.40 1.15 0.68 1 0.68 1.23 0.27 No Training - Post 4.40 1.24 Training - Pre 4.80 1.00 Training - Post 5.00 0.93 Average Score of 10-Item Quiz No Training - Pre 0.44 0.22 0.27 1 0.27 14.48 < 0.001 No Training - Post 0.50 0.24 Training - Pre 0.52 0.24 Training - Post 0.72 0.19 Priority No Training - Pre 4.90 1.20 0.35 1 0.35 0.72 0.40 No Training - Post 4.81 1.34 Training - Pre 4.61 1.12 Training - Post 4.38 1.32 Intention No Training - Pre 3.04 1.67 0.60 1 0.60 0.76 0.39 No Training - Post 3.24 1.51 Training - Pre 3.37 1.35 Training - Post 3.76 1.49 Attitude No Training - Pre 3.51 1.58 0.00 1 0.00 0.00 0.97 No Training - Post 3.82 1.28 Training - Pre 3.85 1.29 Training - Post 4.16 1.26 Perceived Norm No Training - Pre 3.94 1.66 0.07 1 0.07 0.06 0.81 No Training - Post 3.97 1.64 Training - Pre 3.84 1.63 Training - Post 3.94 1.55 Personal Agency No Training - Pre 3.97 1.71 0.50 1 0.50 0.59 0.45 No Training - Post 4.19 1.45 Training - Pre 4.34 1.32 Training - Post 4.39 1.29 Open-Ended Responses We received 188 open-ended qualitative responses from the 399 students who completed the post-assessment across both years (124 responses in 2023, and 64 responses in 2024), providing feedback on two open-ended questions asking what they found most helpful about the presentation and what could have made the presentation more helpful. Students shared that they found the education and explanation of available mental health resources most helpful across both years. For example, one student stated, “It gave resources and methods to support ourselves and friends going through hard mental periods” and another shared, “The presentation provided a number of mental health resources at [the university] that I didn’t previously know about.” Smaller trends also emerged, with students expressing appreciation for the engineering-specific content integrated into the presentation. This tailored content included quotes from engineering student focus groups discussing help seeking, institutional data showing that higher distress was associated with lower end-of-term grades for engineering students and published research relating to engineering culture and student mental health. For example, one student said, “Shows that most engineers deal with some distress, makes me feel not alone”. Students also appreciated how the presentation prioritized mental wellness and challenged mental health stigma (e.g., “It reminded me that I needed to take care of myself”) and the overall engaging and effective style of the speaker and/or the presentation (e.g., “The information was presented in a very understanding and sincere manner”). Notably, many students in the 2023 group reported appreciating the practical self-care skills discussed in the presentation (e.g., “Learning skills to identify stress and bad habits”) When asked what could be changed to make the presentation more helpful, approximately one-third of the 2023 and 2024 respondents stated “nothing,” indicating that either the presentation was already effective (e.g., “The presentation was wonderful”) and/or not providing additional suggestions (e.g., “I couldn’t think of anything while witnessing the presentation”). Smaller observations included students wanting the presentation style to be improved in a specific way (e.g., “The speaker spoke very fast”) or recommendations to improve the presentation content and its accessibility (e.g., “Send us home with [a] pamphlet”). A large number of students in the 2024 group suggested that the presentation should include more of engineers’ direct perspective on mental health, through either testimonials or the presenters themselves having an engineering background (e.g., “...having an engineer…who could sympathize with the students' circumstance, and someone with whom we as engineering students can better relate with, give the presentation might yield better results”). Collectively, these responses show that while students generally viewed the presentation as helpful, they also underscored the value of tailoring future iterations more explicitly to engineering students’ experiences. DISCUSSION The current study contributes to a nascent body of research aimed at promoting mental health help-seeking among engineering undergraduates by evaluating the impact of a brief, scalable mental health training intervention. Findings suggest that our training significantly increased students’ mental health perceptions, knowledge, and skills (i.e., perceived and objective knowledge of available mental health resources) across both 2023 and 2024 groups but did not significantly shift their help-seeking beliefs (e.g., prioritizing academics over mental health needs), help-seeking determinants (e.g., attitude, perceived norm, personal agency), or help-seeking intention. Perceived knowledge of how to access resources and ability to recognize signs of mental health distress both appeared to significantly increase for the training groups when analyzed using a t -tests; however, the more rigorous 2024 Repeated Measures ANOVA indicated that only two of the four previously significant knowledge items remained significant, suggesting that improvements in certain perceived knowledge domains were less robust under stricter analytic scrutiny. However, 2024 findings could be due to a potential ceiling effect of the measure and/or because the 2024 Training was not able to further increase these forms of perceived knowledge from their 2024 baseline levels. Descriptively, we noticed an upward trend in the perceived knowledge items from 2023 baseline to 2024 across the overall samples, which may reflect increased resource awareness over time due to a combination of this college-wide intervention (i.e., students performing better due to the prior year’s training) and broader institutional cultural shifts (i.e., expanded efforts to advertise mental health resources). Students in the Training groups also demonstrated higher objective knowledge scores in both years than those in the No Training groups. These findings suggest that the training not only improved students’ confidence in their knowledge of available resources but also translated into measurable improvements in their factual understanding and retention of the campus mental health resource information. This finding is noteworthy, as difficulty locating accessible mental health resources has been identified as a perceived barrier to help-seeking among engineering students (Wright et al. 2023 ). When comparing results across the 10 items, students tended to perform better when answering questions about resources with descriptive and intuitive names (e.g., “Basic Needs” relating to housing or financial support) compared to when acronyms were used (e.g., the “VIP Center”, relating to support for students who are survivors of sexual or gender-based violence ). This pattern aligns with prior findings that acronym-based labels can impede comprehension, suggesting that universities take a critical look at their naming conventions when developing student-facing resources. For example, Grossman and colleagues (2022) found that patients’ comprehension of health information improved from 62% to 95% when ten common medical abbreviations were replaced with full terms. Overall, scores for the 2024 training were about 10 percentage points higher than those for 2023. This could be due to student exposure to the mental health content and resources during the 2023 training year. Regarding prioritization of mental health, students in both years consistently endorsed the belief that they would prioritize their academic success over their own mental health, regardless of whether they received the training or not. These results are consistent with prior research indicating that engineering students report having limited time to schedule and attend mental health appointments due to their intense course load and believing they must complete and succeed in their academics “by any means necessary”, consequently avoiding and/or delaying help-seeking behaviors (Wright et al. 2021; Wright et al. 2023 ). Similarly, help-seeking attitude, perceived norm, personal agency, and intention all remained unchanged despite the training. Across all years and groups, engineering students reported neutral levels (scores close to the mid-point of the measurement scale) on these help-seeking perception constructs, aligning with prior research reporting neutral-to-slightly-positive help-seeking perceptions among undergraduate engineering students (Hammer et al., 2024 ; Wilson et al., 2022; Wilson, Huth, et al., 2024). In other words, the average engineering student expressed ambivalence about whether seeking help would be good or bad (attitude), whether important people in their lives would want to them seek help (injunctive component of perceived norm), whether they felt capable of seeking help (personal agency), and whether they would plan to seek help if distressed (intention). It is likely that our one-time, brief presentation lacked the dosage (e.g., length and/or frequency of intervention) needed to change these more entrenched help-seeking perceptions reinforced by engineering culture’s emphasis on stoicism, self-reliance, and academic grit (Jensen & Cross 2021 ; Godfrey & Parker 2010 ). Generally, brief interventions are more successful at improving knowledge than shifting perceptions, attitude, and beliefs (Laschke et al., 2023 ). For example, Raghavan and colleagues ( 2024 ) found that a one-time, 90-minute mental health literacy presentation significantly improved students’ understanding of mental illness and help-seeking behaviors in Indian educational settings. However, the long-term outcomes of interventions targeting college students’ mental health literacy is largely unknown, as reported by a 2021 systematic review (Reis et al., 2022 ). Additionally, the literature suggests that shifting deeper, long-term help-seeking perceptions is likely more difficult for brief interventions, compared to improving short-term mental health knowledge. For example, Tan and colleagues ( 2021 ) evaluated a single-session intervention in Singapore that combined an educational presentation with a speaker who had lived experience of depression. The intervention improved students’ recognition of mental health conditions (i.e., objective knowledge) and temporarily shifted their help-seeking preferences, but the latter effects were not maintained at the three-week follow-up. A broader systematic review by Lo and colleagues ( 2018 ) further supports this trend, showing that while mental health literacy among college students reliably improves with brief interventions, lasting changes in stigma, attitude, and behavioral intention were less consistent, likely requiring additional engagement and/or interventions designed to influence help-seeking perceptions directly. As an example, Shahwan and colleagues ( 2020 ) found that, although a 50-minute anti-stigma intervention initially improved help-seeking attitude among university students, those gains declined in follow-up evaluations. A systematic review by Waqas and colleagues ( 2020 ) further highlights that interventions in educational institutions (schools, colleges, universities) that were longer than four weeks are more likely to produce long-term changes in attitude and intention, suggesting that duration and repeated engagement may be critical for shifting entrenched cultural beliefs. Bloom’s Taxonomy of Learning (Bloom et al., 1956 ; Krathwohl et al., 1964 ) may also explain why brief interventions succeed at promoting short-term improvements in mental health literacy but struggle to affect other mental health help-seeking perceptions (e.g., attitude, intention). According to the taxonomy, at the lowest cognitive level, remembering involves recalling facts (e.g., correctly identifying mental health resources on campus and their services from the intervention). In contrast, higher levels such as evaluating or creating require students to critically assess and internalize new perspectives (Bloom et al., 1956 ). Bloom and colleagues also outlined an affective domain of learning targeting values and beliefs; these outcomes are harder to achieve because they require deeper internalization of values, requiring significantly more time and engagement to develop (Krathwohl et al., 1964 ). Therefore, while factual recall can be accomplished in brief interventions, changing how students feel about mental health help seeking likely requires higher-order or affective processes that generally demand more reinforcement over time. This conclusion is supported by other learning models. According to the Elaboration Likelihood Model (ELM), brief interventions may not provide sufficient opportunity, motivation, or repeated exposure for students to process information through the central route. Instead, they are more likely to rely on peripheral cues (e.g., source credibility or message attractiveness) when forming attitudes, limiting the potential for deeper attitudinal change (Petty & Cacioppo, 1986 ). However, beyond dosage alone, the broader cultural context in which engineering students operate may have played a more significant role in shaping the persistence or attenuation of any potential intervention effects. As students exited the room following our 15-minute presentations, they reentered an academic environment that may not consistently reinforce the values promoted during the intervention. If students are subsequently immersed in a departmental or disciplinary culture that sends implicit or explicit messages that stigmatize vulnerability or prioritize academic achievement over well-being (Wright et al. 2021; Wright et al. 2023 ), such environmental cues may “overwrite” or undermine the salience of our brief message. In contrast, interventions are more likely to be effective and sustainable when they are embedded within a cohesive and consistent cultural framework that communicates mental health as a collective priority across messaging, policies, peer norms and organizations, and faculty-student interactions. One such example is a “whole-school approach”: campuses working collaboratively across their academic community (e.g., students, peer organizations, families, staff) while acknowledging the impact of local and government policies to promote student mental health literacy and mental health perceptions (Sontag-Padilla et al., 2016; O’Reilly et al., 2018 ). Future research and practice should consider how single-session interventions can be integrated into broader departmental and institutional strategies that work in concert to shift social norms and institutional climates toward greater valuing of mental health and openness to help-seeking. The qualitative thematic analysis provided additional context to our quantitative findings, particularly highlighting the value of resource education and tailoring the content to engineering undergraduates. Students highlighted the presentation’s use of engineering student data and testimonials from the university, along with discussing cultural norms and expectations around mental health and help seeking, as key strengths, noting that these elements made them feel less alone and validated in their experiences. Many students described the resource-specific content as the most helpful aspect of the presentation, which aligns with the significant improvements observed in both perceived and objective knowledge across both years. Suggestions for improvement frequently emphasized presentational style and relatability of the speaker, with 2024 students especially advocating for future use of presenters with engineering backgrounds. This feedback is supported by existing literature; within U.S. engineering programs, qualitative work shows students face barriers to formal help-seeking and commonly rely on peers to cope, implying that in-group messengers who “get” engineering culture may be more credible and relatable (Jensen et al., 2023 ). Complementing this, a national survey of U.S. science/engineering instructors found faculty believed disclosing their own depression/anxiety would normalize struggle and provide role models for undergraduates, further emphasizing the belief that normalizing mental health distress within the culture could be beneficial (Busch et al., 2024 ). Overall, our findings through this study were consistent with prior literature on brief interventions. As expected, we observed significant improvements in mental health knowledge and awareness of campus resources. A unique central strength of our study was its scale and potential for institutional impact. Unlike conventional programs such as Question, Persuade, Refer (QPR), which typically target small groups of ‘natural helpers’ (e.g., resident advisors, faculty, staff) (Burnette et al., 2015 ’ Tompkins & Witt, 2009 ; Taub et al., 2013 ), our curriculum-embedded intervention reached a full undergraduate engineering population (~ 4,500 students across two years). This scope positions our project among the few large-scale, college-wide efforts to promote mental health literacy in engineering. In contrast to traditional small-group training models, which often result in limited coverage, our intervention achieved widespread exposure across the engineering student body. This greater saturation enhances the probability that distressed students will have access to informed peers who can help them navigate mental health resources. Our program constitutes an early and practical step toward a “whole-college approach” to destigmatizing help-seeking and promoting wellness in engineering education. While our training was not policy-driven (e.g., we did not implement formal mandates such as faculty-required compliance or curricular policy changes), its success lay in being a scalable, low-investment intervention that could be flexibly embedded within existing courses, offering an accessible entry point for broader institutional change. By providing students with accurate, discipline-specific psychoeducation and resource knowledge while normalizing conversations around seeking help toward mental health, the training contributes incremental momentum toward larger, college-supported strategies and programming. Within this context, our brief presentation serves as one voice within a much larger engineering culture: a single message likely competing with other powerful influences previously discussed such as academic norms, performance pressures, and perceptions of self-reliance. Although one 15-minute intervention alone cannot overturn these entrenched cultural dynamics, it can catalyze attitudinal shifts when paired with other consistent reinforcements across the college. This perspective aligns with emerging evidence that meaningful cultural change in STEM education requires multi-level, sustained engagement across students, faculty, and administration. Indeed, recent grants awarded by the National Science Foundation (NSF) to support mental-health initiatives within STEM contexts, including the M-HOPES project for graduate STEM students (Montana State University Billings, n.d.) the five-year Institutional Transformation Project at Montclair State University designed to embed group-counselling into STEM internships (Montclair State University, 2024), and the Engineering Wellness Center at the University of Kentucky designed to prioritize the social and emotional wellness of engineering students (University of Kentucky, n.d.), signal a broader institutional commitment to improving mental health among STEM student populations. Future studies should evaluate how sustained funding, and coordinated programming e.g., faculty development workshops, departmental initiatives, peer-led interventions) and changes to policy structures (e.g., recognition for faculty and staff efforts related to student well-being) can build on this scalable model to foster a cohesive and sustainable culture of wellness. Addressing Limitations Through Future Research Several limitations of this study should be acknowledged. Firstly, although t-test results suggested improvements in several perceived knowledge items, the 2024 Repeated Measures ANOVA analyses demonstrated that only some of these effects remained significant when accounting for within-subject change and between-group differences, indicating that certain knowledge gains may have been more modest than initially suggested. Secondly, while the study included a large sample, the survey responses were voluntary and therefore may be subject to self-selection bias; students who chose to complete the surveys may differ systematically from those who did not, potentially limiting the representativeness of the findings. For instance, because the email inviting students to complete the survey mentioned mental health, students with more positive beliefs about mental health and help seeking might have been more likely to complete the survey. We attempted to mitigate this sampling bias through a monetary incentive for survey participation. Thirdly, demographic data were incomplete for the 2023 Training sample, making it difficult to assess whether observed effects varied across different identities. However, the demographic distribution of those that did provide data was similar to those in the No Training group, suggesting that the data was collected from a representative population of students. Additionally, the time interval between the intervention and post-assessment was not strictly standardized across participants (i.e., some participants provided post-assessment data a few days after receiving the intervention whereas others provided data a few weeks after), which may have contributed to variability in recall and scoring. Finally, the study was conducted at a single large public university in the southeastern United States, and findings may not generalize to other institutional contexts with different engineering cultures, student populations, or mental health resource availability. Future studies should consider implementing longitudinal versions of this training to evaluate whether repeated exposure, combined with broader institutional support and policy changes, can more effectively shift deeply rooted mental health help seeking perceptions. Enhancing the training by having it delivered by engineering student peers may also increase its relatability and destigmatizing impact, as this approach has been positively received in similar interventions (Paul et al., 2020 ). More broadly, additional studies that continue to measure specific help-seeking constructs from the Integrated Behavioral Model of Mental Health Help Seeking (IBM-HS) would enable stronger comparisons across studies and contribute to a more robust understanding of help-seeking patterns within engineering student populations. Conclusion Grounded in the Integrated Behavioral Model for Mental Health Help Seeking, this study advances the limited literature on engineering-specific mental health interventions by demonstrating that a brief, scalable presentation can significantly improve students’ perceived and objective knowledge of mental health resources, an outcome consistent with Bloom’s Taxonomy and expectations for short-form educational programs. Consistent with this theoretical expectation, more entrenched help-seeking beliefs (e.g., prioritizing academics over mental health) and perceptions (intention, attitude, perceived norm, personal agency) were not significantly changed, reflecting the complexity of shifting cultural norms around distress, productivity, and self-reliance within engineering training programs. By reaching nearly 4,500 students across two years, this curriculum-embedded approach represents an early step toward a scalable, whole-college strategy for mental health promotion. Continued efforts are needed to refine interventions for this population and integrate them into coordinated departmental and institutional strategies that make help-seeking a supported and expected part of the engineering student experience. Abbreviations ANOVA: Analyses of Variance DRC: Disability Resource Center ELM: Elaboration Likelihood Model Gen AI: Generative Artificial Intelligence IBM-HS: Integrated Behavioral Model of Mental Health Help Seeking IBM SPSS: International Business Machines Corporation Statistical Package for the Social Sciences IRB: Institutional Review Board LGBQ+: Lesbian, Gay, Bisexual, Queer/Questioning, Plus LGBTQIA: Lesbian, Gay, Bisexual, Transgender, Queer/Questioning, Intersex, Asexual MHSIS: Mental Health Help-Seeking Intention Scale NSF: National Science Foundation QPR: Question, Persuade, Refer ST-TA: Structured Tabular Thematic Analysis STEM: Science, Technology, Engineering, Mathematics UE-MH-HSI: Undergraduate Engineering Mental Health Help-Seeking Instrument Declarations Availability of Data and Materials Researchers interested in accessing our de-identified data or study instruments are welcome to contact the research team for more information. Competing Interests We have no conflicts of interest to disclose, and this manuscript has not been published nor submitted simultaneously for publication elsewhere. Human Ethics and Consent to Participate This study was approved by the Institutional Review Board (Protocol #86047) at [name of institution redacted for masked peer review]. All participants provided informed consent prior to survey participation, and all procedures complied with institutional and national ethical standards for human subjects research. Funding This research was supported by grants from the [ name of institutional redacted ] Institutional Multidisciplinary Paradigm to Accelerate Collaboration and Transformation initiative and the National Science Foundation (Award Numbers [ redacted for masked peer review ] and [redacted for masked peer review ]). Any opinions, findings, conclusions, or recommendations expressed in the material are those of the authors and do not necessarily reflect those of the National Science Foundation. Author’s Contributions [ redacted for masked peer review and included separately in submission ] Acknowledgements The authors acknowledge the contributions of the eight mental health training presenters and [ redacted for masked peer review ], an undergraduate Engineering major who assisted in the thematic coding of our qualitative data. Lastly, thank you to the students who took the time to contribute their perspectives to our studies. Authors’ Information [ redacted for masked peer review ] References Abiade, J., & Moliski, J. (2020, June). Work-in Progress: Identity and transitions laboratory: Utilizing acceptance and commitment therapy framework to support engineering student success. In 2020 ASEE Virtual Annual Conference Content Access . Akter, M. J., Mim, A. S., Afrin, S., Ahad, A., Kundu, A., & Bijoy, M. H. I. (2025, February). Mental Health in Engineering Students: Investigating the Factors of Depression and Coping Mechanisms. In 2025 International Conference on Electrical, Computer and Communication Engineering (ECCE) (pp. 1-7). IEEE. Armstrong, R. A. (2014). When to use the Bonferroni correction. Ophthalmic and physiological optics , 34 (5), 502-508. Arria, A. M., Caldeira, K. M., Vincent, K. B., Winick, E. R., Baron, R. A., & O'Grady, K. E. (2013). Discontinuous college enrollment: Associations with substance use and mental health. Psychiatric Services , 64 (2), 165-172. Asghar, M., Minichiello, A., & Ahmed, S. (2024). Mental health and wellbeing of undergraduate students in engineering: A systematic literature review. Journal of Engineering Education , 113 (4), 1046-1075. Ban, N., Mensah, L. O., Whitwer, M., Hargis, L. E., Wright, C. J., Hammer, J. H., & Wilson, S. A. (2023). “It’s very important to my professors… at least most of them”: How messages from engineering faculty and staff influence student beliefs around seeking help for their mental health. In 2023 ASEE annual conference & exposition. Ban, N., H. Shannon, C. J. Wright, M. E. Miller, L. E. Hargis, E. L. Usher, J. H. Hammer, and S. A. Wilson (2022). "Identifying common perceived stressors and stress-relief strategies among undergraduate engineering students." In ASEE annual conference exposition . Beddoes, K., & Danowitz, A. (2022, August). In their own words: How aspects of engineering education undermine students’ mental health. In 2022 ASEE annual conference & exposition . Blanca, M. J., Arnau, J., García-Castro, F. J., Alarcón, R., & Bono, R. (2023). Repeated measures ANOVA and adjusted F-tests when sphericity is violated: which procedure is best?. Frontiers in Psychology , 14 , 1192453. Bloom, B. S., Engelhart, M. D., Furst, E. J., Hill, W. H., & Krathwohl, D. R. (1956). Taxonomy of educational objectives: The classification of educational goals. Handbook I: Cognitive domain . David McKay Company. Burnette, C., Ramchand, R., & Ayer, L. (2015). Gatekeeper Training for Suicide Prevention: A Theoretical Model and Review of the Evidence. RAND Corporation. Busch, C. A., Barstow, M., Brownell, S. E., & Cooper, K. M. (2024). Why US science and engineering undergraduates who struggle with mental health are left without role models. PLOS Mental Health , 1 (7), e0000086. Cantoni, N. P., & Parker, V. L. (2025). Observing an Intervention to Reduce Treatment Stigma of College Students: Canine-Assisted Counseling vs. Treatment as Usual. Anthrozoös , 1-14. Cornally, N., & McCarthy, G. (2011). Help-seeking behaviour: A concept analysis. International journal of nursing practice , 17 (3), 280-288. Doll, C. M., Michel, C., Rosen, M., Osman, N., Schimmelmann, B. G., & Schultze-Lutter, F. (2021). Predictors of help-seeking behaviour in people with mental health problems: A 3-year prospective community study. BMC Psychiatry, 21 (1), 432. Eren-Sisman, E. N., Cigdemoglu, C., & Geban, O. (2018). The effect of peer-led team learning on undergraduate engineering students’ conceptual understanding, state anxiety, and social anxiety. Chemistry Education Research and Practice , 19 (3), 694-710. Godfrey, E., & Parker, L. (2010). Mapping the cultural landscape in engineering education. Journal of Engineering education , 99 (1), 5-22. Fishbein, M., & Ajzen, I. (2011). Predicting and changing behavior: The reasoned action Gastwirth, J. L., Gel, Y. R., & Miao, W. (2009). The impact of Levene’s test of equality of variances on statistical theory and practice. Statistical Science, 24 (3), 343-360. Grasty, K., Sakri, S., Arnold, A. C., Bekki, J. M., Wilkins-Yel, K. G., Natarajan, M., Bernstein, B. L., & Randall, A. K. (2021, July). Benefits of Utilizing Counseling Services Among Doctoral Women of Color in STEM. In 2021 ASEE Virtual Annual Conference Content Access . Hammer, J. H., Parent, M. C., & Spiker, D. A. (2018). Mental Help Seeking Attitudes Scale (MHSAS): Development, reliability, validity, and comparison with the ATSPPH-SF and IASMHS-PO. Journal of counseling psychology , 65 (1), 74. Hammer, J. H., Vogel, D. L., Grzanka, P. R., Kim, N., Keum, B. T., Adams, C., & Wilson, S. A. (2024). The integrated behavioral model of mental health help seeking (IBM-HS): A health services utilization theory of planned behavior for accessing care. Journal of Counseling Psychology . Hammer, J. H., Wright, C. J., Miller, M. E., & Wilson, S. A. (2024). The Undergraduate Engineering Mental Health Help-Seeking Instrument (UE-MH-HSI): Development and validity evidence. Journal of Engineering Education , 113 (4), 1198-1225. Hampton, C., Reeping, D., & Ozkan, D. S. (2021). Positionality statements in engineering education research: A look at the hand that guides the methodological tools. Studies in Engineering Education , 1 (2). Hyseni Duraku, Z., Davis, H., & Hamiti, E. (2023). Mental health, study skills, social support, and barriers to seeking psychological help among university students: a call for mental health support in higher education. Frontiers in Public Health , 11 , 1220614.Jensen, K. J., & Cross, K. J. (2021). Engineering stress culture: Relationships among mental health, engineering identity, and sense of inclusion. Journal of Engineering Education , 110 (2), 371-392. Jensen, K. J., & Cross, K. J. (2021). Engineering stress culture: Relationships among mental health, engineering identity, and sense of inclusion. Journal of Engineering Education, 110 (2), 371-392. Jensen, K. J., Mirabelli, J. F., Kunze, A. J., Romanchek, T. E., & Cross, K. J. (2023). Undergraduate student perceptions of stress and mental health in engineering culture. International Journal of STEM Education , 10 (1), 30. Joshi, A., & Kiran, R. (2020). Gauging the effectiveness of music and yoga for reducing stress among engineering students: An investigation based on Galvanic Skin Response. Work , 65 (3), 671-678. Kalamatianos, A., Kounenou, K., & Pezirkianidis, C. (2025, February). The Implementation of a Blended Counseling Intervention in Undergraduate Engineering Students: The Effect on Mental Health. In Healthcare (Vol. 13, No. 5, p. 511). MDPI. Kamal, S. A., Sánchez-Peña M. L., Ramirez, N., & Samuel, D. B. (2025, June). Exploring changes in mental health conditions’ stigma levels and help-seeking attitudes among engineering students. In 2025 ASEE Annual Conference & Exposition . Kirn, A., & Benson, L. (2018). Engineering students' perceptions of problem solving and their future. Journal of Engineering Education , 107 (1), 87-112. Krathwohl, D. R., Bloom, B. S., & Masia, B. B. (1964). Taxonomy of educational objectives: Handbook II: Affective domain . David McKay Company. Krause, S. J., Middleton, J. A., Judson, E., Ernzen, J., Beeley, K. R., & Chen, Y. C. (2015, June). Factors impacting retention and success of undergraduate engineering students. In 2015 ASEE Annual Conference & Exposition . Laschke, L., Flottmann, M., & Schlüter, K. (2023). Let’s ask the teachers: A qualitative analysis of health education in schools and its effectiveness. Sustainability, 15 (6), 4887. Lippe, M., Johnson, B., & Carter, P. (2019). Protecting student anonymity in research using a subject-generated identification code. Journal of Professional Nursing , 35 (2), 120-123. Lipson, S. K., Zhou, S., Abelson, S., Heinze, J., Jirsa, M., Morigney, J., Patterson, A., Singh, M., & Eisenberg, D. (2022). Trends in college student mental health and help-seeking by race/ethnicity: Findings from the national Healthy Minds Study, 2013–2021. Journal of Affective Disorders, 306 , 138-147. https://doi.org/10.1016/j.jad.2022.03.038 Liu, L. G., Russell, D., Turchioe, M. R., Myers, A. C., Vawdrey, D. K., & Creber, R. M. M. (2022). Effect of expansion of abbreviations and acronyms on patient comprehension of their health records: a randomized clinical trial. JAMA Network Open , 5 (5), e2212320-e2212320. Lo, K., Gupta, T., & Keating, J. L. (2018). Interventions to promote mental health literacy in university students and their clinical educators: A systematic review of randomised control trials. Health Professions Education, 4(3), Article 2. Melnyk, B. M., Amaya, M., Szalacha, L. A., Hoying, J., Taylor, T., & Bowersox, K. (2015). Feasibility, acceptability, and preliminary effects of the COPE online cognitive-behavioral skill-building program on mental health outcomes and academic performance in freshmen college students: A randomized controlled pilot study. Journal of Child and Adolescent Psychiatric Nursing , 28 (3), 147-154. Miller, I., & Jensen, K. (2020). Introduction of mindfulness in an online engineering core course during the COVID-19 pandemic. Advances in engineering education , 8 (4). Mojtabai, R., Stuart, E. A., Hwang, I., Eaton, W. W., Sampson, N., & Kessler, R. C. (2015). Long-term effects of mental disorders on educational attainment in the National Comorbidity Survey ten-year follow-up. Social psychiatry and psychiatric epidemiology , 50 (10), 1577-1591. Montana State University Billings. (n.d.). M-HOPES: A Mental Health Initiative . Graduate Studies. https://msubillings.edu/grad/m-hopes.htm Montclair State University. (2024, November 11). Montclair State University receives $3 million grant to provide mental-health services during internship experiences. https://www.montclair.edu/newscenter/2024/11/11/montclair-state-university-receives-3-million-grant-to-provide-mental-health-services-during-internship-experiences/ Nazari, A., Garmaroudi, G., Foroushani, A. R., & Hosseinnia, M. (2023). The effect of web-based educational interventions on mental health literacy, stigma and help-seeking intentions/attitudes in young people: systematic review and meta-analysis. BMC psychiatry, 23 (1), 647. Nazari, A., Garmaroudi, G., & Rabiei, M. (2024). A systematic review: increasing mental health literacy in students through “The Guide”. Discover Psychology, 4 (1), 96. O’Sullivan, G. (2011). The relationship between hope, eustress, self-efficacy, and life satisfaction among undergraduates. Social indicators research , 101 (1), 155-172. O’Reilly, M., Svirydzenka, N., Adams, S., & Dogra, N. (2018). Review of mental health promotion interventions in schools. Social psychiatry and psychiatric epidemiology, 53 (7), 647-662. Paul, F. A., Ganie, A. U. R., & Dar, D. R. (2024). Substance use in university students: a comprehensive examination of its effects on academic achievement and psychological well-being. Social Work in Mental Health , 22 (3), 452-484. Paul, R., Dedemus, D., Boyce, M., & Johnston, K. (2020). The “Engineers Have Feelings” project: Integrating mental wellness and lifelong learning skills in first-year undergraduate engineering courses. Proceedings of the Canadian engineering education association (CEEA) . Pedrelli, P., Nyer, M., Yeung, A., Zulauf, C., & Wilens, T. (2015). College students: mental health problems and treatment considerations. Academic psychiatry , 39 (5), 503-511. Petty, R. E., & Cacioppo, J. T. (1986). Communication and persuasion: Central and peripheral routes to attitude change . Springer. Pituch, K. A., & Stevens, J. P. (2015). Applied multivariate statistics for the social sciences: Analyses with SAS and IBM’s SPSS . Routledge. Raghavan, V., Chandrasekaran, S., Paul, V., Pattabiraman, R., Mohan, G., Durairaj, J., Currie, G., Lilford, R., Furtado, V., Madan, J., Birchwood, M., Meyer, C., Sood, M., Chadda, R., Mohan, M., Shah, J., John, S., Padmavati, R., Iyer, S., Thara, R., Singh, S., & the WIC Consortium. (2024). Effectiveness of a mental health literacy module on stigma-related mental health knowledge and behaviour among youth in two educational settings in Chennai, South India: A quasi-experimental study. Asian Journal of Psychiatry, 98 , Article 104074 Reis, A. C., Saheb, R., Moyo, T., Smith, C., & Sperandei, S. (2022). The impact of mental health literacy training programs on the mental health literacy of university students: A systematic review. Prevention Science , 23 (4), 648-662. Robinson, O. C. (2022). Conducting thematic analysis on brief texts: The structured tabular approach. Qualitative Psychology , 9 (2), 194. Rodríguez-Jiménez, R. M., Carmona, M., García-Merino, S., Díaz-Ureña, G., & Lara Bercial, P. J. (2022). Embodied learning for well-being, self-awareness, and stress regulation: a randomized trial with engineering students using a mixed-method approach. Education Sciences , 12 (2), 111. Secules, S., McCall, C., Mejia, J. A., Beebe, C., Masters, A. S., L. Sánchez-Peña, M., & Svyantek, M. (2021). Positionality practices and dimensions of impact on equity research: A collaborative inquiry and call to the community. Journal of Engineering Education , 110 (1), 19-43. Sánchez-Peña, M. L., McAlister, A. M., Ramirez, N. M., & Kamal, S. A. (2025). Elements of engineering culture affecting undergraduate students' mental health and their help-seeking attitudes. Journal of Engineering Education , 114 (3), e70017. Sánchez-Peña, M. L., McAlister, A. M., Ramirez, N., Samuel, D. B., Kamal, S. A., & Xu, X. (2023). Stigma of mental health conditions within engineering culture and its relation to help-seeking attitudes: Insights from the first year of a longitudinal study. In American Society for Engineering Education Annual Conference & Exposition . Shahwan, S., Lau, J. H., Goh, C. M. J., Ong, W. J., Tan, G. T. H., Kwok, K. W., Samari, E., Lee, Y. Y., Teh, W. L., Seet, V., Chang, S., Chong, S. A., & Subramaniam, M. (2020). The potential impact of an anti-stigma intervention on mental health help-seeking attitudes among university students. BMC Psychiatry, 20 , Article 562. Schober, P., & Vetter, T. R. (2018). Repeated measures designs and analysis of longitudinal data: If at first you do not succeed—try, try again. Anesthesia & Analgesia , 127 (2), 569-575. Sheldon, E., Simmonds-Buckley, M., Bone, C., Mascarenhas, T., Chan, N., Wincott, M., Gleeson, H., Sow, K., Hind, D., & Barkham, M. (2021). Prevalence and risk factors for mental health problems in university undergraduate students: A systematic review with meta-analysis. Journal of Affective Disorders, 287 , 282-292. Shim, Y. R., Eaker, R., & Park, J. (2022). Mental health education, awareness and stigma regarding mental illness among college students. Journal of Mental Health & Clinical Psychology, 6 (2), 6-15. Sochacka, N. W., Walther, J., & Pawley, A. L. (2018). Ethical validation: Reframing research ethics in engineering education research to improve research quality. Journal of Engineering Education , 107 (3), 362-379. Sochacka, N. W., Walther, J., Rich, J. R., & Brewer, M. A. (2021). A narrative analysis of stories told about engineering in the public discourse: Implications for equity and inclusion in engineering. Studies in Engineering Education , 2 (2). Sontag-Padilla, L., Dunbar, M. S., Ye, F., Kase, C., Fein, R., Abelson, S., ... & Stein, B. D. (2018). Strengthening college students’ mental health knowledge, awareness, and helping behaviors: the impact of active minds, a peer mental health organization. Journal of the American Academy of Child & Adolescent Psychiatry, 57 (7), 500-507. Su, C. H. (2016). The effects of students' motivation, cognitive load and learning anxiety in gamification software engineering education: a structural equation modeling study. Multimedia Tools and Applications , 75 (16), 10013-10036. Tait, J. E., Alexander, L. A., Hancock, E. I., & Bisset, J. (2024). Interventions to support the mental health and wellbeing of engineering students: a scoping review. European journal of engineering education , 49 (1), 45-69. Tan, G. T. H., Shahwan, S., Abdin, E., Lau, J. H., Goh, C. M. J., Ong, W. J., Samari, E., Kwok, K. W., Chong, S. A., & Subramaniam, M. (2021). Recognition of depression and help-seeking preference among university students in Singapore: An evaluation of the impact of Advancing Research to Eliminate Mental Illness Stigma: An education and contact intervention. Frontiers in Psychiatry, 12 , Article 582730. Taub, D.J., Servaty-Seib, H.L., Miles, N., Lee, J.-Y., Morris, C.A.W., Prieto-Welch, S.L. and Werden, D. (2013), The Impact of Gatekeeper Training for Suicide Prevention on University Resident Assistants. Journal of College Counseling, 16 : 64-78. Tompkins, T. L., & Witt, J. (2009). The short-term effectiveness of a suicide prevention gatekeeper training program in a college setting with residence life advisers. Journal of Primary Prevention, 30 (2), 131–149. University of Kentucky. (n.d.). About us – NSF Grant Team . Engineering Wellness Center. https://engr.uky.edu/ewc/about-us-nsf-grant-team Vick, E., Wilson, S. A., Hammer, J. H., Whitwer, M., & Gentry, A. N. (2025, June). Engineering student mental health status across gender identities: Analysis of data from the Healthy Minds Study. In 2025 ASEE Annual Conference & Exposition . Vitasari, P., Wahab, M. N. A., Herawan, T., Othman, A., & Sinnadurai, S. K. (2011). A pilot study of pre-post anxiety treatment to improve academic performance for engineering students. Procedia-Social and Behavioral Sciences , 15 , 3826-3830. Walton, G. M., Logel, C., Peach, J. M., Spencer, S. J., & Zanna, M. P. (2015). Two brief interventions to mitigate a “chilly climate” transform women’s experience, relationships, and achievement in engineering. Journal of educational Psychology , 107 (2), 468. Wang, X., Yang, M., Ren, L., Wang, Q., Liang, S., Li, Y., Li, Y., Zhan, Q., Huang, S., Xie, K., Liu, J., Li, X., & Wu, S. (2024). Burnout and depression in college students. Psychiatry Research, 335 , 115828. Waqas, A., Malik, S., Fida, A., Abbas, N., Mian, N., Miryala, S., Amray, A. N., Shah, Z., & Naveed, S. (2020). Interventions to reduce stigma related to mental illnesses in educational institutes: A systematic review. Psychiatric Quarterly, 91 (3), 887–903. Watkins, D. C., Hunt, J. B., & Eisenberg, D. (2012). Increased demand for mental health services on college campuses: Perspectives from administrators. Qualitative Social Work , 11 (3), 319-337. Weston, R., & Gore Jr, P. A. (2006). A brief guide to structural equation modeling. The counseling psychologist , 34 (5), 719-751. Whitwer, M. D., Wilson, S. A., Hammer, J. H., & Gomer, B. (2025). Mental health and treatment use in undergraduate engineering students: A comparative analysis to students in other academic fields of study. Journal of Engineering Education , 114 (1), e20629. Wilson, S. A., Blaber, I. P., Hancock, J. M., Pitcher, G. R., & Hammer, J. H. (2023). Delivery of mental health training across a College of Engineering. In Proceedings of the 51st Annual Conference of the European Society for Engineering Education (SEFI) . Wilson, S. A., Huth, A. K., Lamer, S. X., Hammer, J. H., & Whitwer, M. (2024, June). Investigating perceptions that predict mental health related help-seeking in first-year engineering students. In 2024 ASEE Annual Conference & Exposition . Wilson, S.A, Wilder, K., Blackburn-Lynch, W., Hammer, J.H, & Dailey, D. (2022, August). Investigating mental health distress and help-seeking perceptions in first-year engineering students. In 2022 ASEE annual conference & exposition . Wright, C. J., Hargis, L. E., Usher, E. L., Hammer, J. H., Wilson, S. A., & Miller, M. E. (2021, July). Identifying engineering students’ beliefs about seeking help for mental health concerns. In 2021 ASEE Virtual Annual Conference Content Access . Wright, C. J., Wilson, S. A., Hammer, J. H., Hargis, L. E., Miller, M. E., & Usher, E. L. (2023). Mental health in undergraduate engineering students: Identifying facilitators and barriers to seeking help. Journal of Engineering Education , 112 (4), 963-986. Zhao, R., Amanvermez, Y., Pei, J., Castro-Ramirez, F., Rapsey, C., Garcia, C., Ebert, D.D., Haro, J.M., Fodor, L.A., David, O.A., Rankin, O., Chua, S.N., Martínez, V., Bruffaerts, R., Kessler, R.C. and Cuijpers, P. (2025). Research Review: Help-seeking intentions, behaviors, and barriers in college students–a systematic review and meta-analysis. Journal of child psychology and psychiatry . Additional Declarations No competing interests reported. Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-8205457","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":556516801,"identity":"21727692-f461-4d49-a97a-b79cc9015f3b","order_by":0,"name":"Joshua Parrott","email":"","orcid":"","institution":"University of Kentucky","correspondingAuthor":false,"prefix":"","firstName":"Joshua","middleName":"","lastName":"Parrott","suffix":""},{"id":556516802,"identity":"3730f6df-0ac8-4356-8746-626527ed27a3","order_by":1,"name":"Hammer Joseph","email":"","orcid":"","institution":"University of Kentucky","correspondingAuthor":false,"prefix":"","firstName":"Hammer","middleName":"","lastName":"Joseph","suffix":""},{"id":556516809,"identity":"b1fac92c-b453-4af1-85b1-fef49d31497e","order_by":2,"name":"Elahe Vahidi","email":"","orcid":"","institution":"University of Kentucky","correspondingAuthor":false,"prefix":"","firstName":"Elahe","middleName":"","lastName":"Vahidi","suffix":""},{"id":556516811,"identity":"97863502-72dd-4ce0-8dbd-6861238622cf","order_by":3,"name":"Nayeon Kim","email":"","orcid":"","institution":"University of Kentucky","correspondingAuthor":false,"prefix":"","firstName":"Nayeon","middleName":"","lastName":"Kim","suffix":""},{"id":556516813,"identity":"7d932310-3482-40b9-b73d-0978770431b3","order_by":4,"name":"Sarah Wilson","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAAy0lEQVRIiWNgGAWjYDACZuYGMM0PFzlAUAsjRItkA9FaGKBaDOAqCWkxOM7Y/OHjjjp549uHj0n83MEgx3cjgYCWw4xtkjPPHDbcdi4tTbL3DIOxJCEtZkAtzLxtBxi3neExu8HbxpC4gQgtzZ952+rsN/fwmN3828ZQT4yWBmneNubEDTw8ZreBtiQYENJiD/ZL2+HkGWfY0n/LtkkYzjzzAL8Wyf7Dhz98bKuz7e9hPmz4ts1Gnu84AVvQgQRpykfBKBgFo2AUYAcATHFGf4aBRRoAAAAASUVORK5CYII=","orcid":"","institution":"Rowan University","correspondingAuthor":true,"prefix":"","firstName":"Sarah","middleName":"","lastName":"Wilson","suffix":""}],"badges":[],"createdAt":"2025-11-25 16:53:28","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-8205457/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-8205457/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":97647197,"identity":"8e8d8ec9-b17a-42ba-837b-25726d0f621c","added_by":"auto","created_at":"2025-12-08 05:11:27","extension":"docx","order_by":0,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":340344,"visible":true,"origin":"","legend":"","description":"","filename":"AnonymisedMainDocumentwithAbstract.docx","url":"https://assets-eu.researchsquare.com/files/rs-8205457/v1/ddb8a0134c292661ef79bffe.docx"},{"id":97647188,"identity":"4ba885c7-a434-4add-a170-545477171d1c","added_by":"auto","created_at":"2025-12-08 05:11:26","extension":"json","order_by":1,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":6847,"visible":true,"origin":"","legend":"","description":"","filename":"4dcfb288da134d10ae42611afa5104ac.json","url":"https://assets-eu.researchsquare.com/files/rs-8205457/v1/72f9bde72e57a9246fbb284d.json"},{"id":97647189,"identity":"49447515-4488-4b4e-9089-22dd4b62cbb4","added_by":"auto","created_at":"2025-12-08 05:11:26","extension":"xml","order_by":2,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":274664,"visible":true,"origin":"","legend":"","description":"","filename":"4dcfb288da134d10ae42611afa5104ac1enriched.xml","url":"https://assets-eu.researchsquare.com/files/rs-8205457/v1/c9bcc7da63d50e6dfc1a7d6c.xml"},{"id":97674573,"identity":"3b8d0a98-b0f6-4ba4-a872-f2a50366974c","added_by":"auto","created_at":"2025-12-08 09:43:38","extension":"png","order_by":7,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":8500,"visible":true,"origin":"","legend":"","description":"","filename":"Onlinefloatimage1.png","url":"https://assets-eu.researchsquare.com/files/rs-8205457/v1/23220a4ec97fe3e9e0c52ce2.png"},{"id":97647191,"identity":"0cf34037-273f-4217-842e-0540cebad86f","added_by":"auto","created_at":"2025-12-08 05:11:26","extension":"png","order_by":8,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":6438,"visible":true,"origin":"","legend":"","description":"","filename":"Onlinefloatimage2.png","url":"https://assets-eu.researchsquare.com/files/rs-8205457/v1/45152914b723f9988aafb6b4.png"},{"id":97647195,"identity":"142441bd-b08f-4813-a627-b502fec2d7a2","added_by":"auto","created_at":"2025-12-08 05:11:27","extension":"png","order_by":9,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":8580,"visible":true,"origin":"","legend":"","description":"","filename":"Onlinefloatimage3.png","url":"https://assets-eu.researchsquare.com/files/rs-8205457/v1/c169a90cdc8c31199613bab3.png"},{"id":97647194,"identity":"3fbb8b20-05a9-4823-9b63-83b8990ef26b","added_by":"auto","created_at":"2025-12-08 05:11:26","extension":"png","order_by":10,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":10907,"visible":true,"origin":"","legend":"","description":"","filename":"Onlinefloatimage4.png","url":"https://assets-eu.researchsquare.com/files/rs-8205457/v1/24b9cabd9e0562cbbf235cfd.png"},{"id":97647193,"identity":"123d289a-fa16-4dd0-be43-8c3dd11a8443","added_by":"auto","created_at":"2025-12-08 05:11:26","extension":"xml","order_by":11,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":270373,"visible":true,"origin":"","legend":"","description":"","filename":"4dcfb288da134d10ae42611afa5104ac1structuring.xml","url":"https://assets-eu.researchsquare.com/files/rs-8205457/v1/1548fa426c8f19a43f55bffe.xml"},{"id":97647196,"identity":"42c26560-f166-4d49-9bec-b61838236c53","added_by":"auto","created_at":"2025-12-08 05:11:27","extension":"html","order_by":12,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":289362,"visible":true,"origin":"","legend":"","description":"","filename":"earlyproof.html","url":"https://assets-eu.researchsquare.com/files/rs-8205457/v1/71135be3137e5f96686ff740.html"},{"id":97647185,"identity":"2d5fa2f6-88d5-46e2-a835-0ab2460028ef","added_by":"auto","created_at":"2025-12-08 05:11:26","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":15967,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eFigure 2.\u003c/strong\u003e\u003cem\u003e\u003cstrong\u003e Effect of Training on Perceived Knowledge\u003c/strong\u003e\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eNote: \u003c/em\u003eAn asterisk (*) indicates a significant difference between independent groups within years (\u003cem\u003ep\u003c/em\u003e \u0026lt; .05).\u003c/p\u003e","description":"","filename":"floatimage1.png","url":"https://assets-eu.researchsquare.com/files/rs-8205457/v1/8971eac51cd6d2dc2733b33d.png"},{"id":97673502,"identity":"f02ac0a3-70f1-47aa-8887-993530588c0c","added_by":"auto","created_at":"2025-12-08 09:40:27","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":14407,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eFigure 3.\u003c/strong\u003e\u003cem\u003e\u003cstrong\u003e Effect of Training on Objective Knowledge\u003c/strong\u003e\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eNote: \u003c/em\u003eAn asterisk (*) indicates a significant difference between independent groups within years (\u003cem\u003ep\u003c/em\u003e \u0026lt; .05).\u003c/p\u003e","description":"","filename":"floatimage2.png","url":"https://assets-eu.researchsquare.com/files/rs-8205457/v1/ae8ae95071975225b1f3d6a3.png"},{"id":97647187,"identity":"bf470632-b5c5-4e9b-8ff6-11443d3ec422","added_by":"auto","created_at":"2025-12-08 05:11:26","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":17009,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eFigure 4.\u003c/strong\u003e\u003cem\u003e\u003cstrong\u003e Effect of Training on Prioritization of Mental Health and Help-Seeking Intention\u003c/strong\u003e\u003c/em\u003e\u003c/p\u003e","description":"","filename":"floatimage3.png","url":"https://assets-eu.researchsquare.com/files/rs-8205457/v1/2e8d817f236a7a6dee0ca00e.png"},{"id":97647190,"identity":"abc9f7bd-6f88-41ba-b9cc-e82db053ba8f","added_by":"auto","created_at":"2025-12-08 05:11:26","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":21981,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eFigure 5.\u003c/strong\u003e\u003cem\u003e\u003cstrong\u003e Effect of Training on Help-Seeking Perceptions in 2023 and 2024 Independent Sample Studies\u003c/strong\u003e\u003c/em\u003e\u003c/p\u003e","description":"","filename":"floatimage4.png","url":"https://assets-eu.researchsquare.com/files/rs-8205457/v1/8a889bb738729c62a80096c0.png"},{"id":105012940,"identity":"b4725c9e-a324-4354-be57-27607a1c24d1","added_by":"auto","created_at":"2026-03-19 21:39:35","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1801408,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-8205457/v1/8fa06d8f-8653-44e4-9f55-335ca82e8146.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Challenging the Culture of Stress: Evaluating a Brief, Theory-Driven Mental Health Help-Seeking Intervention for Undergraduate Engineering Students","fulltext":[{"header":"INTRODUCTION","content":"\u003cp\u003eMental health concerns and treatment use among undergraduate students have risen in recent years (Lipson et al., \u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e2022\u003c/span\u003e; Sheldon et al., \u003cspan citationid=\"CR63\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; Watkins et al., 2011). Students can remain untreated due to their low mental health help-seeking intention; a meta-analysis found that only 41% of college students with mental health concerns considered seeking help, and just 28% followed through, citing barriers like self-reliance, time constraints, limited resource awareness, and low perceived need (Zhao et al., \u003cspan citationid=\"CR87\" class=\"CitationRef\"\u003e2025\u003c/span\u003e). With low help seeking and poor adherence to treatment, mental health distress among college students can worsen over time, becoming chronic (Pedrelli et al., \u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e2015\u003c/span\u003e) and negatively impacting student retention and academic performance (Mojtabai et al., \u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e2015\u003c/span\u003e; Arria et al., \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e2013\u003c/span\u003e; Melnyk et al., \u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e2015\u003c/span\u003e; Vitasari et al., \u003cspan citationid=\"CR75\" class=\"CitationRef\"\u003e2011\u003c/span\u003e). Therefore, it is crucial to develop strategies to reduce barriers and promote timely access to mental health services for college students broadly (Doll et al., \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e2021\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eWithin undergraduate engineering, students experience high levels of mental health distress yet demonstrate lower treatment utilization compared to peers in other disciplines (Whitwer et al., \u003cspan citationid=\"CR81\" class=\"CitationRef\"\u003e2025\u003c/span\u003e). These mental health challenges can be exacerbated by academic norms (e.g., heavy academic workloads, sleep disturbances, normalization of stress) (Asghar et al., \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e2024\u003c/span\u003e; Akter et al., 2025; Jensen \u0026amp; Cross, \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; Jensen et al., \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e2023\u003c/span\u003e), and cultural norms that emphasize rigor, stoicism, and grit (Godfrey \u0026amp; Parker, \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e2010\u003c/span\u003e; Kirn \u0026amp; Benson, \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). Further, engineering students often prioritize academic obligations over wellbeing (Wright et al., \u003cspan citationid=\"CR86\" class=\"CitationRef\"\u003e2023\u003c/span\u003e; Jensen et al., \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). Therefore, to address this normalization of stress and reduced help seeking in engineering, we created a brief (15-minute) mental health training tailored specifically to engineering undergraduates, grounded in a theoretical model of mental health help seeking. Expanding on prior mental health help-seeking intervention research [\u003cem\u003ecitation redacted for masked peer review\u003c/em\u003e], this study implemented a college-wide intervention and evaluated its impact on engineering students\u0026rsquo; mental health help-seeking perceptions across two cohorts (Fall 2023 and Spring 2024). This allowed us to answer the following research questions:\u003c/p\u003e\u003cp\u003e\u003col\u003e\u003cspan\u003e\u003cli\u003e\u003cp\u003eHow do we develop a mental health training intervention tailored toward the engineering undergraduate population?\u003c/p\u003e\u003c/li\u003e\u003c/span\u003e\u003cspan\u003e\u003cli\u003e\u003cp\u003eHow does a discipline-tailored mental health intervention impact engineering students\u0026rsquo; mental health help-seeking perceptions?\u003c/p\u003e\u003c/li\u003e\u003c/span\u003e\u003c/ol\u003e\u003c/p\u003e\u003cp\u003eTo contextualize this study, the following section reviews additional research on mental health help-seeking and related interventions in engineering education.\u003c/p\u003e\n\u003ch3\u003eMental Health and Help-seeking in Engineering\u003c/h3\u003e\n\u003cp\u003eEngineering students experience high levels of mental health distress (Whitwer et al., \u003cspan citationid=\"CR81\" class=\"CitationRef\"\u003e2025\u003c/span\u003e). In a national sample, 44.4% of engineering students screened positive for current depressive and/or anxiety symptoms (Whitwer et al., \u003cspan citationid=\"CR81\" class=\"CitationRef\"\u003e2025\u003c/span\u003e), with even higher rates observed among female, first-generation, and gender-expansive students in engineering (Vick et al., 2025; Hargis et al., 2021; Jensen \u0026amp; Cross, \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). A 2023 systematic review of 34 studies examining the mental health and well-being of undergraduate engineering students identified stress as the most commonly reported mental health concern, followed by depression, anxiety, and post-traumatic stress disorder (Asghar et al., \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). These concerns put engineering students at risk for attrition, with roughly 45% of students at research institutions either switching to a major unrelated to STEM (Science, Technology, Engineering, Mathematics) or not completing the four-year degree (Kraus et al., 2015). Research has also highlighted key barriers to promoting mental health in this population, including heavy academic workloads, sleep disturbances, and aspects of engineering culture itself (Asghar et al., \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e2024\u003c/span\u003e; Akter et al., 2025). Despite the large percentage of engineering students who screen positive for depression or anxiety, engineering students self-report depressive and anxiety symptoms at lower rates than students in other majors (Whitwer et al., \u003cspan citationid=\"CR81\" class=\"CitationRef\"\u003e2025\u003c/span\u003e). This discrepancy may reflect a reduced recognition of mental health struggles among engineering students, potentially due to limited mental health literacy or reluctance to acknowledge distress (Whitwer et al., \u003cspan citationid=\"CR81\" class=\"CitationRef\"\u003e2025\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eThe literature provides important insights into engineering students\u0026rsquo; mental health help-seeking beliefs, which are shaped by the internalization of dominant cultural norms within the discipline and are associated with reduced help-seeking. Students who endorse beliefs emphasizing competition and meritocracy in engineering report less favorable attitudes toward seeking treatment (S\u0026aacute;nchez-Pe\u0026ntilde;a et al., \u003cspan citationid=\"CR60\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). Cultural norms related to masculinity and Whiteness embedded in engineering culture further discourage help-seeking, particularly among gender and racial minority groups (S\u0026aacute;nchez-Pe\u0026ntilde;a et al., \u003cspan citationid=\"CR59\" class=\"CitationRef\"\u003e2025\u003c/span\u003e). Similarly, culturally reinforced values such as self-reliance and efficiency may strengthen students\u0026rsquo; preference for managing struggles independently rather than developing supportive networks (Wright et al., \u003cspan citationid=\"CR86\" class=\"CitationRef\"\u003e2023\u003c/span\u003e; S\u0026aacute;nchez‐Pe\u0026ntilde;a et al., 2025). Finally, the normalization and trivialization of mental health concerns within engineering programs (Beddoes \u0026amp; Danowitz, 2022) may lead students to prioritize academic success over self-care. As one student explained, \u0026ldquo;you have to prioritize the education and the work that goes towards it instead of \u0026hellip; yourself \u0026hellip; I think a lot of people think that it's just four years \u0026hellip; They need to get through the school and then it'll be fine\u0026rdquo; (Wright et al., \u003cspan citationid=\"CR86\" class=\"CitationRef\"\u003e2023\u003c/span\u003e, p. 974).\u003c/p\u003e\u003cp\u003eAdditional barriers accounting for engineering students\u0026rsquo; decreased likelihood of seeking help include concerns with a lack of appointment availability, and relying on informal support (e.g., peers) in lieu of professional support to cope with distress (Wright et al., \u003cspan citationid=\"CR86\" class=\"CitationRef\"\u003e2023\u003c/span\u003e; Jensen et al., \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). Both perceived and internalized help-seeking stigma (e.g., believing that others view help-seeking as a sign of weakness and endorsing those external views oneself, respectively) further undermine the willingness of engineering students to access care (S\u0026aacute;nchez-Pe\u0026ntilde;a et al., \u003cspan citationid=\"CR60\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). This stigma may be reinforced by students rarely seeing their faculty openly modeling such help-seeking behaviors; the absence of professors who discuss or demonstrate help-seeking can make students feel that faculty do not understand or relate to their struggles (Busch et al., \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). Students often perceive implicit messages from their professors and advisors suggesting that prioritizing mental health may not be supported within their academic environment (Ban et al., \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). Other barriers including the perceived time requirements, opportunity costs associated with seeking help (S\u0026aacute;nchez-Pe\u0026ntilde;a et al., \u003cspan citationid=\"CR60\" class=\"CitationRef\"\u003e2023\u003c/span\u003e; Wright et al., \u003cspan citationid=\"CR86\" class=\"CitationRef\"\u003e2023\u003c/span\u003e), and accessibility beliefs likely further discourage students to prioritize their mental health concerns. Even when students know resources exist, concerns about not finding a \u0026ldquo;good fit\u0026rdquo; with a provider (Beddoes \u0026amp; Danowitz, 2022; Wright et al., \u003cspan citationid=\"CR86\" class=\"CitationRef\"\u003e2023\u003c/span\u003e) or believing the process would be too complicated or inaccessible (Jensen et al., \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e2023\u003c/span\u003e; Wright et al., \u003cspan citationid=\"CR86\" class=\"CitationRef\"\u003e2023\u003c/span\u003e) act as barriers.\u003c/p\u003e\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e\u003ch2\u003eMental Health Help-Seeking Interventions in Engineering\u003c/h2\u003e\u003cp\u003eWithin engineering, there has been an increase in interventions aimed at improving student mental health and well-being. A recent scoping review by Tait and colleagues (2023) examined 33 studies with interventions designed to support the mental health and wellbeing of engineering college students, involving over 4,000 engineering students from 10 countries. The review categorized these 33 interventions into psychological (14), physiological (5), and/or educational (15). Psychological interventions primarily involved mindfulness training, tutoring, social belonging interventions, and assessing social and/or professional support (Miller \u0026amp; Jenson, 2020; Walton et al., \u003cspan citationid=\"CR76\" class=\"CitationRef\"\u003e2015\u003c/span\u003e; Grasty et al., 2021). Physiological interventions included structured breathing exercises and activities designed to promote body awareness including dance movement therapy (Rodr\u0026iacute;guez-Jim\u0026eacute;nez et al., \u003cspan citationid=\"CR57\" class=\"CitationRef\"\u003e2022\u003c/span\u003e) and yogic breathing (Joshi \u0026amp; Kiran, \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). Educational interventions focused on increasing awareness of stress reduction techniques, recognizing signs of mental health distress, and modifying teaching approaches (Abiade \u0026amp; Moliski, 2020; Su, \u003cspan citationid=\"CR68\" class=\"CitationRef\"\u003e2016\u003c/span\u003e). Tait and colleagues (2023) found that mental wellness interventions in engineering education led to improvements in academic achievement, reductions in stress and anxiety, and additional benefits such as improved motivation, positive attitude, physical activity, physiological regulation, spiritual health, self-confidence, health awareness, and communication skills.\u003c/p\u003e\u003cp\u003eThe 33 studies included in Tait and colleagues\u0026rsquo; (2023) scoping review primarily focused on reducing mental health distress among undergraduate engineering students through direct mental health support interventions. However, none of these studies primarily focused on improving engineering undergraduates\u0026rsquo; mental health help-seeking perceptions. In fact, only one reported data regarding mental health help-seeking perceptions: Paul and colleagues (\u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e2020\u003c/span\u003e) integrated weekly 15- to 75-minute mental wellness modules (e.g., exam anxiety, how to access campus academic and mental health support services) and structured self-reflection activities into required first-year engineering coursework. Analysis of these reflections revealed that students generally appreciated the modules, perceived faculty as supportive, and showed increased engagement in help-seeking behaviors. They also expressed a preference for shorter modules (15\u0026ndash;20 minutes) over longer seminars, appreciated the student peers presenting and sharing their own struggles (e.g., academic burnout, mental health), yet continued to view mental wellness as a lower priority compared to academics. Our review of the literature suggested that few published studies beyond the scope of this systematic review exist; one exception is Kalamatianos and colleagues\u0026rsquo; (2025) implementation of a blended counseling intervention among undergraduate engineering students. Their five-week psychoeducational and positive psychology-based program effectively reduced symptoms of depression, anxiety, and stress within this population.\u003c/p\u003e\u003cp\u003eIn summary, there remains a dearth of literature on interventions designed to specifically influence mental health help-seeking perceptions within the engineering student population. Furthermore, extant engineering student mental health studies are often characterized by limitations including the frequent lack of (a) use of psychometrically-vetted measures, (b) grounding in theory, much less mental health help-seeking theory, (c) tailoring of intervention content to the culture of engineering education and engineering students\u0026rsquo; lived experience, (d) brief interventions feasible to deliver at scale to the engineering student body, and/or (e) control groups and pre/post designs to mitigate threats to internal validity (e.g., testing and history effects). Therefore, there is a need for intervention research focused on improving engineering students\u0026rsquo; mental health help-seeking perceptions that address these important limitations.\u003c/p\u003e\u003c/div\u003e\n\u003ch3\u003eTheoretical Framework\u003c/h3\u003e\n\u003cp\u003eThis study was grounded in the Integrated Behavioral Model of Mental Health Help Seeking (IBM-HS), which provides a comprehensive framework for understanding psychological, social and environmental determinants of mental health help seeking and service utilization (Hammer, Vogel, et al., \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). According to the IBM-HS, an individual\u0026rsquo;s intention to seek help serves as the most immediate predictor of their prospective help-seeking behavior (Hammer, Vogel, et al., \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e2024\u003c/span\u003e) and is shaped by the three help-seeking mechanisms of attitude, perceived norm, and personal agency.\u003c/p\u003e\u003cp\u003eAttitude refers to an individual\u0026rsquo;s overall evaluation of seeking help as a good or bad thing and is informed by outcome beliefs (expected results of seeking help) and experiential beliefs (emotional response to the idea of seeking help). Perceived norm reflects the perceived social expectations around help seeking and includes both injunctive norm (influenced by beliefs about what others expect them to do) and descriptive norm (influenced by beliefs about whether others would seek help if in distress). Finally, personal agency refers to an individual\u0026rsquo;s evaluation of their capacity to seek help and their autonomy around the decision to seek help. Personal agency is shaped by logistical beliefs about likely facilitators or barriers to seeking help. For example, a logistical belief is that one must prioritize their academic success over their mental health, a theme that has been noted in existing engineering mental health literature (Wright et al., \u003cspan citationid=\"CR86\" class=\"CitationRef\"\u003e2023\u003c/span\u003e; Hammer, Wright, et al., \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e2024\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eUnderlying these beliefs are broader help-seeking determinants (Hammer, Vogel, et al., \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). One such category of help-seeking determinant is called mental health perceptions, knowledge, and skills. This category includes both perceived and objective mental health literacy (e.g., ability to recognize signs of distress, knowledge of mental health resources and how to access them). Collectively, the help-seeking determinants not only inform the beliefs that shape mechanisms and intention but can also directly influence whether an individual follows through on their intention to seek care (Hammer, Vogel et al., \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). Understanding these determinants, beliefs, and mechanisms provides a foundation for designing interventions that target the specific cognitive, affective, and structural barriers influencing help-seeking among engineering students.\u003c/p\u003e\n\u003ch3\u003eCurrent Study\u003c/h3\u003e\n\u003cp\u003eGrounded in the IBM-HS, our study aimed to address the limitations of previous research on engineering-specific mental health help-seeking interventions. Specifically, we implemented and assessed a 15-minute mental health presentation intervention designed specifically for engineering students that aimed to improve mental health literacy (help-seeking determinant), normalize the prioritization of mental health (help-seeking belief), improve help-seeking attitude, perceived norm, and personal agency (help-seeking mechanisms), and enhance help-seeking intention. Further, open-ended participant feedback regarding the presentations was also collected.\u003c/p\u003e\u003cp\u003eInformed by Bloom\u0026rsquo;s Taxonomy of Learning (Bloom et al., \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e1956\u003c/span\u003e; Krathwohl et al., \u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e1964\u003c/span\u003e), we expected this brief intervention to primarily strengthen engineering students\u0026rsquo; foundational mental health literacy (e.g., knowledge of campus mental health resources, perceived ability to recognize signs of distress) because these outcomes align with the cognitive domain\u0026rsquo;s basic knowledge level. Given the short duration of the training, we did not anticipate substantial changes in broader help-seeking perceptions such as attitudes toward seeking professional help. This expectation is consistent with the larger literature: a meta-analysis of brief web-based mental health literacy interventions for youth conducted by Nazari and colleagues (\u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e2023\u003c/span\u003e) found significant improvements in objective knowledge but no significant changes in stigma or help-seeking attitudes, and a systematic review of classroom-based programs among high school and college students by Nazari and colleagues (\u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e2024\u003c/span\u003e) similarly showed consistent gains in mental health knowledge with only mixed or limited effects on attitudes or stigma. Together, these findings suggest that brief educational interventions can reliably enhance foundational mental health literacy, whereas shifting deeper-seated perceptions (e.g., mental health stigma or help-seeking intention) likely requires more intensive and sustained efforts.\u003c/p\u003e\u003cp\u003eWith this context in mind, our interdisciplinary team sought to conduct develop, implement, and evaluate an intervention explicitly designed to influence engineering students\u0026rsquo; mental health help-seeking perceptions. Findings from this work are intended to inform future intervention development and testing within colleges of engineering nationwide.\u003c/p\u003e"},{"header":"METHOD","content":"\u003cdiv id=\"Sec7\" class=\"Section2\"\u003e\u003ch2\u003eTraining Delivery\u003c/h2\u003e\u003cp\u003eThe mental health intervention was first delivered in Spring 2023 and then adapted for a second round of delivery in Spring 2024. Participants were undergraduate engineering students at the [\u003cem\u003ename of institution redacted for masked peer review\u003c/em\u003e]. To identify courses for recruitment, department chairs were contacted during each fall semester to identify courses within their discipline that would: 1) reach all students across all academic years within the major, 2) limit the overlap of students across courses, and 3) be taught by faculty that would: support the integration of the training into their course, encourage a positive narrative around prioritizing student mental health, and represent the demographics of students within their program. After receiving a list of courses from each department chair, faculty were contacted by the research team\u0026rsquo;s graduate student members, informed about the training and an optional 15-minute post-training facilitated discussion, and asked to schedule a time for the integration of the training within their course during the spring semester. Both the department chair and associate dean for undergraduate education and student success were included in the email to illustrate administrative support for the training. In Spring 2023, 95% (57) of the 60 contacted faculty members agreed to the incorporation of the 15-minute training into their courses. 11 of the 57 faculty also agreed to the additional 15-minute post-training facilitated discussion. A total of 2,592 students were enrolled in courses in which the training was delivered, representing up to 93% of the 2,780 students enrolled in the College of Engineering at the time [\u003cem\u003ecitation redacted for masked peer review]\u003c/em\u003e. In Spring 2024, 46 of the 70 contacted faculty agreed to incorporate the training, and 8 of the 46 faculty also agreed to the facilitated discussion. A total of 1,890 students were enrolled in courses in which the training was delivered, representing up to 67% of the 2,836 students enrolled in the College of Engineering (\u003cem\u003ecitation redacted for masked peer review\u003c/em\u003e). The training was delivered by graduate student research team members from the counseling psychology program at the university, in addition to the [\u003cem\u003ediscipline to be added after review\u003c/em\u003e] associate professor and [\u003cem\u003ediscipline to be added after review\u003c/em\u003e] assistant professor leading the research team. There were three graduate student presenters in 2023 and five presenters in 2024. Collectively, the presenters held a diverse range of identities across gender, race, and academic year, and were all trained in providing culturally responsive care and demonstrated effective public speaking skills.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec8\" class=\"Section2\"\u003e\u003ch2\u003eTraining Description\u003c/h2\u003e\u003cp\u003e The 15-minute mental health trainings were developed based on the findings of empirical research on undergraduate engineering students\u0026rsquo; mental health and help seeking, as highlighted in the prior literature review. The 2024 training was adapted from the previous year based on additional data collected by the research team, along with 2023 participant feedback and ideas from new research team members. University administrators engaged in mental health training and service delivery were consulted to ensure the training content was up-to-date and in accordance with university guidelines. The training was piloted with graduate and undergraduate engineering students to ensure the content met the needs of the engineering student body. To personalize the training to the engineering student context, mental health and help-seeking statistics from engineering students at the university were included, along with direct quotes from semi-structured interviews and focus groups our team had conducted with engineering students. Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e summarizes the training content for 2023 and 2024.\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003e\u003cem\u003eContent of the Engineering Student Mental Health Training for 2023 and 2024\u003c/em\u003e\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"4\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eTopic\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eKey Content Covered\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003e2023\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003e2024\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePrioritizing Mental Health\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eEngineering students feel they do not have time to prioritize mental health and are less likely to seek help (Whitwer et al., \u003cspan citationid=\"CR81\" class=\"CitationRef\"\u003e2025\u003c/span\u003e), (Wright et al., 2021), (Ban et al., \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e2022\u003c/span\u003e)\u003c/p\u003e\u003cp\u003eChronic stress linked to decreased burnout, academic performance, and increased mental health disorders (Wang et al., \u003cspan citationid=\"CR77\" class=\"CitationRef\"\u003e2024\u003c/span\u003e) (Ban et al., \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e2022\u003c/span\u003e)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u003cem\u003e✓\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e\u003cem\u003e✓\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMental Health Resources\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eOverview of campus resources related to mental health and wellness (Paul et al., \u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e2020\u003c/span\u003e)\u003c/p\u003e\u003cp\u003eAdditional resources to support overall well-being (e.g., academic tutoring and accommodations, basic needs, financial support, etc.) (Ban et al., \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e2022\u003c/span\u003e)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u003cem\u003e✓\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e\u003cem\u003e✓\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eRecognizing/ Addressing Mental Distress\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eDifferentiating between normal stress and unhealthy distress and teaching mental health literacy (O\u0026rsquo;Sullivan, \u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e2011\u003c/span\u003e; Shim et al., \u003cspan citationid=\"CR64\" class=\"CitationRef\"\u003e2022\u003c/span\u003e)\u003c/p\u003e\u003cp\u003eTips for peer support (e.g., talking to someone experiencing distress and/or how to advocate for them) (Hyseni Duraku et al., \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e2023\u003c/span\u003e)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u003cem\u003e✓\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e\u003cem\u003e✓\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSubstance abuse\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eRecognizing signs of substance abuse and its impact on academic performance (Paul et al., \u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e2024\u003c/span\u003e)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u003cem\u003e✓\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePractical Skills\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eOverview of small independent habits to promote mental health/wellness (e.g., diet, exercise, self-care, prosocial relationships) (Ban et al., \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e2022\u003c/span\u003e)\u003c/p\u003e\u003cp\u003eCommunity involvement can positively impact mental wellness (e.g., mentorship, student organizations) (Ban et al., \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e2022\u003c/span\u003e)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e\u003cem\u003e✓\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003eFor faculty that agreed to the optional 15-minute post-training facilitated discussion, the discussion was held immediately following the training presentation. Facilitators posed a series of questions (e.g., \u0026ldquo;What are some ways that you have seen or heard high levels of stressed being normalized in engineering?\u0026rdquo; \u0026ldquo;Which stressors are unique to engineering students?\u0026rdquo; \u0026ldquo;What is one thing you want to work on better prioritize your own mental health?\u0026rdquo;) and students were encouraged to discuss in a small group before reporting themes to the larger group.\u003c/p\u003e\u003c/div\u003e\n\u003ch3\u003eQuantitative Data Collection\u003c/h3\u003e\n\u003cp\u003eIn 2023, survey data was collected after completion of the training for two independent sample groups: students who did not receive the training (\u0026ldquo;No Training\u0026rdquo;; \u003cem\u003en\u003c/em\u003e\u0026thinsp;=\u0026thinsp;164), and students that did (\u0026ldquo;Training\u0026rdquo;; \u003cem\u003en\u003c/em\u003e\u0026thinsp;=\u0026thinsp;267). In contrast, survey pretest and posttest data were each collected in 2024 from the Training group (\u003cem\u003en\u003c/em\u003e\u0026thinsp;=\u0026thinsp;64) and the No Training group (\u003cem\u003en\u003c/em\u003e\u0026thinsp;=\u0026thinsp;68). Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e provides demographic information for both 2023 groups and 2024 groups. To anonymously link student survey responses across time (Lippe et al., \u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e2019\u003c/span\u003e), each student was asked to provide a subject-generated four-character identification code by answering the following four questions: 1) the first initial of your mother's name, 2) The number of older brothers you have, 3) the first letter of your middle name and 4) the number of the month in which you were born. In 2023, there was only a small number of linking codes (\u003cem\u003en\u003c/em\u003e\u0026thinsp;=\u0026thinsp;35) across the combined 2023 pre-test and post-test sample size. Consequently, we chose to discard any participants with matching linking codes, allowing for the treatment of the responses as independent Training (pre-test responses) and No Training (post-test responses) groups. In 2024, there was a sufficient number of linked codes (\u003cem\u003en\u003c/em\u003e\u0026thinsp;=\u0026thinsp;132) across the pre-test and post-test samples for the Training and No Training groups, so we were able to perform additional analysis to account for possible history effects.\u003c/p\u003e\u003cp\u003eOnline surveys were administered during the spring semesters of both academic years, collecting quantitative (i.e., perceived knowledge, objective knowledge, prioritization of mental health, intention, mechanisms) and qualitative (i.e., helpful aspects of training; aspects of training to be improved) data. After obtaining approval from the university\u0026rsquo;s Institutional Review Board (IRB; protocol number 86047), students were recruited via email and provided with all necessary information to ensure informed consent and voluntary participation at the start of the survey. Because training sessions were conducted across the 2023 and 2024 academic semesters, and students had the flexibility to complete the surveys at their convenience, the time elapsed between each training and corresponding survey completion varied both within and across the two academic years. Based on demographic data (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e), participants were representative of the engineering population at the university, with most being white, heterosexual male students. Eleven engineering majors were represented (e.g., mechanical, computer science, civil, chemical, electrical, mining, computer engineering, biomedical, biosystems). Across both years among training and no training groups, over a third of the students were freshmen or sophomores (35%), and a minority of students were international (2%), first-generation (14%), or transfer students (10%). Due to challenges with the linking code used for the 2023 survey data, there is limited demographic data for this population. That being said, the demographic distribution of students across each phase of the study was comparable.\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003e\u003cem\u003eSociodemographic Characteristics of the Participants\u003c/em\u003e\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"9\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003eSample Characteristics\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e\u003cp\u003e\u003cem\u003eNo Training 2023 (n\u0026thinsp;=\u0026thinsp;164)\u003c/em\u003e\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e\u003cp\u003e\u003cem\u003eTraining 2023 (n\u0026thinsp;=\u0026thinsp;267)\u003c/em\u003e\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colspan=\"2\" nameend=\"c7\" namest=\"c6\"\u003e\u003cp\u003e\u003cem\u003eNo Training 2024 (n\u0026thinsp;=\u0026thinsp;68)\u003c/em\u003e\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colspan=\"2\" nameend=\"c9\" namest=\"c8\"\u003e\u003cp\u003e\u003cem\u003eTraining 2024 (n\u0026thinsp;=\u0026thinsp;64)\u003c/em\u003e\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u003cem\u003en\u003c/em\u003e\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u003cem\u003e%\u003c/em\u003e\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003e\u003cem\u003en\u003c/em\u003e\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u003cem\u003e%\u003c/em\u003e\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c6\"\u003e\u003cp\u003e\u003cem\u003en\u003c/em\u003e\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c7\"\u003e\u003cp\u003e\u003cem\u003e%\u003c/em\u003e\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c8\"\u003e\u003cp\u003e\u003cem\u003en\u003c/em\u003e\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c9\"\u003e\u003cp\u003e\u003cem\u003e%\u003c/em\u003e\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"7\" nameend=\"c7\" namest=\"c1\"\u003e\u003cp\u003eGender\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMan\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e93\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e67.9%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e56\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e66.7%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e46\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e67.6%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e34\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e\u003cp\u003e53.1%\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eWoman\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e42\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e30.7%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e26\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e31.0%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e19\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e27.9%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e30\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e\u003cp\u003e46.9%\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eGender Expansive\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e2.2%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e2.4%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e4.4%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e\u003cp\u003e0.0%\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePrefer Not to Answer\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.7%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.0%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e1.5%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e\u003cp\u003e0.0%\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eNo Answer Provided\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e27\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e183\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSexual Orientation\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eStraight/Heterosexual\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e115\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e83.9%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e76\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e90.5%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e61\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e89.7%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e59\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e\u003cp\u003e92.2%\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eLGBQ+\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e20\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e14.6%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e8\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e9.5%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e7\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e10.3%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e6\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e\u003cp\u003e9.4%\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePrefer Not to Answer\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e1.5%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e1.2%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e1.5%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e\u003cp\u003e0.0%\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eNo Answer Provided\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e27\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e183\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eRace/Ethnicity\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eWhite or Caucasian\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e109\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e79.6%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e67\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e78.8%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e54\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e79.4%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e55\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e\u003cp\u003e85.9%\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAsian or Asian American\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e12\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e8.8%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e5\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e5.9%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e7\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e10.3%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e\u003cp\u003e6.3%\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eLatino/a/x/e or Hispanic\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e7\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e5.1%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e6\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e7.1%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e5.9%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e\u003cp\u003e4.7%\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eBiracial/Multiracial\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e5\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e3.6%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e5\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e5.9%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e4.4%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e\u003cp\u003e6.3%\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eBlack/African American\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e5\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e3.6%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e5\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e5.9%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e1.5%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e\u003cp\u003e4.7%\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eArab or Arab American\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e2.2%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e1.2%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e0.0%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e\u003cp\u003e3.1%\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAmerican Indian, Native American, or Alaskan Native\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.7%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e2.4%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e0.0%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e\u003cp\u003e1.6%\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eJewish\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.7%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e2.4%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e0.0%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e\u003cp\u003e0.0%\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePacific Islander or Native Hawaiian\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.7%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.0%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e1.5%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e\u003cp\u003e0.0%\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePrefer Not to Answer\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e2.9%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e1.2%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e1.5%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e\u003cp\u003e0.0%\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eNo Answer Provided\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e27\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e182\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003ctfoot\u003e\u003ctr\u003e\u003ctd colspan=\"9\"\u003e\u003cem\u003eNote\u003c/em\u003e. The percentages per category were calculated based on existing demographic data and did not include responses without data. Participants were given the option to select all that apply per category (i.e., Gender, Sexual Orientation, Race/Ethnicity). Gender Expansive included the following options: transgender, non-binary, gender queer, gender fluid, agender, and poly-gender. LGBQ\u0026thinsp;+\u0026thinsp;included the following options: gay, lesbian, bisexual, pansexual, asexual, and queer.\u003c/td\u003e\u003c/tr\u003e\u003c/tfoot\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\n\u003ch3\u003eMeasures\u003c/h3\u003e\n\u003cp\u003eFor both 2023 and 2024 studies, the measures used to assess students\u0026rsquo; help-seeking perceptions and experience with the training are described below.\u003c/p\u003e\u003cdiv id=\"Sec11\" class=\"Section2\"\u003e\u003ch2\u003ePerceived Knowledge\u003c/h2\u003e\u003cp\u003eRespondents completed three items evaluating their perceived knowledge of mental health resources available to students at their university (i.e., \u0026ldquo;I know what mental health resources are available to students on this campus\u0026rdquo;), how to access these services (i.e., \u0026ldquo;I know how to access the available mental health resources on campus\u0026rdquo;), and their ability to recognize signs of mental health distress (i.e., \u0026ldquo;I know how to recognize signs of mental health distress\u0026rdquo;). Each item was rated on a six-point Likert scale from 1 (strongly disagree) to 6 (strongly agree).\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec12\" class=\"Section2\"\u003e\u003ch2\u003eObjective Knowledge\u003c/h2\u003e\u003cp\u003eRespondents completed a 10-item multiple-choice quiz that evaluated their factual knowledge of available resources for students at the university and how to access them. These included resources for mental wellness, academic accommodation and tutoring, financial and basic needs, and survivors of sexual and gender-based violence. All resources were reviewed in the training. For six of the 10 items, respondents were given a hypothetical scenario (e.g., \u0026ldquo;supposed you are seeking financial assistance\u0026hellip;\u0026rdquo;) and asked to choose the most appropriate university resource from a multiple-choice list. Two items asked about the specific purpose and location of the university\u0026rsquo;s main resource for mental health needs. The final two items were true/false questions regarding free mental health resources available to students at the university. For all 10 items, respondents also had the option to choose \u0026ldquo;I\u0026rsquo;m Not Sure\u0026rdquo;. Correct responses were coded as one, whereas incorrect or \u0026ldquo;I\u0026rsquo;m Not Sure\u0026rdquo; responses were coded as zero. An overall \u0026ldquo;percentage correct\u0026rdquo; score on the quiz was calculated for each respondent.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec13\" class=\"Section2\"\u003e\u003ch2\u003ePrioritization of Mental Health\u003c/h2\u003e\u003cp\u003eA single item was used to evaluate how much respondents agreed with the following statement regarding their own mental health prioritization: \u0026ldquo;During my time as an engineering student, I will need to prioritize my academic success over my mental health\u0026rdquo;. This item, which represents a logistical belief, was taken from a larger validated instrument aimed at identifying beliefs that impact mental health treatment access in undergraduate engineering students: The Undergraduate Engineering Mental Health Help-Seeking Instrument (UE-MH-HSI) (Hammer, Wright, et al., \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). The item was rated on a six-point Likert scale from 1 (strongly disagree) to 6 (strongly agree).\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec14\" class=\"Section2\"\u003e\u003ch2\u003eHelp-Seeking Intention\u003c/h2\u003e\u003cp\u003eA single item was used to measure mental health help-seeking intention (i.e., \u0026ldquo;If I had a mental health concern, I would intend to seek help from a mental health professional in the next 3 months\u0026rdquo;). This item was measured on a six-point Likert scale from 1 (extremely unlikely) to 6 (extremely likely). This item was adapted from the Mental Health Help-Seeking Intention Scale (MHSIS; Hammer et al., \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e2018\u003c/span\u003e), which has demonstrated evidence of validity for use with engineering students and utilized in the UE-MH-HSI (Hammer, Wright, et al., \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e2024\u003c/span\u003e).\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec15\" class=\"Section2\"\u003e\u003ch2\u003eHelp-Seeking Mechanisms\u003c/h2\u003e\u003cp\u003eRespondents completed single-item measures of mental health help-seeking attitude, perceived norm, and personal agency. These single-item versions were adapted from the multiple-item measures of these constructs embedded in UE-MH-HSI (Hammer, Wright, et al. \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e2024\u003c/span\u003e):\u003c/p\u003e\u003cp\u003e\u003cb\u003eAttitude.\u003c/b\u003e Attitude was measured with a single item rated on a six-point Likert scale from 1(very bad) to 6 (very good) (i.e., \u0026ldquo;If I had a mental health concern, my seeking help from a mental health professional in the next 3 months would be\u0026hellip;\u0026rdquo;). (Hammer, Wright, et al., \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e2024\u003c/span\u003e).\u003c/p\u003e\u003cp\u003e\u003cb\u003ePerceived Norm.\u003c/b\u003e Perceived Norm was measured with a single item rated on a six-point Likert scale from 1 (I should not) to 6 (I should) (i.e., \u0026ldquo;Most people who are important to me would think that ____ seek help from a mental health professional in the next 3 months\u0026rdquo;). This item focused on the injunctive element of perceived norm (Hammer, Wright, et al., \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e2024\u003c/span\u003e).\u003c/p\u003e\u003cp\u003e\u003cb\u003ePersonal Agency.\u003c/b\u003e Personal Agency was measured with a single item rated on a six-point Likert scale from 1 (completely false) to 6 (completely true) (i.e., \u0026ldquo;I am confident that I could seek help from a mental health professional in the next 3 months\u0026rdquo;). This item focused on the capacity (i.e., degree of confidence) element of respondents\u0026rsquo; self-efficacy (Hammer, Wright, et al., \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e2024\u003c/span\u003e).\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec16\" class=\"Section2\"\u003e\u003ch2\u003eQualitative Open-ended Questions\u003c/h2\u003e\u003cp\u003eRespondents completed two open-ended questions about their experience with the training regarding what they found most helpful (i.e., \u0026ldquo;What was helpful about the mental health presentation in your class?\u0026rdquo;) and how they felt it could be improved (i.e., \u0026ldquo;What could have been different (e.g., topics covered, presentation style) about the mental health presentation to make it more helpful to you?\u0026rdquo;).\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec17\" class=\"Section2\"\u003e\u003ch2\u003eData Cleaning \u0026amp; Analysis\u003c/h2\u003e\u003cp\u003eAcross both years, responses that either lacked usable data or did not provide a four-character identification code were deleted. For 2023 data, identification codes for survey data from students with (\u003cem\u003en\u003c/em\u003e\u0026thinsp;=\u0026thinsp;267) and without (\u003cem\u003en\u003c/em\u003e\u0026thinsp;=\u0026thinsp;164) training were used to ensure that each group was independent (i.e., all codes were unique across both groups). In contrast, 2024 data were cleaned by linking pretest/posttest responses using unique codes; responses without matches or with conflicting information were excluded, and duplicates were deleted to ensure only linking pretest/posttest code matches remained. Additionally, no variables exceeded cutoffs of 3 and 10 for high univariate skewness and kurtosis values (Weston \u0026amp; Gore, \u003cspan citationid=\"CR80\" class=\"CitationRef\"\u003e2006\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eQuantitative data was analyzed using IBM SPSS Statistics Software Version 29. For both the 2023 and 2024 data, independent sample t-tests were conducted comparing mean scores between the No Training and Training groups on all nine measures, Levene\u0026rsquo;s Test (p\u0026thinsp;\u0026lt;\u0026thinsp;.05) was used to measure equality of variances across the two independent groups (Gastwirth et al., \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e2009\u003c/span\u003e). Five of the nine variables were found to violate assumptions of homogeneity. In these cases, homogeneity was not assumed when determining significance. To avoid inflating the Type I error rate when conducting multiple independent-sample t‑tests, we applied a Bonferroni correction, dividing the conventional α\u0026thinsp;=\u0026thinsp;.05 by the number of comparative tests. This resulted in a more stringent significance threshold (i.e., \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;.006), as recommended in prior literature (Armstrong, \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e2014\u003c/span\u003e). For both 2023 and 2024 analyses, we applied a Bonferroni correction to the following eight tests: perceived knowledge (three), help-seeking mechanisms (four), and objective knowledge (one).\u003c/p\u003e\u003cp\u003eBecause the simple comparison of the No Training and Training groups cannot account for potential history effects (events that influence mean scores on the dependent variable between pre-test and post-test measurements), we conducted a supplemental set of analyses to increase confidence in the validity of our results. Using the 2024 data, which measured study variables at both pre- and post-intervention, we conducted a series of Two-Way Repeated Measures Analyses of Variance (ANOVA). This analytical procedure can analyze two factors of interest (the within subject factor of time and the between subject factor of training) from the experimental (Training) and control (No Training) groups, as well as the time x training interaction (Schober \u0026amp; Vetter, \u003cspan citationid=\"CR62\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). Box\u0026rsquo;s Test of Equality of Covariance Matrices (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;.05) was used to compare variation in the two multivariate samples. Four of the nine variables were found to violate Box\u0026rsquo;s Test. However, given the nearly equal sample size groups (Training \u003cem\u003en\u003c/em\u003e\u0026thinsp;=\u0026thinsp;64; No Training \u003cem\u003en\u003c/em\u003e\u0026thinsp;=\u0026thinsp;68), the test results are robust to these violations (Pituch \u0026amp; Stevens, \u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e2015\u003c/span\u003e). Because we had already provided independent samples t-test evidence regarding potential differences between the No Training and Training groups, we focused on using Wilks\u0026rsquo; Lambda to determine whether the interaction effect was significant, which would indicate that the rate of change for the mean score was significantly different from pre to post-intervention (time) between the experimental (Training) and control (No Training) groups. We anticipated that significant differences between the No Training and Training groups detected by the independent sample t-tests would be confirmed by the supplemental examination of the interaction effect for the corresponding Two-Way Repeated Measures ANOVA. Mauchly\u0026rsquo;s test on all nine variables indicated that the assumption of sphericity was met throughout, X\u003csup\u003e2\u003c/sup\u003e(0)\u0026thinsp;=\u0026thinsp;.0, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;.001, and therefore degrees of freedom did not need to be corrected using Greenhouse-Geisser (Blanca et al., \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e2023\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eQualitative data from 2023 and 2024 regarding what respondents found helpful and what they felt could be improved was inductively coded through informal structured tabular thematic analysis (ST-TA). This approach is designed to analyze brief qualitative data (Robinson, \u003cspan citationid=\"CR56\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). After checking the level of coding agreement between two research members, eighteen codes were generated. The qualitative analysis helped provide additional insight into what worked well and what might be addressed to further enhance the effectiveness of the training.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec18\" class=\"Section2\"\u003e\u003ch2\u003eUse of Generative Artificial Intelligence\u003c/h2\u003e\u003cp\u003eOur team members utilized generative artificial intelligence (Gen AI), specifically ChatGPT (OpenAI, GPT-4), to support clarity and consistency in the wording and structure of this manuscript. Gen AI was used during the manuscript development and revision phases to suggest more concise phrasing, reword redundant or awkward phrasing, and improve tone alignment across sections. All content was reviewed and edited by the authors to ensure accuracy, appropriateness, and alignment with our intended meaning. No generative AI tools were used for data generation, analysis, or for producing original content beyond writing support and copyediting. We take full responsibility for the content of the publication.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec19\" class=\"Section2\"\u003e\u003ch2\u003ePOSITIONALITY STATEMENT\u003c/h2\u003e\u003cp\u003eOur research team was composed of two tenured or tenure-track professors (both engineering and non-engineering), one postdoctoral researcher, and two counseling psychology graduate students, possessing a collective domain expertise in mental health help seeking and engineering education, with a mixture of inside and outsider status members to the engineering student population (Secules et al., \u003cspan citationid=\"CR58\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). We represent a range of social, cultural, and disciplinary perspectives, which were intentionally explored and discussed in relation to our motivations, research approach, and engagement with our target population, enhancing the overall quality and rigor of the study (Sochacka et al., \u003cspan citationid=\"CR65\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). Our team collectively affirms the belief that mental health support is a fundamental human right and that accessing professional resources can play a critical role in enhancing individual well-being. We recognize that engineering training environments can often implicitly socialize students to prioritize academic and professional productivity over their own mental health and self-care. Furthermore, we recognize the presence of intrapersonal, interpersonal, and systemic barriers that can hinder distressed undergraduate engineering students from both seeking and receiving consistent and effective access to mental health services. Our eight graduate student presenters also collectively reflected a broad range of social identities (e.g., race/ethnicity, gender, sexual orientation, academic year) which strengthened the relevance and relatability of the trainings for diverse student audiences. The inclusion of this positionality statement aligns with recent calls within engineering education research to promote transparency regarding the influences that shape the research process, particularly within quantitative studies (Hampton et al., \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e2021\u003c/span\u003e).\u003c/p\u003e\u003c/div\u003e"},{"header":"RESULTS","content":"\u003cdiv id=\"Sec21\" class=\"Section2\"\u003e\u003ch2\u003eImpact of Training on Perceived Knowledge\u003c/h2\u003e\u003cp\u003eBetween 2023 and 2024, the 15-minute mental health training was delivered in courses with a total of nearly 4,500 students enrolled. We examined the impact of the brief mental health training on perceived knowledge, help-seeking beliefs and mechanisms, and help-seeking intention across students in the Training and No Training groups. In both years of the training, students in the Training groups reported higher perceived knowledge than the No Training groups across all three perceived knowledge items (Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e and Fig.\u0026nbsp;2). Specifically, compared to students in the No Training groups, the students who received the training had greater perceived knowledge related to (a) knowing what mental health resources are available to students on campus, (b) how to access these resources, and (c) how to recognize signs of mental health distress. Most students at least slightly agreed that they were knowledgeable regarding these three items. However, while approximately 45% of students in the No Training groups reported that they at least slightly agreed (i.e., reporting a score of 4 or higher on the six-point Likert scale) with the statement that, \u0026ldquo;I know what mental health resources are available to students in campus.\u0026rdquo; This is compared to approximately 80% of the students in the Training groups, indicating a noticeable increase in perceived knowledge of resources. This difference was similar for the other two knowledge items. In addition, the 2024 perceived knowledge scores were trending higher across both groups compared to the 2023 scores for both groups, suggesting that 2024 respondents started at a higher perceived knowledge baseline compared to the prior year.\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003e\u003cem\u003eEffect of Training on Perceived Knowledge\u003c/em\u003e\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"7\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eItems\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eGroups\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u003cem\u003eM\u003c/em\u003e\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003e\u003cem\u003eSD\u003c/em\u003e\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u003cem\u003edf\u003c/em\u003e\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c6\"\u003e\u003cp\u003e\u003cem\u003eT\u003c/em\u003e\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c7\"\u003e\u003cp\u003e\u003cem\u003ep\u003c/em\u003e\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"3\" rowspan=\"4\"\u003e\u003cp\u003eI know what mental health resources are available to students on this campus\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e2023 No Training\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e4.09\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e1.40\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003e292.65\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003e-6.37\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e2023 Training\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e4.91\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e1.14\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e2024 No Training\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e4.41\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e1.26\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003e107.99\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003e4.54\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e2024 Training\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e5.22\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.72\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"3\" rowspan=\"4\"\u003e\u003cp\u003eI know how to access the available mental health resources on campus\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e2023 No Training\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e3.79\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e1.50\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003e285.46\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003e-6.33\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e2023 Training\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e4.66\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e1.18\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e2024 No Training\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e4.15\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e1.31\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003e123.11\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003e3.89\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e2024 Training\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e4.92\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.97\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"3\" rowspan=\"4\"\u003e\u003cp\u003eI know how to recognize signs of mental health distress\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e2023 No Training\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e4.52\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e1.24\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003e302.75\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003e-2.96\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003e0.003\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e2023 Training\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e4.86\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e1.06\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e2024 No Training\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e4.40\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e1.24\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003e123.89\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003e3.19\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003e0.002\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e2024 Training\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e5.00\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.93\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003ctfoot\u003e\u003ctr\u003e\u003ctd colspan=\"7\"\u003e\u003cem\u003eNote.\u003c/em\u003e Sample sizes for each independent group from both years were as follows: 2023 No Training, \u003cem\u003en\u003c/em\u003e\u0026thinsp;=\u0026thinsp;164; 2023 Training, \u003cem\u003en\u003c/em\u003e\u0026thinsp;=\u0026thinsp;267; 2024 No Training, \u003cem\u003en\u003c/em\u003e\u0026thinsp;=\u0026thinsp;68; 2024 Training, \u003cem\u003en\u003c/em\u003e\u0026thinsp;=\u0026thinsp;64.\u003c/td\u003e\u003c/tr\u003e\u003c/tfoot\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003e\u003cb\u003eFigure 2.\u003c/b\u003e \u003cb\u003eEffect of Training on Perceived Knowledge\u003c/b\u003e\u003c/p\u003e\u003cp\u003e\u003cem\u003eNote\u003c/em\u003e: An asterisk (*) indicates a significant difference between independent groups within years (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;.05).\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec22\" class=\"Section2\"\u003e\u003ch2\u003eImpact of Training on Objective Knowledge\u003c/h2\u003e\u003cp\u003eAcross both years, students in the Training groups demonstrated better objective knowledge of available resources at the university and how to access them (about 20% more accurate in their responses) than the students in the No Training groups (Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e and Fig.\u0026nbsp;3). In 2023, 68% of students in the Training group achieved a passing score (i.e., 60% or higher), compared to just 25% in the No Training group. In 2024, this pattern persisted, with 84% of students in the Training group passing compared to 49% of the No Training group. Consistent with perceived knowledge outcomes, students in both groups showed improved objective knowledge scores from 2023 to 2024.\u003c/p\u003e\u003cp\u003eTo better understand the objective knowledge results, we examined scores for the individual objective knowledge items. Students in both the Training and No Training groups performed poorly when tested on their objective knowledge of their university\u0026rsquo;s main mental health intake unit (\u0026ldquo;You are concerned about a classmate\u0026rsquo;s mental health. Who do you tell?\u0026rdquo;), with approximately 28% of respondents answering correctly across years. Similarly, respondents performed poorly (approximately 13% correct) when tested on their objective knowledge of the university\u0026rsquo;s resource for interpersonal violence education and prevention (\u0026ldquo;You need support related to gender or sexual based violence. Where do you go?\u0026rdquo;). However, students in the Training groups across both years performed notably well on two true/false items assessing awareness of free mental health services available to students (\u0026ldquo;True or False: students get access to free counseling at the Counseling Center.\u0026rdquo;, \u0026ldquo;True or False: students get access to free counseling through Talkspace\u0026rdquo;) with approximately 90% accuracy across both items compared to 66% accuracy in the No Training groups. Similarly, students in the Training groups across both years performed well on the item assessing knowledge of the appropriate resource for basic housing and financial security needs on campus (\u0026ldquo;You need help related to housing or financial insecurity. Where do you go?\u0026rdquo;), with approximately 82% accuracy, compared to 59% accuracy in the No Training groups across both years.\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab4\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003e\u003cem\u003eEffect of Training in Objective Knowledge\u003c/em\u003e\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"7\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eItems\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eGroups\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u003cem\u003eM\u003c/em\u003e\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003e\u003cem\u003eSD\u003c/em\u003e\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u003cem\u003edf\u003c/em\u003e\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c6\"\u003e\u003cp\u003e\u003cem\u003eT\u003c/em\u003e\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c7\"\u003e\u003cp\u003e\u003cem\u003ep\u003c/em\u003e\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"3\" rowspan=\"4\"\u003e\u003cp\u003eAverage Score of 10-Item Quiz\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e2023 No Training\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e39.13%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.22\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003e349.33\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003e9.68\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e2023 Training\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e62.70%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.25\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e2024 No Training\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e50.45%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.24\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003e124.86\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003e5.53\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e2024 Training\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e71.75%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.19\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003ctfoot\u003e\u003ctr\u003e\u003ctd colspan=\"7\"\u003e\u003cem\u003eNote.\u003c/em\u003e Sample sizes for each independent group from both years were as follows: 2023 No Training, \u003cem\u003en\u003c/em\u003e\u0026thinsp;=\u0026thinsp;164; 2023 Training, \u003cem\u003en\u003c/em\u003e\u0026thinsp;=\u0026thinsp;267; 2024 No Training, \u003cem\u003en\u003c/em\u003e\u0026thinsp;=\u0026thinsp;68; 2024 Training, \u003cem\u003en\u003c/em\u003e\u0026thinsp;=\u0026thinsp;64.\u003c/td\u003e\u003c/tr\u003e\u003c/tfoot\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003e\u003cb\u003eFigure 3.\u003c/b\u003e \u003cb\u003eEffect of Training on Objective Knowledge\u003c/b\u003e\u003c/p\u003e\u003cp\u003e\u003cstrong\u003eNote\u003c/strong\u003e\u003cp\u003eAn asterisk (*) indicates a significant difference between independent groups within years (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;.05).\u003c/p\u003e\u003c/p\u003e\u003cdiv id=\"Sec23\" class=\"Section3\"\u003e\u003ch2\u003eImpact of Training on Prioritization of Mental Health and Help-Seeking Intention\u003c/h2\u003e\u003cp\u003eAcross both years, students in the Training and No Training groups reported similar levels of agreement with the belief that they would need to prioritize their academic success over their mental health (Prioritization) and that they would intend to seek help if they had a mental health concern (Intention) (Table\u0026nbsp;\u003cspan refid=\"Tab5\" class=\"InternalRef\"\u003e5\u003c/span\u003e and Fig.\u0026nbsp;3). Across both years and groups, an average of approximately 84% of students reported at least slightly agreeing with the statement that they would need to prioritize their academic success over their mental health during their time as an engineering student. Likewise, only about 49% of students reported that they would be at least slightly likely to seek help from a mental health professional if they were struggling with their mental health. This highlights the low prioritization of mental health and help seeking within the engineering student population.\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab5\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 5\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003e\u003cem\u003eEffect of Training on Prioritization of Mental Health and Help-Seeking Intention\u003c/em\u003e\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"7\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eItems\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eGroups\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u003cem\u003eM\u003c/em\u003e\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003e\u003cem\u003eSD\u003c/em\u003e\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u003cem\u003edf\u003c/em\u003e\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c6\"\u003e\u003cp\u003e\u003cem\u003eT\u003c/em\u003e\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c7\"\u003e\u003cp\u003e\u003cem\u003ep\u003c/em\u003e\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"3\" rowspan=\"4\"\u003e\u003cp\u003ePriority\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e2023 No Training\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e4.60\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e1.46\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003e429.00\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003e0.36\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003e0.72\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e2023 Training\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e4.65\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e1.39\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e2024 No Training\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e4.81\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e1.34\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003e130.00\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003e-1.87\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003e0.06\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e2024 Training\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e4.38\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e1.32\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"3\" rowspan=\"4\"\u003e\u003cp\u003eIntention\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e2023 No Training\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e3.43\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e1.70\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003e265.20\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003e0.75\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003e0.46\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e2023 Training\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e3.30\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e1.43\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e2024 No Training\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e3.24\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e1.51\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003e127.00\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003e1.97\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003e0.05\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e2024 Training\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e3.76\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e1.49\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003ctfoot\u003e\u003ctr\u003e\u003ctd colspan=\"7\"\u003e\u003cem\u003eNote.\u003c/em\u003e Sample sizes for each independent group from both years were as follows: 2023 No Training, \u003cem\u003en\u003c/em\u003e\u0026thinsp;=\u0026thinsp;164; 2023 Training, \u003cem\u003en\u003c/em\u003e\u0026thinsp;=\u0026thinsp;267; 2024 No Training, \u003cem\u003en\u003c/em\u003e\u0026thinsp;=\u0026thinsp;68; 2024 Training, \u003cem\u003en\u003c/em\u003e\u0026thinsp;=\u0026thinsp;64.\u003c/td\u003e\u003c/tr\u003e\u003c/tfoot\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv id=\"Sec24\" class=\"Section2\"\u003e\u003ch2\u003eImpact of Training on Help-Seeking Mechanisms\u003c/h2\u003e\u003cp\u003eAcross both years, students in the Training and No Training groups reported similar levels of agreement with the idea that their seeking help would be a good thing (attitude), most people important to them would think they should seek help (perceived norm), and they are confident they could seek help if they wanted to (personal agency) (Table\u0026nbsp;\u003cspan refid=\"Tab6\" class=\"InternalRef\"\u003e6\u003c/span\u003e and Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e5\u003c/span\u003e). For all three help-seeking mechanisms, the average student in each group across both years indicated uncertainty (i.e., response averages around three and four, which are in the middle of the six-point response scale) about their perceptions toward seeking professional help. In other words, the average student thought that their seeking help would be neither a good nor bad thing (attitude), felt that most of the important people in their lives would neither approve nor disapprove of their seeking help (perceived norm), and were undecided uncertainty about their ability to seek help (personal agency).\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab6\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 6\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003e\u003cem\u003eIndependent T-Test Outcome on Help-Seeking Perceptions in 2023 and 2024\u003c/em\u003e\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"7\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eItems\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eGroups\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u003cem\u003eM\u003c/em\u003e\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003e\u003cem\u003eSD\u003c/em\u003e\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u003cem\u003edf\u003c/em\u003e\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c6\"\u003e\u003cp\u003e\u003cem\u003eT\u003c/em\u003e\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c7\"\u003e\u003cp\u003e\u003cem\u003ep\u003c/em\u003e\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"3\" rowspan=\"4\"\u003e\u003cp\u003eAttitude\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e2023 No Training\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e3.85\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e1.38\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003e355.00\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003e0.36\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003e0.72\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e2023 Training\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e3.90\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e1.37\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e2024 No Training\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e3.82\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e1.28\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003e127.00\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003e1.52\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003e0.13\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e2024 Training\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e4.16\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e1.26\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"3\" rowspan=\"4\"\u003e\u003cp\u003ePerceived Norm\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e2023 No Training\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e4.10\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e1.56\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003e352.00\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003e-0.03\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003e0.98\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e2023 Training\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e4.09\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e1.58\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e2024 No Training\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e3.97\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e1.64\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003e127.00\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003e-0.12\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003e0.90\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e2024 Training\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e3.94\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e1.55\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"3\" rowspan=\"4\"\u003e\u003cp\u003ePersonal Agency\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e2023 No Training\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e3.96\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e1.55\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003e353.00\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003e0.04\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003e0.97\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e2023 Training\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e3.97\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e1.43\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e2024 No Training\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e4.19\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e1.45\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003e127.00\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003e0.80\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003e0.43\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e2024 Training\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e4.39\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e1.29\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003ctfoot\u003e\u003ctr\u003e\u003ctd colspan=\"7\"\u003e\u003cem\u003eNote\u003c/em\u003e. Sample sizes for each independent group from both years were as follows: 2023 No Training (\u003cem\u003en\u003c/em\u003e\u0026thinsp;=\u0026thinsp;164), 2023 Training\" (\u003cem\u003en\u003c/em\u003e\u0026thinsp;=\u0026thinsp;267), \"2024 No Training (\u003cem\u003en\u003c/em\u003e\u0026thinsp;=\u0026thinsp;68), 2024 Training\u0026rdquo; (\u003cem\u003en\u003c/em\u003e\u0026thinsp;=\u0026thinsp;64).\u003c/td\u003e\u003c/tr\u003e\u003c/tfoot\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cdiv id=\"Sec25\" class=\"Section3\"\u003e\u003ch2\u003eRepeated Measures ANOVA (2024)\u003c/h2\u003e\u003cp\u003eOur Two-Way Repeated Measures ANOVA analyses across our 2024 No Training and Training groups corroborated our independent t-test sample results, with two of the four previously significant items no longer showing significant interaction effects. Of the four significant direct effects found from the 2024 independent t-tests (i.e., the three perceived knowledge items and the one objective knowledge item), two of the three variables (\u0026ldquo;I know how to access mental health resources on campus\u0026rdquo;, \u0026ldquo;I know how to recognize signs of mental health distress\u0026rdquo;, ) did not demonstrate a significant interaction effect during the corresponding Two-Way Repeated Measures ANOVA. This indicates that, when accounting for both within-subject changes over time and between-group differences, these two items did not show evidence that the training had a significantly different effect when compared to students without the training. Descriptive statistics for these specific items indicated that baseline pre-intervention scores for students in the 2024 Training group were higher than those in the 2024 No Training group. This reduced the available range for score increases on the 6-point Likert scale (i.e., a potential ceiling effect), which may have limited the ability to detect a significant interaction effect from pre- to post-intervention. It should also be noted that one of these two non-significant items was non-significant due to our conservative use of Bonferroni correction (i.e., the \u003cem\u003ep\u003c/em\u003e of .01 for the item was not below the Bonferroni-adjusted \u003cem\u003ep\u003c/em\u003e threshold of .006). In summary, in two of the four cases, these supplemental Two-Way Repeated Measures ANOVA analyses supported significant findings of the independent sample t-tests results (See Table\u0026nbsp;\u003cspan refid=\"Tab7\" class=\"InternalRef\"\u003e7\u003c/span\u003e below for the Repeated Measures ANOVA interaction effects).\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab7\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 7\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003e\u003cem\u003eRepeated Measures ANOVA Interaction Effects Outcome for 2024\u003c/em\u003e\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"9\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003eItems\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003eGroups\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003e\u003cem\u003eM\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003e\u003cem\u003eSD\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"5\" nameend=\"c9\" namest=\"c5\"\u003e\u003cp\u003eTime*Training\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eSum of Squares\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e\u003cem\u003edf\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003eMean Square\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e\u003cem\u003eF\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e\u003cem\u003ep\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"3\" rowspan=\"4\"\u003e\u003cp\u003eI know what mental health resources are available to students on this campus\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eNo Training - Pre\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e4.21\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1.41\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\" morerows=\"3\" rowspan=\"4\"\u003e\u003cp\u003e9.21\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\" morerows=\"3\" rowspan=\"4\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\" morerows=\"3\" rowspan=\"4\"\u003e\u003cp\u003e9.21\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\" morerows=\"3\" rowspan=\"4\"\u003e\u003cp\u003e11.18\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\" morerows=\"3\" rowspan=\"4\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eNo Training - Post\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e4.41\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1.26\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eTraining - Pre\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e4.27\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1.37\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eTraining - Post\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e5.22\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.72\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"3\" rowspan=\"4\"\u003e\u003cp\u003eI know how to access the available mental health resources on campus\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eNo Training - Pre\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e3.96\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1.52\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\" morerows=\"3\" rowspan=\"4\"\u003e\u003cp\u003e7.71\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\" morerows=\"3\" rowspan=\"4\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\" morerows=\"3\" rowspan=\"4\"\u003e\u003cp\u003e7.71\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\" morerows=\"3\" rowspan=\"4\"\u003e\u003cp\u003e7.38\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\" morerows=\"3\" rowspan=\"4\"\u003e\u003cp\u003e0.01\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eNo Training - Post\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e4.15\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1.31\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eTraining - Pre\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e4.05\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1.43\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eTraining - Post\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e4.92\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.97\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"3\" rowspan=\"4\"\u003e\u003cp\u003eI know how to recognize signs of mental health distress\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eNo Training - Pre\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e4.40\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1.15\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\" morerows=\"3\" rowspan=\"4\"\u003e\u003cp\u003e0.68\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\" morerows=\"3\" rowspan=\"4\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\" morerows=\"3\" rowspan=\"4\"\u003e\u003cp\u003e0.68\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\" morerows=\"3\" rowspan=\"4\"\u003e\u003cp\u003e1.23\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\" morerows=\"3\" rowspan=\"4\"\u003e\u003cp\u003e0.27\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eNo Training - Post\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e4.40\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1.24\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eTraining - Pre\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e4.80\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1.00\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eTraining - Post\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e5.00\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.93\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"3\" rowspan=\"4\"\u003e\u003cp\u003eAverage Score of 10-Item Quiz\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eNo Training - Pre\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.44\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.22\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\" morerows=\"3\" rowspan=\"4\"\u003e\u003cp\u003e0.27\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\" morerows=\"3\" rowspan=\"4\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\" morerows=\"3\" rowspan=\"4\"\u003e\u003cp\u003e0.27\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\" morerows=\"3\" rowspan=\"4\"\u003e\u003cp\u003e14.48\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\" morerows=\"3\" rowspan=\"4\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eNo Training - Post\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.50\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.24\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eTraining - Pre\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.52\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.24\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eTraining - Post\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.72\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.19\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"3\" rowspan=\"4\"\u003e\u003cp\u003ePriority\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eNo Training - Pre\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e4.90\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1.20\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\" morerows=\"3\" rowspan=\"4\"\u003e\u003cp\u003e0.35\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\" morerows=\"3\" rowspan=\"4\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\" morerows=\"3\" rowspan=\"4\"\u003e\u003cp\u003e0.35\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\" morerows=\"3\" rowspan=\"4\"\u003e\u003cp\u003e0.72\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\" morerows=\"3\" rowspan=\"4\"\u003e\u003cp\u003e0.40\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eNo Training - Post\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e4.81\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1.34\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eTraining - Pre\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e4.61\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1.12\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eTraining - Post\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e4.38\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1.32\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"3\" rowspan=\"4\"\u003e\u003cp\u003eIntention\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eNo Training - Pre\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e3.04\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1.67\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\" morerows=\"3\" rowspan=\"4\"\u003e\u003cp\u003e0.60\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\" morerows=\"3\" rowspan=\"4\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\" morerows=\"3\" rowspan=\"4\"\u003e\u003cp\u003e0.60\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\" morerows=\"3\" rowspan=\"4\"\u003e\u003cp\u003e0.76\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\" morerows=\"3\" rowspan=\"4\"\u003e\u003cp\u003e0.39\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eNo Training - Post\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e3.24\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1.51\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eTraining - Pre\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e3.37\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1.35\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eTraining - Post\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e3.76\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1.49\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"3\" rowspan=\"4\"\u003e\u003cp\u003eAttitude\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eNo Training - Pre\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e3.51\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1.58\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\" morerows=\"3\" rowspan=\"4\"\u003e\u003cp\u003e0.00\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\" morerows=\"3\" rowspan=\"4\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\" morerows=\"3\" rowspan=\"4\"\u003e\u003cp\u003e0.00\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\" morerows=\"3\" rowspan=\"4\"\u003e\u003cp\u003e0.00\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\" morerows=\"3\" rowspan=\"4\"\u003e\u003cp\u003e0.97\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eNo Training - Post\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e3.82\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1.28\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eTraining - Pre\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e3.85\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1.29\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eTraining - Post\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e4.16\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1.26\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"3\" rowspan=\"4\"\u003e\u003cp\u003ePerceived Norm\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eNo Training - Pre\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e3.94\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1.66\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\" morerows=\"3\" rowspan=\"4\"\u003e\u003cp\u003e0.07\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\" morerows=\"3\" rowspan=\"4\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\" morerows=\"3\" rowspan=\"4\"\u003e\u003cp\u003e0.07\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\" morerows=\"3\" rowspan=\"4\"\u003e\u003cp\u003e0.06\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\" morerows=\"3\" rowspan=\"4\"\u003e\u003cp\u003e0.81\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eNo Training - Post\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e3.97\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1.64\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eTraining - Pre\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e3.84\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1.63\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eTraining - Post\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e3.94\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1.55\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"3\" rowspan=\"4\"\u003e\u003cp\u003ePersonal Agency\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eNo Training - Pre\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e3.97\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1.71\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\" morerows=\"3\" rowspan=\"4\"\u003e\u003cp\u003e0.50\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\" morerows=\"3\" rowspan=\"4\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\" morerows=\"3\" rowspan=\"4\"\u003e\u003cp\u003e0.50\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\" morerows=\"3\" rowspan=\"4\"\u003e\u003cp\u003e0.59\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\" morerows=\"3\" rowspan=\"4\"\u003e\u003cp\u003e0.45\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eNo Training - Post\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e4.19\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1.45\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eTraining - Pre\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e4.34\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1.32\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eTraining - Post\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e4.39\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1.29\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec26\" class=\"Section3\"\u003e\u003ch2\u003eOpen-Ended Responses\u003c/h2\u003e\u003cp\u003eWe received 188 open-ended qualitative responses from the 399 students who completed the post-assessment across both years (124 responses in 2023, and 64 responses in 2024), providing feedback on two open-ended questions asking what they found most helpful about the presentation and what could have made the presentation more helpful. Students shared that they found the education and explanation of available mental health resources most helpful across both years. For example, one student stated, \u0026ldquo;It gave resources and methods to support ourselves and friends going through hard mental periods\u0026rdquo; and another shared, \u0026ldquo;The presentation provided a number of mental health resources at [the university] that I didn\u0026rsquo;t previously know about.\u0026rdquo; Smaller trends also emerged, with students expressing appreciation for the engineering-specific content integrated into the presentation. This tailored content included quotes from engineering student focus groups discussing help seeking, institutional data showing that higher distress was associated with lower end-of-term grades for engineering students and published research relating to engineering culture and student mental health. For example, one student said, \u0026ldquo;Shows that most engineers deal with some distress, makes me feel not alone\u0026rdquo;. Students also appreciated how the presentation prioritized mental wellness and challenged mental health stigma (e.g., \u0026ldquo;It reminded me that I needed to take care of myself\u0026rdquo;) and the overall engaging and effective style of the speaker and/or the presentation (e.g., \u0026ldquo;The information was presented in a very understanding and sincere manner\u0026rdquo;). Notably, many students in the 2023 group reported appreciating the practical self-care skills discussed in the presentation (e.g., \u0026ldquo;Learning skills to identify stress and bad habits\u0026rdquo;)\u003c/p\u003e\u003cp\u003eWhen asked what could be changed to make the presentation more helpful, approximately one-third of the 2023 and 2024 respondents stated \u0026ldquo;nothing,\u0026rdquo; indicating that either the presentation was already effective (e.g., \u0026ldquo;The presentation was wonderful\u0026rdquo;) and/or not providing additional suggestions (e.g., \u0026ldquo;I couldn\u0026rsquo;t think of anything while witnessing the presentation\u0026rdquo;). Smaller observations included students wanting the presentation style to be improved in a specific way (e.g., \u0026ldquo;The speaker spoke very fast\u0026rdquo;) or recommendations to improve the presentation content and its accessibility (e.g., \u0026ldquo;Send us home with [a] pamphlet\u0026rdquo;). A large number of students in the 2024 group suggested that the presentation should include more of engineers\u0026rsquo; direct perspective on mental health, through either testimonials or the presenters themselves having an engineering background (e.g., \u0026ldquo;...having an engineer\u0026hellip;who could sympathize with the students' circumstance, and someone with whom we as engineering students can better relate with, give the presentation might yield better results\u0026rdquo;). Collectively, these responses show that while students generally viewed the presentation as helpful, they also underscored the value of tailoring future iterations more explicitly to engineering students\u0026rsquo; experiences.\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e"},{"header":"DISCUSSION","content":"\u003cp\u003eThe current study contributes to a nascent body of research aimed at promoting mental health help-seeking among engineering undergraduates by evaluating the impact of a brief, scalable mental health training intervention. Findings suggest that our training significantly increased students\u0026rsquo; mental health perceptions, knowledge, and skills (i.e., perceived and objective knowledge of available mental health resources) across both 2023 and 2024 groups but did not significantly shift their help-seeking beliefs (e.g., prioritizing academics over mental health needs), help-seeking determinants (e.g., attitude, perceived norm, personal agency), or help-seeking intention. Perceived knowledge of how to access resources and ability to recognize signs of mental health distress both appeared to significantly increase for the training groups when analyzed using a t -tests; however, the more rigorous 2024 Repeated Measures ANOVA indicated that only two of the four previously significant knowledge items remained significant, suggesting that improvements in certain perceived knowledge domains were less robust under stricter analytic scrutiny. However, 2024 findings could be due to a potential ceiling effect of the measure and/or because the 2024 Training was not able to further increase these forms of perceived knowledge from their 2024 baseline levels. Descriptively, we noticed an upward trend in the perceived knowledge items from 2023 baseline to 2024 across the overall samples, which may reflect increased resource awareness over time due to a combination of this college-wide intervention (i.e., students performing better due to the prior year\u0026rsquo;s training) and broader institutional cultural shifts (i.e., expanded efforts to advertise mental health resources).\u003c/p\u003e\u003cp\u003eStudents in the Training groups also demonstrated higher objective knowledge scores in both years than those in the No Training groups. These findings suggest that the training not only improved students\u0026rsquo; confidence in their knowledge of available resources but also translated into measurable improvements in their factual understanding and retention of the campus mental health resource information. This finding is noteworthy, as difficulty locating accessible mental health resources has been identified as a perceived barrier to help-seeking among engineering students (Wright et al. \u003cspan citationid=\"CR86\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). When comparing results across the 10 items, students tended to perform better when answering questions about resources with descriptive and intuitive names (e.g., \u0026ldquo;Basic Needs\u0026rdquo; relating to housing or financial support) compared to when acronyms were used (e.g., the \u0026ldquo;VIP Center\u0026rdquo;, relating to support for students who are survivors of sexual or gender-based violence\u003cem\u003e).\u003c/em\u003e This pattern aligns with prior findings that acronym-based labels can impede comprehension, suggesting that universities take a critical look at their naming conventions when developing student-facing resources. For example, Grossman and colleagues (2022) found that patients\u0026rsquo; comprehension of health information improved from 62% to 95% when ten common medical abbreviations were replaced with full terms. Overall, scores for the 2024 training were about 10 percentage points higher than those for 2023. This could be due to student exposure to the mental health content and resources during the 2023 training year.\u003c/p\u003e\u003cp\u003eRegarding prioritization of mental health, students in both years consistently endorsed the belief that they would prioritize their academic success over their own mental health, regardless of whether they received the training or not. These results are consistent with prior research indicating that engineering students report having limited time to schedule and attend mental health appointments due to their intense course load and believing they must complete and succeed in their academics \u0026ldquo;by any means necessary\u0026rdquo;, consequently avoiding and/or delaying help-seeking behaviors (Wright et al. 2021; Wright et al. \u003cspan citationid=\"CR86\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). Similarly, help-seeking attitude, perceived norm, personal agency, and intention all remained unchanged despite the training. Across all years and groups, engineering students reported neutral levels (scores close to the mid-point of the measurement scale) on these help-seeking perception constructs, aligning with prior research reporting neutral-to-slightly-positive help-seeking perceptions among undergraduate engineering students (Hammer et al., \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e2024\u003c/span\u003e; Wilson et al., 2022; Wilson, Huth, et al., 2024). In other words, the average engineering student expressed ambivalence about whether seeking help would be good or bad (attitude), whether important people in their lives would want to them seek help (injunctive component of perceived norm), whether they felt capable of seeking help (personal agency), and whether they would plan to seek help if distressed (intention).\u003c/p\u003e\u003cp\u003eIt is likely that our one-time, brief presentation lacked the dosage (e.g., length and/or frequency of intervention) needed to change these more entrenched help-seeking perceptions reinforced by engineering culture\u0026rsquo;s emphasis on stoicism, self-reliance, and academic grit (Jensen \u0026amp; Cross \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; Godfrey \u0026amp; Parker \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e2010\u003c/span\u003e). Generally, brief interventions are more successful at improving knowledge than shifting perceptions, attitude, and beliefs (Laschke et al., \u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). For example, Raghavan and colleagues (\u003cspan citationid=\"CR54\" class=\"CitationRef\"\u003e2024\u003c/span\u003e) found that a one-time, 90-minute mental health literacy presentation significantly improved students\u0026rsquo; understanding of mental illness and help-seeking behaviors in Indian educational settings. However, the long-term outcomes of interventions targeting college students\u0026rsquo; mental health literacy is largely unknown, as reported by a 2021 systematic review (Reis et al., \u003cspan citationid=\"CR55\" class=\"CitationRef\"\u003e2022\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eAdditionally, the literature suggests that shifting deeper, long-term help-seeking perceptions is likely more difficult for brief interventions, compared to improving short-term mental health knowledge. For example, Tan and colleagues (\u003cspan citationid=\"CR70\" class=\"CitationRef\"\u003e2021\u003c/span\u003e) evaluated a single-session intervention in Singapore that combined an educational presentation with a speaker who had lived experience of depression. The intervention improved students\u0026rsquo; recognition of mental health conditions (i.e., objective knowledge) and temporarily shifted their help-seeking preferences, but the latter effects were not maintained at the three-week follow-up. A broader systematic review by Lo and colleagues (\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e2018\u003c/span\u003e) further supports this trend, showing that while mental health literacy among college students reliably improves with brief interventions, lasting changes in stigma, attitude, and behavioral intention were less consistent, likely requiring additional engagement and/or interventions designed to influence help-seeking perceptions directly. As an example, Shahwan and colleagues (\u003cspan citationid=\"CR61\" class=\"CitationRef\"\u003e2020\u003c/span\u003e) found that, although a 50-minute anti-stigma intervention initially improved help-seeking attitude among university students, those gains declined in follow-up evaluations. A systematic review by Waqas and colleagues (\u003cspan citationid=\"CR78\" class=\"CitationRef\"\u003e2020\u003c/span\u003e) further highlights that interventions in educational institutions (schools, colleges, universities) that were longer than four weeks are more likely to produce long-term changes in attitude and intention, suggesting that duration and repeated engagement may be critical for shifting entrenched cultural beliefs.\u003c/p\u003e\u003cp\u003eBloom\u0026rsquo;s Taxonomy of Learning (Bloom et al., \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e1956\u003c/span\u003e; Krathwohl et al., \u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e1964\u003c/span\u003e) may also explain why brief interventions succeed at promoting short-term improvements in mental health literacy but struggle to affect other mental health help-seeking perceptions (e.g., attitude, intention). According to the taxonomy, at the lowest cognitive level, \u003cem\u003eremembering\u003c/em\u003e involves recalling facts (e.g., correctly identifying mental health resources on campus and their services from the intervention). In contrast, higher levels such as \u003cem\u003eevaluating\u003c/em\u003e or \u003cem\u003ecreating\u003c/em\u003e require students to critically assess and internalize new perspectives (Bloom et al., \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e1956\u003c/span\u003e). Bloom and colleagues also outlined an affective domain of learning targeting values and beliefs; these outcomes are harder to achieve because they require deeper internalization of values, requiring significantly more time and engagement to develop (Krathwohl et al., \u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e1964\u003c/span\u003e). Therefore, while factual recall can be accomplished in brief interventions, changing how students feel about mental health help seeking likely requires higher-order or affective processes that generally demand more reinforcement over time. This conclusion is supported by other learning models. According to the Elaboration Likelihood Model (ELM), brief interventions may not provide sufficient opportunity, motivation, or repeated exposure for students to process information through the central route. Instead, they are more likely to rely on peripheral cues (e.g., source credibility or message attractiveness) when forming attitudes, limiting the potential for deeper attitudinal change (Petty \u0026amp; Cacioppo, \u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e1986\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eHowever, beyond dosage alone, the broader cultural context in which engineering students operate may have played a more significant role in shaping the persistence or attenuation of any potential intervention effects. As students exited the room following our 15-minute presentations, they reentered an academic environment that may not consistently reinforce the values promoted during the intervention. If students are subsequently immersed in a departmental or disciplinary culture that sends implicit or explicit messages that stigmatize vulnerability or prioritize academic achievement over well-being (Wright et al. 2021; Wright et al. \u003cspan citationid=\"CR86\" class=\"CitationRef\"\u003e2023\u003c/span\u003e), such environmental cues may \u0026ldquo;overwrite\u0026rdquo; or undermine the salience of our brief message. In contrast, interventions are more likely to be effective and sustainable when they are embedded within a cohesive and consistent cultural framework that communicates mental health as a collective priority across messaging, policies, peer norms and organizations, and faculty-student interactions. One such example is a \u0026ldquo;whole-school approach\u0026rdquo;: campuses working collaboratively across their academic community (e.g., students, peer organizations, families, staff) while acknowledging the impact of local and government policies to promote student mental health literacy and mental health perceptions (Sontag-Padilla et al., 2016; O\u0026rsquo;Reilly et al., \u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). Future research and practice should consider how single-session interventions can be integrated into broader departmental and institutional strategies that work in concert to shift social norms and institutional climates toward greater valuing of mental health and openness to help-seeking.\u003c/p\u003e\u003cp\u003e The qualitative thematic analysis provided additional context to our quantitative findings, particularly highlighting the value of resource education and tailoring the content to engineering undergraduates. Students highlighted the presentation\u0026rsquo;s use of engineering student data and testimonials from the university, along with discussing cultural norms and expectations around mental health and help seeking, as key strengths, noting that these elements made them feel less alone and validated in their experiences. Many students described the resource-specific content as the most helpful aspect of the presentation, which aligns with the significant improvements observed in both perceived and objective knowledge across both years. Suggestions for improvement frequently emphasized presentational style and relatability of the speaker, with 2024 students especially advocating for future use of presenters with engineering backgrounds. This feedback is supported by existing literature; within U.S. engineering programs, qualitative work shows students face barriers to formal help-seeking and commonly rely on peers to cope, implying that in-group messengers who \u0026ldquo;get\u0026rdquo; engineering culture may be more credible and relatable (Jensen et al., \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). Complementing this, a national survey of U.S. science/engineering instructors found faculty believed disclosing their own depression/anxiety would normalize struggle and provide role models for undergraduates, further emphasizing the belief that normalizing mental health distress within the culture could be beneficial (Busch et al., \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e2024\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eOverall, our findings through this study were consistent with prior literature on brief interventions. As expected, we observed significant improvements in mental health knowledge and awareness of campus resources. A unique central strength of our study was its scale and potential for institutional impact. Unlike conventional programs such as Question, Persuade, Refer (QPR), which typically target small groups of \u0026lsquo;natural helpers\u0026rsquo; (e.g., resident advisors, faculty, staff) (Burnette et al., \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e2015\u003c/span\u003e\u0026rsquo; Tompkins \u0026amp; Witt, \u003cspan citationid=\"CR72\" class=\"CitationRef\"\u003e2009\u003c/span\u003e; Taub et al., \u003cspan citationid=\"CR71\" class=\"CitationRef\"\u003e2013\u003c/span\u003e), our curriculum-embedded intervention reached a full undergraduate engineering population (~\u0026thinsp;4,500 students across two years). This scope positions our project among the few large-scale, college-wide efforts to promote mental health literacy in engineering. In contrast to traditional small-group training models, which often result in limited coverage, our intervention achieved widespread exposure across the engineering student body. This greater saturation enhances the probability that distressed students will have access to informed peers who can help them navigate mental health resources. Our program constitutes an early and practical step toward a \u0026ldquo;whole-college approach\u0026rdquo; to destigmatizing help-seeking and promoting wellness in engineering education.\u003c/p\u003e\u003cp\u003eWhile our training was not policy-driven (e.g., we did not implement formal mandates such as faculty-required compliance or curricular policy changes), its success lay in being a scalable, low-investment intervention that could be flexibly embedded within existing courses, offering an accessible entry point for broader institutional change. By providing students with accurate, discipline-specific psychoeducation and resource knowledge while normalizing conversations around seeking help toward mental health, the training contributes incremental momentum toward larger, college-supported strategies and programming. Within this context, our brief presentation serves as one voice within a much larger engineering culture: a single message likely competing with other powerful influences previously discussed such as academic norms, performance pressures, and perceptions of self-reliance. Although one 15-minute intervention alone cannot overturn these entrenched cultural dynamics, it can catalyze attitudinal shifts when paired with other consistent reinforcements across the college.\u003c/p\u003e\u003cp\u003eThis perspective aligns with emerging evidence that meaningful cultural change in STEM education requires multi-level, sustained engagement across students, faculty, and administration. Indeed, recent grants awarded by the National Science Foundation (NSF) to support mental-health initiatives within STEM contexts, including the M-HOPES project for graduate STEM students (Montana State University Billings, n.d.) the five-year Institutional Transformation Project at Montclair State University designed to embed group-counselling into STEM internships (Montclair State University, 2024), and the Engineering Wellness Center at the University of Kentucky designed to prioritize the social and emotional wellness of engineering students (University of Kentucky, n.d.), signal a broader institutional commitment to improving mental health among STEM student populations. Future studies should evaluate how sustained funding, and coordinated programming e.g., faculty development workshops, departmental initiatives, peer-led interventions) and changes to policy structures (e.g., recognition for faculty and staff efforts related to student well-being) can build on this scalable model to foster a cohesive and sustainable culture of wellness.\u003c/p\u003e\u003cdiv id=\"Sec28\" class=\"Section2\"\u003e\u003ch2\u003eAddressing Limitations Through Future Research\u003c/h2\u003e\u003cp\u003eSeveral limitations of this study should be acknowledged. Firstly, although t-test results suggested improvements in several perceived knowledge items, the 2024 Repeated Measures ANOVA analyses demonstrated that only some of these effects remained significant when accounting for within-subject change and between-group differences, indicating that certain knowledge gains may have been more modest than initially suggested. Secondly, while the study included a large sample, the survey responses were voluntary and therefore may be subject to self-selection bias; students who chose to complete the surveys may differ systematically from those who did not, potentially limiting the representativeness of the findings. For instance, because the email inviting students to complete the survey mentioned mental health, students with more positive beliefs about mental health and help seeking might have been more likely to complete the survey. We attempted to mitigate this sampling bias through a monetary incentive for survey participation. Thirdly, demographic data were incomplete for the 2023 Training sample, making it difficult to assess whether observed effects varied across different identities. However, the demographic distribution of those that did provide data was similar to those in the No Training group, suggesting that the data was collected from a representative population of students. Additionally, the time interval between the intervention and post-assessment was not strictly standardized across participants (i.e., some participants provided post-assessment data a few days after receiving the intervention whereas others provided data a few weeks after), which may have contributed to variability in recall and scoring. Finally, the study was conducted at a single large public university in the southeastern United States, and findings may not generalize to other institutional contexts with different engineering cultures, student populations, or mental health resource availability. Future studies should consider implementing longitudinal versions of this training to evaluate whether repeated exposure, combined with broader institutional support and policy changes, can more effectively shift deeply rooted mental health help seeking perceptions. Enhancing the training by having it delivered by engineering student peers may also increase its relatability and destigmatizing impact, as this approach has been positively received in similar interventions (Paul et al., \u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). More broadly, additional studies that continue to measure specific help-seeking constructs from the Integrated Behavioral Model of Mental Health Help Seeking (IBM-HS) would enable stronger comparisons across studies and contribute to a more robust understanding of help-seeking patterns within engineering student populations.\u003c/p\u003e\u003c/div\u003e"},{"header":"Conclusion","content":"\u003cp\u003eGrounded in the Integrated Behavioral Model for Mental Health Help Seeking, this study advances the limited literature on engineering-specific mental health interventions by demonstrating that a brief, scalable presentation can significantly improve students\u0026rsquo; perceived and objective knowledge of mental health resources, an outcome consistent with Bloom\u0026rsquo;s Taxonomy and expectations for short-form educational programs. Consistent with this theoretical expectation, more entrenched help-seeking beliefs (e.g., prioritizing academics over mental health) and perceptions (intention, attitude, perceived norm, personal agency) were not significantly changed, reflecting the complexity of shifting cultural norms around distress, productivity, and self-reliance within engineering training programs. By reaching nearly 4,500 students across two years, this curriculum-embedded approach represents an early step toward a scalable, whole-college strategy for mental health promotion. Continued efforts are needed to refine interventions for this population and integrate them into coordinated departmental and institutional strategies that make help-seeking a supported and expected part of the engineering student experience.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cp\u003eANOVA: Analyses of Variance\u003c/p\u003e\n\u003cp\u003eDRC: Disability Resource Center\u003c/p\u003e\n\u003cp\u003eELM: Elaboration Likelihood Model\u003c/p\u003e\n\u003cp\u003eGen AI: Generative Artificial Intelligence\u003c/p\u003e\n\u003cp\u003eIBM-HS: Integrated Behavioral Model of Mental Health Help Seeking\u003c/p\u003e\n\u003cp\u003eIBM SPSS: International Business Machines Corporation Statistical Package for the Social Sciences\u003c/p\u003e\n\u003cp\u003eIRB: Institutional Review Board\u003c/p\u003e\n\u003cp\u003eLGBQ+: Lesbian, Gay, Bisexual, Queer/Questioning, Plus\u003c/p\u003e\n\u003cp\u003eLGBTQIA: Lesbian, Gay, Bisexual, Transgender, Queer/Questioning, Intersex, Asexual\u003c/p\u003e\n\u003cp\u003eMHSIS: Mental Health Help-Seeking Intention Scale\u003c/p\u003e\n\u003cp\u003eNSF: National Science Foundation\u003c/p\u003e\n\u003cp\u003eQPR: Question, Persuade, Refer\u003c/p\u003e\n\u003cp\u003eST-TA: Structured Tabular Thematic Analysis\u003c/p\u003e\n\u003cp\u003eSTEM: Science, Technology, Engineering, Mathematics\u003c/p\u003e\n\u003cp\u003eUE-MH-HSI: Undergraduate Engineering Mental Health Help-Seeking Instrument\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAvailability of Data and Materials\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eResearchers interested in accessing our de-identified data or study instruments are welcome to contact the research team for more information.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting Interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe have no conflicts of interest to disclose, and this manuscript has not been published nor submitted simultaneously for publication elsewhere.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eHuman Ethics and Consent to Participate\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study was approved by the Institutional Review Board (Protocol #86047) at [name of institution redacted for masked peer review]. All participants provided informed consent prior to survey participation, and all procedures complied with institutional and national ethical standards for human subjects research.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis research was supported by grants from the [\u003cem\u003ename of institutional redacted\u003c/em\u003e] Institutional Multidisciplinary Paradigm to Accelerate Collaboration and Transformation initiative and the National Science Foundation (Award Numbers [\u003cem\u003eredacted for masked peer review\u003c/em\u003e] and \u003cem\u003e[redacted for masked peer review\u003c/em\u003e]). Any opinions, findings, conclusions, or recommendations expressed in the material are those of the authors and do not necessarily reflect those of the National Science Foundation.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor\u0026rsquo;s Contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e[\u003cem\u003eredacted for masked peer review and included separately in submission\u003c/em\u003e]\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgements\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors acknowledge the contributions of the eight mental health training presenters and [\u003cem\u003eredacted for masked peer review\u003c/em\u003e], an undergraduate Engineering major who assisted in the thematic coding of our qualitative data. Lastly, thank you to the students who took the time to contribute their perspectives to our studies.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors\u0026rsquo; Information\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e[\u003cem\u003eredacted for masked peer review\u003c/em\u003e]\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eAbiade, J., \u0026amp; Moliski, J. (2020, June). Work-in Progress: Identity and transitions laboratory: Utilizing acceptance and commitment therapy framework to support engineering student success. In \u003cem\u003e2020 ASEE Virtual Annual Conference Content Access\u003c/em\u003e.\u003c/li\u003e\n\u003cli\u003eAkter, M. J., Mim, A. S., Afrin, S., Ahad, A., Kundu, A., \u0026amp; Bijoy, M. H. I. (2025, February). Mental Health in Engineering Students: Investigating the Factors of Depression and Coping Mechanisms. In \u003cem\u003e2025 International Conference on Electrical, Computer and Communication Engineering (ECCE)\u003c/em\u003e (pp. 1-7). IEEE.\u003c/li\u003e\n\u003cli\u003eArmstrong, R. A. (2014). When to use the Bonferroni correction. \u003cem\u003eOphthalmic and physiological optics\u003c/em\u003e, \u003cem\u003e34\u003c/em\u003e(5), 502-508.\u003c/li\u003e\n\u003cli\u003eArria, A. M., Caldeira, K. M., Vincent, K. B., Winick, E. R., Baron, R. A., \u0026amp; O\u0026apos;Grady, K. E. (2013). Discontinuous college enrollment: Associations with substance use and mental health. \u003cem\u003ePsychiatric Services\u003c/em\u003e, \u003cem\u003e64\u003c/em\u003e(2), 165-172.\u003c/li\u003e\n\u003cli\u003eAsghar, M., Minichiello, A., \u0026amp; Ahmed, S. (2024). Mental health and wellbeing of undergraduate students in engineering: A systematic literature review. \u003cem\u003eJournal of Engineering Education\u003c/em\u003e, \u003cem\u003e113\u003c/em\u003e(4), 1046-1075.\u003c/li\u003e\n\u003cli\u003eBan, N., Mensah, L. O., Whitwer, M., Hargis, L. E., Wright, C. J., Hammer, J. H., \u0026amp; Wilson, S. A. (2023). \u0026ldquo;It\u0026rsquo;s very important to my professors\u0026hellip; at least most of them\u0026rdquo;: How messages from engineering faculty and staff influence student beliefs around seeking help for their mental health. In \u003cem\u003e2023 ASEE annual conference \u0026amp; exposition. \u003c/em\u003e\u003c/li\u003e\n\u003cli\u003eBan, N., H. Shannon, C. J. Wright, M. E. Miller, L. E. Hargis, E. L. Usher, J. H. Hammer, and S. A. Wilson (2022). \u0026quot;Identifying common perceived stressors and stress-relief strategies among undergraduate engineering students.\u0026quot; In \u003cem\u003eASEE annual conference exposition\u003c/em\u003e.\u003c/li\u003e\n\u003cli\u003eBeddoes, K., \u0026amp; Danowitz, A. (2022, August). In their own words: How aspects of engineering education undermine students\u0026rsquo; mental health. In \u003cem\u003e2022 ASEE annual conference \u0026amp; exposition\u003c/em\u003e.\u003c/li\u003e\n\u003cli\u003eBlanca, M. J., Arnau, J., Garc\u0026iacute;a-Castro, F. J., Alarc\u0026oacute;n, R., \u0026amp; Bono, R. (2023). Repeated measures ANOVA and adjusted F-tests when sphericity is violated: which procedure is best?. \u003cem\u003eFrontiers in Psychology\u003c/em\u003e, \u003cem\u003e14\u003c/em\u003e, 1192453.\u003c/li\u003e\n\u003cli\u003eBloom, B. S., Engelhart, M. D., Furst, E. J., Hill, W. H., \u0026amp; Krathwohl, D. R. (1956). \u003cem\u003eTaxonomy of educational objectives: The classification of educational goals. Handbook I: Cognitive domain\u003c/em\u003e. David McKay Company.\u003c/li\u003e\n\u003cli\u003eBurnette, C., Ramchand, R., \u0026amp; Ayer, L. (2015). \u003cem\u003eGatekeeper Training for Suicide Prevention: A Theoretical Model and Review of the Evidence.\u003c/em\u003e RAND Corporation.\u003c/li\u003e\n\u003cli\u003eBusch, C. A., Barstow, M., Brownell, S. E., \u0026amp; Cooper, K. M. (2024). Why US science and engineering undergraduates who struggle with mental health are left without role models. \u003cem\u003ePLOS Mental Health\u003c/em\u003e, \u003cem\u003e1\u003c/em\u003e(7), e0000086.\u003c/li\u003e\n\u003cli\u003eCantoni, N. P., \u0026amp; Parker, V. L. (2025). Observing an Intervention to Reduce Treatment Stigma of College Students: Canine-Assisted Counseling vs. Treatment as Usual. \u003cem\u003eAnthrozo\u0026ouml;s\u003c/em\u003e, 1-14.\u003c/li\u003e\n\u003cli\u003eCornally, N., \u0026amp; McCarthy, G. (2011). Help-seeking behaviour: A concept analysis. \u003cem\u003eInternational journal of nursing practice\u003c/em\u003e, \u003cem\u003e17\u003c/em\u003e(3), 280-288.\u003c/li\u003e\n\u003cli\u003eDoll, C. M., Michel, C., Rosen, M., Osman, N., Schimmelmann, B. G., \u0026amp; Schultze-Lutter, F. (2021). Predictors of help-seeking behaviour in people with mental health problems: A 3-year prospective community study. \u003cem\u003eBMC Psychiatry, 21\u003c/em\u003e(1), 432. \u003c/li\u003e\n\u003cli\u003eEren-Sisman, E. N., Cigdemoglu, C., \u0026amp; Geban, O. (2018). The effect of peer-led team learning on undergraduate engineering students\u0026rsquo; conceptual understanding, state anxiety, and social anxiety. \u003cem\u003eChemistry Education Research and Practice\u003c/em\u003e, \u003cem\u003e19\u003c/em\u003e(3), 694-710.\u003c/li\u003e\n\u003cli\u003eGodfrey, E., \u0026amp; Parker, L. (2010). Mapping the cultural landscape in engineering education. \u003cem\u003eJournal of Engineering education\u003c/em\u003e, \u003cem\u003e99\u003c/em\u003e(1), 5-22.\u003c/li\u003e\n\u003cli\u003eFishbein, M., \u0026amp; Ajzen, I. (2011). \u003cem\u003ePredicting and changing behavior: The reasoned action \u003c/em\u003e\u003c/li\u003e\n\u003cli\u003eGastwirth, J. L., Gel, Y. R., \u0026amp; Miao, W. (2009). The impact of Levene\u0026rsquo;s test of equality of variances on statistical theory and practice. \u003cem\u003eStatistical Science, 24\u003c/em\u003e(3), 343-360.\u003c/li\u003e\n\u003cli\u003eGrasty, K., Sakri, S., Arnold, A. C., Bekki, J. M., Wilkins-Yel, K. G., Natarajan, M., Bernstein, B. L., \u0026amp; Randall, A. K. (2021, July). Benefits of Utilizing Counseling Services Among Doctoral Women of Color in STEM. In \u003cem\u003e2021 ASEE Virtual Annual Conference Content Access\u003c/em\u003e.\u003c/li\u003e\n\u003cli\u003eHammer, J. H., Parent, M. C., \u0026amp; Spiker, D. A. (2018). Mental Help Seeking Attitudes Scale (MHSAS): Development, reliability, validity, and comparison with the ATSPPH-SF and IASMHS-PO. \u003cem\u003eJournal of counseling psychology\u003c/em\u003e, \u003cem\u003e65\u003c/em\u003e(1), 74.\u003c/li\u003e\n\u003cli\u003eHammer, J. H., Vogel, D. L., Grzanka, P. R., Kim, N., Keum, B. T., Adams, C., \u0026amp; Wilson, S. A. (2024). The integrated behavioral model of mental health help seeking (IBM-HS): A health services utilization theory of planned behavior for accessing care. \u003cem\u003eJournal of Counseling Psychology\u003c/em\u003e.\u003c/li\u003e\n\u003cli\u003eHammer, J. H., Wright, C. J., Miller, M. E., \u0026amp; Wilson, S. A. (2024). The Undergraduate Engineering Mental Health Help-Seeking Instrument (UE-MH-HSI): Development and validity evidence. \u003cem\u003eJournal of Engineering Education\u003c/em\u003e, \u003cem\u003e113\u003c/em\u003e(4), 1198-1225.\u003c/li\u003e\n\u003cli\u003eHampton, C., Reeping, D., \u0026amp; Ozkan, D. S. (2021). Positionality statements in engineering education research: A look at the hand that guides the methodological tools. \u003cem\u003eStudies in Engineering Education\u003c/em\u003e, \u003cem\u003e1\u003c/em\u003e(2).\u003c/li\u003e\n\u003cli\u003eHyseni Duraku, Z., Davis, H., \u0026amp; Hamiti, E. (2023). Mental health, study skills, social support, and barriers to seeking psychological help among university students: a call for mental health support in higher education. \u003cem\u003eFrontiers in Public Health\u003c/em\u003e, \u003cem\u003e11\u003c/em\u003e, 1220614.Jensen, K. J., \u0026amp; Cross, K. J. (2021). Engineering stress culture: Relationships among mental health, engineering identity, and sense of inclusion. \u003cem\u003eJournal of Engineering Education\u003c/em\u003e, \u003cem\u003e110\u003c/em\u003e(2), 371-392.\u003c/li\u003e\n\u003cli\u003eJensen, K. J., \u0026amp; Cross, K. J. (2021). Engineering stress culture: Relationships among mental health, engineering identity, and sense of inclusion. \u003cem\u003eJournal of Engineering Education, 110\u003c/em\u003e(2), 371-392.\u003c/li\u003e\n\u003cli\u003eJensen, K. J., Mirabelli, J. F., Kunze, A. J., Romanchek, T. E., \u0026amp; Cross, K. J. (2023). Undergraduate student perceptions of stress and mental health in engineering culture. \u003cem\u003eInternational Journal of STEM Education\u003c/em\u003e, \u003cem\u003e10\u003c/em\u003e(1), 30.\u003c/li\u003e\n\u003cli\u003eJoshi, A., \u0026amp; Kiran, R. (2020). Gauging the effectiveness of music and yoga for reducing stress among engineering students: An investigation based on Galvanic Skin Response. \u003cem\u003eWork\u003c/em\u003e, \u003cem\u003e65\u003c/em\u003e(3), 671-678.\u003c/li\u003e\n\u003cli\u003eKalamatianos, A., Kounenou, K., \u0026amp; Pezirkianidis, C. (2025, February). The Implementation of a Blended Counseling Intervention in Undergraduate Engineering Students: The Effect on Mental Health. In \u003cem\u003eHealthcare\u003c/em\u003e (Vol. 13, No. 5, p. 511). MDPI.\u003c/li\u003e\n\u003cli\u003eKamal, S. A., S\u0026aacute;nchez-Pe\u0026ntilde;a M. L., Ramirez, N., \u0026amp; Samuel, D. B. (2025, June). Exploring changes in mental health conditions\u0026rsquo; stigma levels and help-seeking attitudes among engineering students. In \u003cem\u003e2025 ASEE Annual Conference \u0026amp; Exposition\u003c/em\u003e.\u003c/li\u003e\n\u003cli\u003eKirn, A., \u0026amp; Benson, L. (2018). Engineering students\u0026apos; perceptions of problem solving and their future. \u003cem\u003eJournal of Engineering Education\u003c/em\u003e, \u003cem\u003e107\u003c/em\u003e(1), 87-112.\u003c/li\u003e\n\u003cli\u003eKrathwohl, D. R., Bloom, B. S., \u0026amp; Masia, B. B. (1964). \u003cem\u003eTaxonomy of educational objectives: Handbook II: Affective domain\u003c/em\u003e. David McKay Company.\u003c/li\u003e\n\u003cli\u003eKrause, S. J., Middleton, J. A., Judson, E., Ernzen, J., Beeley, K. R., \u0026amp; Chen, Y. C. (2015, June). Factors impacting retention and success of undergraduate engineering students. In \u003cem\u003e2015 ASEE Annual Conference \u0026amp; Exposition\u003c/em\u003e.\u003c/li\u003e\n\u003cli\u003eLaschke, L., Flottmann, M., \u0026amp; Schl\u0026uuml;ter, K. (2023). Let\u0026rsquo;s ask the teachers: A qualitative analysis of health education in schools and its effectiveness. \u003cem\u003eSustainability, 15\u003c/em\u003e(6), 4887.\u003c/li\u003e\n\u003cli\u003eLippe, M., Johnson, B., \u0026amp; Carter, P. (2019). Protecting student anonymity in research using a subject-generated identification code. \u003cem\u003eJournal of Professional Nursing\u003c/em\u003e, \u003cem\u003e35\u003c/em\u003e(2), 120-123.\u003c/li\u003e\n\u003cli\u003eLipson, S. K., Zhou, S., Abelson, S., Heinze, J., Jirsa, M., Morigney, J., Patterson, A., Singh, M., \u0026amp; Eisenberg, D. (2022). Trends in college student mental health and help-seeking by race/ethnicity: Findings from the national Healthy Minds Study, 2013\u0026ndash;2021. \u003cem\u003eJournal of Affective Disorders, 306\u003c/em\u003e, 138-147. https://doi.org/10.1016/j.jad.2022.03.038\u003c/li\u003e\n\u003cli\u003eLiu, L. G., Russell, D., Turchioe, M. R., Myers, A. C., Vawdrey, D. K., \u0026amp; Creber, R. M. M. (2022). Effect of expansion of abbreviations and acronyms on patient comprehension of their health records: a randomized clinical trial. \u003cem\u003eJAMA Network Open\u003c/em\u003e, \u003cem\u003e5\u003c/em\u003e(5), e2212320-e2212320.\u003c/li\u003e\n\u003cli\u003eLo, K., Gupta, T., \u0026amp; Keating, J. L. (2018). \u003cem\u003eInterventions to promote mental health literacy in university students and their clinical educators: A systematic review of randomised control trials.\u003c/em\u003e Health Professions Education, 4(3), Article 2.\u003c/li\u003e\n\u003cli\u003eMelnyk, B. M., Amaya, M., Szalacha, L. A., Hoying, J., Taylor, T., \u0026amp; Bowersox, K. (2015). Feasibility, acceptability, and preliminary effects of the COPE online cognitive-behavioral skill-building program on mental health outcomes and academic performance in freshmen college students: A randomized controlled pilot study. \u003cem\u003eJournal of Child and Adolescent Psychiatric Nursing\u003c/em\u003e, \u003cem\u003e28\u003c/em\u003e(3), 147-154.\u003c/li\u003e\n\u003cli\u003eMiller, I., \u0026amp; Jensen, K. (2020). Introduction of mindfulness in an online engineering core course during the COVID-19 pandemic. \u003cem\u003eAdvances in engineering education\u003c/em\u003e, \u003cem\u003e8\u003c/em\u003e(4).\u003c/li\u003e\n\u003cli\u003eMojtabai, R., Stuart, E. A., Hwang, I., Eaton, W. W., Sampson, N., \u0026amp; Kessler, R. C. (2015). Long-term effects of mental disorders on educational attainment in the National Comorbidity Survey ten-year follow-up. \u003cem\u003eSocial psychiatry and psychiatric epidemiology\u003c/em\u003e, \u003cem\u003e50\u003c/em\u003e(10), 1577-1591.\u003c/li\u003e\n\u003cli\u003eMontana State University Billings. (n.d.). \u003cem\u003eM-HOPES: A Mental Health Initiative\u003c/em\u003e. Graduate Studies. https://msubillings.edu/grad/m-hopes.htm\u003c/li\u003e\n\u003cli\u003eMontclair State University. (2024, November 11). \u003cem\u003eMontclair State University receives $3 million grant to provide mental-health services during internship experiences.\u003c/em\u003e https://www.montclair.edu/newscenter/2024/11/11/montclair-state-university-receives-3-million-grant-to-provide-mental-health-services-during-internship-experiences/\u003c/li\u003e\n\u003cli\u003eNazari, A., Garmaroudi, G., Foroushani, A. R., \u0026amp; Hosseinnia, M. (2023). The effect of web-based educational interventions on mental health literacy, stigma and help-seeking intentions/attitudes in young people: systematic review and meta-analysis. \u003cem\u003eBMC psychiatry, 23\u003c/em\u003e(1), 647.\u003c/li\u003e\n\u003cli\u003eNazari, A., Garmaroudi, G., \u0026amp; Rabiei, M. (2024). A systematic review: increasing mental health literacy in students through \u0026ldquo;The Guide\u0026rdquo;. \u003cem\u003eDiscover Psychology, 4\u003c/em\u003e(1), 96.\u003c/li\u003e\n\u003cli\u003eO\u0026rsquo;Sullivan, G. (2011). The relationship between hope, eustress, self-efficacy, and life satisfaction among undergraduates. \u003cem\u003eSocial indicators research\u003c/em\u003e, \u003cem\u003e101\u003c/em\u003e(1), 155-172.\u003c/li\u003e\n\u003cli\u003eO\u0026rsquo;Reilly, M., Svirydzenka, N., Adams, S., \u0026amp; Dogra, N. (2018). Review of mental health promotion interventions in schools. \u003cem\u003eSocial psychiatry and psychiatric epidemiology, 53\u003c/em\u003e(7), 647-662.\u003c/li\u003e\n\u003cli\u003ePaul, F. A., Ganie, A. U. R., \u0026amp; Dar, D. R. (2024). Substance use in university students: a comprehensive examination of its effects on academic achievement and psychological well-being. \u003cem\u003eSocial Work in Mental Health\u003c/em\u003e, \u003cem\u003e22\u003c/em\u003e(3), 452-484.\u003c/li\u003e\n\u003cli\u003ePaul, R., Dedemus, D., Boyce, M., \u0026amp; Johnston, K. (2020). The \u0026ldquo;Engineers Have Feelings\u0026rdquo; project: Integrating mental wellness and lifelong learning skills in first-year undergraduate engineering courses. \u003cem\u003eProceedings of the Canadian engineering education association (CEEA)\u003c/em\u003e.\u003c/li\u003e\n\u003cli\u003ePedrelli, P., Nyer, M., Yeung, A., Zulauf, C., \u0026amp; Wilens, T. (2015). College students: mental health problems and treatment considerations. \u003cem\u003eAcademic psychiatry\u003c/em\u003e, \u003cem\u003e39\u003c/em\u003e(5), 503-511.\u003c/li\u003e\n\u003cli\u003ePetty, R. E., \u0026amp; Cacioppo, J. T. (1986). \u003cem\u003eCommunication and persuasion: Central and peripheral routes to attitude change\u003c/em\u003e. Springer.\u003c/li\u003e\n\u003cli\u003ePituch, K. A., \u0026amp; Stevens, J. P. (2015). \u003cem\u003eApplied multivariate statistics for the social sciences: Analyses with SAS and IBM\u0026rsquo;s SPSS\u003c/em\u003e. Routledge.\u003c/li\u003e\n\u003cli\u003eRaghavan, V., Chandrasekaran, S., Paul, V., Pattabiraman, R., Mohan, G., Durairaj, J., Currie, G., Lilford, R., Furtado, V., Madan, J., Birchwood, M., Meyer, C., Sood, M., Chadda, R., Mohan, M., Shah, J., John, S., Padmavati, R., Iyer, S., Thara, R., Singh, S., \u0026amp; the WIC Consortium. (2024). Effectiveness of a mental health literacy module on stigma-related mental health knowledge and behaviour among youth in two educational settings in Chennai, South India: A quasi-experimental study. \u003cem\u003eAsian Journal of Psychiatry, 98\u003c/em\u003e, Article 104074\u003c/li\u003e\n\u003cli\u003eReis, A. C., Saheb, R., Moyo, T., Smith, C., \u0026amp; Sperandei, S. (2022). The impact of mental health literacy training programs on the mental health literacy of university students: A systematic review. \u003cem\u003ePrevention Science\u003c/em\u003e, \u003cem\u003e23\u003c/em\u003e(4), 648-662.\u003c/li\u003e\n\u003cli\u003eRobinson, O. C. (2022). Conducting thematic analysis on brief texts: The structured tabular approach. \u003cem\u003eQualitative Psychology\u003c/em\u003e, \u003cem\u003e9\u003c/em\u003e(2), 194.\u003c/li\u003e\n\u003cli\u003eRodr\u0026iacute;guez-Jim\u0026eacute;nez, R. M., Carmona, M., Garc\u0026iacute;a-Merino, S., D\u0026iacute;az-Ure\u0026ntilde;a, G., \u0026amp; Lara Bercial, P. J. (2022). Embodied learning for well-being, self-awareness, and stress regulation: a randomized trial with engineering students using a mixed-method approach. \u003cem\u003eEducation Sciences\u003c/em\u003e, \u003cem\u003e12\u003c/em\u003e(2), 111.\u003c/li\u003e\n\u003cli\u003eSecules, S., McCall, C., Mejia, J. A., Beebe, C., Masters, A. S., L. S\u0026aacute;nchez-Pe\u0026ntilde;a, M., \u0026amp; Svyantek, M. (2021). Positionality practices and dimensions of impact on equity research: A collaborative inquiry and call to the community. \u003cem\u003eJournal of Engineering Education\u003c/em\u003e, \u003cem\u003e110\u003c/em\u003e(1), 19-43.\u003c/li\u003e\n\u003cli\u003eS\u0026aacute;nchez-Pe\u0026ntilde;a, M. L., McAlister, A. M., Ramirez, N. M., \u0026amp; Kamal, S. A. (2025). Elements of engineering culture affecting undergraduate students\u0026apos; mental health and their help-seeking attitudes. \u003cem\u003eJournal of Engineering Education\u003c/em\u003e, \u003cem\u003e114\u003c/em\u003e(3), e70017.\u003c/li\u003e\n\u003cli\u003eS\u0026aacute;nchez-Pe\u0026ntilde;a, M. L., McAlister, A. M., Ramirez, N., Samuel, D. B., Kamal, S. A., \u0026amp; Xu, X. (2023). Stigma of mental health conditions within engineering culture and its relation to help-seeking attitudes: Insights from the first year of a longitudinal study. In \u003cem\u003eAmerican Society for Engineering Education Annual Conference \u0026amp; Exposition\u003c/em\u003e.\u003c/li\u003e\n\u003cli\u003eShahwan, S., Lau, J. H., Goh, C. M. J., Ong, W. J., Tan, G. T. H., Kwok, K. W., Samari, E., Lee, Y. Y., Teh, W. L., Seet, V., Chang, S., Chong, S. A., \u0026amp; Subramaniam, M. (2020). The potential impact of an anti-stigma intervention on mental health help-seeking attitudes among university students. \u003cem\u003eBMC Psychiatry, 20\u003c/em\u003e, Article 562.\u003c/li\u003e\n\u003cli\u003eSchober, P., \u0026amp; Vetter, T. R. (2018). Repeated measures designs and analysis of longitudinal data: If at first you do not succeed\u0026mdash;try, try again. \u003cem\u003eAnesthesia \u0026amp; Analgesia\u003c/em\u003e, \u003cem\u003e127\u003c/em\u003e(2), 569-575.\u003c/li\u003e\n\u003cli\u003eSheldon, E., Simmonds-Buckley, M., Bone, C., Mascarenhas, T., Chan, N., Wincott, M., Gleeson, H., Sow, K., Hind, D., \u0026amp; Barkham, M. (2021). Prevalence and risk factors for mental health problems in university undergraduate students: A systematic review with meta-analysis. \u003cem\u003eJournal of Affective Disorders, 287\u003c/em\u003e, 282-292.\u003c/li\u003e\n\u003cli\u003eShim, Y. R., Eaker, R., \u0026amp; Park, J. (2022). Mental health education, awareness and stigma regarding mental illness among college students. \u003cem\u003eJournal of Mental Health \u0026amp; Clinical Psychology, 6\u003c/em\u003e(2), 6-15.\u003c/li\u003e\n\u003cli\u003eSochacka, N. W., Walther, J., \u0026amp; Pawley, A. L. (2018). Ethical validation: Reframing research ethics in engineering education research to improve research quality. \u003cem\u003eJournal of Engineering Education\u003c/em\u003e, \u003cem\u003e107\u003c/em\u003e(3), 362-379.\u003c/li\u003e\n\u003cli\u003eSochacka, N. W., Walther, J., Rich, J. R., \u0026amp; Brewer, M. A. (2021). A narrative analysis of stories told about engineering in the public discourse: Implications for equity and inclusion in engineering. \u003cem\u003eStudies in Engineering Education\u003c/em\u003e, \u003cem\u003e2\u003c/em\u003e(2).\u003c/li\u003e\n\u003cli\u003eSontag-Padilla, L., Dunbar, M. S., Ye, F., Kase, C., Fein, R., Abelson, S., ... \u0026amp; Stein, B. D. (2018). Strengthening college students\u0026rsquo; mental health knowledge, awareness, and helping behaviors: the impact of active minds, a peer mental health organization. \u003cem\u003eJournal of the American Academy of Child \u0026amp; Adolescent Psychiatry, 57\u003c/em\u003e(7), 500-507.\u003c/li\u003e\n\u003cli\u003eSu, C. H. (2016). The effects of students\u0026apos; motivation, cognitive load and learning anxiety in gamification software engineering education: a structural equation modeling study. \u003cem\u003eMultimedia Tools and Applications\u003c/em\u003e, \u003cem\u003e75\u003c/em\u003e(16), 10013-10036.\u003c/li\u003e\n\u003cli\u003eTait, J. E., Alexander, L. A., Hancock, E. I., \u0026amp; Bisset, J. (2024). Interventions to support the mental health and wellbeing of engineering students: a scoping review. \u003cem\u003eEuropean journal of engineering education\u003c/em\u003e, \u003cem\u003e49\u003c/em\u003e(1), 45-69.\u003c/li\u003e\n\u003cli\u003eTan, G. T. H., Shahwan, S., Abdin, E., Lau, J. H., Goh, C. M. J., Ong, W. J., Samari, E., Kwok, K. W., Chong, S. A., \u0026amp; Subramaniam, M. (2021). Recognition of depression and help-seeking preference among university students in Singapore: An evaluation of the impact of Advancing Research to Eliminate Mental Illness Stigma: An education and contact intervention. \u003cem\u003eFrontiers in Psychiatry, 12\u003c/em\u003e, Article 582730.\u003c/li\u003e\n\u003cli\u003eTaub, D.J., Servaty-Seib, H.L., Miles, N., Lee, J.-Y., Morris, C.A.W., Prieto-Welch, S.L. and Werden, D. (2013), The Impact of Gatekeeper Training for Suicide Prevention on University Resident Assistants. \u003cem\u003eJournal of College Counseling, 16\u003c/em\u003e: 64-78.\u003c/li\u003e\n\u003cli\u003eTompkins, T. L., \u0026amp; Witt, J. (2009). The short-term effectiveness of a suicide prevention gatekeeper training program in a college setting with residence life advisers. \u003cem\u003eJournal of Primary Prevention, 30\u003c/em\u003e(2), 131\u0026ndash;149.\u003c/li\u003e\n\u003cli\u003eUniversity of Kentucky. (n.d.). \u003cem\u003eAbout us \u0026ndash; NSF Grant Team\u003c/em\u003e. Engineering Wellness Center. https://engr.uky.edu/ewc/about-us-nsf-grant-team\u003c/li\u003e\n\u003cli\u003eVick, E., Wilson, S. A., Hammer, J. H., Whitwer, M., \u0026amp; Gentry, A. N. (2025, June). Engineering student mental health status across gender identities: Analysis of data from the Healthy Minds Study. In \u003cem\u003e2025 ASEE Annual Conference \u0026amp; Exposition\u003c/em\u003e.\u003c/li\u003e\n\u003cli\u003eVitasari, P., Wahab, M. N. A., Herawan, T., Othman, A., \u0026amp; Sinnadurai, S. K. (2011). A pilot study of pre-post anxiety treatment to improve academic performance for engineering students. \u003cem\u003eProcedia-Social and Behavioral Sciences\u003c/em\u003e, \u003cem\u003e15\u003c/em\u003e, 3826-3830.\u003c/li\u003e\n\u003cli\u003eWalton, G. M., Logel, C., Peach, J. M., Spencer, S. J., \u0026amp; Zanna, M. P. (2015). Two brief interventions to mitigate a \u0026ldquo;chilly climate\u0026rdquo; transform women\u0026rsquo;s experience, relationships, and achievement in engineering. \u003cem\u003eJournal of educational Psychology\u003c/em\u003e, \u003cem\u003e107\u003c/em\u003e(2), 468.\u003c/li\u003e\n\u003cli\u003eWang, X., Yang, M., Ren, L., Wang, Q., Liang, S., Li, Y., Li, Y., Zhan, Q., Huang, S., Xie, K., Liu, J., Li, X., \u0026amp; Wu, S. (2024). Burnout and depression in college students. \u003cem\u003ePsychiatry Research, 335\u003c/em\u003e, 115828.\u003c/li\u003e\n\u003cli\u003eWaqas, A., Malik, S., Fida, A., Abbas, N., Mian, N., Miryala, S., Amray, A. N., Shah, Z., \u0026amp; Naveed, S. (2020). Interventions to reduce stigma related to mental illnesses in educational institutes: A systematic review. \u003cem\u003ePsychiatric Quarterly, 91\u003c/em\u003e(3), 887\u0026ndash;903.\u003c/li\u003e\n\u003cli\u003eWatkins, D. C., Hunt, J. B., \u0026amp; Eisenberg, D. (2012). Increased demand for mental health services on college campuses: Perspectives from administrators. \u003cem\u003eQualitative Social Work\u003c/em\u003e, \u003cem\u003e11\u003c/em\u003e(3), 319-337.\u003c/li\u003e\n\u003cli\u003eWeston, R., \u0026amp; Gore Jr, P. A. (2006). A brief guide to structural equation modeling. \u003cem\u003eThe counseling psychologist\u003c/em\u003e, \u003cem\u003e34\u003c/em\u003e(5), 719-751.\u003c/li\u003e\n\u003cli\u003eWhitwer, M. D., Wilson, S. A., Hammer, J. H., \u0026amp; Gomer, B. (2025). Mental health and treatment use in undergraduate engineering students: A comparative analysis to students in other academic fields of study. \u003cem\u003eJournal of Engineering Education\u003c/em\u003e, \u003cem\u003e114\u003c/em\u003e(1), e20629.\u003c/li\u003e\n\u003cli\u003eWilson, S. A., Blaber, I. P., Hancock, J. M., Pitcher, G. R., \u0026amp; Hammer, J. H. (2023). Delivery of mental health training across a College of Engineering. In \u003cem\u003eProceedings of the 51st Annual Conference of the European Society for Engineering Education (SEFI)\u003c/em\u003e.\u003c/li\u003e\n\u003cli\u003eWilson, S. A., Huth, A. K., Lamer, S. X., Hammer, J. H., \u0026amp; Whitwer, M. (2024, June). Investigating perceptions that predict mental health related help-seeking in first-year engineering students. In \u003cem\u003e2024 ASEE Annual Conference \u0026amp; Exposition\u003c/em\u003e.\u003c/li\u003e\n\u003cli\u003eWilson, S.A, Wilder, K., Blackburn-Lynch, W., Hammer, J.H, \u0026amp; Dailey, D. (2022, August). Investigating mental health distress and help-seeking perceptions in first-year engineering students. In \u003cem\u003e2022 ASEE annual conference \u0026amp; exposition\u003c/em\u003e.\u003c/li\u003e\n\u003cli\u003eWright, C. J., Hargis, L. E., Usher, E. L., Hammer, J. H., Wilson, S. A., \u0026amp; Miller, M. E. (2021, July). Identifying engineering students\u0026rsquo; beliefs about seeking help for mental health concerns. In \u003cem\u003e2021 ASEE Virtual Annual Conference Content Access\u003c/em\u003e.\u003c/li\u003e\n\u003cli\u003eWright, C. J., Wilson, S. A., Hammer, J. H., Hargis, L. E., Miller, M. E., \u0026amp; Usher, E. L. (2023). Mental health in undergraduate engineering students: Identifying facilitators and barriers to seeking help. \u003cem\u003eJournal of Engineering Education\u003c/em\u003e, \u003cem\u003e112\u003c/em\u003e(4), 963-986.\u003c/li\u003e\n\u003cli\u003eZhao, R., Amanvermez, Y., Pei, J., Castro-Ramirez, F., Rapsey, C., Garcia, C., Ebert, D.D., Haro, J.M., Fodor, L.A., David, O.A., Rankin, O., Chua, S.N., Mart\u0026iacute;nez, V., Bruffaerts, R., Kessler, R.C. and Cuijpers, P. (2025). Research Review: Help-seeking intentions, behaviors, and barriers in college students\u0026ndash;a systematic review and meta-analysis. \u003cem\u003eJournal of child psychology and psychiatry\u003c/em\u003e.\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Engineering students, engineering education, help seeking, mental health, mental health literacy, integrated behavioral model, intention, attitude, perceived norm, knowledge","lastPublishedDoi":"10.21203/rs.3.rs-8205457/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-8205457/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eEngineering undergraduate students report high levels of mental health distress yet exhibit comparatively low rates of engagement with professional mental health services compared to students in other academic majors. These low help-seeking behaviors may be further compounded by the prevailing \u0026ldquo;culture of stress\u0026rdquo; within engineering, which emphasizes self-reliance, stoicism, and academic rigor. Therefore, this study examines the impact of a brief, 15-minute mental health and help-seeking training tailored for engineering students at a large Southeastern U.S. university. Grounded in the Integrated Behavioral Model of Mental Health Help Seeking (IBM-HS), the study evaluates whether the training influenced mental health help-seeking perceptions, including key determinants (e.g., mental health perceptions, knowledge, and skills), beliefs (e.g., prioritizing academics over mental health needs) and mechanisms (e.g., attitude, perceived norm, personal agency) that shape intentions to seek professional support. The study compares training and non-training groups from Fall 2023 (\u003cem\u003en\u003c/em\u003e\u0026thinsp;=\u0026thinsp;431) and Fall 2024 cohorts (\u003cem\u003en\u003c/em\u003e\u0026thinsp;=\u0026thinsp;132) using pre/post survey responses. Findings indicate statistically significant improvements in both perceived and objective knowledge of mental health resources, while help-seeking beliefs, mechanisms, and overall intention did not change significantly. Discussion of our results includes the training\u0026rsquo;s advantages (e.g., low-cost, scalable, and designed to be embedded into existing engineering curricula) and considerations for future research and practices. Overall, our findings highlight the potential for brief, discipline-specific interventions to improve mental health literacy in engineering education while underscoring the need for complementary approaches to shift deeper help-seeking attitudes and norms.\u003c/p\u003e","manuscriptTitle":"Challenging the Culture of Stress: Evaluating a Brief, Theory-Driven Mental Health Help-Seeking Intervention for Undergraduate Engineering Students","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-12-08 05:11:21","doi":"10.21203/rs.3.rs-8205457/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"60f1084e-38c4-4462-8d47-6ad5462d1fbd","owner":[],"postedDate":"December 8th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2026-03-19T21:39:09+00:00","versionOfRecord":[],"versionCreatedAt":"2025-12-08 05:11:21","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-8205457","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-8205457","identity":"rs-8205457","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}