{"paper_id":"0f646daa-39bb-4e4b-a1d8-281e6a5ef287","body_text":"Perceptions and Intentions to Use E-Health Services in Mental Health Care Settings: A Case Study Among Resident Physicians | 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 Perceptions and Intentions to Use E-Health Services in Mental Health Care Settings: A Case Study Among Resident Physicians Loubna Khalil, Zineb Serhier, Manar Jallal, Mohammed Bennani Othmani This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7383021/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 7 You are reading this latest preprint version Abstract Background: Despite growing interest in e-health acceptance, few studies have focused on the acceptance of e-health services, particularly among residents' physicians in mental healthcare settings. This study aims to explore perceptions and behavioral intentions toward the online medical appointment booking system (OMABS) among psychiatry residents in a Moroccan university hospital, focusing on how contextual factors influence their use intention. Methods: Based on factors related to residency training, the characteristics of psychiatric practice, and classic factors of technological acceptance models, a survey was conducted among all 46 psychiatry resident physicians. The small sample size is a result of the naturally limited population rather than a sampling decision. Differences in perceptions across residency years were analyzed using the Kruskal-Wallis test, while Spearman correlation assessed the relationship between independent variables and use intention. Additionally, residency year was tested as a moderating variable through the inclusion of interaction terms in the analysis. Results: Findings reported favorable perceptions of OMABS' usefulness, relative ease of use, data security, and reliability. However, these perceptions varied over the later residency year, becoming more influenced by curriculum exposure, peer support, and direct experience than by usability testing or security analysis. Contextual factors, such as a heavy workload and time constraints, low autonomy in managing consultations, the inherent complexity of psychiatric care, and insufficient integration of technology into the medical curriculum, were perceived as barriers. Correlation analysis indicated that perceived usefulness, security, and even perceived workload and time constraints were positively associated with use intention, whereas the other contextual factors were not significant. Conclusions: To our knowledge, this is the first study exploring resident physicians’ acceptance of e-appointment services in psychiatric care within a developing country. The Findings reveal that residents' physicians' intention to use e-health services is more associated with perceived operational benefits than with contextual barriers. These insights may guide policy development and implementation of e-health among medical trainees. correlation analysis e-appointment system e-services mental health Morocco perceptions resident physicians technology acceptance use intention Introduction Digital health technology is revolutionizing the production and delivery of mental health services, driving a paradigm shift that has yielded multifaceted implications for healthcare consumers and providers [1]. A notable innovation in this transformation is the online medical appointment booking system (OMABS), which has altered the traditional method of scheduling and managing medical appointments. Previous studies have identified OMABS as one of the most practical internet-based health services, offering significant benefits in efficiency, profitability, productivity, accessibility, and quality of healthcare services [2–8]. Delivering mental health care comes with its own set of challenges, shaped by both the complexity of mental health conditions and the broader difficulties in accessing healthcare. People dealing with mental health issues often need continuous support, timely interventions, and treatment plans tailored to their unique emotional and physical needs [9]. Considering these specific requirements and challenges, implementing e-appointment systems holds particular promise. In Morocco, healthcare organizations are progressively more dependent on incorporating OMABS, reflecting a notable turn toward the digital transformation of the healthcare sector. The national online platform \"Mawiidi\" exemplifies this progress, designed to simplify and enhance the appointment scheduling experience. However, the successful deployment and use of such systems remain limited [8,10] and are influenced by factors such as insufficient technical expertise, inadequate digital infrastructure, and resistance from healthcare professionals [11]. Resident physicians in mental health settings, as emerging healthcare professionals, play a critical role in the acceptance and use of e-health services due to their direct and frequent interaction with patients and digital platforms. Their acceptance and use of e-appointment services may be shaped by a complex interplay of factors, including concerns about data confidentiality, training context, and the specific demands of psychiatric care. Theoretical models grounded in the framework of technology acceptance, such as the technology acceptance model (TAM) [12] and the unified theory of acceptance and use of technology (UTAUT) [13], offer insights into the factors that drive the use intention of technology in various contexts. These models emphasize the roles of individual, technological, and organizational factors in influencing an individual’s behavior toward using technology. However, limited research has specifically applied these models to explore the intention to use e-health services among physicians in training. For instance, Steininger and Stiglbauer employed an extended TAM to examine Electronic Health Record (EHR) adoption among Austrian resident doctors. Their findings revealed that social influence, prior experience with health technologies, and privacy concerns significantly influenced perceived usefulness, which in turn fostered more favorable attitudes and stronger behavioral intentions toward using EHR systems [14]. Similarly, Wang et al. examined the use intention of Virtual Reality among graduate medical education (GME) trainees and found that perceived usefulness, ease of use, and enjoyment were significant predictors of the intention to use virtual reality as a therapeutic tool [15]. Samadbeik et al. investigated the factors influencing mHealth use intention among medical science trainees and identified perceived usefulness and ease of use as key determinants of both attitude and intention to use these tools [16]. Humphrey-Murto et al. examined the factors influencing the use intention of electronic health records by physicians and residents in two different hospitals and found that workflow changes, insufficient ongoing support, and emotional responses like frustration and anxiety were significant barriers to effective electronic health record acceptance and use [17]. Despite these contributions, the literature lacks the nuanced application of technology acceptance frameworks to understand the use intention of e-health services among resident physicians in mental healthcare settings, a context characterized by specific clinical, organizational, and psychosocial challenges. Few studies have investigated how contextual factors within psychiatric residency, such as workload, autonomy, and complexity of care, may shape technology acceptance and use of OMABS, leaving a notable gap in understanding the interaction between these contextual factors and the use intention of e-health services. The systematic literature review exploring user acceptance of medical e-appointment systems for mental healthcare highlights this gap in research [18]. It states that limited studies have focused specifically on e-appointment systems, and none have thoroughly examined the perceptions and behavioral intentions of resident physicians working in mental healthcare settings. This gap leaves an unclear understanding of how this category of resident physicians perceives and intends to use e-appointment technologies. As key stakeholders in the delivery of psychiatric care, resident physicians hold valuable perspectives on the feasibility and integration of such technologies. Their perspectives are precious, as these emerging professionals offer insights into the future potential for integrating such e-services within mental health practices. Addressing this gap is essential to ensuring the successful adoption and use of OMABS in mental healthcare, ultimately enhancing patient care and service efficiency. This study aims to explore resident physicians' perceptions and intentions to use OMABS within the Moroccan mental healthcare context. Specifically, it focuses on resident physicians at the Psychiatry Department of the University Hospital in Casablanca, Morocco. Given the limited size of this professional group, the study included the entire population of 46 residents. The study was based on selected factors specific to the residency training context, the psychiatric care field, and the classic factors of technological acceptance that align with the study objective. It attempts to answer the following questions: Are resident physicians working in mental health settings currently using OMABS? What are their perceptions of this service? Do these perceptions differ across residency years? What are the primary factors associated with the intention to use this service? Does residency year moderate the association of these factors with the intention to use this service? To our knowledge, this is the first study exploring resident physicians’ acceptance of e-appointment services in psychiatric care. The paper is structured as follows: first, we outline the proposed hypotheses. Next, we present the methods employed to examine resident physicians' perceptions and intentions to use OMABS. We then present the key results, discuss their implications, propose directions for future research, and conclude. Hypotheses development To explore resident physicians' perceptions and intentions to use OMABS in mental healthcare settings, the study draws upon selected factors specific to the residency training context, the characteristics of the psychiatric care field, and the classic factors of technological acceptance that align with the study objective. The following hypotheses were proposed to be tested. General Technology Acceptance Factors Perceived usefulness Perceived usefulness is widely recognized as one of the most influential factors in determining technology acceptance, particularly in healthcare. It refers to the extent to which residents' physicians believe that e-health services will facilitate and enhance their work efficiency. In mental healthcare, residents' physicians are often faced with time pressure and complex cases. When e-health services like OMABS are seen as enhancing efficiency and access, they are more likely to be accepted and integrated into daily practice. Several studies have indicated that perceived usefulness is a key predictor of intention to use or adopt new technology across various healthcare fields [19], including the mental health field [20–22]. Therefore, we hypothesize that: Hypothesis 1 (H1): Perceived usefulness is positively associated with resident physicians’ intention to use OMABS. Perceived ease of use Perceived ease of use is the degree to which residents' physicians believe that using technology will be simple and easy, even under high workload conditions. In healthcare environments, especially in mental health settings where workflows are often complex and unpredictable, resident physicians are more likely to embrace e-health services if these tools are perceived as user-friendly and requiring minimal time or training. Numerous studies have posited the positive influence of ease of use on health technology acceptance [23–25]. Hence, the following hypothesis is proposed to be tested. Hypothesis 2 (H2): Perceived ease of use is positively associated with resident physicians’ intention to use OMABS. Social Influence Social influence refers to the perceived pressure or encouragement from important others, such as senior physicians, supervisors, or peers, to use technology [13]. In the mental healthcare setting, where hierarchical relationships and mentorship are prevalent, the recommendations or positive experiences shared by supervisors, senior psychiatrists, and peers can significantly shape resident physicians' attitudes toward adopting new technologies such as the e-appointment service. Several studies [26–28] have emphasized that social influence positively impacts users' behavioral intention to adopt health technologies. Consequently, we hypothesize that: Hypothesis 3 (H3): Social influence is positively associated with resident physicians’ intention to use OMABS. Factors Related to the Residency Training Context The training context of resident physicians is critical to their intention to use new technologies in clinical practice. It encompasses several aspects, including the structure and delivery of training, available resources, support, and the overall work environment. Here are key variables that we have considered to evaluate whether residents’ training context encourages the use of technology and supports acceptance of e-services: perceived workload and time constraints, autonomy in managing consultations, institutional support, and medical curriculum support. Perceived Workload and Time Constraints Perceived workload and time constraints factor reflect the perceived time constraints and work demands experienced by resident physicians in mental health settings. This category of trainee physicians often faces long-duration shifts, extended weekly work hours, and emotional fatigue[29], which can limit their capacity to explore or adopt new e-health solutions, even when these tools are potentially beneficial. If e-health services, such as OMABS, are perceived as time-saving and compatible with existing workflows, they may be welcomed as facilitators rather than as additional burdens [30]. However, if the health technology is seen as time-consuming and workload-arising, overworked resident physicians may resist its implementation, regardless of its potential value [31,32]. Prior studies have suggested that higher workload hinders the acceptance of digital health services among healthcare professionals [33,34]. In this regard, we hypothesize that: Hypothesis 4 (H4): Higher perceived workload and time constraints are negatively associated with resident physicians’ intention to use OMABS. Perceived Autonomy in Managing Consultations Autonomy in managing consultations reflects the degree of control that resident physicians perceive they have over their clinical tasks, including scheduling and patient management. This perceived autonomy may influence their acceptance and use of e-health services like the OMABS. Striking the right balance between the autonomy of trainee physicians and the supervision of senior physicians remains a well-documented challenge in medical education [35]. When residents, especially in mental health settings, feel empowered to control their consultation schedules, they are more likely to perceive such systems as supportive rather than restrictive. On the other hand, if scheduling decisions are tightly regulated by supervisors, residents may see digital tools as reinforcing hierarchical constraints rather than enhancing efficiency. Therefore, we hypothesize that: Hypothesis 5 (H5): Higher perceived autonomy in managing consultations is positively associated with resident physicians’ intention to use OMABS. Institutional Support Institutional Support measures whether adequate resources and support are available to help residents' physicians use OMABS effectively. The degree of supervision and institutional support can impact the residents' ability and willingness to integrate e-health services into their practice. If the hospital offers adequate support, resident physicians are more likely to adopt such services, as mentioned by previous studies [24,36]. Therefore, we hypothesize that: Hypothesis 6 (H6): The institutional support is positively associated with resident physicians’ intention to use OMABS. Medical Curriculum Support Medical digital health education plays a significant role in shaping physicians' ability to use the technology effectively in clinical practice [37,38]. As health technologies, such as e-appointment services, telemedicine, and electronic health records (EHR), become more integrated into healthcare, the medical curriculum must adapt to ensure that resident physicians are adequately prepared to navigate these tools [39–41]. Proper training ensures that resident physicians not only know how to use these systems but also feel confident and competent in integrating them into their daily clinical practice. Based on this, we hypothesize that: Hypothesis 7 (H7): The integration of technology into the medical curriculum is positively associated with resident physicians’ intention to use OMABS. Factors Specific to Psychiatric Care Complexity of Psychiatric Care The psychiatric care system presents several challenges that can influence the use of e-health services by residents' physicians. Its unique characteristics, including patient compliance, the unpredictability of psychiatric consultations, the significant variation in their duration [42], the need for flexible scheduling, potential patient difficulties in using online systems, and concerns about direct human interaction [43], can make relying on an online appointment system difficult and consequently influence the intention to use it among resident physicians. Based on these considerations, we proposed the following hypothesis: Hypothesis 8 (H8): The Complexity of psychiatric care is negatively associated with resident physicians’ intention to use OMABS. Perceived Security and Reliability Prior studies have shown that confidentiality concerns and trust have a significant influence on the acceptance and use of health technology [24]. Resident physicians may be reluctant to adopt e-health services if they perceive a risk to patient privacy or data security. This concern is even greater in the context of mental health care, where violations of confidentiality could have serious ethical or legal consequences. Conversely, trust in technology, particularly in its security and reliability, plays an essential role in mitigating these concerns. Studies have shown that healthcare professionals are more likely to adopt digital tools when they trust the system and believe it adequately protects patient data [28,44,45]. Therefore, we hypothesize that: Hypothesis 9 (H9): Perceived security and reliability are positively associated with resident physicians’ intention to use OMABS. Residency year Residency year was also incorporated as a moderating variable through interaction terms with each construct. It represents the level of professional experience, which is likely to influence exposure to and familiarity with OMABS. Residency year was hypothesized to moderate the association between all variables and use intention, with the expectation that the strength of this relationship may vary across different residency levels. The following hypotheses were proposed to be tested. Hypothesis 10 (H10): Residency year moderates the relationship between perceived usefulness of OMABS and resident physicians’ intention to use OMABS. Hypothesis 11 (H11): Residency year moderates the relationship between perceived ease of use of OMABS and resident physicians’ intention to use OMABS. Hypothesis 12 (H12): Residency year moderates the relationship between social influence and resident physicians’ intention to use OMABS. Hypothesis 13 (H13): Residency year moderates the relationship between perceived workload and time constraints and resident physicians’ intention to use OMABS. Hypothesis 14 (H14): Residency year moderates the relationship between perceived autonomy in managing consultations and resident physicians’ intention to use OMABS. Hypothesis 15 (H15): Residency year moderates the relationship between institutional support and resident physicians’ intention to use OMABS. Hypothesis 16 (H16): Residency year moderates the relationship between medical curriculum support and resident physicians’ intention to use OMABS. Hypothesis 17 (H17): Residency year moderates the relationship between the complexity of psychiatric care and resident physicians’ intention to use OMABS. Hypothesis 18 (H18): Residency year moderates the relationship between perceived security and reliability and resident physicians’ intention to use OMABS. Methods Study Design This research employed a quantitative approach to investigate mental health resident physicians' perceptions and intentions regarding using OMABS. Data was collected over two months, March and April 2025, targeting resident physicians affiliated with the Psychiatry Department of Ibn Rochd University Hospital in Casablanca, Morocco. The target population comprised 46 resident physicians, representing all those specializing in mental health at this University Hospital. The small sample size is a result of the naturally limited population rather than a sampling decision. Given the relatively small population size, a census approach was adopted, ensuring that every eligible individual was included in the study. This approach aimed to maximize representativeness, provide a comprehensive and unbiased analysis of OMABS adoption within this unique context, and enhance the validity of findings by capturing a comprehensive view of perceptions and use intentions. Data Collect A structured survey questionnaire consisting of eight questions was used to gather data. Given that no established questionnaire for measuring intentions to use e-health services among resident physicians in mental health care is available. The questionnaire was developed from existing technology acceptance literature [13] and adapted subsequently to the context of e-health services in psychiatry. The questionnaire began with demographic questions covering participants' age, gender, and their prior and current experiences with the OMABS in both professional and personal contexts. Subsequently, constructs derived from residency training context, the characteristics of the psychiatric care field, and the classic factors of technological acceptance were operationalized into distinct sections, covering perceived ease of use, perceived usefulness, social influence, perceived workload and time constraints, perceived autonomy in managing consultations, perceived institutional support, medical curriculum support, complexity of psychiatric care, and perceived security and reliability. The survey included a combination of constructs, with some evaluated through several items while others were assessed using just two. This design choice was guided by theoretical insights and the constraints of surveying resident physicians in mental healthcare, who deal with significant workload and time constraints. In some cases, literature has shown that two well-formulated items can effectively represent the underlying dimension without compromising validity or reliability, particularly when these items reflect clear and distinct aspects of the concept [46]. In this study, the decision to include two items to measure some constructs was guided by the need to reduce respondent burden while still maintaining the validity and reliability of the instrument. A Likert scale was used to assess the questionnaire items, ranging from 1 to 5 (1 = strongly disagree, 2 = disagree, 3 = neutral, 4 = agree, 5 = strongly agree). The questionnaire was initially designed in French and distributed as paper copies directly to the target population. The English version of the questionnaire is provided as a supplementary file (Supplementary File 1). Data Analysis The data were subjected to descriptive analysis and given as percentages, medians, and interquartile ranges since none of the variables followed a normal distribution. Comparisons across residency years (1 through 4) were conducted using the Kruskal-Wallis test. Effect sizes, eta-squared (ε²), were calculated to quantify the proportion of variance explained by residency year for Kruskal-Wallis tests. For significant differences identified across residency years, the Dwass-Steel-Critchlow-Fligner (DSCF) pairwise comparison test was applied where appropriate. Statistical significance was set at p < 0.05. Content validity was ensured through an expert assessment to verify the overall coherence and alignment of the questionnaire with the concepts it was supposed to test. Cronbach’s alpha was calculated for the entire instrument to evaluate internal consistency. Spearman’s correlation was employed to assess the strength and direction of the association between the intention to use OMABS and each of the following independent variables: perceived usefulness, perceived ease of use, social influence, perceived workload and time constraints, institutional support, autonomy in managing consultations, medical curriculum, complexity of psychiatric care, and perceived security and reliability. The residency year was incorporated as a moderating variable through interaction terms. Spearman’s correlation analysis was selected over logistic regression due to the small number of observations, combined with an unbalanced distribution of the dependent variable, use intention, which limited the statistical power of logistic regression. Additionally, the variables were ordinal, measured using Likert scales, and significantly deviated from a normal distribution (p < 0.05) based on the Shapiro-Wilk test, making a non-parametric method such as Spearman’s correlation more appropriate. Correlation coefficients (ρ) were interpreted as follows: values between [0-1] and [0-3] as weak, [0-3] and [0-5] as moderate, and values above [0-5] as strong associations. The analyses were performed using the statistical software JAMOVI version 2.2.5, known for its simplicity and efficiency in handling and analyzing data. Its intuitive interface facilitated a streamlined analytical process, ensuring that the findings were both precise and interpretable. Results Measurement model Cronbach's α was measured to assess how well the items for each construct measured the same basic construct. The results showed that all constructs achieved acceptable levels of consistency, with Cronbach’s alpha values above the recommended 0.70. The global reliability score for the entire scale was 0.79, indicating a reliable structure. Thus, the questionnaire provides consistent and reliable measurements of the constructs that are being studied. Table 1 reports the Cronbach's alpha for each construct. Table1.The measuring model's Cronbach's alpha coefficients. Construct Items Cronbach’s α Use Intention UI1. I intend to use the OMABS in my daily mental health care activities. 0.92 UI2. I plan to integrate OMABS into my routine mental health care activities. Perceived Usefulness PU1. Using the OMABS would lead to more efficient patient appointment scheduling. 0.79 PU2. Using the OMABS would improve access to mental healthcare. PU3. Using the OMABS in my routine would enhance the quality of mental healthcare services. PU4. Overall, I find the OMABS useful in my daily practice. Perceived Ease of Use PEOU1. I would find OMABS easy to use. 0.78 PEOU2. Learning to use the OMABS is easy for me. PEOU3. It would be easy for me to become skillful at using the OMABS. Social Influence SI1.I believe my likelihood of using the OMABS will increase if colleagues around me use it. 0.76 SI2. I would feel out of touch if I did not use the OMABS. Perceived Workload and Time Constraints PWTC1. Due to time constraints during my shifts, I am unlikely to use OMABS 0.95 PWTC2. My clinical workload prevents me from adopting additional tools like OMABS, even if they are useful. Perceived Autonomy in Managing Consultations PAMC1. I have full autonomy in scheduling and managing patient appointments. 0.86 PAMC2. I do not need approval from supervisors to adjust my consultation schedule. Perceived Institutional Support PIS1. The hospital provides the necessary resources and support to use OMABS. 0.93 PIS2. I can have adequate training and support for using OMABS. Medical Curriculum Support MCS1. My residency program includes training on the use of digital health technologies. 0.79 MCS2. The curriculum underscores technology’s impact on care and efficiency, enhancing my willingness to use OMABS. Complexity of Psychiatric Care CPC1. The psychiatric care process is too complex for an OMABS to be effective. 0.80 CPC2. Managing psychiatric patients requires flexible scheduling that OMABS may not provide. CPC3. Many psychiatric patients may struggle to use an OMABS due to cognitive, emotional, or technological barriers. CPC4.The absence of direct human interaction in online scheduling concerns me. Perceived Security and Reliability PSR1. I trust that the OMABS system will securely handle patient information. 0.87 PSR. I believe that OMABS is reliable in managing patient appointments. Demographic Characteristics of the Sample The questionnaire was administered to all 46 resident physicians specializing in mental health at the Psychiatry Department of the University Hospital in Morocco, ensuring full coverage of the target population. Table 2 summarizes the demographic characteristics of the participants, including age, gender, and their prior use of OMABS in both personal and professional contexts. Table 2. Sample Characteristics (n=46). Variables n (%) Age (years) ≤ 30 31 (67.39) > 30 15 (32.61) Gender Female 40 (86.96) Male 6 (13.9) Residency Year 1st Year 2 (4.35) 2nd Year 14 (30.43 3rd Year 9 (19.57) 4th Year 21 (45.65) Previous use of OMABS in a professional context 2 (4.35) Reported Frequency of Use Rarely 2 (4.35) Previous use of OMABS in a personal context 2 (4.35) Reported Frequency of Use Rarely 2 (4.35) Note. All other response options of frequency of Use (“never,” “sometimes,” “often,” “very often”) received no responses. Descriptive statistics indicated that 86.96% of the respondents were female, 45.65% were in their 4th year of residency, and 67.39% were under 30 years of age, highlighting an active and relatively youthful group likely to be more receptive to technological advancements. However, only 4.35% reported prior use of the OMABS in both personal and professional contexts, with the frequency of use being rare. Perceptions of Using OMABS Among Resident Physicians Descriptive statistics for each dimension of the study are reported in Table 3, offering an initial understanding of participants' perceptions of the key variables associated with their intention to use OMABS. Since none of the variables followed a normal distribution, the median and interquartile range were calculated. Table 3. Descriptive Analysis of the Variables. Variables Median IQR UI 4 1.37 PU 3.75 0.75 PEOU 3.33 1.25 SI 3 0.87 PWTC 4 0.75 PAMC 2 0.5 PIS 3 1.75 MCS 2 0.5 CPC 4.25 0.25 PSR 3.5 1 UI = Use Intention, PU = Perceived Usefulness, PEOU = Perceived Ease of Use, SI = Social Influence, PWTC = Perceived Workload and Time Constraints, PAMC = Perceived Autonomy in Managing Consultations, PIS = Perceived Institutional Support, MCS = Medical Curriculum Support, CPC = Complexity of Psychiatric Care, PSR = Perceived Security and Reliability. Resident physicians expressed a general positive intention toward using OMABS (Median = 4, IQR = 1.37). Perceived usefulness (3.75), perceived ease of use (3.33), and perceived security and reliability (3.5) were rated as moderate, indicating an appreciation for the potential usefulness of OMABS, its relative ease of use, and its ability to ensure data protection and operational reliability. The median score for social influence and institutional support indicates neutral perceptions regarding peer or institutional encouragement to use OMABS. In contrast, the contextual factors of residency training and psychiatric care, including heavy workload and time constraints, low autonomy in managing consultations, limited institutional support, inherent complexity of psychiatric care, and insufficient integration of technology into the medical curriculum, were perceived as barriers to the use of OMABS. Differences in Perceptions of Using OMABS Across Residency Years Table 4 summarizes the test values derived from Kruskal-Wallis’s test, its associated p-values, and the effect sizes. Each row corresponds to one of the measured variables, exploring differences in resident physicians' perceptions of OMABS across residency years. Table 4. Variations in Perceptions of OMABS Across Residency Years. Variables χ² p-value ε² UI 8.981 0.03* 0.1996 PU 6.734 0.081 0.1496 PEOU 2.090 0.554 0.0464 SI 18.698 < .001** 0.4155 PWTC 6.183 0.103 0.1374 PAMC 4.061 0.255 0.0902 PIS 0.864 0.834 0.0192 MCS 12.243 0.007** 0.2721 CPC 9.744 0.02* 0.2165 PSR 5.536 0.136 0.1230 *Significant at p < 0.05 **Significant at p < 0.01 Four constructs were found to differ significantly across residency years according to the Kruskal–Wallis’s test: use intention (p =.030, ε² = 0.20), social influence (p <.001, ε² = 0.42), medical curriculum support (p =.007, ε² = 0.27), and complexity of psychiatric care (p =.020, ε² = 0.22). All were associated with medium to large effect sizes, suggesting that a significant amount of the variation in these perceptions can be attributed to the residency year. In contrast, despite their moderate effect sizes, perceived usefulness, perceived workload, and time constraints, perceived autonomy in managing consultations, and perceived security and reliability did not vary significantly by residency year, suggesting possible underlying differences that require more investigation. Finally, negligible effect sizes and no significant variation were observed for perceived ease of use and perceived institutional support, suggesting consistent perceptions toward these two constructs across all residency years. To further investigate the significant differences identified by Kruskal-Wallis’s test, the DSCF pairwise comparison test was conducted. The DSCF test revealed significant differences in social influence, medical curriculum support, and complexity of psychiatric care across residency year groups. Table 5 outlines the main results. Table 5. Comparison of Perceptions Across Residency Years for Key Variables. Variable Group Comparison W (Test value) p-value UI Year 1 vs. Year 2 3.02 0.142 Year 1 vs. Year 3 0.00 1.000 Year 1 vs. Year 4 2.27 0.377 Year 2 vs. Year 3 -3.29 0.092 Year 2 vs. Year 4 -1.70 0.624 Year 3 vs. Year 4 2.66 0.237 SI Year 2 vs. Year 3 -5.619 < .001** Year 3 vs. Year 4 5.185 0.001** MCS Year 2 vs. Year 4 -4.15 0.018* CPC Year 3 vs. Year 4 -39.404 0.027* *Significant at p < 0.05 **Significant at p < 0.01 The analysis reported significant variations in perceptions across residency years regarding the use of OMABS. Although perceptions of use intention differed significantly overall (χ² = 8.981, p = 0.03), the pairwise DSCF comparisons did not identify statistically significant differences between specific year groups (p > 0.05). In contrast, perceptions of peer influence toward using OMABS vary significantly during the residency years, particularly around the third year. A significant difference also emerged between the second and fourth years of residency (p = 0.018) regarding the perceived support of the medical curriculum toward using digital health tools; these perceptions differed particularly at later training years. Finally, fourth-year residents perceived the complexity of psychiatric care differently, as outlined by the significant difference observed between the third and fourth years of residency (p = 0.027). Correlation analysis Spearman correlation analysis was conducted to test the proposed hypotheses. The findings supported only three of the hypotheses, while the remaining were not supported. Table 6 presents a summary of the findings. Table 6. Hypothesis results. Variables Hypothesis rho p-value Decision PU vs UI H1 0.536 < .001** Supported PEU vs UI H2 0.143 0.344 Not supported SI vs UI H3 0.213 0.155 Not supported PWTA vs UI H4 0.860 < .001** Not Supported PAMC vs UI H5 -0.082 0.587 Not supported PIS vs UI H6 -0.273 0.066 Not supported MC vs UI H7 0.041 0.787 Not supported CPC vs UI H8 -0.083 0.585 Not supported PSR vs UI H9 0.557 < .001** Supported PU*Residency year vs UI H10 0.175 0.245 Not supported PEU*Residency year vs UI H11 0.040 0.793 Not supported SI*Residency year vs UI H12 0.079 0.601 Not supported PWTA*Residency year vs UI H13 0.343 0.020* Supported PAMC*Residency year vs UI H14 -0.077 0.611 Not supported PIS*Residency year vs UI H15 -0.261 0.079 Not supported MC*Residency year vs UI H16 -0.077 0.612 Not supported CPC*Residency year vs UI H17 -0.036 0.811 Not supported PSR*Residency year vs UI H18 0.274 0.066 Not supported *Significant at p < 0.05 **Significant at p < 0.01 Surprisingly, a strong and statistically significant positive correlation was identified between perceived workload and time constraints and intention to use OMABS (ρ = 0.860, p < .001), which contradicts the hypothesis that higher perceived workload and time constraints are negatively associated with resident physicians’ intention to use OMABS. Moreover, both perceived usefulness (ρ = 0.536, p < 0.001) and perceived security and reliability (ρ = 0.557, p < 0.001) showed moderate to strong positive correlations with intention to use OMABS, which supports the hypotheses that perceived usefulness, security, and reliability are positively associated with the use intention of OMABS. Conversely, perceived ease of use, social influence, perceived institutional support, perceived autonomy in managing consultations, medical curriculum support, and the complexity of psychiatric care were not significantly correlated with the intention to use OMABS (p > 0.05), which does not align with the initially proposed hypotheses. Regarding interaction terms between residency year and each variable, only one significant positive correlation was observed between the interaction term PWTA × residency year and the use intention of OMABS (ρ = 0.343, p = 0.020), which support the hypothesis that residency year moderates the relationship between perceived workload and time constraints and resident physicians’ intention to use OMABS. The Other interaction terms were not statistically significant (p>0.05) and therefore did not support the remaining hypotheses. Discussion This study, guided by the technology acceptance framework and enriched by constructs derived from resident physicians' training context and the characteristics of the psychiatric care field, explored resident physicians’ perceptions and intentions regarding the use of OMABS in the mental healthcare settings. The results provided a comprehensive understanding of the nuances surrounding the perceptions and intentions toward using technology in this specialized healthcare setting. Resident physicians, typically younger and assumed to be more receptive to new technology, were found to have limited familiarity with e-appointment services for either work-related or personal use. This lack of familiarity can be attributed to the traditional medical training curriculum, which often excludes exposure to digital health tools, despite the rapid evolution of healthcare delivery and practice. This proposal was supported by resident physicians, who pointed out the lack of integration of new technologies in their medical curriculum and training program. These findings underscore the urgent need to integrate digital health training into residency programs, as highlighted by previous studies [41,47–49]. Doing so will better prepare medical trainees to meet the growing technological demands of the healthcare industry, ensuring more effective and efficient responses to its evolving requirements. In general, favorable perceptions toward the OMABS' potential benefits, relative ease of use, and capacity to protect data and function reliably were expressed by resident physicians. In contrast, unfavorable perceptions were linked to contextual factors related to residency training and the complexity of psychiatric care. Factors like heavy workload and time constraints, low autonomy in managing consultations, the inherent complexity of psychiatric care, and insufficient integration of technology into the medical curriculum were cited as barriers. This reflects widespread concerns about contextual and structural barriers that can impede the acceptance and use of OMABS. These findings are consistent with prior research [17,50], indicating that physicians in training tend to have a favorable attitude toward the potential benefits of e-health services and acknowledge their value in improving patient care, but they often face contextual and structural barriers that limit their adoption and use. However, correlation analysis provided significant clarifications. Perceived autonomy in managing consultations, institutional support, medical curriculum support, and complexity of psychiatric care were not significantly associated with resident physicians’ intention to use OMABS. This suggests that, in clinical settings such as mental healthcare, even if contextual factors are perceived as barriers, they are not associated with intention to use e-health services. Such findings contradict some assumptions of the extended TAM and UTAUT models, which often regard contextual enablers as key determinants of technology adoption. The intention could be more driven by other determinants, including perceived relevance, reliability, and time-saving benefits, rather than by contextual factors such as autonomy or curriculum design. It is also possible that resident physicians consider such barriers as an inherent characteristic of psychiatric care that technology cannot simplify, so it does not affect their intention to use OMABS. This insight was confirmed by our correlation analysis between perceived usefulness and perceived security, and reliability and use intention of OMABS. It has revealed that perceived usefulness and perceived security and reliability correlated positively with resident physicians’ intention to use OMABS, aligning with prior studies [51–53] emphasizing the perceived usefulness of technology as a key determinant of technology acceptance and use and with studies [54–56] considering trust in security and reliability as a cornerstone of technology acceptance, particularly in healthcare, where concerns about data privacy and confidentiality are paramount. A particularly unexpected finding was the strong positive correlation between perceived workload and time constraints and intention to use OMABS. The analysis revealed that resident physicians experiencing greater workload and tighter schedules were more inclined to use OMABS, which contradicts the hypothesis that higher workload and time constraints are associated with low intention to use OMABS. This result suggests that residents who feel the greatest pressure are those who perceive OMABS as a useful and potentially time-saving tool that can help them ease their burden. This aligns with the study by Chen et al. [57], who reported that radiology residents in China intend to adopt digital tools when they perceive them as saving time and reducing cognitive load, even in high-pressure environments. Conversely, perceived ease of use and social influence were not correlated with the intention to use OMABS. Although these determinants are commonly emphasized in the technology acceptance literature [13,58–60], their relatively neutral or moderate scores in this study suggest they may be less critical in the specific context of mental healthcare. The observed variations in perceptions, particularly at later training stages, regarding medical curriculum support, use intention, social influence, and complexity of psychiatric care support the idea that resident physicians' perceptions of e-health services such as OMABS varied dynamically during their training as their clinical exposure and assignments increased. They are founded more on exposure to curriculum, peer support, and direct experience than on usability testing or security analysis. This finding is in line with previous research [15], indicating that stage-specific experience shapes attitudes toward health technology acceptance and use. Therefore, intervention and training program design by year of residency could enhance the adoption of e-health services within psychiatric care. Contrary to the effect of residency year on perceptions, the relationship between interaction terms and resident physicians' intention to use OMABS was not statistically significant; there was a single significant positive correlation between the interaction term PWTC*residency year and use intention of OMABS. This would imply that the more workload and time pressure that resident physicians see themselves experiencing in their training, the more helpful OMABS is likely to be in managing their work. In summary, this study's findings suggest that while resident physicians in mental healthcare settings recognize both the advantages and barriers associated with the use of OMABS, their intention to use e-health services is more associated with perceived operational benefits than with certain structural or contextual barriers. Theoretical and Practical Implications These findings carry significant theoretical and practical implications. From a practical perspective, findings may guide strategies for optimizing e-health services integration in high-pressure medical training settings. Follow-up implementation activities are required to focus on strengthening perceptions of efficiency and usefulness, along with filling integration gaps in training programs and clinical work processes. Equally important is the implementation of robust data protection measures to strengthen user trust, particularly in a field like mental healthcare, where confidentiality is paramount. Tailored training programs are essential to meet the specific needs of residents at different stages of their medical training. Such programs should focus on equipping residents with the skills and confidence necessary to effectively use the system, ensuring that they feel supported throughout their learning and professional growth. From a theoretical perspective, the study examined contextual factors, such as perceived workload and time constraints, curriculum design, and the complexity of psychiatric care, that are not commonly explored in traditional health technology acceptance models. It also reaffirms the importance of perceived usefulness as a central construct of the technology acceptance framework but does not support the common association between perceived ease of use, social influence and technology acceptance, suggesting that while the technology acceptance framework remains a robust tool for understanding use intention, the relevance of certain constructs may vary depending on the specific healthcare setting and user group. This insight underscores the need for continued refinement and contextualization of these theoretical models to better analyze the nuances of technology adoption in specialized fields like mental healthcare. Study Limitations The limitations of this study constitute opportunities for future research. The study sample consisted of a small group of resident physicians from the University Hospital in Morocco. While this limited sample size may constrain the generalizability of the findings to broader populations, it is representative of the specific target population for this study and provides useful insights that apply to similar psychiatric settings. To enhance the robustness of the results, future studies should include resident physicians in psychiatry from other University hospitals across Morocco to be able to reach stronger findings that more accurately represent the perceptions and intentions to use e-health services from a wider variety of resident physicians. While the small sample size and reliance on correlational analysis limit the ability to establish causation, the findings still provide a useful starting point for specifying important associations. These could be validated through longitudinal studies, the inclusion of more representative samples, and the application of robust modeling techniques, such as regression analysis or structural equation modeling, to confirm the findings and further clarify the acceptance of e-health services among medical trainees in mental healthcare. Some of the constructs were measured by two items, which were adequate for this study's objectives. However, it is known that multi-item scales typically offer stronger evidence of construct validity and reliability. Hence, future research could overcome this limitation and thereby improve psychometric robustness by including more items to these constructs. Several key constructs, like perceived usefulness, workload and time constraints, autonomy in managing consultations, and security and reliability, were not significantly varying between residency years, even though the effect sizes were moderate. This may be due to the limited sample size, which may not have been sufficient to detect smaller variations, or to the limited sensitivity of the questionnaire items in capturing subtle differences. Further research with larger populations and more sensitive measures is required to better understand how these variables can vary across residency years. The focus on specific contextual factors may have omitted other potentially relevant determinants, such as patient-related factors, including digital literacy, or broader policy influences, including national digital health strategies. Future research might investigate the influence of these constructs to identify which will have a considerable influence on the intention to use e-health services in mental healthcare settings. Our analysis revealed varied perceptions of using OMABS over the later residency year. It will be interesting to use more qualitative research methodologies, such as interviews or focus group discussions, to explore the critical role of residency years in influencing the adoption of e-appointment services. Conclusions The findings provided by this study make an original contribution to the literature. The evidence provided by exploring resident physicians' perceptions and intentions to use e-health services within a niche but relevant setting of mental healthcare can inform future research and guide policy development and implementation of e-health services among medical trainees. While several variables were hypothesized to affect use intention, a few demonstrated statistically significant associations. Notably, perceived workload and time constraints showed a strong positive correlation with intention to use OMABS, raising new questions about how pressure and digital openness interact in clinical environments. Perceived usefulness and perceived security, and reliability were moderately and positively correlated with the intention to use OMABS, as commonly demonstrated by technology acceptance models, confirming that functional benefits and system security beliefs are relevant factors of technology acceptance and use. Declarations Ethics approval and consent to participate The study adhered to the principles outlined in the Declaration of Helsinki, the ethical guidelines of the Ethics Committee of Hassan II University in Morocco, and the Moroccan law No. 09-08 on personal data protection. The study was conducted using an anonymous and non-identifiable questionnaire. Participation was entirely voluntary, and no interventions were involved. No personal data that could identify participants was collected. All participants were informed of the study's objective and that the data collected would be used only for scientific research purposes. Informed consent was obtained from all participants before their involvement in the study. Consent for publication Not applicable. Competing interests The authors declare no competing interests. Funding Not applicable. Availability of data and materials Data sets and output files of the data analysis are available from the authors on request. Acknowledgements Special thanks to the staff of the Psychiatry Department of the University Hospital in Casablanca, Morocco. Authors’ information Authors and Affiliations Clinical Neurosciences and Mental Health Laboratory, Faculty of Medicine and Pharmacy, Hassan II University, Casablanca, Morocco; Loubna Khalil, Zineb Serhier, Manar Jallal, Mohammed Bennani Othmani Authors’ Contributions The authorship and contributions of each author to this manuscript are as follows: LK : Conceptualization, Methodology, Analysis and interpretation of data, Writing original draft; ZS : Supervision, Validation, review, and Editing; MJ Methodology, Revising and Validation; MBO : Validation, Review, and Editing. All authors read and approved the final manuscript. Corresponding author E-mail address: [email protected] Declaration of generative AI and AI-assisted technologies in the writing process. During the preparation of this work, the author(s) used Grammarly (V.1.2.116.1536) in order to correct grammatical errors and improve the readability and language of the manuscript. 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Supplementary Files Questionnaireperceptionsandintentionsofresidentphysicians.docx Cite Share Download PDF Status: Under Review Version 1 posted Reviews received at journal 08 Oct, 2025 Reviewers agreed at journal 23 Sep, 2025 Reviewers invited by journal 18 Sep, 2025 Editor assigned by journal 16 Sep, 2025 Editor invited by journal 25 Aug, 2025 Submission checks completed at journal 23 Aug, 2025 First submitted to journal 23 Aug, 2025 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. 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13:01:07\",\"extension\":\"docx\",\"order_by\":0,\"title\":\"\",\"display\":\"\",\"copyAsset\":false,\"role\":\"supplement\",\"size\":42303,\"visible\":true,\"origin\":\"\",\"legend\":\"\",\"description\":\"\",\"filename\":\"Questionnaireperceptionsandintentionsofresidentphysicians.docx\",\"url\":\"https://assets-eu.researchsquare.com/files/rs-7383021/v1/fa4e3b59e47a7dae1d79c8dd.docx\"}],\"financialInterests\":\"No competing interests reported.\",\"formattedTitle\":\"Perceptions and Intentions to Use E-Health Services in Mental Health Care Settings: A Case Study Among Resident Physicians\",\"fulltext\":[{\"header\":\"Introduction\",\"content\":\"\\u003cp\\u003eDigital health technology is revolutionizing the production and delivery of mental health services, driving a paradigm shift that has yielded multifaceted implications for healthcare consumers and providers\\u0026nbsp;[1]. A notable innovation in this transformation is the online medical appointment booking system (OMABS), which has altered the traditional method of scheduling and managing medical appointments. Previous studies have identified OMABS as one of the most practical internet-based health services, offering significant benefits in efficiency, profitability, productivity, accessibility, and quality of healthcare services\\u0026nbsp;[2\\u0026ndash;8]. \\u0026nbsp;\\u003c/p\\u003e\\n\\u003cp\\u003eDelivering mental health care comes with its own set of challenges, shaped by both the complexity of mental health conditions and the broader difficulties in accessing healthcare. People dealing with mental health issues often need continuous support, timely interventions, and treatment plans tailored to their unique emotional and physical needs\\u0026nbsp;[9]. Considering these specific requirements and challenges, implementing e-appointment systems holds particular promise.\\u0026nbsp;\\u003c/p\\u003e\\n\\u003cp\\u003eIn Morocco, healthcare organizations are progressively more dependent on incorporating OMABS, reflecting a notable turn toward the digital transformation of the healthcare sector. The national online platform \\u0026quot;Mawiidi\\u0026quot; exemplifies this progress, designed to simplify and enhance the appointment scheduling experience. However, the successful deployment and use of such systems remain limited\\u0026nbsp;[8,10]\\u0026nbsp;and are influenced by factors such as insufficient technical expertise, inadequate digital infrastructure, and resistance from healthcare professionals\\u0026nbsp;[11].\\u0026nbsp;\\u003c/p\\u003e\\n\\u003cp\\u003eResident physicians in mental health settings, as emerging healthcare professionals, play a critical role in the acceptance and use of e-health services due to their direct and frequent interaction with patients and digital platforms. Their acceptance and use of e-appointment services may be shaped by a complex interplay of factors, including concerns about data confidentiality, training context, and the specific demands of psychiatric care.\\u003c/p\\u003e\\n\\u003cp\\u003eTheoretical models grounded in the framework of technology acceptance, such as the technology acceptance model (TAM)\\u0026nbsp;[12]\\u0026nbsp;and the unified theory of acceptance and use of technology (UTAUT)\\u0026nbsp;[13], offer insights into the factors that drive the use intention of technology in various contexts. These models emphasize the roles of individual, technological, and organizational factors in influencing an individual\\u0026rsquo;s behavior toward using technology. However, limited research has specifically applied these models to explore the intention to use e-health services among physicians in training. For instance, Steininger and Stiglbauer employed an extended TAM to examine Electronic Health Record (EHR) adoption among Austrian resident doctors. Their findings revealed that social influence, prior experience with health technologies, and privacy concerns significantly influenced perceived usefulness, which in turn fostered more favorable attitudes and stronger behavioral intentions toward using EHR systems\\u0026nbsp;[14]. Similarly, Wang et al. examined the use intention of Virtual Reality among graduate medical education (GME) trainees and found that perceived usefulness, ease of use, and enjoyment were significant predictors of the intention to use virtual reality as a therapeutic tool\\u0026nbsp;[15]. Samadbeik et al. investigated the factors influencing mHealth use intention among medical science trainees and identified perceived usefulness and ease of use as key determinants of both attitude and intention to use these tools\\u0026nbsp;[16]. Humphrey-Murto et al. examined the factors influencing the use intention of electronic health records by physicians and residents in two different hospitals and found that workflow changes, insufficient ongoing support, and emotional responses like frustration and anxiety were significant barriers to effective electronic health record acceptance and use\\u0026nbsp;[17].\\u0026nbsp;\\u003c/p\\u003e\\n\\u003cp\\u003eDespite these contributions, the literature lacks the nuanced application of technology acceptance frameworks to understand the use intention of e-health services among resident physicians in mental healthcare settings, a context characterized by specific clinical, organizational, and psychosocial challenges. Few studies have investigated how contextual factors within psychiatric residency, such as workload, autonomy, and complexity of care, may shape technology acceptance and use of OMABS, leaving a notable gap in understanding the interaction between these contextual factors and the use intention of e-health services. The systematic literature review exploring user acceptance of medical e-appointment systems for mental healthcare highlights this gap in research\\u0026nbsp;[18]. It states that limited studies have focused specifically on e-appointment systems, and none have thoroughly examined the perceptions and behavioral intentions of resident physicians working in mental healthcare settings. This gap leaves an unclear understanding of how this category of resident physicians perceives and intends to use e-appointment technologies. As key stakeholders in the delivery of psychiatric care, resident physicians hold valuable perspectives on the feasibility and integration of such technologies. Their perspectives are precious, as these emerging professionals offer insights into the future potential for integrating such e-services within mental health practices. Addressing this gap is essential to ensuring the successful adoption and use of OMABS in mental healthcare, ultimately enhancing patient care and service efficiency.\\u003c/p\\u003e\\n\\u003cp\\u003eThis study aims to explore resident physicians\\u0026apos; perceptions and intentions to use OMABS within the Moroccan mental healthcare context. Specifically, it focuses on resident physicians at the Psychiatry Department of the University Hospital in Casablanca, Morocco. Given the limited size of this professional group, the study included the entire population of 46 residents.\\u0026nbsp;\\u003c/p\\u003e\\n\\u003cp\\u003eThe study was based on selected factors specific to the residency training context, the psychiatric care field, and the classic factors of technological acceptance that align with the study objective. It attempts to answer the following questions: Are resident physicians working in mental health settings currently using OMABS? What are their perceptions of this service? Do these perceptions differ across residency years? What are the primary factors associated with the intention to use this service?\\u0026nbsp;Does residency year moderate the association of these factors with the intention to use this service?\\u003c/p\\u003e\\n\\u003cp\\u003eTo our knowledge, this is the first study exploring resident physicians\\u0026rsquo; acceptance of e-appointment services in psychiatric care. The paper is structured as follows: first, we outline the proposed hypotheses. Next, we present the methods employed to examine resident physicians\\u0026apos; perceptions and intentions to use OMABS. We then present the key results, discuss their implications, propose directions for future research, and conclude.\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cstrong\\u003eHypotheses development\\u0026nbsp;\\u003c/strong\\u003e\\u003c/p\\u003e\\n\\u003cp\\u003eTo explore resident physicians\\u0026apos; perceptions and intentions to use OMABS in mental healthcare settings, the study draws upon selected factors specific to the residency training context, the characteristics of the psychiatric care field, and the classic factors of technological acceptance that align with the study objective. The following hypotheses were proposed to be tested.\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cstrong\\u003e\\u003cem\\u003eGeneral Technology Acceptance Factors\\u003c/em\\u003e\\u003c/strong\\u003e\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cstrong\\u003ePerceived usefulness\\u0026nbsp;\\u003c/strong\\u003e\\u003c/p\\u003e\\n\\u003cp\\u003ePerceived usefulness is widely recognized as one of the most influential factors in determining technology acceptance, particularly in healthcare. It refers to the extent to which residents\\u0026apos; physicians believe that e-health services will facilitate and enhance their work efficiency. In mental healthcare, residents\\u0026apos; physicians are often faced with time pressure and complex cases. When e-health services like OMABS are seen as enhancing efficiency and access, they are more likely to be accepted and integrated into daily practice. Several studies have indicated that perceived usefulness is a key predictor of intention to use or adopt new technology across various healthcare fields\\u0026nbsp;[19], including the mental health field\\u0026nbsp;[20\\u0026ndash;22]. Therefore, we hypothesize that:\\u0026nbsp;\\u003c/p\\u003e\\n\\u003cp\\u003eHypothesis 1 (H1): Perceived usefulness is positively associated with resident physicians\\u0026rsquo; intention to use OMABS.\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cstrong\\u003ePerceived ease of use\\u0026nbsp;\\u003c/strong\\u003e\\u003c/p\\u003e\\n\\u003cp\\u003ePerceived ease of use is the degree to which residents\\u0026apos; physicians believe that using technology will be simple and easy, even under high workload conditions. In healthcare environments, especially in mental health settings where workflows are often complex and unpredictable, resident physicians are more likely to embrace e-health services if these tools are perceived as user-friendly and requiring minimal time or training. Numerous studies have posited the positive influence of ease of use on health technology acceptance\\u0026nbsp;[23\\u0026ndash;25]. Hence, the following hypothesis is proposed to be tested. \\u0026nbsp;\\u003c/p\\u003e\\n\\u003cp\\u003eHypothesis 2 (H2): Perceived ease of use is positively associated with resident physicians\\u0026rsquo; intention to use OMABS.\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cstrong\\u003eSocial Influence\\u003c/strong\\u003e\\u003c/p\\u003e\\n\\u003cp\\u003eSocial influence refers to the perceived pressure or encouragement from important others, such as senior physicians, supervisors, or peers, to use technology\\u0026nbsp;[13]. In the mental healthcare setting, where hierarchical relationships and mentorship are prevalent, the recommendations or positive experiences shared by supervisors, senior psychiatrists, and peers can significantly shape resident physicians\\u0026apos; attitudes toward adopting new technologies such as the e-appointment service. Several studies\\u0026nbsp;[26\\u0026ndash;28]\\u0026nbsp;have emphasized that social influence positively impacts users\\u0026apos; behavioral intention to adopt health technologies. Consequently, we hypothesize that:\\u003c/p\\u003e\\n\\u003cp\\u003eHypothesis 3 (H3): Social influence is positively associated with resident physicians\\u0026rsquo; intention to use OMABS.\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cstrong\\u003e\\u003cem\\u003eFactors Related to the Residency Training Context\\u003c/em\\u003e\\u003c/strong\\u003e\\u003c/p\\u003e\\n\\u003cp\\u003eThe training context of resident physicians is critical to their intention to use new technologies in clinical practice. It encompasses several aspects, including the structure and delivery of training, available resources, support, and the overall work environment. Here are key variables that we have considered to evaluate whether residents\\u0026rsquo; training context encourages the use of technology and supports acceptance of e-services: perceived workload and time constraints, autonomy in managing consultations, institutional support, and\\u0026nbsp;medical curriculum support.\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cstrong\\u003ePerceived Workload and Time Constraints\\u003c/strong\\u003e\\u003c/p\\u003e\\n\\u003cp\\u003ePerceived workload and time constraints factor reflect the perceived time constraints and work demands experienced by resident physicians in mental health settings. This category of trainee physicians often faces long-duration shifts, extended weekly work hours, and emotional fatigue[29], which can limit their capacity to explore or adopt new e-health solutions, even when these tools are potentially beneficial. If e-health services, such as OMABS, are perceived as time-saving and compatible with existing workflows, they may be welcomed as facilitators rather than as additional burdens\\u0026nbsp;[30]. However, if the health technology is seen as time-consuming and workload-arising, overworked resident physicians may resist its implementation, regardless of its potential value\\u0026nbsp;[31,32]. Prior studies have suggested that higher workload hinders the acceptance of digital health services among healthcare professionals\\u0026nbsp;[33,34]. In this regard, we hypothesize that:\\u0026nbsp;\\u003c/p\\u003e\\n\\u003cp\\u003eHypothesis 4 (H4): Higher perceived workload and time constraints are negatively associated with resident physicians\\u0026rsquo; intention to use OMABS.\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cstrong\\u003ePerceived Autonomy in Managing Consultations\\u003c/strong\\u003e\\u003c/p\\u003e\\n\\u003cp\\u003eAutonomy in managing consultations reflects the degree of control that resident physicians perceive they have over their clinical tasks, including scheduling and patient management. This perceived autonomy may influence their acceptance and use of e-health services like the OMABS. Striking the right balance between the autonomy of trainee physicians and the supervision of senior physicians remains a well-documented challenge in medical education\\u0026nbsp;[35]. When residents, especially in mental health settings, feel empowered to control their consultation schedules, they are more likely to perceive such systems as supportive rather than restrictive. On the other hand, if scheduling decisions are tightly regulated by supervisors, residents may see digital tools as reinforcing hierarchical constraints rather than enhancing efficiency. Therefore, we hypothesize that:\\u003c/p\\u003e\\n\\u003cp\\u003eHypothesis 5 (H5): Higher perceived autonomy in managing consultations is positively associated with resident physicians\\u0026rsquo; intention to use OMABS.\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cstrong\\u003eInstitutional Support\\u0026nbsp;\\u003c/strong\\u003e\\u003c/p\\u003e\\n\\u003cp\\u003eInstitutional Support measures whether adequate resources and support are available to help residents\\u0026apos; physicians use OMABS effectively. The degree of supervision and institutional support can impact the residents\\u0026apos; ability and willingness to integrate e-health services into their practice. If the hospital offers adequate support, resident physicians are more likely to adopt such services, as mentioned by previous studies\\u0026nbsp;[24,36]. Therefore, we hypothesize that:\\u003c/p\\u003e\\n\\u003cp\\u003eHypothesis 6 (H6): The institutional support is positively associated with resident physicians\\u0026rsquo; intention to use OMABS.\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cstrong\\u003eMedical Curriculum Support\\u003c/strong\\u003e\\u003c/p\\u003e\\n\\u003cp\\u003eMedical digital health education plays a significant role in shaping physicians\\u0026apos; ability to use the technology effectively in clinical practice\\u0026nbsp;[37,38]. As health technologies, such as e-appointment services, telemedicine, and electronic health records (EHR), become more integrated into healthcare, the medical curriculum must adapt to ensure that resident physicians are adequately prepared to navigate these tools\\u0026nbsp;[39\\u0026ndash;41]. Proper training ensures that resident physicians not only know how to use these systems but also feel confident and competent in integrating them into their daily clinical practice. \\u0026nbsp;Based on this, we hypothesize that:\\u003c/p\\u003e\\n\\u003cp\\u003eHypothesis 7 (H7): The integration of technology into the medical curriculum is positively associated with resident physicians\\u0026rsquo; intention to use OMABS.\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cstrong\\u003e\\u003cem\\u003eFactors Specific to Psychiatric Care\\u003c/em\\u003e\\u003c/strong\\u003e\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cstrong\\u003eComplexity of Psychiatric Care\\u003c/strong\\u003e\\u003c/p\\u003e\\n\\u003cp\\u003eThe psychiatric care system presents several challenges that can influence the use of e-health services by residents\\u0026apos; physicians. Its unique characteristics, including patient compliance, the unpredictability of psychiatric consultations, the significant variation in their duration\\u0026nbsp;[42], the need for flexible scheduling, potential patient difficulties in using online systems, and concerns about direct human interaction\\u0026nbsp;[43], can make relying on an online appointment system difficult and consequently influence the intention to use it among resident physicians. Based on these considerations, we proposed the following hypothesis:\\u003c/p\\u003e\\n\\u003cp\\u003eHypothesis 8 (H8): The Complexity of psychiatric care is negatively associated with resident physicians\\u0026rsquo; intention to use OMABS.\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cstrong\\u003ePerceived Security and Reliability\\u003c/strong\\u003e\\u003c/p\\u003e\\n\\u003cp\\u003ePrior studies have shown that confidentiality concerns and trust have a significant influence on the acceptance and use of health technology\\u0026nbsp;[24]. Resident physicians may be reluctant to adopt e-health services if they perceive a risk to patient privacy or data security. This concern is even greater in the context of mental health care, where violations of confidentiality could have serious ethical or legal consequences. Conversely, trust in technology, particularly in its security and reliability, plays an essential role in mitigating these concerns. Studies have shown that healthcare professionals are more likely to adopt digital tools when they trust the system and believe it adequately protects patient data\\u0026nbsp;[28,44,45]. Therefore, we hypothesize that:\\u003c/p\\u003e\\n\\u003cp\\u003eHypothesis 9 (H9): Perceived security and reliability are positively associated with resident physicians\\u0026rsquo; intention to use OMABS.\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cstrong\\u003e\\u003cem\\u003eResidency year\\u003c/em\\u003e\\u003c/strong\\u003e\\u003c/p\\u003e\\n\\u003cp\\u003eResidency year was also incorporated as a moderating variable through interaction terms with each construct. It represents the level of professional experience, which is likely to influence exposure to and familiarity with OMABS. Residency year was hypothesized to moderate the association between all variables and use intention, with the expectation that the strength of this relationship may vary across different residency levels. The following hypotheses were proposed to be tested.\\u003c/p\\u003e\\n\\u003cp\\u003eHypothesis 10 (H10): Residency year moderates the relationship between perceived usefulness of OMABS and resident physicians\\u0026rsquo; intention to use OMABS.\\u003c/p\\u003e\\n\\u003cp\\u003eHypothesis 11 (H11): Residency year moderates the relationship between perceived ease of use of OMABS and resident physicians\\u0026rsquo; intention to use OMABS.\\u0026nbsp;\\u003c/p\\u003e\\n\\u003cp\\u003eHypothesis 12 (H12): Residency year moderates the relationship between social influence and resident physicians\\u0026rsquo; intention to use OMABS.\\u0026nbsp;\\u003c/p\\u003e\\n\\u003cp\\u003eHypothesis 13 (H13): Residency year moderates the relationship between perceived workload and time constraints and resident physicians\\u0026rsquo; intention to use OMABS.\\u003c/p\\u003e\\n\\u003cp\\u003eHypothesis 14 (H14): Residency year moderates the relationship between perceived autonomy in managing consultations and resident physicians\\u0026rsquo; intention to use OMABS.\\u003c/p\\u003e\\n\\u003cp\\u003eHypothesis 15 (H15): Residency year moderates the relationship between institutional support and resident physicians\\u0026rsquo; intention to use OMABS.\\u003c/p\\u003e\\n\\u003cp\\u003eHypothesis 16 (H16): Residency year moderates the relationship between medical curriculum support and resident physicians\\u0026rsquo; intention to use OMABS.\\u003c/p\\u003e\\n\\u003cp\\u003eHypothesis 17 (H17): Residency year moderates the relationship between the complexity of psychiatric care and resident physicians\\u0026rsquo; intention to use OMABS.\\u003c/p\\u003e\\n\\u003cp\\u003eHypothesis 18 (H18): Residency year moderates the relationship between perceived security and reliability and resident physicians\\u0026rsquo; intention to use OMABS.\\u003c/p\\u003e\"},{\"header\":\"Methods\",\"content\":\"\\u003cp\\u003e\\u003cstrong\\u003e\\u003cem\\u003eStudy Design\\u003c/em\\u003e\\u003c/strong\\u003e\\u003c/p\\u003e\\n\\u003cp\\u003eThis research employed a quantitative approach to investigate mental health resident physicians\\u0026apos; perceptions and intentions regarding using OMABS. Data was collected over two months, March and April 2025, targeting resident physicians affiliated with the Psychiatry Department of Ibn Rochd University Hospital in Casablanca, Morocco. The target population comprised 46 resident physicians, representing all those specializing in mental health at this University Hospital. The small sample size is a result of the naturally limited population rather than a sampling decision. Given the relatively small population size, a census approach was adopted, ensuring that every eligible individual was included in the study. This approach aimed to maximize representativeness, provide a comprehensive and unbiased analysis of OMABS adoption within this unique context, and enhance the validity of findings by capturing a comprehensive view of perceptions and use intentions.\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cstrong\\u003e\\u003cem\\u003eData Collect\\u0026nbsp;\\u003c/em\\u003e\\u003c/strong\\u003e\\u003c/p\\u003e\\n\\u003cp\\u003eA structured survey questionnaire consisting of eight questions was used to gather data. Given that no established questionnaire for measuring intentions to use e-health services among resident physicians in mental health care is available. The questionnaire was developed from existing technology acceptance literature\\u0026nbsp;[13] and adapted subsequently to the context of e-health services in psychiatry.\\u003c/p\\u003e\\n\\u003cp\\u003eThe questionnaire began with demographic questions covering participants\\u0026apos; age, gender, and their prior and current experiences with the OMABS in both professional and personal contexts. Subsequently, constructs derived from residency training context, the characteristics of the psychiatric care field, and the classic factors of technological acceptance were operationalized into distinct sections, covering perceived ease of use, perceived usefulness, social influence, perceived workload and time constraints, perceived autonomy in managing consultations, perceived institutional support, medical curriculum support, complexity of psychiatric care, and perceived security and reliability.\\u0026nbsp;\\u003c/p\\u003e\\n\\u003cp\\u003eThe survey included a combination of constructs, with some evaluated through several items while others were assessed using just two. This design choice was guided by theoretical insights and the constraints of surveying resident physicians in mental healthcare, who deal with significant workload and time constraints. In some cases, literature has shown that two well-formulated items can effectively represent the underlying dimension without compromising validity or reliability, particularly when these items reflect clear and distinct aspects of the concept [46]. In this study, the decision to include two items to measure some constructs was guided by the need to reduce respondent burden while still maintaining the validity and reliability of the instrument.\\u003c/p\\u003e\\n\\u003cp\\u003eA Likert scale was used to assess the questionnaire items, ranging from 1 to 5 (1 = strongly disagree, 2 = disagree, 3 = neutral, 4 = agree, 5 = strongly agree).\\u0026nbsp;The questionnaire was initially designed in French and distributed as paper copies directly to the target population.\\u003c/p\\u003e\\n\\u003cp\\u003eThe English version of the questionnaire is provided as a supplementary file (Supplementary File 1).\\u003c/p\\u003e\\n\\u003cp\\u003e\\u0026nbsp;\\u003cstrong\\u003e\\u003cem\\u003eData Analysis\\u003c/em\\u003e\\u003c/strong\\u003e\\u003c/p\\u003e\\n\\u003cp\\u003eThe data were subjected to descriptive analysis and given as percentages, medians, and interquartile ranges since none of the variables followed a normal distribution. Comparisons across residency years (1 through 4) were conducted using the Kruskal-Wallis test. Effect sizes, eta-squared (\\u0026epsilon;\\u0026sup2;), were calculated to quantify the proportion of variance explained by residency year for Kruskal-Wallis tests. For significant differences identified across residency years, the Dwass-Steel-Critchlow-Fligner (DSCF) pairwise comparison test was applied where appropriate. Statistical significance was set at p \\u0026lt; 0.05.\\u003c/p\\u003e\\n\\u003cp\\u003eContent validity was ensured through an expert assessment to verify the overall coherence and alignment of the questionnaire with the concepts it was supposed to test. Cronbach\\u0026rsquo;s alpha was calculated for the entire instrument to evaluate internal consistency.\\u0026nbsp;\\u003c/p\\u003e\\n\\u003cp\\u003eSpearman\\u0026rsquo;s correlation was employed to assess the strength and direction of the association between the intention to use OMABS and each of the following independent variables: perceived usefulness, perceived ease of use, social influence, perceived workload and time constraints, institutional support, autonomy in managing consultations, medical curriculum, complexity of psychiatric care, and perceived security and reliability. The residency year was incorporated as a moderating variable through interaction terms.\\u0026nbsp;\\u003c/p\\u003e\\n\\u003cp\\u003eSpearman\\u0026rsquo;s correlation analysis was selected over logistic regression due to the small number of observations, combined with an unbalanced distribution of the dependent variable, use intention, which limited the statistical power of logistic regression. Additionally, the variables were ordinal, measured using Likert scales, and significantly deviated from a normal distribution (p \\u0026lt; 0.05) based on the Shapiro-Wilk test, making a non-parametric method such as Spearman\\u0026rsquo;s correlation more appropriate.\\u003c/p\\u003e\\n\\u003cp\\u003eCorrelation coefficients (\\u0026rho;) were interpreted as follows: values between\\u0026nbsp;[0-1]\\u0026nbsp;and\\u0026nbsp;[0-3]\\u0026nbsp;as weak,\\u0026nbsp;[0-3]\\u0026nbsp;and\\u0026nbsp;[0-5]\\u0026nbsp;as moderate, and values above\\u0026nbsp;[0-5]\\u0026nbsp;as strong associations.\\u003c/p\\u003e\\n\\u003cp\\u003eThe analyses were performed using the statistical software JAMOVI version 2.2.5, known for its simplicity and efficiency in handling and analyzing data. Its intuitive interface facilitated a streamlined analytical process, ensuring that the findings were both precise and interpretable.\\u0026nbsp;\\u003c/p\\u003e\"},{\"header\":\"Results\",\"content\":\"\\u003cp\\u003e\\u003cstrong\\u003e\\u003cem\\u003eMeasurement model\\u003c/em\\u003e\\u003c/strong\\u003e\\u003c/p\\u003e\\n\\u003cp\\u003eCronbach\\u0026apos;s \\u0026alpha; was measured to assess how well the items for each construct measured the same basic construct. The results showed that all constructs achieved acceptable levels of consistency, with Cronbach\\u0026rsquo;s alpha values above the recommended 0.70. The global reliability score for the entire scale was 0.79, indicating a reliable structure. Thus, the questionnaire provides consistent and reliable measurements of the constructs that are being studied. Table 1 reports the Cronbach\\u0026apos;s alpha for each construct.\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cstrong\\u003eTable1.The measuring model\\u0026apos;s Cronbach\\u0026apos;s alpha coefficients.\\u003c/strong\\u003e\\u003c/p\\u003e\\n\\u003ctable border=\\\"0\\\" cellspacing=\\\"0\\\" cellpadding=\\\"0\\\" width=\\\"642\\\"\\u003e\\n \\u003ctbody\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 140px;\\\"\\u003e\\n \\u003cp\\u003e\\u003cstrong\\u003eConstruct\\u003c/strong\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 421px;\\\"\\u003e\\n \\u003cp\\u003e\\u003cstrong\\u003eItems\\u003c/strong\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 80px;\\\"\\u003e\\n \\u003cp\\u003e\\u003cstrong\\u003eCronbach\\u0026rsquo;s \\u0026alpha;\\u003c/strong\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd rowspan=\\\"2\\\" valign=\\\"top\\\" style=\\\"width: 140px;\\\"\\u003e\\n \\u003cp\\u003e\\u003cstrong\\u003eUse\\u003cbr\\u003e\\u0026nbsp;Intention\\u003c/strong\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 421px;\\\"\\u003e\\n \\u003cp\\u003eUI1. I intend to use the OMABS in my daily mental health care activities.\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 80px;\\\"\\u003e\\n \\u003cp\\u003e\\u003cstrong\\u003e0.92\\u003c/strong\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 421px;\\\"\\u003e\\n \\u003cp\\u003eUI2. I plan to integrate OMABS into my routine mental health care activities.\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 80px;\\\"\\u003e\\n \\u003cp\\u003e\\u0026nbsp;\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd rowspan=\\\"4\\\" valign=\\\"top\\\" style=\\\"width: 140px;\\\"\\u003e\\n \\u003cp\\u003e\\u003cstrong\\u003ePerceived\\u003cbr\\u003e\\u0026nbsp;Usefulness\\u003c/strong\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 421px;\\\"\\u003e\\n \\u003cp\\u003ePU1. Using the OMABS would lead to more efficient patient appointment scheduling.\\u0026nbsp;\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 80px;\\\"\\u003e\\n \\u003cp\\u003e\\u003cstrong\\u003e0.79\\u003c/strong\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 421px;\\\"\\u003e\\n \\u003cp\\u003ePU2. Using the OMABS would improve access to mental healthcare.\\u0026nbsp;\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 80px;\\\"\\u003e\\n \\u003cp\\u003e\\u0026nbsp;\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 421px;\\\"\\u003e\\n \\u003cp\\u003ePU3. Using the OMABS in my routine would enhance the quality of mental healthcare services.\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 80px;\\\"\\u003e\\n \\u003cp\\u003e\\u0026nbsp;\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 421px;\\\"\\u003e\\n \\u003cp\\u003ePU4. Overall, I find the OMABS useful in my daily practice.\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 80px;\\\"\\u003e\\n \\u003cp\\u003e\\u0026nbsp;\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd rowspan=\\\"3\\\" valign=\\\"top\\\" style=\\\"width: 140px;\\\"\\u003e\\n \\u003cp\\u003e\\u003cstrong\\u003ePerceived\\u003cbr\\u003e\\u0026nbsp;Ease of Use\\u003c/strong\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 421px;\\\"\\u003e\\n \\u003cp\\u003ePEOU1. I would find OMABS easy to use.\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 80px;\\\"\\u003e\\n \\u003cp\\u003e\\u003cstrong\\u003e0.78\\u003c/strong\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 421px;\\\"\\u003e\\n \\u003cp\\u003ePEOU2. Learning to use the OMABS is easy for me.\\u0026nbsp;\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 80px;\\\"\\u003e\\n \\u003cp\\u003e\\u0026nbsp;\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 421px;\\\"\\u003e\\n \\u003cp\\u003ePEOU3. It would be easy for me to become skillful at using the OMABS.\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 80px;\\\"\\u003e\\n \\u003cp\\u003e\\u0026nbsp;\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd rowspan=\\\"2\\\" valign=\\\"top\\\" style=\\\"width: 140px;\\\"\\u003e\\n \\u003cp\\u003e\\u003cstrong\\u003eSocial Influence\\u003c/strong\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 421px;\\\"\\u003e\\n \\u003cp\\u003eSI1.I believe my likelihood of using the OMABS will increase if colleagues around me use it.\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 80px;\\\"\\u003e\\n \\u003cp\\u003e\\u003cstrong\\u003e0.76\\u003c/strong\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 421px;\\\"\\u003e\\n \\u003cp\\u003eSI2. I would feel out of touch if I did not use the OMABS.\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 80px;\\\"\\u003e\\n \\u003cp\\u003e\\u0026nbsp;\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd rowspan=\\\"2\\\" valign=\\\"top\\\" style=\\\"width: 140px;\\\"\\u003e\\n \\u003cp\\u003e\\u003cstrong\\u003ePerceived Workload\\u0026nbsp;\\u003cbr\\u003e\\u0026nbsp;and Time Constraints\\u003c/strong\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 421px;\\\"\\u003e\\n \\u003cp\\u003ePWTC1. Due to time constraints during my shifts, I am unlikely to use OMABS\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 80px;\\\"\\u003e\\n \\u003cp\\u003e\\u003cstrong\\u003e0.95\\u003c/strong\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 421px;\\\"\\u003e\\n \\u003cp\\u003ePWTC2. My clinical workload prevents me from adopting additional tools like OMABS, even if they are useful.\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 80px;\\\"\\u003e\\n \\u003cp\\u003e\\u0026nbsp;\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd rowspan=\\\"2\\\" valign=\\\"top\\\" style=\\\"width: 140px;\\\"\\u003e\\n \\u003cp\\u003e\\u003cstrong\\u003ePerceived Autonomy in Managing Consultations\\u003c/strong\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 421px;\\\"\\u003e\\n \\u003cp\\u003ePAMC1. I have full autonomy in scheduling and managing patient appointments.\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 80px;\\\"\\u003e\\n \\u003cp\\u003e\\u003cstrong\\u003e0.86\\u003c/strong\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 421px;\\\"\\u003e\\n \\u003cp\\u003ePAMC2. I do not need approval from supervisors to adjust my consultation schedule.\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 80px;\\\"\\u003e\\n \\u003cp\\u003e\\u0026nbsp;\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd rowspan=\\\"2\\\" valign=\\\"top\\\" style=\\\"width: 140px;\\\"\\u003e\\n \\u003cp\\u003e\\u003cstrong\\u003ePerceived Institutional\\u0026nbsp;\\u003cbr\\u003e\\u0026nbsp;Support\\u003c/strong\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 421px;\\\"\\u003e\\n \\u003cp\\u003ePIS1. The hospital provides the necessary resources and support to use OMABS.\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 80px;\\\"\\u003e\\n \\u003cp\\u003e\\u003cstrong\\u003e0.93\\u003c/strong\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 421px;\\\"\\u003e\\n \\u003cp\\u003ePIS2. I can have adequate training and support for using OMABS.\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 80px;\\\"\\u003e\\n \\u003cp\\u003e\\u0026nbsp;\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd rowspan=\\\"2\\\" valign=\\\"top\\\" style=\\\"width: 140px;\\\"\\u003e\\n \\u003cp\\u003e\\u003cstrong\\u003eMedical Curriculum\\u0026nbsp;\\u003c/strong\\u003e\\u003c/p\\u003e\\n \\u003cp\\u003e\\u003cstrong\\u003eSupport\\u003c/strong\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 421px;\\\"\\u003e\\n \\u003cp\\u003eMCS1. My residency program includes training on the use of digital health technologies.\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 80px;\\\"\\u003e\\n \\u003cp\\u003e\\u003cstrong\\u003e0.79\\u003c/strong\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 421px;\\\"\\u003e\\n \\u003cp\\u003eMCS2. The curriculum underscores technology\\u0026rsquo;s impact on care and efficiency, enhancing my willingness to use OMABS.\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 80px;\\\"\\u003e\\n \\u003cp\\u003e\\u0026nbsp;\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd rowspan=\\\"4\\\" valign=\\\"top\\\" style=\\\"width: 140px;\\\"\\u003e\\n \\u003cp\\u003e\\u003cstrong\\u003eComplexity of\\u0026nbsp;\\u003cbr\\u003e\\u0026nbsp;Psychiatric Care\\u003c/strong\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 421px;\\\"\\u003e\\n \\u003cp\\u003eCPC1. The psychiatric care process is too complex for an OMABS to be effective.\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 80px;\\\"\\u003e\\n \\u003cp\\u003e\\u003cstrong\\u003e0.80\\u003c/strong\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 421px;\\\"\\u003e\\n \\u003cp\\u003eCPC2. Managing psychiatric patients requires flexible scheduling that OMABS may not provide.\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 80px;\\\"\\u003e\\n \\u003cp\\u003e\\u0026nbsp;\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 421px;\\\"\\u003e\\n \\u003cp\\u003eCPC3. Many psychiatric patients may struggle to use an OMABS due to cognitive, emotional, or technological barriers.\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 80px;\\\"\\u003e\\n \\u003cp\\u003e\\u0026nbsp;\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 421px;\\\"\\u003e\\n \\u003cp\\u003eCPC4.The absence of direct human interaction in online scheduling concerns me.\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 80px;\\\"\\u003e\\n \\u003cp\\u003e\\u0026nbsp;\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd rowspan=\\\"2\\\" valign=\\\"top\\\" style=\\\"width: 140px;\\\"\\u003e\\n \\u003cp\\u003e\\u003cstrong\\u003ePerceived Security\\u003cbr\\u003e\\u0026nbsp;and Reliability\\u003c/strong\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 421px;\\\"\\u003e\\n \\u003cp\\u003ePSR1. I trust that the OMABS system will securely handle patient information.\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 80px;\\\"\\u003e\\n \\u003cp\\u003e\\u003cstrong\\u003e0.87\\u003c/strong\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 421px;\\\"\\u003e\\n \\u003cp\\u003ePSR. I believe that OMABS is reliable in managing patient appointments.\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 80px;\\\"\\u003e\\n \\u003cp\\u003e\\u0026nbsp;\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003c/tbody\\u003e\\n\\u003c/table\\u003e\\n\\u003cp\\u003e\\u003cstrong\\u003e\\u003cem\\u003eDemographic Characteristics of the Sample\\u0026nbsp;\\u003c/em\\u003e\\u003c/strong\\u003e\\u003c/p\\u003e\\n\\u003cp\\u003eThe questionnaire was administered to all 46 resident physicians specializing in mental health at the Psychiatry Department of the University Hospital in Morocco, ensuring full coverage of the target population. Table 2 summarizes the demographic characteristics of the participants, including age, gender, and their prior use of OMABS in both personal and professional contexts.\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cstrong\\u003eTable 2. Sample Characteristics (n=46).\\u003c/strong\\u003e\\u003c/p\\u003e\\n\\u003ctable border=\\\"0\\\" cellspacing=\\\"0\\\" cellpadding=\\\"0\\\" width=\\\"645\\\"\\u003e\\n \\u003ctbody\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 417px;\\\"\\u003e\\n \\u003cp\\u003e\\u003cstrong\\u003eVariables\\u003c/strong\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 228px;\\\"\\u003e\\n \\u003cp\\u003e\\u003cstrong\\u003en (%)\\u003c/strong\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 417px;\\\"\\u003e\\n \\u003cp\\u003e\\u003cstrong\\u003eAge (years)\\u003c/strong\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 228px;\\\"\\u003e\\u003cbr\\u003e\\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 417px;\\\"\\u003e\\n \\u003cp\\u003e\\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp;\\u0026le; 30\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 228px;\\\"\\u003e\\n \\u003cp\\u003e31 (67.39)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 417px;\\\"\\u003e\\n \\u003cp\\u003e\\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026gt; 30\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 228px;\\\"\\u003e\\n \\u003cp\\u003e15 (32.61)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 417px;\\\"\\u003e\\n \\u003cp\\u003e\\u003cstrong\\u003eGender\\u003c/strong\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 228px;\\\"\\u003e\\u003cbr\\u003e\\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 417px;\\\"\\u003e\\n \\u003cp\\u003e\\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp;Female\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 228px;\\\"\\u003e\\n \\u003cp\\u003e40 (86.96)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 417px;\\\"\\u003e\\n \\u003cp\\u003e\\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp;Male\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 228px;\\\"\\u003e\\n \\u003cp\\u003e6 (13.9)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 417px;\\\"\\u003e\\n \\u003cp\\u003e\\u003cstrong\\u003eResidency Year\\u003c/strong\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 228px;\\\"\\u003e\\n \\u003cp\\u003e\\u0026nbsp;\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 417px;\\\"\\u003e\\n \\u003cp\\u003e1st Year\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 228px;\\\"\\u003e\\n \\u003cp\\u003e2 (4.35)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 417px;\\\"\\u003e\\n \\u003cp\\u003e2nd Year\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 228px;\\\"\\u003e\\n \\u003cp\\u003e14 (30.43\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 417px;\\\"\\u003e\\n \\u003cp\\u003e3rd Year\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 228px;\\\"\\u003e\\n \\u003cp\\u003e9 (19.57)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 417px;\\\"\\u003e\\n \\u003cp\\u003e4th Year\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 228px;\\\"\\u003e\\n \\u003cp\\u003e21 (45.65)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 417px;\\\"\\u003e\\n \\u003cp\\u003e\\u003cstrong\\u003ePrevious use of OMABS in a professional context\\u003c/strong\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 228px;\\\"\\u003e\\n \\u003cp\\u003e2 (4.35)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 417px;\\\"\\u003e\\n \\u003cp\\u003e\\u003cstrong\\u003eReported Frequency of Use\\u003c/strong\\u003e\\u003c/p\\u003e\\n \\u003cul\\u003e\\n \\u003cli\\u003eRarely\\u003c/li\\u003e\\n \\u003c/ul\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 228px;\\\"\\u003e\\n \\u003cp\\u003e\\u0026nbsp;\\u003c/p\\u003e\\n \\u003cp\\u003e2 (4.35)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 417px;\\\"\\u003e\\n \\u003cp\\u003e\\u003cstrong\\u003ePrevious use of OMABS in a personal context\\u003c/strong\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 228px;\\\"\\u003e\\n \\u003cp\\u003e2 (4.35)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 417px;\\\"\\u003e\\n \\u003cp\\u003e\\u003cstrong\\u003eReported Frequency of Use\\u003c/strong\\u003e\\u003c/p\\u003e\\n \\u003cul\\u003e\\n \\u003cli\\u003eRarely\\u003c/li\\u003e\\n \\u003c/ul\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 228px;\\\"\\u003e\\n \\u003cp\\u003e\\u0026nbsp;\\u003c/p\\u003e\\n \\u003cp\\u003e2 (4.35)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003c/tbody\\u003e\\n\\u003c/table\\u003e\\n\\u003cp\\u003eNote. All other response options of frequency of Use (\\u0026ldquo;never,\\u0026rdquo; \\u0026ldquo;sometimes,\\u0026rdquo; \\u0026ldquo;often,\\u0026rdquo; \\u0026ldquo;very often\\u0026rdquo;) received no responses.\\u003c/p\\u003e\\n\\u003cp\\u003eDescriptive statistics indicated that 86.96% of the respondents were female, 45.65% were in their 4th year of residency, and 67.39% were under 30 years of age, highlighting an active and relatively youthful group likely to be more receptive to technological advancements. However, only 4.35% reported prior use of the OMABS in both personal and professional contexts, with the frequency of use being rare.\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cstrong\\u003e\\u003cem\\u003ePerceptions of Using OMABS Among Resident Physicians\\u003c/em\\u003e\\u003c/strong\\u003e\\u003c/p\\u003e\\n\\u003cp\\u003eDescriptive statistics for each dimension of the study are reported in Table 3, offering an initial understanding of participants\\u0026apos; perceptions of the key variables associated with their intention to use OMABS. Since none of the variables followed a normal distribution, the median and interquartile range were calculated.\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cstrong\\u003eTable 3. Descriptive Analysis of the Variables.\\u003c/strong\\u003e\\u003c/p\\u003e\\n\\u003ctable border=\\\"0\\\" cellspacing=\\\"0\\\" cellpadding=\\\"0\\\" width=\\\"624\\\"\\u003e\\n \\u003ctbody\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 217px;\\\"\\u003e\\n \\u003cp\\u003e\\u003cstrong\\u003eVariables\\u003c/strong\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 198px;\\\"\\u003e\\n \\u003cp\\u003e\\u003cstrong\\u003eMedian\\u003c/strong\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 208px;\\\"\\u003e\\n \\u003cp\\u003e\\u003cstrong\\u003eIQR\\u003c/strong\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 217px;\\\"\\u003e\\n \\u003cp\\u003e\\u003cstrong\\u003eUI\\u003c/strong\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 198px;\\\"\\u003e\\n \\u003cp\\u003e4\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 208px;\\\"\\u003e\\n \\u003cp\\u003e1.37\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 217px;\\\"\\u003e\\n \\u003cp\\u003e\\u003cstrong\\u003ePU\\u003c/strong\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 198px;\\\"\\u003e\\n \\u003cp\\u003e3.75\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 208px;\\\"\\u003e\\n \\u003cp\\u003e0.75\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 217px;\\\"\\u003e\\n \\u003cp\\u003e\\u003cstrong\\u003ePEOU\\u003c/strong\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 198px;\\\"\\u003e\\n \\u003cp\\u003e3.33\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 208px;\\\"\\u003e\\n \\u003cp\\u003e1.25\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 217px;\\\"\\u003e\\n \\u003cp\\u003e\\u003cstrong\\u003eSI\\u003c/strong\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 198px;\\\"\\u003e\\n \\u003cp\\u003e3\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 208px;\\\"\\u003e\\n \\u003cp\\u003e0.87\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 217px;\\\"\\u003e\\n \\u003cp\\u003e\\u003cstrong\\u003ePWTC\\u003c/strong\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 198px;\\\"\\u003e\\n \\u003cp\\u003e4\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 208px;\\\"\\u003e\\n \\u003cp\\u003e0.75\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 217px;\\\"\\u003e\\n \\u003cp\\u003e\\u003cstrong\\u003ePAMC\\u003c/strong\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 198px;\\\"\\u003e\\n \\u003cp\\u003e2\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 208px;\\\"\\u003e\\n \\u003cp\\u003e0.5\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 217px;\\\"\\u003e\\n \\u003cp\\u003e\\u003cstrong\\u003ePIS\\u003c/strong\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 198px;\\\"\\u003e\\n \\u003cp\\u003e3\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 208px;\\\"\\u003e\\n \\u003cp\\u003e1.75\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 217px;\\\"\\u003e\\n \\u003cp\\u003e\\u003cstrong\\u003eMCS\\u003c/strong\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 198px;\\\"\\u003e\\n \\u003cp\\u003e2\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 208px;\\\"\\u003e\\n \\u003cp\\u003e0.5\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 217px;\\\"\\u003e\\n \\u003cp\\u003e\\u003cstrong\\u003eCPC\\u003c/strong\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 198px;\\\"\\u003e\\n \\u003cp\\u003e4.25\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 208px;\\\"\\u003e\\n \\u003cp\\u003e0.25\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 217px;\\\"\\u003e\\n \\u003cp\\u003e\\u003cstrong\\u003ePSR\\u003c/strong\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 198px;\\\"\\u003e\\n \\u003cp\\u003e3.5\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 208px;\\\"\\u003e\\n \\u003cp\\u003e1\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003c/tbody\\u003e\\n\\u003c/table\\u003e\\n\\u003cp\\u003eUI = Use Intention, PU = Perceived Usefulness, PEOU = Perceived Ease of Use, SI = Social Influence, PWTC = Perceived Workload and Time Constraints,\\u0026nbsp;PAMC = Perceived\\u0026nbsp;Autonomy in Managing Consultations,\\u0026nbsp;PIS = Perceived\\u0026nbsp;Institutional Support, MCS = Medical Curriculum Support, CPC = Complexity of Psychiatric Care,\\u0026nbsp;PSR =\\u0026nbsp;Perceived Security and Reliability.\\u003c/p\\u003e\\n\\u003cp\\u003eResident physicians expressed a general positive intention toward using OMABS (Median = 4, IQR = 1.37). Perceived usefulness (3.75), perceived ease of use (3.33), and perceived security and reliability (3.5) were rated as moderate, indicating an appreciation for the potential usefulness of OMABS, its relative ease of use, and its ability to ensure data protection and operational reliability. The median score for social influence and institutional support indicates neutral perceptions regarding peer or institutional encouragement to use OMABS. In contrast, the contextual factors of residency training and psychiatric care, including heavy workload and time constraints, low autonomy in managing consultations, limited institutional support, inherent complexity of psychiatric care, and insufficient integration of technology into the medical curriculum, were perceived as barriers to the use of OMABS.\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cstrong\\u003e\\u003cem\\u003eDifferences in Perceptions of Using OMABS Across Residency Years\\u003c/em\\u003e\\u003c/strong\\u003e\\u003c/p\\u003e\\n\\u003cp\\u003eTable 4 summarizes the test values derived from Kruskal-Wallis\\u0026rsquo;s test, its associated p-values, and the effect sizes. Each row corresponds to one of the measured variables, exploring differences in resident physicians\\u0026apos; perceptions of OMABS across residency years.\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cstrong\\u003eTable 4. Variations in Perceptions of OMABS Across Residency Years.\\u003c/strong\\u003e\\u003c/p\\u003e\\n\\u003ctable border=\\\"0\\\" cellspacing=\\\"0\\\" cellpadding=\\\"0\\\" width=\\\"624\\\"\\u003e\\n \\u003ctbody\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 180px;\\\"\\u003e\\n \\u003cp\\u003e\\u003cstrong\\u003eVariables\\u003c/strong\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 142px;\\\"\\u003e\\n \\u003cp\\u003e\\u003cstrong\\u003e\\u0026chi;\\u0026sup2;\\u003c/strong\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 151px;\\\"\\u003e\\n \\u003cp\\u003e\\u003cstrong\\u003ep-value\\u003c/strong\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 151px;\\\"\\u003e\\n \\u003cp\\u003e\\u003cstrong\\u003e\\u0026epsilon;\\u0026sup2;\\u003c/strong\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 180px;\\\"\\u003e\\n \\u003cp\\u003e\\u003cstrong\\u003eUI\\u003c/strong\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 142px;\\\"\\u003e\\n \\u003cp\\u003e8.981\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 151px;\\\"\\u003e\\n \\u003cp\\u003e0.03*\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 151px;\\\"\\u003e\\n \\u003cp\\u003e0.1996\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 180px;\\\"\\u003e\\n \\u003cp\\u003e\\u003cstrong\\u003ePU\\u003c/strong\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 142px;\\\"\\u003e\\n \\u003cp\\u003e6.734\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 151px;\\\"\\u003e\\n \\u003cp\\u003e0.081\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 151px;\\\"\\u003e\\n \\u003cp\\u003e0.1496\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 180px;\\\"\\u003e\\n \\u003cp\\u003e\\u003cstrong\\u003ePEOU\\u003c/strong\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 142px;\\\"\\u003e\\n \\u003cp\\u003e2.090\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 151px;\\\"\\u003e\\n \\u003cp\\u003e0.554\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 151px;\\\"\\u003e\\n \\u003cp\\u003e0.0464\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 180px;\\\"\\u003e\\n \\u003cp\\u003e\\u003cstrong\\u003eSI\\u003c/strong\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 142px;\\\"\\u003e\\n \\u003cp\\u003e18.698\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 151px;\\\"\\u003e\\n \\u003cp\\u003e\\u0026lt;\\u0026thinsp;.001**\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 151px;\\\"\\u003e\\n \\u003cp\\u003e0.4155\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 180px;\\\"\\u003e\\n \\u003cp\\u003e\\u003cstrong\\u003ePWTC\\u003c/strong\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 142px;\\\"\\u003e\\n \\u003cp\\u003e6.183\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 151px;\\\"\\u003e\\n \\u003cp\\u003e0.103\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 151px;\\\"\\u003e\\n \\u003cp\\u003e0.1374\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 180px;\\\"\\u003e\\n \\u003cp\\u003e\\u003cstrong\\u003ePAMC\\u003c/strong\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 142px;\\\"\\u003e\\n \\u003cp\\u003e4.061\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 151px;\\\"\\u003e\\n \\u003cp\\u003e0.255\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 151px;\\\"\\u003e\\n \\u003cp\\u003e0.0902\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 180px;\\\"\\u003e\\n \\u003cp\\u003e\\u003cstrong\\u003ePIS\\u003c/strong\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 142px;\\\"\\u003e\\n \\u003cp\\u003e0.864\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 151px;\\\"\\u003e\\n \\u003cp\\u003e0.834\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 151px;\\\"\\u003e\\n \\u003cp\\u003e0.0192\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 180px;\\\"\\u003e\\n \\u003cp\\u003e\\u003cstrong\\u003eMCS\\u003c/strong\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 142px;\\\"\\u003e\\n \\u003cp\\u003e12.243\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 151px;\\\"\\u003e\\n \\u003cp\\u003e0.007**\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 151px;\\\"\\u003e\\n \\u003cp\\u003e0.2721\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 180px;\\\"\\u003e\\n \\u003cp\\u003e\\u003cstrong\\u003eCPC\\u003c/strong\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 142px;\\\"\\u003e\\n \\u003cp\\u003e9.744\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 151px;\\\"\\u003e\\n \\u003cp\\u003e0.02*\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 151px;\\\"\\u003e\\n \\u003cp\\u003e0.2165\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 180px;\\\"\\u003e\\n \\u003cp\\u003e\\u003cstrong\\u003ePSR\\u003c/strong\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 142px;\\\"\\u003e\\n \\u003cp\\u003e5.536\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 151px;\\\"\\u003e\\n \\u003cp\\u003e0.136\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 151px;\\\"\\u003e\\n \\u003cp\\u003e0.1230\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003c/tbody\\u003e\\n\\u003c/table\\u003e\\n\\u003cp\\u003e*Significant at p \\u0026lt; 0.05\\u003cbr\\u003e\\u0026nbsp;**Significant at p \\u0026lt; 0.01\\u0026nbsp;\\u003c/p\\u003e\\n\\u003cp\\u003eFour constructs were found to differ significantly across residency years according to the Kruskal\\u0026ndash;Wallis\\u0026rsquo;s test: use intention (p =.030, \\u0026epsilon;\\u0026sup2; = 0.20), social influence (p \\u0026lt;.001, \\u0026epsilon;\\u0026sup2; = 0.42), medical curriculum support (p =.007, \\u0026epsilon;\\u0026sup2; = 0.27), and complexity of psychiatric care (p =.020, \\u0026epsilon;\\u0026sup2; = 0.22). All were associated with medium to large effect sizes, suggesting that a significant amount of the variation in these perceptions can be attributed to the residency year.\\u003c/p\\u003e\\n\\u003cp\\u003eIn contrast, despite their moderate effect sizes, perceived usefulness, perceived workload, and time constraints, perceived autonomy in managing consultations, and perceived security and reliability did not vary significantly by residency year, suggesting possible underlying differences that require more investigation.\\u0026nbsp;\\u003c/p\\u003e\\n\\u003cp\\u003eFinally, negligible effect sizes and no significant variation were observed for perceived ease of use and perceived institutional support, suggesting consistent perceptions toward these two constructs across all residency years.\\u003c/p\\u003e\\n\\u003cp\\u003eTo further investigate the significant differences identified by Kruskal-Wallis\\u0026rsquo;s test, the DSCF pairwise comparison test was conducted. The DSCF test revealed significant differences in social influence, medical curriculum support, and complexity of psychiatric care across residency year groups. Table 5 outlines the main results.\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cstrong\\u003eTable 5. Comparison of Perceptions Across Residency Years for Key Variables.\\u003c/strong\\u003e\\u003c/p\\u003e\\n\\u003ctable border=\\\"0\\\" cellspacing=\\\"0\\\" cellpadding=\\\"0\\\" width=\\\"645\\\"\\u003e\\n \\u003ctbody\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 173px;\\\"\\u003e\\n \\u003cp\\u003e\\u003cstrong\\u003eVariable\\u003c/strong\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 192px;\\\"\\u003e\\n \\u003cp\\u003e\\u003cstrong\\u003eGroup Comparison\\u003c/strong\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 135px;\\\"\\u003e\\n \\u003cp\\u003e\\u003cstrong\\u003eW (Test value)\\u003c/strong\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 144px;\\\"\\u003e\\n \\u003cp\\u003e\\u003cstrong\\u003ep-value\\u003c/strong\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd rowspan=\\\"6\\\" valign=\\\"top\\\" style=\\\"width: 173px;\\\"\\u003e\\n \\u003cp\\u003e\\u003cstrong\\u003eUI\\u003c/strong\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 192px;\\\"\\u003e\\n \\u003cp\\u003eYear 1 vs. Year 2\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 135px;\\\"\\u003e\\n \\u003cp\\u003e3.02\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 144px;\\\"\\u003e\\n \\u003cp\\u003e0.142\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 192px;\\\"\\u003e\\n \\u003cp\\u003eYear 1 vs. Year 3\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 135px;\\\"\\u003e\\n \\u003cp\\u003e0.00\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 144px;\\\"\\u003e\\n \\u003cp\\u003e1.000\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 192px;\\\"\\u003e\\n \\u003cp\\u003eYear 1 vs. Year 4\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 135px;\\\"\\u003e\\n \\u003cp\\u003e2.27\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 144px;\\\"\\u003e\\n \\u003cp\\u003e0.377\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 192px;\\\"\\u003e\\n \\u003cp\\u003eYear 2 vs. Year 3\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 135px;\\\"\\u003e\\n \\u003cp\\u003e-3.29\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 144px;\\\"\\u003e\\n \\u003cp\\u003e0.092\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 192px;\\\"\\u003e\\n \\u003cp\\u003eYear 2 vs. Year 4\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 135px;\\\"\\u003e\\n \\u003cp\\u003e-1.70\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 144px;\\\"\\u003e\\n \\u003cp\\u003e0.624\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 192px;\\\"\\u003e\\n \\u003cp\\u003eYear 3 vs. Year 4\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 135px;\\\"\\u003e\\n \\u003cp\\u003e2.66\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 144px;\\\"\\u003e\\n \\u003cp\\u003e0.237\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd rowspan=\\\"2\\\" valign=\\\"top\\\" style=\\\"width: 173px;\\\"\\u003e\\n \\u003cp\\u003e\\u003cstrong\\u003eSI\\u003c/strong\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 192px;\\\"\\u003e\\n \\u003cp\\u003eYear 2 vs. Year 3\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 135px;\\\"\\u003e\\n \\u003cp\\u003e-5.619\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 144px;\\\"\\u003e\\n \\u003cp\\u003e\\u0026lt;\\u0026thinsp;.001**\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 192px;\\\"\\u003e\\n \\u003cp\\u003eYear 3 vs. Year 4\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 135px;\\\"\\u003e\\n \\u003cp\\u003e5.185\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 144px;\\\"\\u003e\\n \\u003cp\\u003e0.001**\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 173px;\\\"\\u003e\\n \\u003cp\\u003e\\u003cstrong\\u003eMCS\\u003c/strong\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 192px;\\\"\\u003e\\n \\u003cp\\u003eYear 2 vs. Year 4\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 135px;\\\"\\u003e\\n \\u003cp\\u003e-4.15\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 144px;\\\"\\u003e\\n \\u003cp\\u003e0.018*\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 173px;\\\"\\u003e\\n \\u003cp\\u003e\\u003cstrong\\u003eCPC\\u003c/strong\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 192px;\\\"\\u003e\\n \\u003cp\\u003eYear 3 vs. Year 4\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 135px;\\\"\\u003e\\n \\u003cp\\u003e-39.404\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 144px;\\\"\\u003e\\n \\u003cp\\u003e0.027*\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003c/tbody\\u003e\\n\\u003c/table\\u003e\\n\\u003cp\\u003e*Significant at p \\u0026lt; 0.05\\u003cbr\\u003e\\u0026nbsp;**Significant at p \\u0026lt; 0.01\\u0026nbsp;\\u003c/p\\u003e\\n\\u003cp\\u003eThe analysis reported significant variations in perceptions across residency years regarding the use of OMABS. Although perceptions of use intention differed significantly overall (\\u0026chi;\\u0026sup2; = 8.981, p = 0.03), the pairwise DSCF comparisons did not identify statistically significant differences between specific year groups (p \\u0026gt; 0.05). In contrast, perceptions of peer influence toward using OMABS vary significantly during the residency years, particularly around the third year. A significant difference also emerged between the second and fourth years of residency (p = 0.018) regarding the perceived support of the medical curriculum toward using digital health tools; these perceptions differed particularly at later training years. Finally, fourth-year residents perceived the complexity of psychiatric care differently, as outlined by the significant difference observed between the third and fourth years of residency (p = 0.027).\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cstrong\\u003e\\u003cem\\u003eCorrelation analysis\\u003c/em\\u003e\\u003c/strong\\u003e\\u003c/p\\u003e\\n\\u003cp\\u003eSpearman correlation analysis was conducted to test the proposed hypotheses. The findings supported only three of the hypotheses, while the remaining were not supported. Table 6 presents a summary of the findings.\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cstrong\\u003eTable 6. Hypothesis results.\\u003c/strong\\u003e\\u003c/p\\u003e\\n\\u003ctable border=\\\"0\\\" cellspacing=\\\"0\\\" cellpadding=\\\"0\\\" width=\\\"635\\\"\\u003e\\n \\u003ctbody\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 244px;\\\"\\u003e\\n \\u003cp\\u003e\\u003cstrong\\u003eVariables\\u003c/strong\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 98px;\\\"\\u003e\\n \\u003cp\\u003e\\u003cstrong\\u003eHypothesis\\u003c/strong\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 78px;\\\"\\u003e\\n \\u003cp\\u003e\\u003cstrong\\u003erho\\u003c/strong\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 88px;\\\"\\u003e\\n \\u003cp\\u003e\\u003cstrong\\u003ep-value\\u003c/strong\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 127px;\\\"\\u003e\\n \\u003cp\\u003e\\u003cstrong\\u003eDecision\\u003c/strong\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 244px;\\\"\\u003e\\n \\u003cp\\u003e\\u003cstrong\\u003ePU vs UI\\u003c/strong\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 98px;\\\"\\u003e\\n \\u003cp\\u003eH1\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 78px;\\\"\\u003e\\n \\u003cp\\u003e0.536\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 88px;\\\"\\u003e\\n \\u003cp\\u003e\\u003cstrong\\u003e\\u0026lt;\\u0026thinsp;.001**\\u003c/strong\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 127px;\\\"\\u003e\\n \\u003cp\\u003e\\u003cstrong\\u003eSupported\\u003c/strong\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 244px;\\\"\\u003e\\n \\u003cp\\u003e\\u003cstrong\\u003ePEU vs UI\\u003c/strong\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 98px;\\\"\\u003e\\n \\u003cp\\u003eH2\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 78px;\\\"\\u003e\\n \\u003cp\\u003e0.143\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 88px;\\\"\\u003e\\n \\u003cp\\u003e0.344\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 127px;\\\"\\u003e\\n \\u003cp\\u003eNot supported\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 244px;\\\"\\u003e\\n \\u003cp\\u003e\\u003cstrong\\u003eSI vs UI\\u003c/strong\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 98px;\\\"\\u003e\\n \\u003cp\\u003eH3\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 78px;\\\"\\u003e\\n \\u003cp\\u003e0.213\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 88px;\\\"\\u003e\\n \\u003cp\\u003e0.155\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 127px;\\\"\\u003e\\n \\u003cp\\u003eNot supported\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 244px;\\\"\\u003e\\n \\u003cp\\u003e\\u003cstrong\\u003ePWTA vs UI\\u003c/strong\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 98px;\\\"\\u003e\\n \\u003cp\\u003eH4\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 78px;\\\"\\u003e\\n \\u003cp\\u003e0.860\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 88px;\\\"\\u003e\\n \\u003cp\\u003e\\u003cstrong\\u003e\\u0026lt;\\u0026thinsp;.001**\\u003c/strong\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 127px;\\\"\\u003e\\n \\u003cp\\u003eNot Supported\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 244px;\\\"\\u003e\\n \\u003cp\\u003e\\u003cstrong\\u003ePAMC vs UI\\u003c/strong\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 98px;\\\"\\u003e\\n \\u003cp\\u003eH5\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 78px;\\\"\\u003e\\n \\u003cp\\u003e-0.082\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 88px;\\\"\\u003e\\n \\u003cp\\u003e0.587\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 127px;\\\"\\u003e\\n \\u003cp\\u003eNot supported\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 244px;\\\"\\u003e\\n \\u003cp\\u003e\\u003cstrong\\u003ePIS vs UI\\u003c/strong\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 98px;\\\"\\u003e\\n \\u003cp\\u003eH6\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 78px;\\\"\\u003e\\n \\u003cp\\u003e-0.273\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 88px;\\\"\\u003e\\n \\u003cp\\u003e0.066\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 127px;\\\"\\u003e\\n \\u003cp\\u003eNot supported\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 244px;\\\"\\u003e\\n \\u003cp\\u003e\\u003cstrong\\u003eMC vs UI\\u003c/strong\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 98px;\\\"\\u003e\\n \\u003cp\\u003eH7\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 78px;\\\"\\u003e\\n \\u003cp\\u003e0.041\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 88px;\\\"\\u003e\\n \\u003cp\\u003e0.787\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 127px;\\\"\\u003e\\n \\u003cp\\u003eNot supported\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 244px;\\\"\\u003e\\n \\u003cp\\u003e\\u003cstrong\\u003eCPC vs UI\\u003c/strong\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 98px;\\\"\\u003e\\n \\u003cp\\u003eH8\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 78px;\\\"\\u003e\\n \\u003cp\\u003e-0.083\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 88px;\\\"\\u003e\\n \\u003cp\\u003e0.585\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 127px;\\\"\\u003e\\n \\u003cp\\u003eNot supported\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 244px;\\\"\\u003e\\n \\u003cp\\u003e\\u003cstrong\\u003ePSR vs UI\\u003c/strong\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 98px;\\\"\\u003e\\n \\u003cp\\u003eH9\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 78px;\\\"\\u003e\\n \\u003cp\\u003e0.557\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 88px;\\\"\\u003e\\n \\u003cp\\u003e\\u003cstrong\\u003e\\u0026lt;\\u0026thinsp;.001**\\u003c/strong\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 127px;\\\"\\u003e\\n \\u003cp\\u003e\\u003cstrong\\u003eSupported\\u003c/strong\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 244px;\\\"\\u003e\\n \\u003cp\\u003e\\u003cstrong\\u003ePU*Residency year vs UI\\u003c/strong\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 98px;\\\"\\u003e\\n \\u003cp\\u003eH10\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 78px;\\\"\\u003e\\n \\u003cp\\u003e0.175\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 88px;\\\"\\u003e\\n \\u003cp\\u003e0.245\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 127px;\\\"\\u003e\\n \\u003cp\\u003eNot supported\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 244px;\\\"\\u003e\\n \\u003cp\\u003e\\u003cstrong\\u003ePEU*Residency year vs UI\\u003c/strong\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 98px;\\\"\\u003e\\n \\u003cp\\u003eH11\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 78px;\\\"\\u003e\\n \\u003cp\\u003e0.040\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 88px;\\\"\\u003e\\n \\u003cp\\u003e0.793\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 127px;\\\"\\u003e\\n \\u003cp\\u003eNot supported\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 244px;\\\"\\u003e\\n \\u003cp\\u003e\\u003cstrong\\u003eSI*Residency year vs UI\\u003c/strong\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 98px;\\\"\\u003e\\n \\u003cp\\u003eH12\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 78px;\\\"\\u003e\\n \\u003cp\\u003e0.079\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 88px;\\\"\\u003e\\n \\u003cp\\u003e0.601\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 127px;\\\"\\u003e\\n \\u003cp\\u003eNot supported\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 244px;\\\"\\u003e\\n \\u003cp\\u003e\\u003cstrong\\u003ePWTA*Residency year vs UI\\u003c/strong\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 98px;\\\"\\u003e\\n \\u003cp\\u003eH13\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 78px;\\\"\\u003e\\n \\u003cp\\u003e0.343\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 88px;\\\"\\u003e\\n \\u003cp\\u003e\\u003cstrong\\u003e0.020*\\u003c/strong\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 127px;\\\"\\u003e\\n \\u003cp\\u003e\\u003cstrong\\u003eSupported\\u003c/strong\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 244px;\\\"\\u003e\\n \\u003cp\\u003e\\u003cstrong\\u003ePAMC*Residency year vs UI\\u003c/strong\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 98px;\\\"\\u003e\\n \\u003cp\\u003eH14\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 78px;\\\"\\u003e\\n \\u003cp\\u003e-0.077\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 88px;\\\"\\u003e\\n \\u003cp\\u003e0.611\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 127px;\\\"\\u003e\\n \\u003cp\\u003eNot supported\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 244px;\\\"\\u003e\\n \\u003cp\\u003e\\u003cstrong\\u003ePIS*Residency year vs UI\\u003c/strong\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 98px;\\\"\\u003e\\n \\u003cp\\u003eH15\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 78px;\\\"\\u003e\\n \\u003cp\\u003e-0.261\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 88px;\\\"\\u003e\\n \\u003cp\\u003e0.079\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 127px;\\\"\\u003e\\n \\u003cp\\u003eNot supported\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 244px;\\\"\\u003e\\n \\u003cp\\u003e\\u003cstrong\\u003eMC*Residency year vs UI\\u003c/strong\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 98px;\\\"\\u003e\\n \\u003cp\\u003eH16\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 78px;\\\"\\u003e\\n \\u003cp\\u003e-0.077\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 88px;\\\"\\u003e\\n \\u003cp\\u003e0.612\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 127px;\\\"\\u003e\\n \\u003cp\\u003eNot supported\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 244px;\\\"\\u003e\\n \\u003cp\\u003e\\u003cstrong\\u003eCPC*Residency year vs UI\\u003c/strong\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 98px;\\\"\\u003e\\n \\u003cp\\u003eH17\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 78px;\\\"\\u003e\\n \\u003cp\\u003e-0.036\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 88px;\\\"\\u003e\\n \\u003cp\\u003e0.811\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 127px;\\\"\\u003e\\n \\u003cp\\u003eNot supported\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 244px;\\\"\\u003e\\n \\u003cp\\u003e\\u003cstrong\\u003ePSR*Residency year vs UI\\u003c/strong\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 98px;\\\"\\u003e\\n \\u003cp\\u003eH18\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 78px;\\\"\\u003e\\n \\u003cp\\u003e0.274\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 88px;\\\"\\u003e\\n \\u003cp\\u003e0.066\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 127px;\\\"\\u003e\\n \\u003cp\\u003eNot supported\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003c/tbody\\u003e\\n\\u003c/table\\u003e\\n\\u003cp\\u003e*Significant at p \\u0026lt; 0.05\\u003cbr\\u003e\\u0026nbsp;**Significant at p \\u0026lt; 0.01\\u0026nbsp;\\u003c/p\\u003e\\n\\u003cp\\u003eSurprisingly, a strong and statistically significant positive correlation was identified between perceived workload and time constraints and intention to use OMABS (\\u0026rho; = 0.860, p \\u0026lt; .001), which contradicts the hypothesis that higher perceived workload and time constraints are negatively associated with resident physicians\\u0026rsquo; intention to use OMABS. Moreover, both perceived usefulness (\\u0026rho; = 0.536, p \\u0026lt; 0.001) and perceived security and reliability (\\u0026rho; = 0.557, p \\u0026lt; 0.001) showed moderate to strong positive correlations with intention to use OMABS, which supports the hypotheses that perceived usefulness, security, and reliability are positively associated with the use intention of OMABS. Conversely, perceived ease of use, social influence, perceived institutional support, perceived autonomy in managing consultations, medical curriculum support, and the complexity of psychiatric care were not significantly correlated with the intention to use OMABS (p \\u0026gt; 0.05), which does not align with the initially proposed hypotheses.\\u0026nbsp;\\u003c/p\\u003e\\n\\u003cp\\u003eRegarding interaction terms between residency year and each variable, only one significant positive correlation was observed between the interaction term PWTA \\u0026times; residency year and the use intention of OMABS (\\u0026rho; = 0.343, p = 0.020), which support the hypothesis that residency year moderates the relationship between perceived workload and time constraints and resident physicians\\u0026rsquo; intention to use OMABS. The Other interaction terms were not statistically significant (p\\u0026gt;0.05) and therefore did not support the remaining hypotheses.\\u003c/p\\u003e\"},{\"header\":\"Discussion\",\"content\":\"\\u003cp\\u003eThis study, guided by the technology acceptance framework and enriched by constructs derived from resident physicians\\u0026apos; training context and the characteristics of the psychiatric care field, explored resident physicians\\u0026rsquo; perceptions and intentions regarding the use of OMABS in the mental healthcare settings. The results provided a comprehensive understanding of the nuances surrounding the perceptions and intentions toward using technology in this specialized healthcare setting.\\u0026nbsp;\\u003c/p\\u003e\\n\\u003cp\\u003eResident physicians, typically younger and assumed to be more receptive to new technology, were found to have limited familiarity with e-appointment services for either work-related or personal use. This lack of familiarity can be attributed to the traditional medical training curriculum, which often excludes exposure to digital health tools, despite the rapid evolution of healthcare delivery and practice. This proposal was supported by resident physicians, who pointed out the lack of integration of new technologies in their medical curriculum and training program. These findings underscore the urgent need to integrate digital health training into residency programs, as highlighted by previous studies\\u0026nbsp;[41,47\\u0026ndash;49]. Doing so will better prepare medical trainees to meet the growing technological demands of the healthcare industry, ensuring more effective and efficient responses to its evolving requirements.\\u003c/p\\u003e\\n\\u003cp\\u003eIn general, favorable perceptions toward the OMABS\\u0026apos; potential benefits, relative ease of use, and capacity to protect data and function reliably were expressed by resident physicians. In contrast, unfavorable perceptions were linked to contextual factors related to residency training and the complexity of psychiatric care. Factors like heavy workload and time constraints, low autonomy in managing consultations, the inherent complexity of psychiatric care, and insufficient integration of technology into the medical curriculum were cited as barriers. This reflects widespread concerns about contextual and structural barriers that can impede the acceptance and use of OMABS. These findings are consistent with prior research\\u0026nbsp;[17,50], indicating that physicians in training tend to have a favorable attitude toward the potential benefits of e-health services and acknowledge their value in improving patient care, but they often face contextual and structural barriers that limit their adoption and use.\\u003c/p\\u003e\\n\\u003cp\\u003eHowever, correlation analysis provided significant clarifications. Perceived autonomy in managing consultations, institutional support, medical curriculum support, and complexity of psychiatric care were not significantly associated with resident physicians\\u0026rsquo; intention to use OMABS. This suggests that, in clinical settings such as mental healthcare, even if contextual factors are perceived as barriers, they are not associated with intention to use e-health services. Such findings contradict some assumptions of the extended TAM and UTAUT models, which often regard contextual enablers as key determinants of technology adoption.\\u0026nbsp;\\u003c/p\\u003e\\n\\u003cp\\u003eThe intention could be more driven by other determinants, including perceived relevance, reliability, and time-saving benefits, rather than by contextual factors such as autonomy or curriculum design. It is also possible that resident physicians consider such barriers as an inherent characteristic of psychiatric care that technology cannot simplify, so it does not affect their intention to use OMABS.\\u0026nbsp;\\u003c/p\\u003e\\n\\u003cp\\u003eThis insight was confirmed by our correlation analysis between perceived usefulness and perceived security, and reliability and use intention of OMABS. \\u0026nbsp;It has revealed that perceived usefulness and perceived security and reliability correlated positively with resident physicians\\u0026rsquo; intention to use OMABS, aligning with prior studies\\u0026nbsp;[51\\u0026ndash;53]\\u0026nbsp;emphasizing the perceived usefulness of technology as a key determinant of technology acceptance and use and with studies\\u0026nbsp;[54\\u0026ndash;56]\\u0026nbsp;considering trust in security and reliability as a cornerstone of technology acceptance, particularly in healthcare, where concerns about data privacy and confidentiality are paramount.\\u003c/p\\u003e\\n\\u003cp\\u003eA particularly unexpected finding was the strong positive correlation between perceived workload and time constraints and intention to use OMABS. The analysis revealed that resident physicians experiencing greater workload and tighter schedules were more inclined to use OMABS, which contradicts the hypothesis that higher workload and time constraints are associated with low intention to use OMABS. \\u0026nbsp;This result suggests that residents who feel the greatest pressure are those who perceive OMABS as a useful and potentially time-saving tool that can help them ease their burden. This aligns with the study by Chen et al.\\u0026nbsp;[57], who reported that radiology residents in China intend to adopt digital tools when they perceive them as saving time and reducing cognitive load, even in high-pressure environments.\\u003c/p\\u003e\\n\\u003cp\\u003eConversely, perceived ease of use and social influence were not correlated with the intention to use OMABS. Although these determinants are commonly emphasized in the technology acceptance literature \\u0026nbsp;[13,58\\u0026ndash;60], their relatively neutral or moderate scores in this study suggest they may be less critical in the specific context of mental healthcare.\\u0026nbsp;\\u003c/p\\u003e\\n\\u003cp\\u003eThe observed variations in perceptions, particularly at later training stages, regarding medical curriculum support, use intention, social influence, and complexity of psychiatric care support the idea that resident physicians\\u0026apos; perceptions of e-health services such as OMABS varied dynamically during their training as their clinical exposure and assignments increased. They are founded more on exposure to curriculum, peer support, and direct experience than on usability testing or security analysis. This finding is in line with previous research\\u0026nbsp;[15], indicating that stage-specific experience shapes attitudes toward health technology acceptance and use. Therefore, intervention and training program design by year of residency could enhance the adoption of e-health services within psychiatric care.\\u0026nbsp;\\u003c/p\\u003e\\n\\u003cp\\u003eContrary to the effect of residency year on perceptions, the relationship between interaction terms and resident physicians\\u0026apos; intention to use OMABS was not statistically significant; there was a single significant positive correlation between the interaction term PWTC*residency year and use intention of OMABS. This would imply that the more workload and time pressure that resident physicians see themselves experiencing in their training, the more helpful OMABS is likely to be in managing their work.\\u0026nbsp;\\u003c/p\\u003e\\n\\u003cp\\u003eIn summary, this study\\u0026apos;s findings suggest that while resident physicians in mental healthcare settings recognize both the advantages and barriers associated with the use of OMABS, their intention to use e-health services is more associated with perceived operational benefits than with certain structural or contextual barriers.\\u0026nbsp;\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cstrong\\u003e\\u003cem\\u003eTheoretical and Practical Implications\\u003c/em\\u003e\\u003c/strong\\u003e\\u003c/p\\u003e\\n\\u003cp\\u003eThese findings carry significant theoretical and practical implications. From a practical perspective, findings may guide strategies for optimizing e-health services integration in high-pressure medical training settings. Follow-up implementation activities are required to focus on strengthening perceptions of efficiency and usefulness, along with filling integration gaps in training programs and clinical work processes. Equally important is the implementation of robust data protection measures to strengthen user trust, particularly in a field like mental healthcare, where confidentiality is paramount. Tailored training programs are essential to meet the specific needs of residents at different stages of their medical training. Such programs should focus on equipping residents with the skills and confidence necessary to effectively use the system, ensuring that they feel supported throughout their learning and professional growth.\\u003c/p\\u003e\\n\\u003cp\\u003eFrom a theoretical perspective, the study examined contextual factors, such as perceived workload and time constraints, curriculum design, and the complexity of psychiatric care, that are not commonly explored in traditional health technology acceptance models. It also reaffirms the importance of perceived usefulness as a central construct of the technology acceptance framework but does not support the common association between perceived ease of use, social influence and technology acceptance, suggesting that while the technology acceptance framework remains a robust tool for understanding use intention, the relevance of certain constructs may vary depending on the specific healthcare setting and user group. This insight underscores the need for continued refinement and contextualization of these theoretical models to better analyze the nuances of technology adoption in specialized fields like mental healthcare.\\u0026nbsp;\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cstrong\\u003e\\u003cem\\u003eStudy Limitations\\u0026nbsp;\\u003c/em\\u003e\\u003c/strong\\u003e\\u003c/p\\u003e\\n\\u003cp\\u003eThe limitations of this study constitute opportunities for future research. The study sample consisted of a small group of resident physicians from the University Hospital in Morocco. While this limited sample size may constrain the generalizability of the findings to broader populations, it is representative of the specific target population for this study and provides useful insights that apply to similar psychiatric settings. To enhance the robustness of the results, future studies should include resident physicians in psychiatry from other University hospitals across Morocco to be able to reach stronger findings that more accurately represent the perceptions and intentions to use e-health services from a wider variety of resident physicians.\\u0026nbsp;\\u003c/p\\u003e\\n\\u003cp\\u003eWhile the small sample size and reliance on correlational analysis\\u0026nbsp;limit the ability to establish causation, the findings still provide a useful starting point for specifying important associations. These could be validated through longitudinal studies, the inclusion of more representative samples, and the application of robust modeling techniques, such as regression analysis or structural equation modeling, to confirm the findings and further clarify the acceptance of e-health services among medical trainees in mental healthcare.\\u003c/p\\u003e\\n\\u003cp\\u003eSome of the constructs were measured by two items, which were adequate for this study\\u0026apos;s objectives. However, it is known that multi-item scales typically offer stronger evidence of construct validity and reliability. Hence, future research could overcome this limitation and thereby improve psychometric robustness by including more items to these constructs.\\u003c/p\\u003e\\n\\u003cp\\u003eSeveral key constructs, like perceived usefulness, workload and time constraints, autonomy in managing consultations, and security and reliability, were not significantly varying between residency years, even though the effect sizes were moderate. This may be due to the limited sample size, which may not have been sufficient to detect smaller variations, or to the limited sensitivity of the questionnaire items in capturing subtle differences. Further research with larger populations and more sensitive measures is required to better understand how these variables can vary across residency years.\\u003c/p\\u003e\\n\\u003cp\\u003eThe focus on specific contextual factors may have omitted other potentially relevant determinants, such as patient-related factors, including digital literacy, or broader policy influences, including national digital health strategies. Future research might investigate the influence of these constructs to identify which will have a considerable influence on the intention to use e-health services in mental healthcare settings.\\u0026nbsp;\\u003c/p\\u003e\\n\\u003cp\\u003eOur analysis revealed varied perceptions of using OMABS over the later residency year. It will be interesting to use more qualitative research methodologies, such as interviews or focus group discussions, to explore the critical role of residency years in influencing the adoption of e-appointment services.\\u0026nbsp;\\u003c/p\\u003e\"},{\"header\":\"Conclusions\",\"content\":\"\\u003cp\\u003eThe findings provided by this study make an original contribution to the literature. The evidence provided by exploring resident physicians' perceptions and intentions to use e-health services within a niche but relevant setting of mental healthcare can inform future research and guide policy development and implementation of e-health services among medical trainees.\\u003c/p\\u003e\\u003cp\\u003eWhile several variables were hypothesized to affect use intention, a few demonstrated statistically significant associations. Notably, perceived workload and time constraints showed a strong positive correlation with intention to use OMABS, raising new questions about how pressure and digital openness interact in clinical environments. Perceived usefulness and perceived security, and reliability were moderately and positively correlated with the intention to use OMABS, as commonly demonstrated by technology acceptance models, confirming that functional benefits and system security beliefs are relevant factors of technology acceptance and use.\\u003c/p\\u003e\"},{\"header\":\"Declarations\",\"content\":\"\\u003cp\\u003e\\u003cstrong\\u003eEthics approval and consent to participate\\u003c/strong\\u003e\\u003c/p\\u003e\\n\\u003cp\\u003eThe study adhered to the principles outlined in the Declaration of Helsinki, the ethical guidelines of the Ethics Committee of Hassan II University in Morocco, and the Moroccan law No. 09-08 on personal data protection. The study was conducted using an anonymous and non-identifiable questionnaire. Participation was entirely voluntary, and no interventions were involved. No personal data that could identify participants was collected. All participants were informed of the study\\u0026apos;s objective and that the data collected would be used only for scientific research purposes. Informed consent was obtained from all participants before their involvement in the study.\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cstrong\\u003eConsent for publication\\u003c/strong\\u003e\\u003c/p\\u003e\\n\\u003cp\\u003eNot applicable.\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cstrong\\u003eCompeting interests\\u003c/strong\\u003e\\u003c/p\\u003e\\n\\u003cp\\u003eThe authors declare no competing interests.\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cstrong\\u003eFunding\\u003c/strong\\u003e\\u003c/p\\u003e\\n\\u003cp\\u003eNot applicable.\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cstrong\\u003eAvailability of data and materials\\u003c/strong\\u003e\\u003c/p\\u003e\\n\\u003cp\\u003eData sets and output files of the data analysis are available from the authors on request.\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cstrong\\u003eAcknowledgements\\u003c/strong\\u003e\\u003c/p\\u003e\\n\\u003cp\\u003eSpecial thanks to the staff of the Psychiatry Department of the University Hospital in Casablanca, Morocco.\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cstrong\\u003eAuthors\\u0026rsquo; information\\u003c/strong\\u003e\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cem\\u003eAuthors and Affiliations\\u003c/em\\u003e\\u003c/p\\u003e\\n\\u003cp\\u003eClinical Neurosciences and Mental Health Laboratory, Faculty of Medicine and Pharmacy, Hassan II University, Casablanca, Morocco;\\u003c/p\\u003e\\n\\u003cp\\u003eLoubna Khalil, Zineb Serhier, Manar Jallal, Mohammed Bennani Othmani\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cstrong\\u003eAuthors\\u0026rsquo; Contributions\\u003c/strong\\u003e\\u003c/p\\u003e\\n\\u003cp\\u003eThe authorship and contributions of each author to this manuscript are as follows:\\u003c/p\\u003e\\n\\u003col\\u003e\\n \\u003cli\\u003e\\u003cstrong\\u003eLK\\u003c/strong\\u003e: Conceptualization, Methodology, Analysis and interpretation of data, Writing original draft;\\u003c/li\\u003e\\n \\u003cli\\u003e\\u003cstrong\\u003eZS\\u003c/strong\\u003e: Supervision, Validation, review, and Editing;\\u003c/li\\u003e\\n \\u003cli\\u003e\\u003cstrong\\u003eMJ\\u003c/strong\\u003e Methodology, Revising and Validation;\\u003c/li\\u003e\\n \\u003cli\\u003e\\u003cstrong\\u003eMBO\\u003c/strong\\u003e: Validation, Review, and Editing.\\u003c/li\\u003e\\n\\u003c/ol\\u003e\\n\\u003cp\\u003eAll authors read and approved the final manuscript.\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cem\\u003eCorresponding author\\u003c/em\\u003e\\u003c/p\\u003e\\n\\u003cp\\u003eE-mail address: loubna12@gmail.com\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cstrong\\u003eDeclaration of generative AI and AI-assisted technologies in the writing process.\\u003c/strong\\u003e\\u003c/p\\u003e\\n\\u003cp\\u003eDuring the preparation of this work, the author(s) used Grammarly (V.1.2.116.1536) in order to correct grammatical errors and improve the readability and language of the manuscript. After using this tool, the author(s) reviewed and edited the content as needed and take(s) full responsibility for the content of the published article.\\u003c/p\\u003e\"},{\"header\":\"References\",\"content\":\"\\u003col\\u003e\\n\\u003cli\\u003ePaul M, Maglaras L, Ferrag MA, Almomani I. Digitization of healthcare sector: A study on privacy and security concerns. ICT Express. 2023 Aug 1;9(4):571\\u0026ndash;88. \\u003c/li\\u003e\\n\\u003cli\\u003eKitsios F, Stefanakakis S, Kamariotou M, Dermentzoglou L. E-service Evaluation: User satisfaction measurement and implications in health sector. Comput Stand Interfaces. 2019 Mar;63:16\\u0026ndash;26. \\u003c/li\\u003e\\n\\u003cli\\u003eZhang X, Yu P, Yan J, Spil ITAM. Using diffusion of innovation theory to understand the factors impacting patient acceptance and use of consumer e-health innovations: a case study in a primary care clinic. 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Healthcare. 2024 Jan;12(15):1531. \\u003c/li\\u003e\\n\\u003cli\\u003eKhalil L, Serhier Z, Bennani Othmani M. Exploring Patients\\u0026rsquo; Acceptance of Mental Health E-services in Morocco: A Quantitative Approach. Cureus [Internet]. 2024 Dec 21 [cited 2025 Jan 5]; Available from: https://www.cureus.com/articles/321984-exploring-patients-acceptance-of-mental-health-e-services-in-morocco-a-quantitative-approach\\u003c/li\\u003e\\n\\u003cli\\u003eWu P, Zhang R, Luan J, Zhu M. Factors affecting physicians using mobile health applications: an empirical study. BMC Health Serv Res. 2022 Jan 4;22(1):24. \\u003c/li\\u003e\\n\\u003cli\\u003eHsieh PJ. Physicians\\u0026rsquo; acceptance of electronic medical records exchange: An extension of the decomposed TPB model with institutional trust and perceived risk. Int J Med Inf. 2015 Jan 1;84(1):1\\u0026ndash;14. \\u003c/li\\u003e\\n\\u003cli\\u003eArfi WB, Nasr IB, Kondrateva G, Hikkerova L. The role of trust in intention to use the IoT in eHealth: Application of the modified UTAUT in a consumer context. Technol Forecast Soc Change. 2021 Jun 1;167:120688. \\u003c/li\\u003e\\n\\u003cli\\u003eChen Y, Wu Z, Wang P, Xie L, Yan M, Jiang M, et al. Radiology Residents\\u0026rsquo; Perceptions of Artificial Intelligence: Nationwide Cross-Sectional Survey Study. J Med Internet Res. 2023 Oct 19;25(1):e48249. \\u003c/li\\u003e\\n\\u003cli\\u003eEngin M, G\\u0026uuml;rses F. Adoption of Hospital Information Systems in Public Hospitals in Turkey: An Analysis with the Unified Theory of Acceptance and Use of Technology Model. Int J Innov Technol Manag. 2019;16(6). \\u003c/li\\u003e\\n\\u003cli\\u003eDiel S, Doctor E, Reith R, Buck C, Eymann T. Examining supporting and constraining factors of physicians\\u0026rsquo; acceptance of telemedical online consultations: a survey study. BMC Health Serv Res. 2023;23(1). \\u003c/li\\u003e\\n\\u003cli\\u003eHossainNazmul, YokotaFumihiko, SultanaNazneen, AhmedAshir. Factors Influencing Rural End-Users\\u0026rsquo; Acceptance of e-Health in Developing Countries: A Study on Portable Health Clinic in Bangladesh. Telemed E-Health [Internet]. 2019 Mar 18 [cited 2024 Nov 24]; Available from: https://www.liebertpub.com/doi/10.1089/tmj.2018.0039\\u003c/li\\u003e\\n\\u003c/ol\\u003e\"}],\"fulltextSource\":\"\",\"fullText\":\"\",\"funders\":[],\"hasAdminPriorityOnWorkflow\":false,\"hasManuscriptDocX\":true,\"hasOptedInToPreprint\":true,\"hasPassedJournalQc\":\"\",\"hasAnyPriority\":false,\"hideJournal\":false,\"highlight\":\"\",\"institution\":\"\",\"isAcceptedByJournal\":false,\"isAuthorSuppliedPdf\":false,\"isDeskRejected\":\"\",\"isHiddenFromSearch\":false,\"isInQc\":false,\"isInWorkflow\":false,\"isPdf\":false,\"isPdfUpToDate\":true,\"isWithdrawnOrRetracted\":false,\"journal\":{\"display\":true,\"email\":\"info@researchsquare.com\",\"identity\":\"bmc-health-services-research\",\"isNatureJournal\":false,\"hasQc\":true,\"allowDirectSubmit\":false,\"externalIdentity\":\"bhsr\",\"sideBox\":\"Learn more about [BMC Health Services Research](http://bmchealthservres.biomedcentral.com/)\",\"snPcode\":\"\",\"submissionUrl\":\"https://www.editorialmanager.com/BHSR/default.aspx\",\"title\":\"BMC Health Services Research\",\"twitterHandle\":\"BMC_series\",\"acdcEnabled\":true,\"dfaEnabled\":false,\"editorialSystem\":\"em\",\"reportingPortfolio\":\"BMC Series\",\"inReviewEnabled\":true,\"inReviewRevisionsEnabled\":true},\"keywords\":\"correlation analysis, e-appointment system, e-services, mental health, Morocco, perceptions, resident physicians, technology acceptance, use intention\",\"lastPublishedDoi\":\"10.21203/rs.3.rs-7383021/v1\",\"lastPublishedDoiUrl\":\"https://doi.org/10.21203/rs.3.rs-7383021/v1\",\"license\":{\"name\":\"CC BY 4.0\",\"url\":\"https://creativecommons.org/licenses/by/4.0/\"},\"manuscriptAbstract\":\"\\u003cp\\u003e\\u003cstrong\\u003eBackground:\\u003c/strong\\u003e Despite growing interest in e-health acceptance, few studies have focused on the acceptance of e-health services, particularly among residents' physicians in mental healthcare settings. This study aims to explore perceptions and behavioral intentions toward the online medical appointment booking system (OMABS) among psychiatry residents in a Moroccan university hospital, focusing on how contextual factors influence their use intention.\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cstrong\\u003eMethods:\\u003c/strong\\u003e Based on factors related to residency training, the characteristics of psychiatric practice, and classic factors of technological acceptance models, a survey was conducted among all 46 psychiatry resident physicians. The small sample size is a result of the naturally limited population rather than a sampling decision. Differences in perceptions across residency years were analyzed using the Kruskal-Wallis test, while Spearman correlation assessed the relationship between independent variables and use intention. Additionally, residency year was tested as a moderating variable through the inclusion of interaction terms in the analysis.\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cstrong\\u003eResults:\\u003c/strong\\u003e Findings reported favorable perceptions of OMABS' usefulness, relative ease of use, data security, and reliability. However, these perceptions varied over the later residency year, becoming more influenced by curriculum exposure, peer support, and direct experience than by usability testing or security analysis.\\u003c/p\\u003e\\n\\u003cp\\u003eContextual factors, such as a heavy workload and time constraints, low autonomy in managing consultations, the inherent complexity of psychiatric care, and insufficient integration of technology into the medical curriculum, were perceived as barriers.\\u003c/p\\u003e\\n\\u003cp\\u003eCorrelation analysis indicated that perceived usefulness, security, and even perceived workload and time constraints were positively associated with use intention, whereas the other contextual factors were not significant.\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cstrong\\u003eConclusions:\\u003c/strong\\u003e To our knowledge, this is the first study exploring resident physicians’ acceptance of e-appointment services in psychiatric care within a developing country. The Findings reveal that residents' physicians' intention to use e-health services is more associated with perceived operational benefits than with contextual barriers. These insights may guide policy development and implementation of e-health among medical trainees.\\u003c/p\\u003e\",\"manuscriptTitle\":\"Perceptions and Intentions to Use E-Health Services in Mental Health Care Settings: A Case Study Among Resident Physicians\",\"msid\":\"\",\"msnumber\":\"\",\"nonDraftVersions\":[{\"code\":1,\"date\":\"2025-09-29 13:01:02\",\"doi\":\"10.21203/rs.3.rs-7383021/v1\",\"editorialEvents\":[{\"type\":\"communityComments\",\"content\":0},{\"type\":\"editorInvitedReview\",\"content\":\"\",\"date\":\"2025-10-09T02:51:41+00:00\",\"index\":\"hide\",\"fulltext\":\"\"},{\"type\":\"reviewerAgreed\",\"content\":\"124801368388614716887191940039687744452\",\"date\":\"2025-09-23T10:43:40+00:00\",\"index\":\"hide\",\"fulltext\":\"\"},{\"type\":\"reviewersInvited\",\"content\":\"\",\"date\":\"2025-09-18T05:24:57+00:00\",\"index\":\"\",\"fulltext\":\"\"},{\"type\":\"editorAssigned\",\"content\":\"\",\"date\":\"2025-09-16T04:26:55+00:00\",\"index\":\"\",\"fulltext\":\"\"},{\"type\":\"editorInvited\",\"content\":\"\",\"date\":\"2025-08-25T05:23:50+00:00\",\"index\":\"\",\"fulltext\":\"\"},{\"type\":\"checksComplete\",\"content\":\"\",\"date\":\"2025-08-23T16:57:16+00:00\",\"index\":\"\",\"fulltext\":\"\"},{\"type\":\"submitted\",\"content\":\"BMC Health Services Research\",\"date\":\"2025-08-23T16:53:57+00:00\",\"index\":\"\",\"fulltext\":\"\"}],\"status\":\"published\",\"journal\":{\"display\":true,\"email\":\"info@researchsquare.com\",\"identity\":\"bmc-health-services-research\",\"isNatureJournal\":false,\"hasQc\":true,\"allowDirectSubmit\":false,\"externalIdentity\":\"bhsr\",\"sideBox\":\"Learn more about [BMC Health Services Research](http://bmchealthservres.biomedcentral.com/)\",\"snPcode\":\"\",\"submissionUrl\":\"https://www.editorialmanager.com/BHSR/default.aspx\",\"title\":\"BMC Health Services Research\",\"twitterHandle\":\"BMC_series\",\"acdcEnabled\":true,\"dfaEnabled\":false,\"editorialSystem\":\"em\",\"reportingPortfolio\":\"BMC Series\",\"inReviewEnabled\":true,\"inReviewRevisionsEnabled\":true}}],\"origin\":\"\",\"ownerIdentity\":\"a78e6d86-fa64-42cc-bfdf-7e5144a5a119\",\"owner\":[],\"postedDate\":\"September 29th, 2025\",\"published\":true,\"recentEditorialEvents\":[],\"rejectedJournal\":[],\"revision\":\"\",\"amendment\":\"\",\"status\":\"under-review\",\"subjectAreas\":[],\"tags\":[],\"updatedAt\":\"2025-09-29T13:01:02+00:00\",\"versionOfRecord\":[],\"versionCreatedAt\":\"2025-09-29 13:01:02\",\"video\":\"\",\"vorDoi\":\"\",\"vorDoiUrl\":\"\",\"workflowStages\":[]},\"version\":\"v1\",\"identity\":\"rs-7383021\",\"journalConfig\":\"researchsquare\"},\"__N_SSP\":true},\"page\":\"/article/[identity]/[[...version]]\",\"query\":{\"redirect\":\"/article/rs-7383021\",\"identity\":\"rs-7383021\",\"version\":[\"v1\"]},\"buildId\":\"XKTyCvWXoU3ODBz1xrDgd\",\"isFallback\":false,\"isExperimentalCompile\":false,\"dynamicIds\":[84888],\"gssp\":true,\"scriptLoader\":[]}","source_license":"CC-BY-4.0","license_restricted":false}