Mind-Body Study: protocol for a prospective cohort investigating lifestyle behaviours and mental health outcomes among university students in Australia

Mind-Body Study: protocol for a prospective cohort investigating lifestyle behaviours and mental health outcomes among university students in Australia | 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 Mind-Body Study: protocol for a prospective cohort investigating lifestyle behaviours and mental health outcomes among university students in Australia Xirun Yang, Steve Simpson-Yap, Prince Atorkey, Nupur Nag This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-9044751/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 5 You are reading this latest preprint version Abstract Background: Anxiety, depression, and poor sleep affect up to 41% of university students, with potential adverse impacts on academic performance and quality of life. How students manage their mental wellbeing may inform supports needed. Methods: An observational study recruited students enrolled at universities in Australia to complete an online survey assessing demographics, health behaviours, self-management strategies, and outcomes of anxiety, depression, sleep quality, resilience, and quality of life. Survey responders were emailed invitations to complete a follow-up survey six months later. Results: The survey was opened by 1,976 persons; 47% met eligibility criteria, provided informed consent, and completed baseline survey. Majority participants were aged 18–25 years, female, non-Caucasian, international, and enrolled postgraduate. Validated tools revealed moderate/severe anxiety (27%), moderate/severe depression (29%), poor sleep quality (49%), low resilience (31%), and low/moderate quality of life (57%). Top mental wellbeing management strategies were social interaction, online activities and physical activities. Forty-five percent of participants (n=383) completed follow-up survey. Conclusions: Recruitment and retention for collection of self-reported health data may benefit from co-design, collaboration, and incentive-based approaches. The frequent use of social, online, and physical activities to self-manage wellbeingwarrant further investigation into their efficacy for mental wellbeing. Mental health self-management lifestyle medicine health data collection observational study Figures Figure 1 Figure 2 Figure 3 Introduction Mental health conditions (MHCs) account for 18% of the global disease burden [ 1 ]. An umbrella review of 1644 studies in university students reported a high prevalence of MHCs including anxiety (40%), depression (35%), and sleep disorders (41%) [ 2 ]. Another study, across 18 countries, reported a 57% life-time prevalence of mental disorders, including anxiety (13%) and depression (23%) among university students [ 3 ]. In Australia, a study of 12,347 university students reported up to 29% prevalence of depression, anxiety, and insufficient sleep [ 4 ]. Additional indicators of poor mental wellbeing among university students have been reported, including a study across 18 countries showing 36% experience low resilience [ 5 ]. Another study among 868 university students in Spain, reported 34% experienced low to moderate quality of life (QoL) during their academic course [ 6 ]. These mental health outcomes are interrelated and associated with increased engagement in health-risk behaviours, poor academic performance, course drop out, strained interpersonal relationships, and poor employment outcomes [ 7 – 9 ]. The high prevalence of MHCs, combined with limited accessibility and increasing costs of health resources [ 10 , 11 ], underscores the importance of understanding management strategies and their effectiveness on mental wellbeing. Such insights may guide health promotion to enhance education as well as structural and service provisions to support effective strategies for prevention and management. Global frameworks emphasise the need to address mental wellbeing through a combination of structural, psychosocial, and biological determinants [ 12 , 13 ]. These holistic approaches recognise that mental wellbeing is influenced by individual biology and genetics, as well as social and economic aspects. While evidence supports the benefits of behaviour change interventions, stress management programs, engagement with nature, and physical activity on mental wellbeing [ 14 – 16 ], few studies assess self-management strategies adopted by university students. A cross-sectional study of 3,256 Australia-based university students conducted in 2019 reported that music, social and physical activities were the top three activities used to manage stress [ 17 ]. Stress is commonly reported as a contributing factor of MHCs [ 18 , 19 ], therefore it is probable that activities to manage stress mitigate risk of MHCs. In a second study among 4,698 university students in China, conducted during the COVID-19 pandemic, physical activity, spiritual growth, and stress management were the top 3 strategies use to manage mental wellbeing [ 20 ]. To better understand mental wellbeing among university students, an online longitudinal study was developed and implemented to assess prevalence of MHCs, as well as mental wellbeing management strategies and their effectiveness. Data collection challenges and future recommendations are outlined, and baseline characteristics of the population are described with intent to provide a data resource for researchers. Methods/Results Study design The Mind Body Study (MBS) is a longitudinal study capturing self-reported survey data at two time points, six months apart, using Qualtrics survey software (Qualtrics, Provo, UT). Ethics approved by The University of Melbourne ID: 2025-24145-64052-2. The survey was developed by NN and XY, with questions selected based on literature and research interest, with consideration of minimising participant burden and adherence to ethical conduct of research. Feedback from the Ethics Committee and trial tests conducted by the core research team (XY, NN, SSY) were incorporated. The survey was then piloted on 10 self-selected volunteer postgraduate students recruited through advertisement on a WhatsApp group for postgraduate students. Feedback from student pilot testing primarily regarded length (too long), logic and flow (design errors), and interpretation (ambiguity of questions); these were addressed, retested among the same group of students, and used for the final survey iteration. Power calculations estimated a requirement of 720 participants to detect a 0.2 standard deviation difference in the mean Patient Health Questionnaire score measuring depression (primary outcome) across a dichotomous exposure with 80% power and a 5% two-sided-alpha level. Prior studies report 40% survey response [ 21 ] and 26% attrition for studies with follow-up of six months or longer [ 22 ]. Accounting for predicted attrition at follow-up, recruitment was targeted to > 2400 participants at baseline to enable robust prospective analyses. Recruitment ceased at 948 complete baseline survey responses due to time constraints of collecting 6-month follow-up data before the end of the academic year. Participant recruitment Study participants were recruited (Fig. 1 ) for five weeks, from March 13th to April 18th 2024, by advertising the study via multiple modes: flyers (n = 300–350) placed at locations with high density student populations including university campuses, public transport stops, cafes, beauty salons, student accommodations, and supermarkets; direct contact to known faculty members (n = 67) to advertise the survey through lectures and student learning portals; and online via daily and frequent posts on NN’s and XY’s respectively social media channels as well as single posts to consenting university students’ group social media channels. The students’ groups/associations (n = 95) and Facebook groups (n = 150) comprising > 500 members across 42 Australia-based universities), were emailed/messaged directly to request promotion of the study. Of these, 5% (n = 5) of student association groups, and 80% (n = 120) of Facebook groups agreed to have the promotional flyer posted once on their social media channels. Survey responders indicated source of notice of study as email (44%), social media (30%), peer/friend referral (19%), and flyer (7%), suggesting direct email as the most efficient study recruitment method. MBS was promoted as a research study on mental wellbeing management among university students, with a chance to win 1 of 15 $ 100 gift vouchers upon completion of the survey. Participants opening a link or QR code were directed to three eligibility questions confirming: (1) student enrolled at a university in Australia, (2) aged ≥18 years, and (3) no self-reported diagnosis of bipolar disorder, eating disorder, major depressive disorder, post-traumatic stress disorder, or schizophrenia. Those eligible were required to read a participant information sheet and confirm consent by selecting a checkbox before commencing the survey. Two email reminders, one week apart, were sent to partial responders to encourage survey completion. Participants who completed the baseline survey and provided a valid email address (n = 836), were emailed an invitation to the six-month follow-up survey, with a unique study identification number (ID) and survey link. Email and unique ID were used to link their baseline and 6-month follow-up responses. Follow-up recruitment used the same strategy as baseline, including re-promoting the raffle draw and reminders to partial survey completers. Data collection The survey comprised 53 mandatory questions (Table 1), estimated for completion within 15 minutes. Validated tools were used to assess MHCs and health outcomes, and five demographic questions removed from the follow-up survey. Below text provides additional details excluded in the Table. Lifestyle factors were provided with a definition and examples adapted from the Australian National guidelines [ 23 , 24 ]. Each were queried by frequency (never, less than weekly, 1–2 times per week, 3–5 times per week, daily, and prefer not to say): consumed excessive alcohol (> 4 standard drinks/day or > 10 standard drinks /week); smoked tobacco/vapes; consumed foods from the 5 food groups; consumed ultra-processed foods; consumed high-sugar drinks; consumed high-saturated-fat foods; taken illicit substances; and volunteering. Strategies to manage wellbeing were based on GCBH and WHO frameworks [ 12 , 13 ], and were provided with examples for clarity. Strategies were: physical activity (e.g. gym, sports, swimming, cycling, hiking), learning activity (e.g. reading, listening to music, arts and crafts), social interaction (time with family and/or friends), mind and body activity (e.g. meditation, yoga, massage), prescribed medication, over the counter medication, health professional (e.g. psychologist, therapist, psychiatrist), substance use (e.g. alcohol, tobacco, illicit substances), online activity (e.g. social media, gaming, watching series/movies), and other (free text). Participants were queried on their use of these strategies to manage anxiety, depression, sleep, wellbeing, and none, as separate columns. Mind-body activities were based on definitions from National Center for Complementary, Alternative, or Integrative Health [ 25 ] with frequency scale of never, less than weekly, 1–2 times per week, 3–5 times per week, and daily. Selection of options other than ‘never’ resulted in query of practice duration ( 3 years), session length (1h), a single selection option for purpose (treat health conditions/symptoms, improve mental and/or physical wellbeing, reduce stress), effectiveness in addressing purpose (4-point Likert Scale: not at all to very much), and multi-selection options for modality (App, online, in-person (1 to 1), in-person (group), and self-practice), and barriers and facilitators of engaging with selected practice modalities (seven multiple choice options regarding cost, content, privacy, reminder, support, time, and other) based on prior literature [ 26 ]. Health outcomes were assessed using validated tools with the criteria as per guidelines for binary analysis: moderate/ severe anxiety: General Anxiety Disorder (GAD-7 > 9 [ 27 ]); moderate/ severe depression: Patient Health Questionnaire (PHQ-8 > 9 [ 28 ]); poor sleep quality: Single-Item Sleep Quality Scale (SQS < 6 [ 29 ]); low resilience: Brief Resilience Scale (BRS < 3 [ 30 ]); and low/moderate quality of life: EQ-VAS < 80 (embedded within the EQ-5D-5L) [ 31 ]. Data cleaning and analysis Of 1,977 people who opened the survey link, 19% (n = 380) did not meet eligibility criteria: age < 18 years (n = 17), not Australian university students (n = 63), had a pre-existing mental condition (n = 280); 15% (n = 304) did not consent to participate; and 17% (n = 345) submitted an incomplete survey (Fig. 1 ). Complete baseline surveys (n = 948) were screened for suspicious responses based on prior criteria [ 32 – 34 ] and enumerated in Table 2 . Random pattern email address, IP address outside Australia, and multiple responses having similar/identical phrasing were the top criteria for removing suspicious responses. Fraudulent and suspicious responses (13%, n = 112/948) were removed from the analysis leaving n = 836 participants in the baseline analysis dataset. These participants were emailed a 6-month follow-up survey, from which 46% (n = 384) provided complete responses. Follow-up survey responses are reported in a subsequent analytical manuscript. In the current manuscript, characteristics of participants who completed the survey at baseline, and their use of strategies to manage mental wellbeing, are reported. Statistical analyses were conducted using Stata/SE 18.0 (StataCorp, College Station, USA). Most baseline participants were aged 18–25 years (61%), female (72%), non-Caucasian (75%), with lower-than-average SES (9%), and not living alone (73%; Fig. 2 A). Educational demographics were majority international students (55%), enrolled in a postgraduate degree (61%), enrolled full time (91%), located on an urban campus (91%), and studying at The University of Melbourne (75%; Fig. 2 B). Health outcomes queried showed moderate/severe anxiety (26%), moderate/severe depression (29%), poor sleep quality (49%), low resilience (31%), low/moderate QoL (57%), and few self-reported diagnosed chronic health conditions (14%; five examples provided). Top three strategies used for MHC vs overall wellbeing management were online activities (48% vs 38%), physical activity (47% vs 38%), and social interaction (45% vs 49%, Fig. 3 ). Moderate used strategies were learning (36% vs 37%) and mind-body activities (33% vs 23%), and health professionals (16% vs 6%). Least utilised were prescribed medications (13% vs 9%), OTC medications (11% vs 10%), substance use (12% vs 6%), and other (6% vs 16%). Table 1. Survey variables and measurements Domain Scale/item Content No. Items Question type Baseline 6-month follow-up Demographics Age, gender, ethnicity, enrolment status, university, campus, degree, residential status, socioeconomic status, living circumstance 10 Multiple choice ✓ Campus, degree, university, socioeconomic status, living circumstance Lifestyle Alcohol, tobacco/vape, balanced diet, ultra-processed foods, high-sugar drinks, volunteering 6 5-point Likert never to daily ✓ ✓ Lifestyle attitudes “Do you have any comments regarding lifestyle for the management of mental wellbeing?” 1 Free text ✓ Lifestyle changes “What changes, if any, have you made about your lifestyle in the management of your wellbeing since the first survey?” 1 Free text ✓ Self-management strategies Physical activity, learning activity, time with family and/or friends (social interaction), mind and body activity, prescribed medication, over-the-counter medication, health professional, substance use, online activity, other (free text). 10 Options: used to manage wellbeing, anxiety, depression, sleep, or none of these ✓ ✓ Mind-body activities Meditation, yoga/Tai Chi, guided imagery/progressive relaxation, creative art, physical activity, massage/acupuncture/Reiki, spirituality/faith 7 Multiple choice for frequency, duration, session length, practice history, reason, practice mode, barrier, and facilitator of practice mode ✓ ✓ Mental health Anxiety 7 General Anxiety Disorder-7 ✓ ✓ Mental health Depression 8 Patient Health Questionnaire-8 ✓ ✓ Mental health Sleep 1 Single-Item Sleep Quality Scale ✓ ✓ Health status Chronic condition 1 Any diagnosed diabetes, asthma, cardiovascular disease, Chronic Obstructive Pulmonary Disease, or cancer ✓ ✓ Health status Quality of life 9 EQ-5D-5L-Psychosocial ✓ ✓ Health status Resilience 6 Brief Resilience Scale ✓ ✓ Information source Email, friend/relative/peer, flyer, Facebook, LinkedIn, other (free text) 1 Multiple choice ✓ Free text questions How can your university support students’ wellbeing? 1 Free text ✓ What else would you like to know about lifestyle, mental health and wellbeing? 1 Free text ✓ Table 2 Criteria and numbers of removed suspicious responses Category Indicator Classification N = 112 n (%) Fit Evidence of inattention Survey completed within 5 minutes Fraudulent 8 (7%) Identical response to free text question (> 10 words) provided more than one respondent Fraudulent 30 (27%) Survey completed within 10 minutes Suspicious 19 (17%) Multiple responses having similar phrasing in free text questions Suspicious 54 (48%) Duplicate or unusual response Duplicate response to closed-ended item on a page (straight-lining of multiple-choice answers) Suspicious 0 Nonsensical or irrelevant response Suspicious 10 (9%) Random pattern email (e.g., random alphabet including mixed of lower and upper letter + number @gmail.com) Suspicious 90 (80%) IP address located outside the designated study area Suspicious 72 (72%) Incorrect responses to verifiable items Qualtrics quality check not passed Fraudulent 20 (18%) Recruitment through uninvolved organisation identified from free text questions Suspicious 0 Discussion MHCs are reported in up to 41% of university students [ 2 ], however, little has been reported on how students manage their mental wellbeing. A survey was developed to capture prevalence and management of MHCs among university students, with aim to inform strategies to support mental wellbeing in this population. Our focus was on modifiable lifestyle factors as identified among primary self-management strategies for mental wellbeing management [ 12 , 13 ]. Studies have measured lifestyle among university students: these include populations in Australia, China, German, and Taiwan, focus on broad conceptual or policy perspectives of lifestyle factors based different frameworks, rather than on investigating individual-level lifestyle factors from mental wellbeing pillars or self-management strategies qualitatively and quantitively [ 4 , 17 , 20 , 35 , 36 ]. These studies were conducted pre and during COVID-19 pandemic and only one included follow-up [ 37 ]. The authors reported a 15% increase of MHCs from pre- to during pandemic with a higher prevalence in international students compared to domestic. Diet, exercise and substance use were queried at baseline and reported frequency, but their association with MHCs were not assessed [ 4 , 37 ]. The MBS extends on these prior studies by capturing multiple self-management strategies, lifestyle factors, mental wellbeing outcomes with a 6-month follow-up, as well as qualitative assessment of perspectives on lifestyle for mental wellbeing management. Participant recruitment for research studies poses challenges including limited efficiency, high cost, low information reliability, privacy-related concerns, and survey burden [ 38 ]. Online methods address challenges of efficiency, cost-effectiveness, and scalability enabling diverse, targeted outreach, as well as anonymised and convenient participation [ 33 , 39 ]. In the MBS, online and off-line recruitment methods were used; 74% of participants reported being recruited via either direct email (44%) or social media (30%), 19% through peer referral, and 7% via flyers. This pattern partially aligns with prior studies comparing three recruitment methods, where social media consistently showed the largest number of responses, followed by direct email, and offline flyers the least. Of these methods, direct email achieved the highest eligibility and completion rates [ 40 , 41 ]. These findings suggest that utilising multiple recruitment methods are likely to optimise reach and completion rates for online health data surveys. However, the efficacy of recruitment is contingent on dissemination pathways. For example, though we contacted student enrolment services, as well as student associations and wellbeing services requesting dissemination of the study advertisement, only 5% agreed. Most did not respond, and few declined based on breech of privacy concerns, or conflict of interest in supporting research from another university. The limitation in dissemination is reflected in 75% of MBS participants being enrolled in a single university. Future recommendations include use of paid online advertising targeting populations meeting the inclusion criteria, which has been shown to be efficient and effective in obtaining quality responses, especially when combined with monetary incentives [ 39 , 40 , 42 ]. Further, early collaboration with university Chancellery and/or the Minister of Education, and involving stakeholders such as students unions in co-designing the survey would increase reach and participation, build trust, and improve population representation with stratified sampling, as demonstrated in large national studies [ 4 , 20 , 35 , 36 ]. Of 1,977 persons who opened the MBS, 65% (1,293) were eligible, and consented to participate. Of these, 65% (836) submitted complete and non-suspicious responses, of whom 46% (383) completed the follow-up survey. These findings highlight provision of up to 50% non-participants in power calculations. Other health surveys among university students have reported participation loss due to ineligibility (5–12%), fraudulent responses (11–17%), and attrition at follow-up (44%) [ 4 , 20 , 35 ]. These factors may be reduced by a broader inclusion criteria, data quality checks and time stamping as implemented in the MBS, and feedback reporting for higher retention at follow-up [ 33 ]. Despite participant loss, our baseline survey response rate of 65% is higher than the 12–28% reported in other wellbeing studies [ 4 , 8 , 35 , 36 ] and 46–52% of online studies in university students [ 21 ], but lower that the 95% achieved in a China based study which utilised stratified cluster sampling based on discipline and degree, were supported by the universities, and distributed to students through social media platforms [ 20 ]. In low response studies, authors postulated topic sensitivity, survey length, poor literacy of data use, and fear of personal identification as potential predictors [ 21 ]. Survey completers were near-equal proportions of domestic vs international students, near-equal enrolled in undergraduate vs postgraduate degrees, representative of the demographics reported in previous study [ 4 ]. The MBS provides opportunity to identify specific population needs. For example, international students in Australia have 5% higher prevalence for MHCs than domestic students [ 4 ], and have different lifestyle adoption and stressors for MHCs [ 43 ]. Undergraduates report poorer mental health than graduate students in US [ 44 ]. The 86% female MBS respondents are not representative of near equal ratio of male to female students, highlighting the need to focus on recruitment of males for future health surveys. According to Australian national data, men aged 20–30 have 12–15% higher prevalence of suicide than their female counterparts [ 45 ], highlighting the need to understand gender differences in mental health prevalence and management. MBS is novel in collection open-ended responses to attitudes and changes of lifestyle at follow-up thus providing a holistic view of lifestyle strategies for MHCs management. In regard to frequency of MHCs observed in MBS participants, moderate/severe anxiety was identified in 26%, in line with 24% reported among in a 2019 Australia study [ 4 ] and lower than the 32–38% reported in international studies during COVID-19 [ 20 , 46 ]. Twenty-nine percent of MBS participants had moderate/severe depression and 49% had poor sleep quality, comparable to the 28–30% and 33–49% respectively, reported in prior studies [ 4 , 46 , 47 ]. MHCs can contribute to long-term adverse effects on health, resilience, and QoL [ 5 ]. High resilience and QoL are associated with lower severity of depression and anxiety and improved sleep, conversely low resilience and QoL can exacerbate these conditions [ 48 , 49 ]. Among MBS participants, 14% reported chronic conditions, and 31% met the criteria for low resilience and 57% for low/moderate QoL. In a review of 41 global studies, low resilience was reported among 33% of students [ 50 ] while a study in Spain reported low/moderate QoL among 34% of Spanish university student population [ 6 ]. Variations in prevalence across studies may be attributable to population biases, measurement tool and criteria defining MHCs, and time and geographic location of data collection. The high frequency of MHCs, low resilience and QoL, among MBS participants further supports a need to focus on strategies to support mental wellbeing among university students. MBS identified top self-management care strategies to manage MHCs and wellbeing as physical activity, social interaction, and online activities. Others have previously identified music, social and physical activity to manage stress [ 17 ], and physical activity, spiritual growth, and stress management to manage wellbeing [ 20 ]. While physical and social interaction are pillars for mental wellbeing recommended by the GCBH [ 13 ], the use of online activities (entertainment, gaming, and social media provided as examples) for MHCs and wellbeing management among MBS participants may represent activities of stress management and/or social interaction. However, evidence regarding the effects of online activity on MHCs is mixed depending on intensity and intention of use. A review reports excessive social media use is associated with higher risks of anxiety, depression, and sleep problems [ 51 ], while other study highlights that moderate or purposeful social media engagement can provide emotional support, reduce loneliness and MHCs’ symptoms [ 52 ]. Query into content, frequency, type of activities, and patterns of engagement are necessary to evaluate effects of online activities. Fewer than 20% of MBS participants used health professionals or prescription medications to manage MHCs or wellbeing. This may be an under-representation given participants diagnosed with severe MHCs were ineligible for the study; alternatively, it may be that low/moderate symptoms may not display help seeking behaviours, or that barriers of cost, stigma, and general lack of knowledge about services limit use as reported among 18–23 years old in US [ 53 ]. The results suggest knowledge and utilisation of lifestyle for mental wellbeing management among university students, which in future will be assessed in subgroup analyses and against qualitative responses to lifestyle attitudes. Strengths and limitations The primary strengths of this study include insights to challenges in capturing survey health data among university students at minimal cost, and insights on frequency of MHCs and management strategies for mental wellbeing. The MBS dataset provides opportunities for longitudinal and mixed-methods epidemiological analyses to understand mental wellbeing among a diverse university student population. Limitations are acknowledged; primarily generalisability of population profile due to biases in recruitment mostly from direct email and therefore potential desire to assist peers; in the population being predominantly female and from a single urban based university campus; and due to 55% attrition at follow-up. However, these biases are comparable to past wellbeing survey studies [ 4 , 17 ] and methods to reduce these biases in future studies are suggested. The brevity of MBS survey, aiming to reduce responders’ burden and increase completion, limits the detail of captured data; nevertheless, MBS is one of few with comprehensive quantitively and qualitative data on mental wellbeing self-management via lifestyle factors with a longitudinal design. Conclusions Recruitment and retention for collection of self-reported health data may benefit from co-design, collaboration, and incentive-based approaches. The frequent use of social, online, and physical activities to self-manage wellbeing warrant further investigation into their efficacy for mental wellbeing. Future research capturing data from male and rural based participants is needed. Declarations Acknowledgments The authors thank contributors assisting with pilot testing and promotion of MBS, study participants, and research funders. Data Availability Statement: Data available upon reasonable request to NN. Author Contributions: Xirun Yang: investigation, methodology, data curation, formal analysis, original draft preparation, writing—review and editing, funding acquisition; Steve Simpson-Yap: investigation, writing—review and editing; Prince Atorkey: writing—review and editing; Nupur Nag: investigation, conceptualisation, methodology, visualization, original draft preparation, writing—review and editing, supervision, project administration, funding acquisition. Funding: China Scholarship Council - University of Melbourne PhD Scholarship to XY (under the supervision of NN). The University of Melbourne Population Health Investing in Research Students’ Training Grants to XY for MBS participant incentives. The funders had no role in the design of the study; in the collection, analyses, or interpretation of data; in the writing of the manuscript, or in the decision to publish the results. Institutional Review Board Statement: Study approved by The University of Melbourne Human Research Ethics Committee (ID: 2025-24145-64052-2). Informed Consent Statement Participants meeting the eligibility criteria were directed to read an online plain language statement and at the end of this document, requested to select a tick-box to confirm consent to participate in the study. Conflicts of Interest The author(s) declare no potential conflicts of interest. References GBD. Global, regional, and national burden of 12 mental disorders in 204 countries and territories, 1990–2019: a systematic analysis for the Global Burden of Disease Study 2019. Lancet Psychiatry. 2022;9(2):137–50. Paiva U, Cortese S, Flor M, Moncada-Parra A, Lecumberri A, Eudave L, Magallón S, García-González S, Sobrino-Morras Á, Piqué I, et al. Prevalence of mental disorder symptoms among university students: An umbrella review. Neurosci Biobehavioral Reviews. 2025;175:106244. 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Barriers to and Facilitators of User Engagement With Digital Mental Health Interventions: Systematic Review. J Med Internet Res. 2021;23(3):e24387. Spitzer RL, Kroenke K, Williams JB, Löwe B. A brief measure for assessing generalized anxiety disorder: the GAD-7. Arch Intern Med. 2006;166(10):1092–7. Kroenke K, Strine TW, Spitzer RL, Williams JB, Berry JT, Mokdad AH. The PHQ-8 as a measure of current depression in the general population. J Affect Disord. 2009;114(1–3):163–73. Snyder E, Cai B, DeMuro C, Morrison MF, Ball W. A New Single-Item Sleep Quality Scale: Results of Psychometric Evaluation in Patients With Chronic Primary Insomnia and Depression. J Clin Sleep Med. 2018;14(11):1849–57. Smith BW, Dalen J, Wiggins K, Tooley E, Christopher P, Bernard J. The brief resilience scale: assessing the ability to bounce back. Int J Behav Med. 2008;15(3):194–200. McCaffrey N, Kaambwa B, Currow DC, Ratcliffe J. Health-related quality of life measured using the EQ-5D–5L: South Australian population norms. Health Qual Life Outcomes. 2016;14(1):133. Pinzón N, Koundinya V, Galt RE, Dowling WO, Baukloh M, Taku-Forchu NC, Schohr T, Roche LM, Ikendi S, Cooper M, et al. AI-powered fraud and the erosion of online survey integrity: an analysis of 31 fraud detection strategies. Front Res Metr Anal. 2024;9:1432774. Lei F. Online recruitment for an online survey study: Our experience of dealing with fraudsters. Appl Nurs Res. 2024;80:151854. Pozzar R, Hammer MJ, Underhill-Blazey M, Wright AA, Tulsky JA, Hong F, Gundersen DA, Berry DL. Threats of Bots and Other Bad Actors to Data Quality Following Research Participant Recruitment Through Social Media: Cross-Sectional Questionnaire. J Med Internet Res. 2020;22(10):e23021. Weber A, Kroiss K, Reismann L, Jansen P, Hirschfelder G, Sedlmeier AM, Stein MJ, Bohmann P, Leitzmann MF, Jochem C. Health-Promoting and Sustainable Behavior in University Students in Germany: A Cross-Sectional Study. Int J Environ Res Public Health 2023, 20(7). Chao DP. Health-promoting lifestyle and its predictors among health-related and non-health-related university students in Taiwan: a cross-sectional quantitative study. BMC Public Health. 2023;23(1):827. Russell MA, Reavley N, Williams I, Li W, Tarzia L, Chondros P, Sanci L. Changes in mental health across the COVID-19 pandemic for local and international university students in Australia: a cohort study. BMC Psychol. 2023;11(1):55. Reagan L, Nowlin SY, Birdsall SB, Gabbay J, Vorderstrasse A, Johnson C. D'Eramo Melkus G: Integrative Review of Recruitment of Research Participants Through Facebook. Nurs Res. 2019;68(6):423–32. Tsaltskan V, Sanchez Baez R, Firestein GS. Cost-effectiveness of social media advertising as a recruitment tool: A systematic review and meta-analysis. J Clin Transl Sci. 2023;7(1):e180. Sledzieski N, Gallicano TD, Shaikh S, Levens S. Optimizing Recruitment for Qualitative Research: A Comparison of Social Media, Emails, and Offline Methods. Int J Qualitative Methods. 2023;22:16094069231162539. Smith R, Alvarez C, Crixell S, Lane MA. The Food, Feelings, and Family Study: comparison of the efficacy of traditional methods, social media, and broadcast email to recruit pregnant women to an observational, longitudinal nutrition study. BMC Pregnancy Childbirth. 2021;21(1):203. Sobolewski J, Rothschild A, Freeman A. The Impact of Incentives on Data Collection for Online Surveys: Social Media Recruitment Study. JMIR Form Res. 2024;8:e50240. Minutillo S, Cleary M, Hills P, Visentin A. Mental health considerations for international students. Issues Ment Health Nurs. 2020;41(6):494–9. Liu Y, Frazier PA, Porta CM, Lust K. Mental health of US undergraduate and graduate students before and during the COVID-19 pandemic: Differences across sociodemographic groups. Psychiatry Res. 2022;309:114428. Suicide. & self-harm monitoring [ https://www.aihw.gov.au/suicide-self-harm-monitoring/overview/suicide-deaths] Deng J, Zhou F, Hou W, Silver Z, Wong CY, Chang O, Drakos A, Zuo QK, Huang E. The prevalence of depressive symptoms, anxiety symptoms and sleep disturbance in higher education students during the COVID-19 pandemic: A systematic review and meta-analysis. Psychiatry Res. 2021;301:113863. Schmickler JM, Blaschke S, Robbins R, Mess F. Determinants of Sleep Quality: A Cross-Sectional Study in University Students. Int J Environ Res Public Health 2023, 20(3). Szegedi K, Győri Z, Juhász T. Factors affecting quality of life and learning-life balance of university students in business higher education. Humanit Social Sci Commun. 2024;11(1):113. Ang WHD, Shorey S, Hoo MXY, Chew HSJ, Lau Y. The role of resilience in higher education: A meta-ethnographic analysis of students' experiences. J Prof Nurs. 2021;37(6):1092–109. Chua JH, Cheng CKT, Cheng LJ, Ang WHD, Lau Y. Global prevalence of resilience in higher education students: A systematic review, meta-analysis and meta-regression. Curr Psychol. 2023;42(26):22645–63. Ahmed O, Walsh EI, Dawel A, Alateeq K, Espinoza Oyarce DA, Cherbuin N. Social media use, mental health and sleep: A systematic review with meta-analyses. J Affect Disord. 2024;367:701–12. Naslund JA, Bondre A, Torous J, Aschbrenner KA. Social Media and Mental Health: Benefits, Risks, and Opportunities for Research and Practice. J Technol Behav Sci. 2020;5(3):245–57. Cadigan JM, Lee CM, Larimer ME. Young Adult Mental Health: a Prospective Examination of Service Utilization, Perceived Unmet Service Needs, Attitudes, and Barriers to Service Use. Prev Sci. 2019;20(3):366–76. Additional Declarations No competing interests reported. Cite Share Download PDF Status: Under Review Version 1 posted Reviewers invited by journal 02 Apr, 2026 Editor invited by journal 11 Mar, 2026 Editor assigned by journal 11 Mar, 2026 Submission checks completed at journal 11 Mar, 2026 First submitted to journal 05 Mar, 2026 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-9044751","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":618933141,"identity":"eb71439c-750f-4cbc-87fb-b680f2d770c4","order_by":0,"name":"Xirun Yang","email":"","orcid":"","institution":"The University of Melbourne","correspondingAuthor":false,"prefix":"","firstName":"Xirun","middleName":"","lastName":"Yang","suffix":""},{"id":618933142,"identity":"4272f1b5-d8d7-405b-abd8-95dae78aa979","order_by":1,"name":"Steve Simpson-Yap","email":"","orcid":"","institution":"The University of Melbourne","correspondingAuthor":false,"prefix":"","firstName":"Steve","middleName":"","lastName":"Simpson-Yap","suffix":""},{"id":618933143,"identity":"b87e2aa6-1005-4577-b248-ba161965d5e2","order_by":2,"name":"Prince Atorkey","email":"","orcid":"","institution":"University of Newcastle","correspondingAuthor":false,"prefix":"","firstName":"Prince","middleName":"","lastName":"Atorkey","suffix":""},{"id":618933144,"identity":"2acb0db3-99b5-4ba9-a413-9954b8c443da","order_by":3,"name":"Nupur Nag","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA2UlEQVRIiWNgGAWjYLCCDwwMPAwMzG1AJjNxOhhngLUwkqCFmQeik0gt5tLNj1/btt2R0W1vbHvAUGGd2MB+xgCvFss5x8ysc9ue8ZidOdhuwHAmPbGBJwe/FoMbCWbGuW2HecxuJLZJMLYdTmxgIKgl/ZuxJUjL/YdALf+AWvjfENKSY/yYEWwLI1BLA1CLBEFbcsoYe84BtZxJbDdIOJZu3CbxrICQwzZ/+FF22N7s+OFjDz7UWMv28ydvwKsFCNgk4MwEEJeQeiBg/kCEolEwCkbBKBjJAAAtrkkTl+/NMwAAAABJRU5ErkJggg==","orcid":"","institution":"The University of Melbourne","correspondingAuthor":true,"prefix":"","firstName":"Nupur","middleName":"","lastName":"Nag","suffix":""}],"badges":[],"createdAt":"2026-03-06 00:53:30","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-9044751/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-9044751/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":106724306,"identity":"a7a0c01c-8d24-44c0-b396-0a39a2e76e1c","added_by":"auto","created_at":"2026-04-12 18:27:21","extension":"jpg","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":35914,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eParticipant recruitment flow chart.\u003c/strong\u003e A total of 1,977 individuals responded to the study advertisement. After screening for eligibility and removing incomplete or suspicious responses, 836 participants completed the baseline survey. At 6-month follow-up, 383 participants provided valid responses. Analysed population highlighted in bold.\u003c/p\u003e","description":"","filename":"Picture1.jpg","url":"https://assets-eu.researchsquare.com/files/rs-9044751/v1/893a4014c8e6b281b7a32000.jpg"},{"id":106468643,"identity":"ca3238ad-4f42-4ba5-a5a7-0dbe0f6a7267","added_by":"auto","created_at":"2026-04-09 00:42:38","extension":"jpg","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":90041,"visible":true,"origin":"","legend":"\u003cp\u003e(A) Sociodemographic and (B) health status of baseline survey completers. Higher proportions of participants were female, international, full-time, and enrolled at a single university. Five of six mental wellbeing indicators were identified in 26-57% of participants. \u003cem\u003eAbbreviations: BRS\u0026lt;3: low resilience; GAD-7\u0026gt;9: moderate/severe anxiety; PHQ-8\u0026gt;9: moderate/severe depression, EA-VAS\u0026lt;80: low/moderate quality of life; SES: socioeconomic; SQS\u0026lt;6: poor sleep quality\u003c/em\u003e\u003c/p\u003e","description":"","filename":"Picture2.jpg","url":"https://assets-eu.researchsquare.com/files/rs-9044751/v1/6766edf8c1851cc5474431c6.jpg"},{"id":106468644,"identity":"124771d9-de66-497c-9f6a-7b12f724d4a8","added_by":"auto","created_at":"2026-04-09 00:42:38","extension":"jpg","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":61050,"visible":true,"origin":"","legend":"\u003cp\u003eStrategies for MHCs and overall wellbeing management.\u003cstrong\u003e \u003c/strong\u003eOf ten strategies queried, highest proportions of participants used social, online, and physical activities. \u003cem\u003eAbbreviations: Med, medication; OTC, over the counter; Social, social interaction.\u003c/em\u003e\u003c/p\u003e","description":"","filename":"Picture3.jpg","url":"https://assets-eu.researchsquare.com/files/rs-9044751/v1/43a175a7aa3201f814b22d12.jpg"},{"id":106726819,"identity":"a23867a8-21b8-44dc-b719-b38cf883e23e","added_by":"auto","created_at":"2026-04-12 18:37:21","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":999198,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-9044751/v1/f35c38d1-7569-4e0d-9162-846745219505.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Mind-Body Study: protocol for a prospective cohort investigating lifestyle behaviours and mental health outcomes among university students in Australia","fulltext":[{"header":"Introduction","content":"\u003cp\u003eMental health conditions (MHCs) account for 18% of the global disease burden [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. An umbrella review of 1644 studies in university students reported a high prevalence of MHCs including anxiety (40%), depression (35%), and sleep disorders (41%) [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. Another study, across 18 countries, reported a 57% life-time prevalence of mental disorders, including anxiety (13%) and depression (23%) among university students [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]. In Australia, a study of 12,347 university students reported up to 29% prevalence of depression, anxiety, and insufficient sleep [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]. Additional indicators of poor mental wellbeing among university students have been reported, including a study across 18 countries showing 36% experience low resilience [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]. Another study among 868 university students in Spain, reported 34% experienced low to moderate quality of life (QoL) during their academic course [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]. These mental health outcomes are interrelated and associated with increased engagement in health-risk behaviours, poor academic performance, course drop out, strained interpersonal relationships, and poor employment outcomes [\u003cspan additionalcitationids=\"CR8\" citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eThe high prevalence of MHCs, combined with limited accessibility and increasing costs of health resources [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e, \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e], underscores the importance of understanding management strategies and their effectiveness on mental wellbeing. Such insights may guide health promotion to enhance education as well as structural and service provisions to support effective strategies for prevention and management. Global frameworks emphasise the need to address mental wellbeing through a combination of structural, psychosocial, and biological determinants [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e, \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]. These holistic approaches recognise that mental wellbeing is influenced by individual biology and genetics, as well as social and economic aspects.\u003c/p\u003e \u003cp\u003eWhile evidence supports the benefits of behaviour change interventions, stress management programs, engagement with nature, and physical activity on mental wellbeing [\u003cspan additionalcitationids=\"CR15\" citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e], few studies assess self-management strategies adopted by university students. A cross-sectional study of 3,256 Australia-based university students conducted in 2019 reported that music, social and physical activities were the top three activities used to manage stress [\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e]. Stress is commonly reported as a contributing factor of MHCs [\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e, \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e], therefore it is probable that activities to manage stress mitigate risk of MHCs. In a second study among 4,698 university students in China, conducted during the COVID-19 pandemic, physical activity, spiritual growth, and stress management were the top 3 strategies use to manage mental wellbeing [\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eTo better understand mental wellbeing among university students, an online longitudinal study was developed and implemented to assess prevalence of MHCs, as well as mental wellbeing management strategies and their effectiveness. Data collection challenges and future recommendations are outlined, and baseline characteristics of the population are described with intent to provide a data resource for researchers.\u003c/p\u003e"},{"header":"Methods/Results","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eStudy design\u003c/h2\u003e \u003cp\u003eThe Mind Body Study (MBS) is a longitudinal study capturing self-reported survey data at two time points, six months apart, using Qualtrics survey software (Qualtrics, Provo, UT). Ethics approved by The University of Melbourne ID: 2025-24145-64052-2.\u003c/p\u003e \u003cp\u003e The survey was developed by NN and XY, with questions selected based on literature and research interest, with consideration of minimising participant burden and adherence to ethical conduct of research. Feedback from the Ethics Committee and trial tests conducted by the core research team (XY, NN, SSY) were incorporated. The survey was then piloted on 10 self-selected volunteer postgraduate students recruited through advertisement on a WhatsApp group for postgraduate students. Feedback from student pilot testing primarily regarded length (too long), logic and flow (design errors), and interpretation (ambiguity of questions); these were addressed, retested among the same group of students, and used for the final survey iteration.\u003c/p\u003e \u003cp\u003ePower calculations estimated a requirement of 720 participants to detect a 0.2 standard deviation difference in the mean Patient Health Questionnaire score measuring depression (primary outcome) across a dichotomous exposure with 80% power and a 5% two-sided-alpha level. Prior studies report 40% survey response [\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e] and 26% attrition for studies with follow-up of six months or longer [\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e]. Accounting for predicted attrition at follow-up, recruitment was targeted to \u0026gt;\u0026thinsp;2400 participants at baseline to enable robust prospective analyses. Recruitment ceased at 948 complete baseline survey responses due to time constraints of collecting 6-month follow-up data before the end of the academic year.\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eParticipant recruitment\u003c/h3\u003e\n\u003cp\u003eStudy participants were recruited (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e) for five weeks, from March 13th to April 18th 2024, by advertising the study via multiple modes: flyers (n\u0026thinsp;=\u0026thinsp;300\u0026ndash;350) placed at locations with high density student populations including university campuses, public transport stops, cafes, beauty salons, student accommodations, and supermarkets; direct contact to known faculty members (n\u0026thinsp;=\u0026thinsp;67) to advertise the survey through lectures and student learning portals; and online via daily and frequent posts on NN\u0026rsquo;s and XY\u0026rsquo;s respectively social media channels as well as single posts to consenting university students\u0026rsquo; group social media channels. The students\u0026rsquo; groups/associations (n\u0026thinsp;=\u0026thinsp;95) and Facebook groups (n\u0026thinsp;=\u0026thinsp;150) comprising\u0026thinsp;\u0026gt;\u0026thinsp;500 members across 42 Australia-based universities), were emailed/messaged directly to request promotion of the study. Of these, 5% (n\u0026thinsp;=\u0026thinsp;5) of student association groups, and 80% (n\u0026thinsp;=\u0026thinsp;120) of Facebook groups agreed to have the promotional flyer posted once on their social media channels. Survey responders indicated source of notice of study as email (44%), social media (30%), peer/friend referral (19%), and flyer (7%), suggesting direct email as the most efficient study recruitment method.\u003c/p\u003e \u003cp\u003eMBS was promoted as a research study on mental wellbeing management among university students, with a chance to win 1 of 15 \u003cspan\u003e$\u003c/span\u003e100 gift vouchers upon completion of the survey. Participants opening a link or QR code were directed to three eligibility questions confirming: (1) student enrolled at a university in Australia, (2) aged \u0026ge;18 years, and (3) no self-reported diagnosis of bipolar disorder, eating disorder, major depressive disorder, post-traumatic stress disorder, or schizophrenia. Those eligible were required to read a participant information sheet and confirm consent by selecting a checkbox before commencing the survey. Two email reminders, one week apart, were sent to partial responders to encourage survey completion.\u003c/p\u003e \u003cp\u003eParticipants who completed the baseline survey and provided a valid email address (n\u0026thinsp;=\u0026thinsp;836), were emailed an invitation to the six-month follow-up survey, with a unique study identification number (ID) and survey link. Email and unique ID were used to link their baseline and 6-month follow-up responses. Follow-up recruitment used the same strategy as baseline, including re-promoting the raffle draw and reminders to partial survey completers.\u003c/p\u003e\n\u003ch3\u003eData collection\u003c/h3\u003e\n\u003cp\u003eThe survey comprised 53 mandatory questions (Table\u0026nbsp;1), estimated for completion within 15 minutes. Validated tools were used to assess MHCs and health outcomes, and five demographic questions removed from the follow-up survey. Below text provides additional details excluded in the Table.\u003c/p\u003e \u003cp\u003eLifestyle factors were provided with a definition and examples adapted from the Australian National guidelines [\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e, \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e]. Each were queried by frequency (never, less than weekly, 1\u0026ndash;2 times per week, 3\u0026ndash;5 times per week, daily, and prefer not to say): consumed excessive alcohol (\u0026gt;\u0026thinsp;4 standard drinks/day or \u0026gt;\u0026thinsp;10 standard drinks /week); smoked tobacco/vapes; consumed foods from the 5 food groups; consumed ultra-processed foods; consumed high-sugar drinks; consumed high-saturated-fat foods; taken illicit substances; and volunteering.\u003c/p\u003e \u003cp\u003eStrategies to manage wellbeing were based on GCBH and WHO frameworks [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e, \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e], and were provided with examples for clarity. Strategies were: physical activity (e.g. gym, sports, swimming, cycling, hiking), learning activity (e.g. reading, listening to music, arts and crafts), social interaction (time with family and/or friends), mind and body activity (e.g. meditation, yoga, massage), prescribed medication, over the counter medication, health professional (e.g. psychologist, therapist, psychiatrist), substance use (e.g. alcohol, tobacco, illicit substances), online activity (e.g. social media, gaming, watching series/movies), and other (free text). Participants were queried on their use of these strategies to manage anxiety, depression, sleep, wellbeing, and none, as separate columns.\u003c/p\u003e \u003cp\u003eMind-body activities were based on definitions from National Center for Complementary, Alternative, or Integrative Health [\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e] with frequency scale of never, less than weekly, 1\u0026ndash;2 times per week, 3\u0026ndash;5 times per week, and daily. Selection of options other than \u0026lsquo;never\u0026rsquo; resulted in query of practice duration (\u0026lt;\u0026thinsp;6 months, 6\u0026ndash;12 months, 1\u0026ndash;3 years, \u0026gt;\u0026thinsp;3 years), session length (\u0026lt;\u0026thinsp;10mins, 10-30min, 30-60min, \u0026gt;1h), a single selection option for purpose (treat health conditions/symptoms, improve mental and/or physical wellbeing, reduce stress), effectiveness in addressing purpose (4-point Likert Scale: not at all to very much), and multi-selection options for modality (App, online, in-person (1 to 1), in-person (group), and self-practice), and barriers and facilitators of engaging with selected practice modalities (seven multiple choice options regarding cost, content, privacy, reminder, support, time, and other) based on prior literature [\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eHealth outcomes were assessed using validated tools with the criteria as per guidelines for binary analysis: moderate/ severe anxiety: General Anxiety Disorder (GAD-7\u0026thinsp;\u0026gt;\u0026thinsp;9 [\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e]); moderate/ severe depression: Patient Health Questionnaire (PHQ-8\u0026thinsp;\u0026gt;\u0026thinsp;9 [\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e]); poor sleep quality: Single-Item Sleep Quality Scale (SQS\u0026thinsp;\u0026lt;\u0026thinsp;6 [\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e]); low resilience: Brief Resilience Scale (BRS\u0026thinsp;\u0026lt;\u0026thinsp;3 [\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e]); and low/moderate quality of life: EQ-VAS\u0026thinsp;\u0026lt;\u0026thinsp;80 (embedded within the EQ-5D-5L) [\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e].\u003c/p\u003e\n\u003ch3\u003eData cleaning and analysis\u003c/h3\u003e\n\u003cp\u003eOf 1,977 people who opened the survey link, 19% (n\u0026thinsp;=\u0026thinsp;380) did not meet eligibility criteria: age\u0026thinsp;\u0026lt;\u0026thinsp;18 years (n\u0026thinsp;=\u0026thinsp;17), not Australian university students (n\u0026thinsp;=\u0026thinsp;63), had a pre-existing mental condition (n\u0026thinsp;=\u0026thinsp;280); 15% (n\u0026thinsp;=\u0026thinsp;304) did not consent to participate; and 17% (n\u0026thinsp;=\u0026thinsp;345) submitted an incomplete survey (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). Complete baseline surveys (n\u0026thinsp;=\u0026thinsp;948) were screened for suspicious responses based on prior criteria [\u003cspan additionalcitationids=\"CR33\" citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e] and enumerated in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e2\u003c/span\u003e. Random pattern email address, IP address outside Australia, and multiple responses having similar/identical phrasing were the top criteria for removing suspicious responses. Fraudulent and suspicious responses (13%, n\u0026thinsp;=\u0026thinsp;112/948) were removed from the analysis leaving n\u0026thinsp;=\u0026thinsp;836 participants in the baseline analysis dataset. These participants were emailed a 6-month follow-up survey, from which 46% (n\u0026thinsp;=\u0026thinsp;384) provided complete responses. Follow-up survey responses are reported in a subsequent analytical manuscript.\u003c/p\u003e \u003cp\u003eIn the current manuscript, characteristics of participants who completed the survey at baseline, and their use of strategies to manage mental wellbeing, are reported. Statistical analyses were conducted using Stata/SE 18.0 (StataCorp, College Station, USA).\u003c/p\u003e \u003cp\u003eMost baseline participants were aged 18\u0026ndash;25 years (61%), female (72%), non-Caucasian (75%), with lower-than-average SES (9%), and not living alone (73%; Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eA). Educational demographics were majority international students (55%), enrolled in a postgraduate degree (61%), enrolled full time (91%), located on an urban campus (91%), and studying at The University of Melbourne (75%; Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eB). Health outcomes queried showed moderate/severe anxiety (26%), moderate/severe depression (29%), poor sleep quality (49%), low resilience (31%), low/moderate QoL (57%), and few self-reported diagnosed chronic health conditions (14%; five examples provided).\u003c/p\u003e \u003cp\u003eTop three strategies used for MHC vs overall wellbeing management were online activities (48% vs 38%), physical activity (47% vs 38%), and social interaction (45% vs 49%, Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e). Moderate used strategies were learning (36% vs 37%) and mind-body activities (33% vs 23%), and health professionals (16% vs 6%). Least utilised were prescribed medications (13% vs 9%), OTC medications (11% vs 10%), substance use (12% vs 6%), and other (6% vs 16%).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"No\" id=\"Taba\" border=\"1\"\u003e \u003ccolgroup cols=\"9\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colspan=\"7\" nameend=\"c8\" namest=\"c2\"\u003e \u003cp\u003eTable\u0026nbsp;1. Survey variables and measurements\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"1\" nameend=\"c9\" namest=\"c9\"\u003e\u0026nbsp;\u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eDomain\u003c/b\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003eScale/item Content\u003c/b\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003e\u003cb\u003eNo. Items\u003c/b\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003eQuestion type\u003c/b\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cb\u003eBaseline\u003c/b\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u003cb\u003e6-month follow-up\u003c/b\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"1\" nameend=\"c9\" namest=\"c9\"\u003e\u0026nbsp;\u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eDemographics\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eAge, gender, ethnicity, enrolment status, university, campus, degree, residential status, socioeconomic status, living circumstance\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e \u003cp\u003eMultiple choice\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e✓\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003eCampus, degree, university, socioeconomic status, living circumstance\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c9\" namest=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eLifestyle\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eAlcohol, tobacco/vape, balanced diet, ultra-processed foods, high-sugar drinks, volunteering\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003e6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e5-point Likert never to daily\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e✓\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e✓\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c9\" namest=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eLifestyle attitudes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cem\u003e\u0026ldquo;Do you have any comments regarding lifestyle for the management of mental wellbeing?\u0026rdquo;\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eFree text\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e✓\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c9\" namest=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eLifestyle changes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cem\u003e\u0026ldquo;What changes, if any, have you made about your lifestyle in the management of your wellbeing since the first survey?\u0026rdquo;\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eFree text\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e✓\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c9\" namest=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eSelf-management strategies\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003ePhysical activity, learning activity, time with family and/or friends (social interaction), mind and body activity, prescribed medication, over-the-counter medication, health professional, substance use, online activity, other (free text).\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003e10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eOptions: used to manage wellbeing, anxiety, depression, sleep, or none of these\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e✓\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e✓\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c9\" namest=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eMind-body activities\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eMeditation, yoga/Tai Chi, guided imagery/progressive relaxation, creative art, physical activity, massage/acupuncture/Reiki, spirituality/faith\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003e7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eMultiple choice for frequency, duration, session length, practice history, reason, practice mode, barrier, and facilitator of practice mode\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e✓\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e✓\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eMental health\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eAnxiety\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003e7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eGeneral Anxiety Disorder-7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e✓\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e✓\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c9\" namest=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eMental health\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eDepression\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003e8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003ePatient Health Questionnaire-8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e✓\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e✓\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c9\" namest=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eMental health\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eSleep\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eSingle-Item Sleep Quality Scale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e✓\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e✓\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c9\" namest=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eHealth status\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eChronic condition\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eAny diagnosed diabetes, asthma, cardiovascular disease, Chronic Obstructive Pulmonary Disease, or cancer\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e✓\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e✓\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c9\" namest=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eHealth status\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eQuality of life\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003e9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eEQ-5D-5L-Psychosocial\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e✓\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e✓\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c9\" namest=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eHealth status\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eResilience\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003e6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eBrief Resilience Scale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e✓\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e✓\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c9\" namest=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eInformation source\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eEmail, friend/relative/peer, flyer, Facebook, LinkedIn, other (free text)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eMultiple choice\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e✓\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c9\" namest=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" morerows=\"1\" nameend=\"c2\" namest=\"c1\" rowspan=\"2\"\u003e \u003cp\u003eFree text questions\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eHow can your university support students\u0026rsquo; wellbeing?\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eFree text\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e✓\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c9\" namest=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eWhat else would you like to know about lifestyle, mental health and wellbeing?\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eFree text\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e✓\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c9\" namest=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eCriteria and numbers of removed suspicious responses\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"4\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCategory\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eIndicator\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eClassification\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eN\u0026thinsp;=\u0026thinsp;112\u003c/p\u003e \u003cp\u003en (%) Fit\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003e\u003cb\u003eEvidence of inattention\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSurvey completed within 5 minutes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eFraudulent\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e8 (7%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eIdentical response to free text question (\u0026gt;\u0026thinsp;10 words) provided more than one respondent\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eFraudulent\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e30 (27%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSurvey completed within 10 minutes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eSuspicious\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e19 (17%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMultiple responses having similar phrasing in free text questions\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eSuspicious\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e54 (48%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"3\" rowspan=\"4\"\u003e \u003cp\u003e\u003cb\u003eDuplicate or unusual response\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eDuplicate response to closed-ended item on a page (straight-lining of multiple-choice answers)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eSuspicious\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNonsensical or irrelevant response\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eSuspicious\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e10 (9%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eRandom pattern email (e.g., random alphabet including mixed of lower and upper letter\u0026thinsp;+\u0026thinsp;number @gmail.com)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eSuspicious\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e90 (80%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eIP address located outside the designated study area\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eSuspicious\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e72 (72%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e\u003cb\u003eIncorrect responses to verifiable items\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eQualtrics quality check not passed\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eFraudulent\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e20 (18%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eRecruitment through uninvolved organisation identified from free text questions\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eSuspicious\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eMHCs are reported in up to 41% of university students [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e], however, little has been reported on how students manage their mental wellbeing. A survey was developed to capture prevalence and management of MHCs among university students, with aim to inform strategies to support mental wellbeing in this population. Our focus was on modifiable lifestyle factors as identified among primary self-management strategies for mental wellbeing management [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e, \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]. Studies have measured lifestyle among university students: these include populations in Australia, China, German, and Taiwan, focus on broad conceptual or policy perspectives of lifestyle factors based different frameworks, rather than on investigating individual-level lifestyle factors from mental wellbeing pillars or self-management strategies qualitatively and quantitively [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e, \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e, \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e, \u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e, \u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e]. These studies were conducted pre and during COVID-19 pandemic and only one included follow-up [\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e]. The authors reported a 15% increase of MHCs from pre- to during pandemic with a higher prevalence in international students compared to domestic. Diet, exercise and substance use were queried at baseline and reported frequency, but their association with MHCs were not assessed [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e, \u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e]. The MBS extends on these prior studies by capturing multiple self-management strategies, lifestyle factors, mental wellbeing outcomes with a 6-month follow-up, as well as qualitative assessment of perspectives on lifestyle for mental wellbeing management.\u003c/p\u003e \u003cp\u003eParticipant recruitment for research studies poses challenges including limited efficiency, high cost, low information reliability, privacy-related concerns, and survey burden [\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e]. Online methods address challenges of efficiency, cost-effectiveness, and scalability enabling diverse, targeted outreach, as well as anonymised and convenient participation [\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e, \u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e]. In the MBS, online and off-line recruitment methods were used; 74% of participants reported being recruited via either direct email (44%) or social media (30%), 19% through peer referral, and 7% via flyers. This pattern partially aligns with prior studies comparing three recruitment methods, where social media consistently showed the largest number of responses, followed by direct email, and offline flyers the least. Of these methods, direct email achieved the highest eligibility and completion rates [\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e, \u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e]. These findings suggest that utilising multiple recruitment methods are likely to optimise reach and completion rates for online health data surveys. However, the efficacy of recruitment is contingent on dissemination pathways. For example, though we contacted student enrolment services, as well as student associations and wellbeing services requesting dissemination of the study advertisement, only 5% agreed. Most did not respond, and few declined based on breech of privacy concerns, or conflict of interest in supporting research from another university. The limitation in dissemination is reflected in 75% of MBS participants being enrolled in a single university. Future recommendations include use of paid online advertising targeting populations meeting the inclusion criteria, which has been shown to be efficient and effective in obtaining quality responses, especially when combined with monetary incentives [\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e, \u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e, \u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e]. Further, early collaboration with university Chancellery and/or the Minister of Education, and involving stakeholders such as students unions in co-designing the survey would increase reach and participation, build trust, and improve population representation with stratified sampling, as demonstrated in large national studies [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e, \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e, \u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e, \u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eOf 1,977 persons who opened the MBS, 65% (1,293) were eligible, and consented to participate. Of these, 65% (836) submitted complete and non-suspicious responses, of whom 46% (383) completed the follow-up survey. These findings highlight provision of up to 50% non-participants in power calculations. Other health surveys among university students have reported participation loss due to ineligibility (5\u0026ndash;12%), fraudulent responses (11\u0026ndash;17%), and attrition at follow-up (44%) [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e, \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e, \u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e]. These factors may be reduced by a broader inclusion criteria, data quality checks and time stamping as implemented in the MBS, and feedback reporting for higher retention at follow-up [\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e]. Despite participant loss, our baseline survey response rate of 65% is higher than the 12\u0026ndash;28% reported in other wellbeing studies [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e, \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e, \u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e, \u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e] and 46\u0026ndash;52% of online studies in university students [\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e], but lower that the 95% achieved in a China based study which utilised stratified cluster sampling based on discipline and degree, were supported by the universities, and distributed to students through social media platforms [\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e]. In low response studies, authors postulated topic sensitivity, survey length, poor literacy of data use, and fear of personal identification as potential predictors [\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eSurvey completers were near-equal proportions of domestic vs international students, near-equal enrolled in undergraduate vs postgraduate degrees, representative of the demographics reported in previous study [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]. The MBS provides opportunity to identify specific population needs. For example, international students in Australia have 5% higher prevalence for MHCs than domestic students [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e], and have different lifestyle adoption and stressors for MHCs [\u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e]. Undergraduates report poorer mental health than graduate students in US [\u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e]. The 86% female MBS respondents are not representative of near equal ratio of male to female students, highlighting the need to focus on recruitment of males for future health surveys. According to Australian national data, men aged 20\u0026ndash;30 have 12\u0026ndash;15% higher prevalence of suicide than their female counterparts [\u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e45\u003c/span\u003e], highlighting the need to understand gender differences in mental health prevalence and management. MBS is novel in collection open-ended responses to attitudes and changes of lifestyle at follow-up thus providing a holistic view of lifestyle strategies for MHCs management.\u003c/p\u003e \u003cp\u003eIn regard to frequency of MHCs observed in MBS participants, moderate/severe anxiety was identified in 26%, in line with 24% reported among in a 2019 Australia study [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e] and lower than the 32\u0026ndash;38% reported in international studies during COVID-19 [\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e, \u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e46\u003c/span\u003e]. Twenty-nine percent of MBS participants had moderate/severe depression and 49% had poor sleep quality, comparable to the 28\u0026ndash;30% and 33\u0026ndash;49% respectively, reported in prior studies [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e, \u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e46\u003c/span\u003e, \u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e47\u003c/span\u003e]. MHCs can contribute to long-term adverse effects on health, resilience, and QoL [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]. High resilience and QoL are associated with lower severity of depression and anxiety and improved sleep, conversely low resilience and QoL can exacerbate these conditions [\u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e48\u003c/span\u003e, \u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e49\u003c/span\u003e]. Among MBS participants, 14% reported chronic conditions, and 31% met the criteria for low resilience and 57% for low/moderate QoL. In a review of 41 global studies, low resilience was reported among 33% of students [\u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e50\u003c/span\u003e] while a study in Spain reported low/moderate QoL among 34% of Spanish university student population [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]. Variations in prevalence across studies may be attributable to population biases, measurement tool and criteria defining MHCs, and time and geographic location of data collection. The high frequency of MHCs, low resilience and QoL, among MBS participants further supports a need to focus on strategies to support mental wellbeing among university students.\u003c/p\u003e \u003cp\u003eMBS identified top self-management care strategies to manage MHCs and wellbeing as physical activity, social interaction, and online activities. Others have previously identified music, social and physical activity to manage stress [\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e], and physical activity, spiritual growth, and stress management to manage wellbeing [\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e]. While physical and social interaction are pillars for mental wellbeing recommended by the GCBH [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e], the use of online activities (entertainment, gaming, and social media provided as examples) for MHCs and wellbeing management among MBS participants may represent activities of stress management and/or social interaction. However, evidence regarding the effects of online activity on MHCs is mixed depending on intensity and intention of use. A review reports excessive social media use is associated with higher risks of anxiety, depression, and sleep problems [\u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e51\u003c/span\u003e], while other study highlights that moderate or purposeful social media engagement can provide emotional support, reduce loneliness and MHCs\u0026rsquo; symptoms [\u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e52\u003c/span\u003e]. Query into content, frequency, type of activities, and patterns of engagement are necessary to evaluate effects of online activities. Fewer than 20% of MBS participants used health professionals or prescription medications to manage MHCs or wellbeing. This may be an under-representation given participants diagnosed with severe MHCs were ineligible for the study; alternatively, it may be that low/moderate symptoms may not display help seeking behaviours, or that barriers of cost, stigma, and general lack of knowledge about services limit use as reported among 18\u0026ndash;23 years old in US [\u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e53\u003c/span\u003e]. The results suggest knowledge and utilisation of lifestyle for mental wellbeing management among university students, which in future will be assessed in subgroup analyses and against qualitative responses to lifestyle attitudes.\u003c/p\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003eStrengths and limitations\u003c/h2\u003e \u003cp\u003eThe primary strengths of this study include insights to challenges in capturing survey health data among university students at minimal cost, and insights on frequency of MHCs and management strategies for mental wellbeing. The MBS dataset provides opportunities for longitudinal and mixed-methods epidemiological analyses to understand mental wellbeing among a diverse university student population.\u003c/p\u003e \u003cp\u003eLimitations are acknowledged; primarily generalisability of population profile due to biases in recruitment mostly from direct email and therefore potential desire to assist peers; in the population being predominantly female and from a single urban based university campus; and due to 55% attrition at follow-up. However, these biases are comparable to past wellbeing survey studies [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e, \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e] and methods to reduce these biases in future studies are suggested. The brevity of MBS survey, aiming to reduce responders\u0026rsquo; burden and increase completion, limits the detail of captured data; nevertheless, MBS is one of few with comprehensive quantitively and qualitative data on mental wellbeing self-management via lifestyle factors with a longitudinal design.\u003c/p\u003e \u003c/div\u003e"},{"header":"Conclusions","content":"\u003cp\u003eRecruitment and retention for collection of self-reported health data may benefit from co-design, collaboration, and incentive-based approaches. The frequent use of social, online, and physical activities to self-manage wellbeing warrant further investigation into their efficacy for mental wellbeing. Future research capturing data from male and rural based participants is needed.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAcknowledgments\u0026nbsp; \u0026nbsp; \u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors thank contributors assisting with pilot testing and promotion of MBS, study participants, and research funders.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData Availability Statement:\u0026nbsp;\u003c/strong\u003eData available upon reasonable request to NN.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor Contributions:\u003c/strong\u003e \u003cstrong\u003eXirun Yang:\u003c/strong\u003e investigation, methodology, data curation, formal analysis, original draft preparation, writing—review and editing, funding acquisition;\u0026nbsp;\u003cstrong\u003eSteve Simpson-Yap:\u003c/strong\u003e investigation, writing—review and editing; \u003cstrong\u003ePrince Atorkey:\u003c/strong\u003e writing—review and editing; \u003cstrong\u003eNupur Nag:\u003c/strong\u003e investigation, conceptualisation, methodology, visualization, original draft preparation, writing—review and editing, supervision, project administration, funding acquisition.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding:\u003c/strong\u003e China Scholarship Council - University of Melbourne PhD Scholarship to XY (under the supervision of NN). The University of Melbourne Population Health Investing in Research Students’ Training Grants to XY for MBS participant incentives. The funders had no role in the design of the study; in the collection, analyses, or interpretation of data; in the writing of the manuscript, or in the decision to publish the results.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eInstitutional Review Board Statement:\u0026nbsp;\u003c/strong\u003eStudy approved by The University of Melbourne Human Research Ethics Committee (ID: 2025-24145-64052-2).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eInformed Consent Statement\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eParticipants meeting the eligibility criteria were directed to read an online plain language statement and at the end of this document, requested to select a tick-box to confirm consent to participate in the study.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConflicts of Interest\u003c/strong\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThe author(s) declare no potential conflicts of interest.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eGBD. 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Curr Psychol. 2023;42(26):22645\u0026ndash;63.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAhmed O, Walsh EI, Dawel A, Alateeq K, Espinoza Oyarce DA, Cherbuin N. Social media use, mental health and sleep: A systematic review with meta-analyses. J Affect Disord. 2024;367:701\u0026ndash;12.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eNaslund JA, Bondre A, Torous J, Aschbrenner KA. Social Media and Mental Health: Benefits, Risks, and Opportunities for Research and Practice. J Technol Behav Sci. 2020;5(3):245\u0026ndash;57.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eCadigan JM, Lee CM, Larimer ME. Young Adult Mental Health: a Prospective Examination of Service Utilization, Perceived Unmet Service Needs, Attitudes, and Barriers to Service Use. Prev Sci. 2019;20(3):366\u0026ndash;76.\u003c/span\u003e\u003c/li\u003e\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":"[email protected]","identity":"bmc-public-health","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"pubh","sideBox":"Learn more about [BMC Public Health](http://bmcpublichealth.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/pubh/default.aspx","title":"BMC Public Health","twitterHandle":"@BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Mental health, self-management, lifestyle medicine, health data collection, observational study","lastPublishedDoi":"10.21203/rs.3.rs-9044751/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-9044751/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003eBackground:\u003c/strong\u003e Anxiety, depression, and poor sleep affect up to 41% of university students, with potential adverse impacts on academic performance and quality of life. How students manage their mental wellbeing may inform supports needed.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMethods:\u003c/strong\u003e An observational study recruited students enrolled at universities in Australia to complete an online survey assessing demographics, health behaviours, self-management strategies, and outcomes of anxiety, depression, sleep quality, resilience, and quality of life. Survey responders were emailed invitations to complete a follow-up survey six months later.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eResults:\u003c/strong\u003e The survey was opened by 1,976 persons; 47% met eligibility criteria, provided informed consent, and completed baseline survey. Majority participants were aged 18–25 years, female, non-Caucasian, international, and enrolled postgraduate. Validated tools revealed moderate/severe anxiety (27%), moderate/severe depression (29%), poor sleep quality (49%), low resilience (31%), and low/moderate quality of life (57%). Top mental wellbeing management strategies were social interaction, online activities and physical activities. Forty-five percent of participants (n=383) completed follow-up survey.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConclusions:\u003c/strong\u003e Recruitment and retention for collection of self-reported health data may benefit from co-design, collaboration, and incentive-based approaches. The frequent use of social, online, and physical activities to self-manage wellbeingwarrant further investigation into their efficacy for mental wellbeing.\u003c/p\u003e","manuscriptTitle":"Mind-Body Study: protocol for a prospective cohort investigating lifestyle behaviours and mental health outcomes among university students in Australia","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-04-09 00:42:34","doi":"10.21203/rs.3.rs-9044751/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"reviewersInvited","content":"","date":"2026-04-02T07:31:21+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2026-03-11T09:33:11+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2026-03-11T07:26:00+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2026-03-11T07:25:58+00:00","index":"","fulltext":""},{"type":"submitted","content":"BMC Public Health","date":"2026-03-06T00:43:42+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"bmc-public-health","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"pubh","sideBox":"Learn more about [BMC Public Health](http://bmcpublichealth.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/pubh/default.aspx","title":"BMC Public Health","twitterHandle":"@BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"3ea9e6e5-b2e9-40be-a6bd-b7c36cc928c9","owner":[],"postedDate":"April 9th, 2026","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[],"tags":[],"updatedAt":"2026-04-09T00:42:34+00:00","versionOfRecord":[],"versionCreatedAt":"2026-04-09 00:42:34","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-9044751","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-9044751","identity":"rs-9044751","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}