literature review about mental health of students

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• Published: 13 July 2021

Systematic review and meta-analysis of depression, anxiety, and suicidal ideation among Ph.D. students

• Emily N. Satinsky 1 ,
• Tomoki Kimura 2 ,
• Mathew V. Kiang 3 , 4 ,
• Rediet Abebe 5 , 6 ,
• Scott Cunningham 7 ,
• Hedwig Lee 8 ,
• Xiaofei Lin 9 ,
• Cindy H. Liu 10 , 11 ,
• Igor Rudan 12 ,
• Srijan Sen 13 ,
• Mark Tomlinson 14 , 15 ,
• Miranda Yaver 16 &
• Alexander C. Tsai 1 , 11 , 17  

Scientific Reports volume  11 , Article number:  14370 ( 2021 ) Cite this article

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• Epidemiology
• Health policy
• Quality of life

University administrators and mental health clinicians have raised concerns about depression and anxiety among Ph.D. students, yet no study has systematically synthesized the available evidence in this area. After searching the literature for studies reporting on depression, anxiety, and/or suicidal ideation among Ph.D. students, we included 32 articles. Among 16 studies reporting the prevalence of clinically significant symptoms of depression across 23,469 Ph.D. students, the pooled estimate of the proportion of students with depression was 0.24 (95% confidence interval [CI], 0.18–0.31; I 2  = 98.75%). In a meta-analysis of the nine studies reporting the prevalence of clinically significant symptoms of anxiety across 15,626 students, the estimated proportion of students with anxiety was 0.17 (95% CI, 0.12–0.23; I 2  = 98.05%). We conclude that depression and anxiety are highly prevalent among Ph.D. students. Data limitations precluded our ability to obtain a pooled estimate of suicidal ideation prevalence. Programs that systematically monitor and promote the mental health of Ph.D. students are urgently needed.

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Introduction.

Mental health problems among graduate students in doctoral degree programs have received increasing attention 1 , 2 , 3 , 4 . Ph.D. students (and students completing equivalent degrees, such as the Sc.D.) face training periods of unpredictable duration, financial insecurity and food insecurity, competitive markets for tenure-track positions, and unsparing publishing and funding models 5 , 6 , 7 , 8 , 9 , 10 , 11 , 12 —all of which may have greater adverse impacts on students from marginalized and underrepresented populations 13 , 14 , 15 . Ph.D. students’ mental health problems may negatively affect their physical health 16 , interpersonal relationships 17 , academic output, and work performance 18 , 19 , and may also contribute to program attrition 20 , 21 , 22 . As many as 30 to 50% of Ph.D. students drop out of their programs, depending on the country and discipline 23 , 24 , 25 , 26 , 27 . Further, while mental health problems among Ph.D. students raise concerns for the wellbeing of the individuals themselves and their personal networks, they also have broader repercussions for their institutions and academia as a whole 22 .

Despite the potential public health significance of this problem, most evidence syntheses on student mental health have focused on undergraduate students 28 , 29 or graduate students in professional degree programs (e.g., medical students) 30 . In non-systematic summaries, estimates of the prevalence of clinically significant depressive symptoms among Ph.D. students vary considerably 31 , 32 , 33 . Reliable estimates of depression and other mental health problems among Ph.D. students are needed to inform preventive, screening, or treatment efforts. To address this gap in the literature, we conducted a systematic review and meta-analysis to explore patterns of depression, anxiety, and suicidal ideation among Ph.D. students.

Flowchart of included articles.

The evidence search yielded 886 articles, of which 286 were excluded as duplicates (Fig.  1 ). An additional nine articles were identified through reference lists or grey literature reports published on university websites. Following a title/abstract review and subsequent full-text review, 520 additional articles were excluded.

Of the 89 remaining articles, 74 were unclear about their definition of graduate students or grouped Ph.D. and non-Ph.D. students without disaggregating the estimates by degree level. We obtained contact information for the authors of most of these articles (69 [93%]), requesting additional data. Three authors clarified that their study samples only included Ph.D. students 34 , 35 , 36 . Fourteen authors confirmed that their study samples included both Ph.D. and non-Ph.D. students but provided us with data on the subsample of Ph.D. students 37 , 38 , 39 , 40 , 41 , 42 , 43 , 44 , 45 , 46 , 47 , 48 , 49 , 50 . Where authors clarified that the sample was limited to graduate students in non-doctoral degree programs, did not provide additional data on the subsample of Ph.D. students, or did not reply to our information requests, we excluded the studies due to insufficient information (Supplementary Table S1 ).

Ultimately, 32 articles describing the findings of 29 unique studies were identified and included in the review 16 , 32 , 33 , 34 , 35 , 36 , 37 , 38 , 39 , 40 , 41 , 42 , 43 , 44 , 45 , 46 , 47 , 48 , 50 , 51 , 52 , 53 , 54 , 55 , 56 , 57 , 58 , 59 , 60 , 61 , 62 (Table 1 ). Overall, 26 studies measured depression, 19 studies measured anxiety, and six studies measured suicidal ideation. Three pairs of articles reported data on the same sample of Ph.D. students 33 , 38 , 45 , 51 , 53 , 56 and were therefore grouped in Table 1 and reported as three studies. Publication dates ranged from 1979 to 2019, but most articles (22/32 [69%]) were published after 2015. Most studies were conducted in the United States (20/29 [69%]), with additional studies conducted in Australia, Belgium, China, Iran, Mexico, and South Korea. Two studies were conducted in cross-national settings representing 48 additional countries. None were conducted in sub-Saharan Africa or South America. Most studies included students completing their degrees in a mix of disciplines (17/29 [59%]), while 12 studies were limited to students in a specific field (e.g., biomedicine, education). The median sample size was 172 students (interquartile range [IQR], 68–654; range, 6–6405). Seven studies focused on mental health outcomes in demographic subgroups, including ethnic or racialized minority students 37 , 41 , 43 , international students 47 , 50 , and sexual and gender minority students 42 , 54 .

In all, 16 studies reported the prevalence of depression among a total of 23,469 Ph.D. students (Fig.  2 ; range, 10–47%). Of these, the most widely used depression scales were the PHQ-9 (9 studies) and variants of the Center for Epidemiologic Studies-Depression scale (CES-D, 4 studies) 63 , and all studies assessed clinically significant symptoms of depression over the past one to two weeks. Three of these studies reported findings based on data from different survey years of the same parent study (the Healthy Minds Study) 40 , 42 , 43 , but due to overlap in the survey years reported across articles, these data were pooled. Most of these studies were based on data collected through online surveys (13/16 [81%]). Ten studies (63%) used random or systematic sampling, four studies (25%) used convenience sampling, and two studies (13%) used multiple sampling techniques.

Pooled estimate of the proportion of Ph.D. students with clinically significant symptoms of depression.

The estimated proportion of Ph.D. students assessed as having clinically significant symptoms of depression was 0.24 (95% confidence interval [CI], 0.18–0.31; 95% predictive interval [PI], 0.04–0.54), with significant evidence of between-study heterogeneity (I 2  = 98.75%). A subgroup analysis restricted to the twelve studies conducted in the United States yielded similar findings (pooled estimate [ES] = 0.23; 95% CI, 0.15–0.32; 95% PI, 0.01–0.60), with no appreciable difference in heterogeneity (I 2  = 98.91%). A subgroup analysis restricted to the studies that used the PHQ-9 to assess depression yielded a slightly lower prevalence estimate and a slight reduction in heterogeneity (ES = 0.18; 95% CI, 0.14–0.22; 95% PI, 0.07–0.34; I 2  = 90.59%).

Nine studies reported the prevalence of clinically significant symptoms of anxiety among a total of 15,626 Ph.D. students (Fig.  3 ; range 4–49%). Of these, the most widely used anxiety scale was the 7-item Generalized Anxiety Disorder scale (GAD-7, 5 studies) 64 . Data from three of the Healthy Minds Study articles were pooled into two estimates, because the scale used to measure anxiety changed midway through the parent study (i.e., the Patient Health Questionnaire-Generalized Anxiety Disorder [PHQ-GAD] scale was used from 2007 to 2012 and then switched to the GAD-7 in 2013 40 ). Most studies (8/9 [89%]) assessed clinically significant symptoms of anxiety over the past two to four weeks, with the one remaining study measuring anxiety over the past year. Again, most of these studies were based on data collected through online surveys (7/9 [78%]). Five studies (56%) used random or systematic sampling, two studies (22%) used convenience sampling, and two studies (22%) used multiple sampling techniques.

Pooled estimate of the proportion of Ph.D. students with clinically significant symptoms of anxiety.

The estimated proportion of Ph.D. students assessed as having anxiety was 0.17 (95% CI, 0.12–0.23; 95% PI, 0.02–0.41), with significant evidence of between-study heterogeneity (I 2  = 98.05%). The subgroup analysis restricted to the five studies conducted in the United States yielded a slightly lower proportion of students assessed as having anxiety (ES = 0.14; 95% CI, 0.08–0.20; 95% PI, 0.00–0.43), with no appreciable difference in heterogeneity (I 2  = 98.54%).

Six studies reported the prevalence of suicidal ideation (range, 2–12%), but the recall windows varied greatly (e.g., ideation within the past 2 weeks vs. past year), precluding pooled estimation.

Additional stratified pooled estimates could not be obtained. One study of Ph.D. students across 54 countries found that phase of study was a significant moderator of mental health, with students in the comprehensive examination and dissertation phases more likely to experience distress compared with students primarily engaged in coursework 59 . Other studies identified a higher prevalence of mental ill-health among women 54 ; lesbian, gay, bisexual, transgender, and queer (LGBTQ) students 42 , 54 , 60 ; and students with multiple intersecting identities 54 .

Several studies identified correlates of mental health problems including: project- and supervisor-related issues, stress about productivity, and self-doubt 53 , 62 ; uncertain career prospects, poor living conditions, financial stressors, lack of sleep, feeling devalued, social isolation, and advisor relationships 61 ; financial challenges 38 ; difficulties with work-life balance 58 ; and feelings of isolation and loneliness 52 . Despite these challenges, help-seeking appeared to be limited, with only about one-quarter of Ph.D. students reporting mental health problems also reporting that they were receiving treatment 40 , 52 .

Risk of bias

Twenty-one of 32 articles were assessed as having low risk of bias (Supplementary Table S2 ). Five articles received one point for all five categories on the risk of bias assessment (lowest risk of bias), and one article received no points (highest risk). The mean risk of bias score was 3.22 (standard deviation, 1.34; median, 4; IQR, 2–4). Restricting the estimation sample to 12 studies assessed as having low risk of bias, the estimated proportion of Ph.D. students with depression was 0.25 (95% CI, 0.18–0.33; 95% PI, 0.04–0.57; I 2  = 99.11%), nearly identical to the primary estimate, with no reduction in heterogeneity. The estimated proportion of Ph.D. students with anxiety, among the 7 studies assessed as having low risk of bias, was 0.12 (95% CI, 0.07–0.17; 95% PI, 0.01–0.34; I 2  = 98.17%), again with no appreciable reduction in heterogeneity.

In our meta-analysis of 16 studies representing 23,469 Ph.D. students, we estimated that the pooled prevalence of clinically significant symptoms of depression was 24%. This estimate is consistent with estimated prevalence rates in other high-stress biomedical trainee populations, including medical students (27%) 30 , resident physicians (29%) 65 , and postdoctoral research fellows (29%) 66 . In the sample of nine studies representing 15,626 Ph.D. students, we estimated that the pooled prevalence of clinically significant symptoms of anxiety was 17%. While validated screening instruments tend to over-identify cases of depression (relative to structured clinical interviews) by approximately a factor of two 67 , 68 , our findings nonetheless point to a major public health problem among Ph.D. students. Available data suggest that the prevalence of depressive and anxiety disorders in the general population ranges from 5 to 7% worldwide 69 , 70 . In contrast, prevalence estimates of major depressive disorder among young adults have ranged from 13% (for young adults between the ages of 18 and 29 years in the 2012–2013 National Epidemiologic Survey on Alcohol and Related Conditions III 71 ) to 15% (for young adults between the ages of 18 and 25 in the 2019 U.S. National Survey on Drug Use and Health 72 ). Likewise, the prevalence of generalized anxiety disorder was estimated at 4% among young adults between the ages of 18 and 29 in the 2001–03 U.S. National Comorbidity Survey Replication 73 . Thus, even accounting for potential upward bias inherent in these studies’ use of screening instruments, our estimates suggest that the rates of recent clinically significant symptoms of depression and anxiety are greater among Ph.D. students compared with young adults in the general population.

Further underscoring the importance of this public health issue, Ph.D. students face unique stressors and uncertainties that may put them at increased risk for mental health and substance use problems. Students grapple with competing responsibilities, including coursework, teaching, and research, while also managing interpersonal relationships, social isolation, caregiving, and financial insecurity 3 , 10 . Increasing enrollment in doctoral degree programs has not been matched with a commensurate increase in tenure-track academic job opportunities, intensifying competition and pressure to find employment post-graduation 5 . Advisor-student power relations rarely offer options for recourse if and when such relationships become strained, particularly in the setting of sexual harassment, unwanted sexual attention, sexual coercion, and rape 74 , 75 , 76 , 77 , 78 . All of these stressors may be magnified—and compounded by stressors unrelated to graduate school—for subgroups of students who are underrepresented in doctoral degree programs and among whom mental health problems are either more prevalent and/or undertreated compared with the general population, including Black, indigenous, and other people of color 13 , 79 , 80 ; women 81 , 82 ; first-generation students 14 , 15 ; people who identify as LGBTQ 83 , 84 , 85 ; people with disabilities; and people with multiple intersecting identities.

Structural- and individual-level interventions will be needed to reduce the burden of mental ill-health among Ph.D. students worldwide 31 , 86 . Despite the high prevalence of mental health and substance use problems 87 , Ph.D. students demonstrate low rates of help-seeking 40 , 52 , 88 . Common barriers to help-seeking include fears of harming one’s academic career, financial insecurity, lack of time, and lack of awareness 89 , 90 , 91 , as well as health care systems-related barriers, including insufficient numbers of culturally competent counseling staff, limited access to psychological services beyond time-limited psychotherapies, and lack of programs that address the specific needs either of Ph.D. students in general 92 or of Ph.D. students belonging to marginalized groups 93 , 94 . Structural interventions focused solely on enhancing student resilience might include programs aimed at reducing stigma, fostering social cohesion, and reducing social isolation, while changing norms around help-seeking behavior 95 , 96 . However, structural interventions focused on changing stressogenic aspects of the graduate student environment itself are also needed 97 , beyond any enhancements to Ph.D. student resilience, including: undercutting power differentials between graduate students and individual faculty advisors, e.g., by diffusing power among multiple faculty advisors; eliminating racist, sexist, and other discriminatory behaviors by faculty advisors 74 , 75 , 98 ; valuing mentorship and other aspects of “invisible work” that are often disproportionately borne by women faculty and faculty of color 99 , 100 ; and training faculty members to emphasize the dignity of, and adequately prepare Ph.D. students for, non-academic careers 101 , 102 .

Our findings should be interpreted with several limitations in mind. First, the pooled estimates are characterized by a high degree of heterogeneity, similar to meta-analyses of depression prevalence in other populations 30 , 65 , 103 , 104 , 105 . Second, we were only able to aggregate depression prevalence across 16 studies and anxiety prevalence across nine studies (the majority of which were conducted in the U.S.) – far fewer than the 183 studies included in a meta-analysis of depression prevalence among medical students 30 and the 54 studies included in a meta-analysis of resident physicians 65 . These differences underscore the need for more rigorous study in this critical area. Many articles were either excluded from the review or from the meta-analyses for not meeting inclusion criteria or not reporting relevant statistics. Future research in this area should ensure the systematic collection of high-quality, clinically relevant data from a comprehensive set of institutions, across disciplines and countries, and disaggregated by graduate student type. As part of conducting research and addressing student mental health and wellbeing, university deans, provosts, and chancellors should partner with national survey and program institutions (e.g., Graduate Student Experience in the Research University [gradSERU] 106 , the American College Health Association National College Health Assessment [ACHA-NCHA], and HealthyMinds). Furthermore, federal agencies that oversee health and higher education should provide resources for these efforts, and accreditation agencies should require monitoring of mental health and programmatic responses to stressors among Ph.D. students.

Third, heterogeneity in reporting precluded a meta-analysis of the suicidality outcomes among the few studies that reported such data. While reducing the burden of mental health problems among graduate students is an important public health aim in itself, more research into understanding non-suicidal self-injurious behavior, suicide attempts, and completed suicide among Ph.D. students is warranted. Fourth, it is possible that the grey literature reports included in our meta-analysis are more likely to be undertaken at research-intensive institutions 52 , 60 , 61 . However, the direction of bias is unpredictable: mental health problems among Ph.D. students in research-intensive environments may be more prevalent due to detection bias, but such institutions may also have more resources devoted to preventive, screening, or treatment efforts 92 . Fifth, inclusion in this meta-analysis and systematic review was limited to those based on community samples. Inclusion of clinic-based samples, or of studies conducted before or after specific milestones (e.g., the qualifying examination or dissertation prospectus defense), likely would have yielded even higher pooled prevalence estimates of mental health problems. And finally, few studies provided disaggregated data according to sociodemographic factors, stage of training (e.g., first year, pre-prospectus defense, all-but-dissertation), or discipline of study. These factors might be investigated further for differences in mental health outcomes.

Clinically significant symptoms of depression and anxiety are pervasive among graduate students in doctoral degree programs, but these are understudied relative to other trainee populations. Structural and clinical interventions to systematically monitor and promote the mental health and wellbeing of Ph.D. students are urgently needed.

This systematic review and meta-analysis follows the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) approach (Supplementary Table S3 ) 107 . This study was based on data collected from publicly available bibliometric databases and did not require ethical approval from our institutional review boards.

Eligibility criteria

Studies were included if they provided data on either: (a) the number or proportion of Ph.D. students with clinically significant symptoms of depression or anxiety, ascertained using a validated scale; or (b) the mean depression or anxiety symptom severity score and its standard deviation among Ph.D. students. Suicidal ideation was examined as a secondary outcome.

We excluded studies that focused on graduate students in non-doctoral degree programs (e.g., Master of Public Health) or professional degree programs (e.g., Doctor of Medicine, Juris Doctor) because more is known about mental health problems in these populations 30 , 108 , 109 , 110 and because Ph.D. students face unique uncertainties. To minimize the potential for upward bias in our pooled prevalence estimates, we excluded studies that recruited students from campus counseling centers or other clinic-based settings. Studies that measured affective states, or state anxiety, before or after specific events (e.g., terrorist attacks, qualifying examinations) were also excluded.

If articles described the study sample in general terms (i.e., without clarifying the degree level of the participants), we contacted the authors by email for clarification. Similarly, if articles pooled results across graduate students in doctoral and non-doctoral degree programs (e.g., reporting a single estimate for a mixed sample of graduate students), we contacted the authors by email to request disaggregated data on the subsample of Ph.D. students. If authors did not reply after two contact attempts spaced over 2 months, or were unable to provide these data, we excluded these studies from further consideration.

Search strategy and data extraction

PubMed, Embase, PsycINFO, ERIC, and Business Source Complete were searched from inception of each database to November 5, 2019. The search strategy included terms related to mental health symptoms (e.g., depression, anxiety, suicide), the study population (e.g., graduate, doctoral), and measurement category (e.g., depression, Columbia-Suicide Severity Rating Scale) (Supplementary Table S4 ). In addition, we searched the reference lists and the grey literature.

After duplicates were removed, we screened the remaining titles and abstracts, followed by a full-text review. We excluded articles following the eligibility criteria listed above (i.e., those that were not focused on Ph.D. students; those that did not assess depression and/or anxiety using a validated screening tool; those that did not report relevant statistics of depression and/or anxiety; and those that recruited students from clinic-based settings). Reasons for exclusion were tracked at each stage. Following selection of included articles, two members of the research team extracted data and conducted risk of bias assessments. Discrepancies were discussed with a third member of the research team. Key extraction variables included: study design, geographic region, sample size, response rate, demographic characteristics of the sample, screening instrument(s) used for assessment, mean depression or anxiety symptom severity score (and its standard deviation), and the number (or proportion) of students experiencing clinically significant symptoms of depression or anxiety.

Risk of bias assessment

Following prior work 30 , 65 , the Newcastle–Ottawa Scale 111 was adapted and used to assess risk of bias in the included studies. Each study was assessed across 5 categories: sample representativeness, sample size, non-respondents, ascertainment of outcomes, and quality of descriptive statistics reporting (Supplementary Information S5 ). Studies were judged as having either low risk of bias (≥ 3 points) or high risk of bias (< 3 points).

Analysis and synthesis

Before pooling the estimated prevalence rates across studies, we first transformed the proportions using a variance-stabilizing double arcsine transformation 112 . We then computed pooled estimates of prevalence using a random effects model 113 . Study specific confidence intervals were estimated using the score method 114 , 115 . We estimated between-study heterogeneity using the I 2 statistic 116 . In an attempt to reduce the extent of heterogeneity, we re-estimated pooled prevalence restricting the analysis to studies conducted in the United States and to studies in which depression assessment was based on the 9-item Patient Health Questionnaire (PHQ-9) 117 . All analyses were conducted using Stata (version 16; StataCorp LP, College Station, Tex.). Where heterogeneity limited our ability to summarize the findings using meta-analysis, we synthesized the data using narrative review.

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Acknowledgements

We thank the following investigators for generously sharing their time and/or data: Gordon J. G. Asmundson, Ph.D., Amy J. L. Baker, Ph.D., Hillel W. Cohen, Dr.P.H., Alcir L. Dafre, Ph.D., Deborah Danoff, M.D., Daniel Eisenberg, Ph.D., Lou Farrer, Ph.D., Christy B. Fraenza, Ph.D., Patricia A. Frazier, Ph.D., Nadia Corral-Frías, Ph.D., Hanga Galfalvy, Ph.D., Edward E. Goldenberg, Ph.D., Robert K. Hindman, Ph.D., Jürgen Hoyer, Ph.D., Ayako Isato, Ph.D., Azharul Islam, Ph.D., Shanna E. Smith Jaggars, Ph.D., Bumseok Jeong, M.D., Ph.D., Ju R. Joeng, Nadine J. Kaslow, Ph.D., Rukhsana Kausar, Ph.D., Flavius R. W. Lilly, Ph.D., Sarah K. Lipson, Ph.D., Frances Meeten, D.Phil., D.Clin.Psy., Dhara T. Meghani, Ph.D., Sterett H. Mercer, Ph.D., Masaki Mori, Ph.D., Arif Musa, M.D., Shizar Nahidi, M.D., Ph.D., Arthur M. Nezu, Ph.D., D.H.L., Angelo Picardi, M.D., Nicole E. Rossi, Ph.D., Denise M. Saint Arnault, Ph.D., Sagar Sharma, Ph.D., Bryony Sheaves, D.Clin.Psy., Kennon M. Sheldon, Ph.D., Daniel Shepherd, Ph.D., Keisuke Takano, Ph.D., Sara Tement, Ph.D., Sherri Turner, Ph.D., Shawn O. Utsey, Ph.D., Ron Valle, Ph.D., Caleb Wang, B.S., Pengju Wang, Katsuyuki Yamasaki, Ph.D.

A.C.T. acknowledges funding from the Sullivan Family Foundation. This paper does not reflect an official statement or opinion from the County of San Mateo.  

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A.C.T. conceptualized the study and provided supervision. T.K. conducted the search. E.N.S. contacted authors for additional information not reported in published articles. E.N.S. and T.K. extracted data and performed the quality assessment appraisal. E.N.S. and A.C.T. conducted the statistical analysis and drafted the manuscript. T.K., M.V.K., R.A., S.C., H.L., X.L., C.H.L., I.R., S.S., M.T. and M.Y. contributed to the interpretation of the results. All authors provided critical feedback on drafts and approved the final manuscript.

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Mental health literacy in a diverse sample of undergraduate students: demographic, psychological, and academic correlates

• Rona Miles   ORCID: orcid.org/0000-0002-4216-8739 1 ,
• Laura Rabin 1 ,
• Anjali Krishnan 1 ,
• Evan Grandoit 1 , 2 &
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Investigating variables associated with mental health literacy in the college-age population takes us one step closer to providing intervention for this vulnerable group, where growing rates of psychological disorders are a serious public concern. This study adds to the existing literature by incorporating, within a single model, multi-faceted variables (demographic, psychological, and academic) that contribute to mental health literacy in demographically and ethnically diverse college students.

Participants were undergraduate students enrolled at nine different colleges that are part of a large, urban, public university system. A total of 1213 respondents (62.0% female, 73.3% non-white) completed an in-person assessment of mental health literacy and answered questions about demographics, college experience, and mental health experience. Data were analyzed to identify which variables best discriminated between high, mid-level, and low performers on this assessment.

Discriminant correspondence analysis revealed that the difference between high and low performers (accounting for 90.27% of the total variance) was driven by participants who had taken at least one course related to clinical psychology and who typically majored in psychology and applied health science fields. These participants were more likely to report being white, female, between the ages of 28–32, and in the fourth year or later of their undergraduate program. In addition, high performers were more likely to have been diagnosed and/or treated for a psychological disorder, have more experience with psychological disorders through personal, family, or peer history, and have families who are open to discussing mental health issues.

The main contributor to variation in mental health literacy scores was having taken a clinical psychology course, followed by majoring in psychology. Importantly, our findings identified not only the high performers, but also the low performers, for whom an increase in knowledge and awareness of mental health is crucial to overall psychological well-being. These results have important implications for the design of educational interventions aimed at improving mental health literacy at the college level, especially for students who otherwise would not have been exposed to this information from coursework or their major.

Peer Review reports

Mental health literacy—defined as knowledge and beliefs regarding psychological disorders, which in turn fosters the ability to identify, manage, and prevent such disorders—originated in Jorm et al.’s [ 1 ] influential paper on this topic. Included in this definition are recognition of the symptoms of psychological disorders, knowledge of their causes and risk factors, attitudes regarding mental health, and the capacity to access both mental health information and professional services. Emerging from this multifaceted construct is the premise that improving the level of mental health literacy within communities and the public at large can lead to early recognition and appropriate intervention for psychological disorders. Due to the high prevalence rates of mental health issues that occur in the college population [ 2 , 3 ] and because early adulthood is frequently the time of onset for common psychological disorders [ 4 ], increasing the mental health literacy of college students is crucial.

Concerns regarding the college population are further established by a recent national survey conducted by the American College Health Association, where when asked about their experiences in the past 12 months, more than 45% of undergraduate students reported having had difficulty functioning due to depression, and more than 65% reported having had overwhelming anxiety [ 5 ]. Furthermore, in a recent international study by the World Health Organization, more than 30% of first-year undergraduates reported that at some point in the past 12 months, they experienced at least one of the mood, anxiety, or substance disorders addressed in the survey [ 6 ].

With the goal of facilitating better mental health literacy for college students, it is critical to identify the factors related to both increased and decreased knowledge in this area. Doing so provides a unique opportunity to highlight student groups in need of interventions, which when implemented, have the potential to improve mental health literacy in this vulnerable population.

Demographic and psychological factors associated with mental health literacy

The variable that has most often been studied in relation to mental health literacy is gender, with females repeatedly associated with better mental health literacy. Specifically, females displayed higher rates of recognition than males in studies that have focused on depression [ 7 , 8 , 9 , 10 ] and anxiety disorders [ 11 ], and male gender has been associated with poor mental health literacy in relation to depression [ 12 , 13 ] and eating disorders [ 14 ]. It does seem, however, that gender differences may vary based on disorder being addressed, as a gender difference was apparent for knowledge of depression, but not for knowledge of psychosis [ 12 ]. In line with this finding, females perceived a greater need for treatment than did males for both generalized anxiety disorder and psychosis, but no gender difference was observed regarding perceived need for treatment for depression [ 15 ]. Furthermore, one study did not report any gender differences in overall mental health literacy [ 16 ]. Thus, despite some inconsistencies, overall the literature supports the association of female gender with higher mental health literacy.

In looking at age as a factor associated with mental health literacy, performance of different age groups within studies was compared. One study found that participants in the 18–29 age group displayed higher rates of identification for most anxiety-related disorders as compared to those in the 30–44 and 45–71 age groups [ 11 ]. Additionally, another study found that a greater proportion of participants in the youngest age group (20–34 years) showed evidence of depression recognition, as compared to those in the two older age groups (35–49 years and 50–64 years) [ 7 ]. Furthermore, in a study on mental health literacy for depression, participants ages 60–69 were determined to have poor cognition in relation to depression when compared to participants ages 30–59 [ 13 ]. Similarly, another study determined that participants age 70 and older showed lower ability to recognize symptoms of depression than those in all other age groups (18–24 years; 25–39 years; 40–54 years; 55–69 years) [ 17 ]. However, in this same study, those in the youngest group (18–24 years) were more likely than those in the oldest group (70+ years) to incorrectly identify schizophrenia as depression. Challenging the findings that age in general relates to better mental health literacy, no differences were found between those in the 18–24 age group and those in the 25–64 age group in terms of general knowledge of mental health [ 16 ]. Therefore, though there seems to be an association between age and mental health literacy, more research is needed in order to establish a clear pattern of findings.

Research has also examined whether experience with mental health-related issues is associated with mental health literacy, with mixed results. In a study that assessed recognition of depression and schizophrenia, previous personal experience with mental health treatment was associated with symptom recognition of these disorders [ 18 ]. Furthermore, a study that assessed participants’ ability to identify depression found that having a personal history of treatment for a mental health issue correlated with more positive perceptions about treatment [ 7 ]. However, in this same study, neither a personal history of a mental health issue, nor a current episode of depression, was associated with better depression recognition. Adding to these discrepant findings, as the number of psychological diagnoses that participants experienced over the course of their lives increased, and as the number of mental health services being used by their families increased, so did their mental health literacy for mood disorders [ 19 ]. This study also found that as the number of current diagnoses of participants increased, knowledge of mood disorders decreased, perhaps suggesting that the presence of current diagnoses negatively impacts mental health literacy. Additionally, severity of a disorder has been found to influence mental health literacy, as one study found that participants categorized as “high” depressed were significantly less likely to recognize depression in comparison to those categorized as “low” depressed [ 8 ]. Further complicating the attempt to find an overall relationship between experience with mental health-related issues and mental health literacy, no association was found between personal experience with mental illness and mental health literacy for anxiety disorders [ 11 ]. Due to these inconsistent findings, personal experience and its relation to mental health literacy should be further examined.

Factors associated with mental health literacy related to college experience

Several studies have focused on factors related to mental health literacy in college students [ 8 , 9 , 18 , 20 , 21 , 22 , 23 ] with some of these studies investigating variables specifically related to college experience, such as year in college and field of study. In line with findings that correct recognition of depression was associated with being in the later years of college study [ 22 ], male graduate students were found to have higher mental health literacy than undergraduates [ 21 ]. Regarding field of study, participants who had studied psychology and medicine had the highest true symptom scores for both schizophrenia and depression, when compared to students from other disciplines [ 18 ], and medically-focused undergraduates were more adept at recognizing depression and knowing about appropriate treatment options [ 22 ]. Supporting this finding, participants who had studied psychology or psychiatry reported that they recognized and could define the disorders more often than did students of other fields of study [ 20 ]. Thus, evidence seems consistent that both higher years of study and field of study are related to mental health literacy, however, these studies are not common, and additional variables directly related to college experience should be investigated for a more comprehensive understanding of the factors associated with mental health literacy in the college population.

Current study

Based on a comprehensive review of the literature, we identified several gaps in knowledge related to factors associated with mental health literacy. Some studies included a limited number of variables in their models, and many studies assessed knowledge of just 1–2 disorders, particularly depression and schizophrenia or just depression. Most importantly, however, there are a limited number of studies addressing the factors related to mental health literacy in a college population, few of which include variables related particularly to college experience. The current study seeks to improve upon existing research by: 1) incorporating multifaceted demographic, psychological, and academic variables within a single model, and 2) assessing knowledge and related topics of more than 20 psychological disorders from the DSM-5 [ 24 ]. Some of our included variables have been utilized previously, while others, to our knowledge, are novel and directly relevant to college students’ experiences. Through this comprehensive approach, we seek to capture the variance in performance on an assessment of mental health literacy for college students for the vital purpose of improving knowledge and awareness of mental health in this at-risk population.

Participants and procedure

Data were collected from undergraduate students enrolled at nine different colleges that are part of a large, urban, public university system in the northeastern United States. Using a convenience sampling method, participants were most commonly recruited in classrooms, after members of the research team obtained permission from professors to administer surveys during class time. Other methods of recruitment and administration included in-person invitation in populated campus locations (e.g., cafeterias, student lounges), postings in college-generated subject pool listings, and scheduled administration periods conducted in reserved classrooms. Students were given $5 for their participation, except those from the subject pool who were given research credit. Participants’ multiple choice and handwritten responses were entered into a Statistical Program for Social Sciences (SPSS; [ 25 ]) database and each entry was double-checked for accuracy.

A power analysis was conducted using G*Power3 [ 26 ], with conservative estimates at 1% significance level, 50% power and a small effect size (f = 0.05). Based on the power analysis (under the assumptions of a MANOVA framework [ 27 ]), a total sample size of 300 participants would be required to detect differences in the three performance levels (low, mid-level, high) for mental health literacy scores based on the 11 variables included in the analysis.

This study was designed as a paper-and-pencil survey, which was administered exclusively in-person to prevent participants from searching online for answers to the mental health literacy items. Before taking the survey, the study’s purpose and procedures were read to prospective participants by research assistants, including that the study was about mental health literacy and would take approximately 30–40 min. Prospective participants were also told that participation was voluntary and that they could withdraw at any point without consequence. All methods of recruitment, consent, and administration were conducted according to an IRB-approved protocol.

A two-page form preceded the actual survey and inquired about four areas: (1) demographics; (2) college experience; (3) mental health experience; and (4) openness to mental health issues. Participants then answered items from the Mental Health Literacy Assessment for College Students (MHLA-c), which was created by licensed clinical psychologists with expertise in the field of psychopathology and higher education, with some items adapted from the Multiple-Choice Knowledge of Mental Illnesses Test/MC-KOMIT [ 28 ]. The MHLA-c is a uni-dimensional instrument, with scores approximately normally distributed, and with preliminary psychometric support including evidence for internal consistency reliability, content validity, and construct validity (refer to [ 29 ], for information related to measure development and validation).

To reduce participant burden, as students completed multiple-choice items from the MHLA-c and a two-page form related to demographic and relevant experiential variables, the MHLA-c items were split into two different forms, which each included 38 items (see Additional file 1 for sample items). These items consisted of multiple-choice questions with five possible answer choices, and drew on knowledge and related topics of more than 20 disorders from the DSM-5 [ 24 ]. Content domains included: (1) knowledge of mental health disorders including etiology, risk factors, diagnoses, symptoms, treatment, course of illness, and outcome; and (2) application of content knowledge including level of insight, manifestation of symptoms in everyday life, responding to others, accessing help from professionals, and prevention of negative outcomes [ 29 ].

Organization of variables

We used percent correct to quantify performance. However, our goal was not to look at individual participant performance, but rather to differentiate between participants who had varying degrees of mental health literacy. Therefore, we categorized participants into low performers (0–32% correct), mid-level performers (33–67% correct), and high performers (68–100% correct) in an attempt to target specific categories of performance. Age was binned into five categories (18–22, 23–27, 28–32, 33–37, and 38+ years) to differentiate the traditional undergraduate college students from those who typically spend more time completing their undergraduate studies or are returning for a college degree. Variables such as gender and ethnicity were scored categorically. Coursework was binned into two categories (presence or absence of a course related to clinical psychology), and included courses such as abnormal psychology, abnormal psychology in children, psychotherapy, and counseling psychology. Current year in college was binned into three categories (first or second year, third year, and fourth year or later) and college major was binned into seven categories (psychology, applied health sciences, STEM [science, technology, engineering, mathematics], humanities/social sciences, business/economics/accounting, education, and other). Responses to experience with psychological disorders were binned on level of exposure (none, some, or more) of personal, family, or peer history with psychological disorders. Finally, personal diagnosis and/or treatment of a psychological disorder was binned into two categories (presence or absence), as was openness of immediate family to talking about mental health issues (yes or no), and consideration of using campus academic and/or mental health services (yes or no).

Statistical analyses

The purpose of this study was to identify which variables best discriminated between high, mid-level, and low performers on an assessment of mental health literacy. As our research question was correlational rather than predictive in nature, and our data were a combination of categorical, numeric, and ordinal variables, we used a discriminant correspondence analysis or DiCA [ 30 , 31 ], which preserves the inherent categorical nature of these multivariate data as opposed to a traditional discriminant analysis or logistic regression. DiCA is an extension of Correspondence Analysis and Multiple Correspondence Analysis [ 32 , 33 ], and these techniques handle categorical data in the same way that discriminant analysis and principal components analysis handle continuous data [ 30 ]. DiCA analyzes the differences between categories of observations (e.g., performance levels) based on multiple variables (e.g., age, gender, field of study), and represents these differences in the form of new, uncorrelated variables known as components, which are linear combinations of the original variables. These components reveal how categories of observations (e.g., performance levels) are different from each other, and which variables (e.g., age, gender, field of study) contribute to those differences. For a particular component, categories that are dissimilar to each other are oppositely signed, and categories that are similar to each other have the same sign (see [ 34 ] for a more detailed application of DiCA).

In the current study, DiCA was used to identify qualitative differences between patterns of responses on mental health literacy scores based on demographics (age, gender, ethnicity), college experience (year in college, college major, coursework), mental health experience (having been diagnosed and/or treated for a psychological disorder, having experience based on personal, family, or peer history with a psychological disorder), and openness to mental health issues (considering the use of academic and/or mental health college services, openness of family to discuss mental health issues).

Inference procedures

For DiCA, a permutation test is used to determine whether the overall variance of the data is statistically significant, and to also determine whether the variance explained by each component is statistically significant [ 35 ]. In addition, bootstrap tests are used to generate multivariate confidence intervals to differentiate between categories in the overall component space, and to also identify which variables significantly contribute to each component [ 31 , 34 , 36 , 37 , 38 , 39 ] (see [ 34 ] for more details on inference procedures). While data organization was performed on SPSS and Microsoft Excel (2011), all further statistical analyses were conducted in R [ 40 ] as DiCA was specifically created using the R programming language [ 41 ]. Tables for descriptive statistics were generated using jamovi (also an R-based software; [ 42 ]).

Descriptive findings

Data were collected from 1255 participants, but due to missing data, 42 participants were excluded from the final statistical analysis, which resulted in a final sample size of 1213 participants. Specifically, 18 participants omitted the questions on diagnosis and/or treatment; 14 omitted their age; 6 omitted their year in college; 2 omitted their ethnicity; 1 omitted gender; and 1 omitted both questions on age and diagnosis and/or treatment.

The final set of variables, their levels, and a summary of the descriptive statistics can be found in Table  1 . Mental health literacy scores were approximately normally distributed and categorized as follows: 18.2% fell into the 0 – 32nd percentile (low); 53.5% fell into the 33 – 67th percentile (medium); and 28.3% fell into the 68 – 100th percentile (high).

DiCA findings

DiCA generated two components that described the overall variance of the data. Component 1 represented the difference between high-performers and low performers, while component 2 represented the difference between the mid-level performers and all other performers (Fig.  1 , center panel). The overall variance (also known as inertia ) was found to be statistically significant via a permutation test (inertia = 0.049, p perm  < 0.001). The variance explained by each component was also statistically significant (component 1 = 90.27%, p perm  < 0.001, component 2 = 9.73%, p perm  < 0.001), via separate permutation tests. The reliability of assignment of individuals to their respective performance categories (low, mid-level, high) was also found to be statistically significant ( R 2  = 0.18, p perm  < 0.001). Finally, bootstrap ratio tests showed that low, mid-level, and high performers statistically differed from each other ( p boot  < 0.001) and contributed to the overall variance of the data (Table  2 ).

Results from DiCA showing bootstrap confidence intervals for three performance levels (center), and bootstrap ratio bars for statistically significant variables associated with high performers (left) and low performers (right) for component 1. Longer bars represent more reliable variables associated with performance, while shorter bars represent statistically significant, but less reliable variables associated with performance. The dotted vertical lines represent a p  < 0.05 threshold such that variables that do not cross the dotted lines (shown in light grey) are not statistically significant for that component

These findings imply that overall there exists a statistically significant difference in the levels of mental health literacy performance across participants. Specifically, the largest variance in the data was explained by the difference in the pattern of responses of low performers as compared to high performers, followed by the pattern of responses of mid-level performers.

In order to determine which variables significantly contributed to the variance explained by both component 1 and component 2, additional bootstrap tests were conducted for each variable (Table  3 ). The variables that significantly contributed to the difference between the high and low performers were: coursework related to clinical psychology, college major, diagnosis and/or treatment for a psychological disorder, ethnicity, year in college, gender, experience with psychological disorders based on personal, family or peer history, family openness to discussing mental health issues, and age (Fig. 1 , right and left panels).

Component 1 specifically revealed that high-performers were more likely to have taken at least one course related to clinical psychology, to typically major in psychology and applied health science fields, and to currently be in the fourth year or higher of their undergraduate program. These participants were also more likely to report being female, white, and between the ages of 28–32. In addition, high-performers were more likely to have been diagnosed and/or treated for a psychological disorder, to have more experience with psychological disorders based on personal, family, or peer history, and to have families who are reported to be more open to discussing mental health issues.

In contrast, low-performers were less likely to have taken a clinical psychology course, to typically major in economics/business or STEM fields, and to currently be in the first or second year of their undergraduate program. These participants were also more likely to report being male, Asian/Asian American, Black/African American, or Hispanic/Latino, and between the ages of 18–22. In addition, low-performers were less likely to have been diagnosed and/or treated for a psychological disorder, less likely to have experience with psychological disorders through personal, family, or peer history, and less likely to have families who were reported to being open to discussing mental health issues.

Component 2 identified the mid-level performers as being different from high or low-level performers. This difference was driven by participants who were more likely to be female, to major in education, to have not taken any clinical psychology course, to have not been diagnosed and/or treated for a psychological disorder, but who were more likely to consider taking campus-offered academic services.

The present study sought to identify factors associated with mental health literacy in a diverse group of undergraduate students. Mental health literacy was quantified using multiple-choice items that assessed conceptual knowledge of specific disorders and the application of that knowledge in everyday life.

We used Discriminant Correspondence Analysis (DiCA), which is a versatile technique for analyzing multiple variables within a single model. This technique is novel and has, thus far, not been used in studies that examine the factors associated with mental health literacy. Using DiCA, we identified student groups who had higher mental health literacy scores. However, in light of the purpose of the study, which was to understand the mental health needs of college students, it was vital to also focus on those student groups with lower mental health literacy scores. In highlighting these results, we shed light on the vulnerable student groups in need of intervention for the purpose of increasing mental health literacy in a college population.

Component 1 findings

The main contributor to variation in scores between high, mid-level, and low performers was having taken a course related to clinical psychology. This finding, though correlational, suggests that formal coursework related to clinical psychology positively affects literacy of mental health. Though previous research has not specifically investigated whether clinical coursework for college students directly increases mental health literacy, there is evidence that Mental Health First Aid/MHFA [ 43 ], an educational training program where participants are trained to help others in crises related to mental health, improved participants’ mental health knowledge, recognition of psychological disorders, and knowledge of effective treatments [ 44 , 45 , 46 ]. Additionally, Transitions [ 47 , 48 ], an educational resource for post-secondary students, which addresses life-skills and mental health information, improved students’ knowledge of mental health, decreased stigma, and increased help-seeking behaviors [ 49 , 50 ]. Evidence that these programs have had a positive impact on mental health literacy of participants underscores the importance and potential benefits of education in this area.

The question of whether mental health literacy can be taught as a course is an important one. Underlying our main finding, where taking a class related to clinical psychology impacted mental health literacy, is the following question: Is the clinical psychology class in itself incorporating literacy of mental health and thus increasing students’ scores on an assessment of mental health literacy? Or, do students who have higher mental health literacy to begin with, gravitate towards these types of classes? If the former, then the argument can be made that mental health literacy could be taught, but if the latter, would taking such a course actually be effective in increasing mental health literacy? More research is needed to answer this question, specifically to assess if a college course focusing on mental health would increase the mental health literacy of students who have not taken a class related to clinical psychology.

Another factor accounting for the difference in scores between high and low performers was majoring in psychology and applied health science fields, as compared to majoring in other fields, specifically business/economics or STEM fields. This finding corresponds to a study that reported that students of psychology and medicine displayed a higher level of mental health literacy, as well as having determined that male students of natural science, economics, and law were particularly weak at recognizing symptoms of schizophrenia and depression [ 18 ]. Further supporting this result is a finding that male STEM majors had lower mental health knowledge than students from non-STEM fields [ 21 ]. In general, these studies have examined the relationship between overall disciplines and mental health literacy as opposed to individual majors, and our study, as well, assessed domains of study as opposed to particular majors. However, if participants would be studied more narrowly, via their specific majors, more information could be provided on how concentrated areas of study relate to mental health literacy. Thus, further research is needed to investigate whether differences observed in mental health literacy performance are associated with any individual college majors, with the purpose of directing interventions towards these specific groups.

All of the demographic variables including gender, age, and ethnicity, significantly contributed to differences in mental health literacy scores. Specifically, students who reported being female, white, and between the ages of 28–32, were more likely to earn higher scores as compared to students who reported being male, Asian/Asian American, Black/African American, or Hispanic/Latino, and between the ages of 18–22 years. Our finding that females tend to score higher than males aligns with the literature on gender and mental health literacy in college settings [ 51 ]. These consistent findings may allude to the premise that gender socialization is at the core of the apparent gender discrepancies of mental health literacy (see [ 51 ] for a discussion on gender socialization and how it relates to mental health literacy).

Participants in the 28–32 age group were more likely to be among the high performers, while participants in the 18–22 age group were more likely to be among the low performers. This finding seems to differ from previous research that found that individuals in the youngest age groups scored highest on identification of disorders [ 7 , 11 ]. However, there is, in fact, agreement between our results and these studies because the ages of our highest scoring group (28–32) aligns with the upper ages of the youngest groups (18–29 and 20–34) in these studies. Also noteworthy is that participants in our study who had the highest scores were older within a relatively young age group, which parallels a study addressing age and mental health literacy, where being older, albeit within a relatively young age group, was associated with higher performance in university students [ 9 ]. However, our results are difficult to directly compare with previous studies due to the variation in age groups. For example, other studies’ oldest age groups were 60–69 [ 13 ] and 70+ [ 17 ] and our oldest age group was 38+, with only 7 participants above the age of 50. Similarly, it is difficult to compare the results of our lowest scoring group (18–22) with other studies, as research on this age bracket in relation to mental health literacy is scarce. This is unfortunate because the traditional age of college students falls approximately in this age bracket and based on our results these may be the students who are most in need of intervention. In future research, greater consistency in the age ranges utilized across similar samples would help reveal the true pattern of relationship between age and mental health literacy.

In terms of ethnicity, our finding corresponds to a study that found that students who were white had higher scores on depression recognition, as compared to students who were non-white [ 8 ]. In further support, a study on college-age males found that undergraduate students who were white had higher mental health literacy than Asian and other undergraduates [ 21 ]. It has been suggested that these results may be the effect of mental health literacy reflecting a Western conceptualization of mental health (see [ 52 ] for a discussion on mental health literacy as it relates to cultural diversity), possibly calling into question the overall conclusion that non-whites have lower mental health literacy than whites. With this in mind, mental health assessments should incorporate more culturally aligned items in order to tap into experiences of minorities regarding knowledge, awareness, attitude, and treatment of mental health.

In our sample, students who were in their fourth year or later of their undergraduate program scored higher than students in their first, second, or third year. Though this may be the result of increased academic knowledge and life experience, it may also be that familiarity with a college campus makes it more likely for a student to access available mental health services, a factor that potentially contributes to increased mental health literacy.

Having been diagnosed and/or treated for a psychological disorder impacted mental health literacy performance in our sample. Though there is limited research on whether having been diagnosed affects mental health literacy in college students, treatment experience has been shown to impact symptom recognition of depression and schizophrenia [ 18 ] and generalized anxiety disorder [ 8 ]. In the general population, however, some studies have found that being diagnosed or treated for a mental health issue does influence knowledge of certain mental health disorders [ 53 ], while others have found that it does not [ 7 , 11 , 54 ]. Though research has not established a consensus, our findings were, nonetheless, statistically significant. The inconsistency in results may be related to our population of study and may suggest that being diagnosed or treated impacts mental health literacy, particularly in college students. More research is needed to determine if this is so, with the possibility that the significance of this factor varies based on the population being studied. Another possibility is that personal experience with mental health issues is broader than has been addressed in previous research. Rather than personal experience being limited to personal diagnosis and/or treatment or general use of mental health services, we also extended experience with psychological disorders to include one’s family or close friends. These items were included in a question that asked respondents to check off as many areas of experience that pertained to them. Results were statistically significant and, in fact, the more experience respondents reported to have had, the more likely they were to have higher scores.

The role of family is important for an individual’s well-being, especially in the area of mental health. Prior research has found that respondents regard family as an important source of help for mental health issues [ 10 , 55 ], though family openness to discussing mental health issues and its impact on mental health literacy does not seem to have been addressed. In an attempt to investigate the association between these two variables, we asked respondents if their immediate family was open to talking about mental health issues and those who responded in the affirmative were more likely to have higher mental health literacy scores. This finding suggests that openness to discussing mental health issues may play a role in the mental health literacy of college students. It is interesting to note that in contrast to other variables investigated in this study such as gender, age, ethnicity, year in college, and being diagnosed and/or treated for a psychological disorder, this variable, much like the clinical course previously discussed, is not immutable and can thus be incorporated into an intervention. Doing so as a community outreach initiative or family training would have the potential to increase mental health literacy in a meaningful and far-reaching manner.

The variable that did not have a significant impact on differentiating between low, mid-level, and high-performing participants was potential use of college services. Specifically, we asked respondents whether they would consider taking advantage of various campus mental health services (e.g., personal counseling, drug and alcohol counseling, and mental health awareness training) and academic services (e.g., time management, stress management, test anxiety management), to which they answered “yes” or “no”. It is possible that our non-significant findings relate to the way in which we phrased the question. As opposed to asking about willingness to access campus services, a better query might have been a measure of treatment use, such as whether participants had actually accessed any campus services, as treatment utilization behaviors have been associated with higher mental health literacy [ 56 ].

Component 2 findings

Based on results from component 2, one of the statistically significant variables that separated mid-level performers from high and low-level performers was being an education major. Specifically, mid-level performers were more likely to be female, to be education majors, to have not taken a clinical course, to not have been diagnosed and/or treated, but who would consider using academic services in areas such as test anxiety, stress management, and time management. This might relate to the premise that education majors have more of an awareness of mental health-related issues, as compared to STEM or business/economics majors. Furthermore, the willingness of these education majors to consider campus-offered academic services, a variable found to be statistically significant for component 2, but not statistically significant for component 1, may relate to the value that education majors place on educational services.

Study limitations and future directions

Our study has the strength of assessing mental health literacy in a large and diverse sample of undergraduate college students utilizing numerous variables, which to our knowledge are more extensive than have been previously incorporated in a single study. However, due to the study design and logistical issues, we were not able to randomly select students for participation and instead used a convenience sample. In addition, as participation was voluntary, we had a higher percentage (62.0%) of women in our sample. Furthermore, all participants were from the same city and enrolled at commuter colleges, a population that is quite different from traditional undergraduates. In light of this, it is difficult to ascertain whether findings can be generalized to undergraduate students from a different geographic location and enrolled at a residential college. Also, as noted above, this study was correlational and conclusions about the directionality of the findings cannot be drawn—particularly for variables such as college major and formal coursework related to clinical psychology.

In terms of future directions, efforts should focus on addressing vulnerable students’ mental health needs by: 1) increasing awareness of, and access to, clinical services available on campus, especially to those who typically do not feel comfortable availing themselves to such services, such as males and minority groups, in a manner that is culturally accommodating and sensitive; and 2) developing an educational curriculum intended to increase mental health literacy across majors and offering a 1-credit abnormal psychology “light” course to students during their freshman and sophomore years in college. Though important in terms of its broad sweep as an educational intervention, ideally, it is the student groups with lower mental health literacy performance that would be targeted for this course, where data collected in this area could then foster a campaign geared towards these students and provide a rationale for intervention (e.g., providing psychoeducation, promoting awareness of college resources, increasing availability of treatment), all at the college level.

Due to the prevalence of psychological disorders among the college population, students’ mental health literacy, which includes understanding of mental health disorders and how to recognize, manage, and seek treatment for such disorders, is critical. In our study, the most robust contributors to mental health literacy were: 1) coursework : those who have taken a clinical psychology course, particularly those who are psychology majors and; 2) experience : those who have experience with mental health issues because they have been diagnosed and/or treated for a psychological disorder or because they have family or experience with a psychological disorder. Our findings offer a basis for understanding the mental health needs of diverse undergraduate students by providing an opportunity to identify not only those with high mental health literacy, but also those with low mental health literacy. Identification of both of these groups is critical in providing a direction for intervention in terms of educational and clinical services, with the aim of increasing the mental health literacy and overall psychological well-being of college students.

Availability of data and materials

The datasets used for the current study are available from the corresponding author upon reasonable request. Additionally, the survey will be made available to interested researchers.

Abbreviations

• Discriminant Correspondence Analysis

Diagnostic and statistical manual of mental disorders

Mental Health Literacy Assessment for College Students

Science, technology, engineering, and mathematics

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Acknowledgements

The authors would like to thank Rose Bergdoll, Eliezer Graber, Faigy Mandelbaum, Crystal Quinn, Nina Steinfeld, Genéa Stewart, Amanda Strano, and David Turbeville for their contributions towards various aspects of this study.

The authors would also like to acknowledge Dr. Stephen Kelly, Mike Esposito, and John Tessitore from the JCK Foundation for their support.

This study was funded by a grant from the JCK Foundation. Named in memory of John Cleaver Kelly, who lost his battle with OCD and depression in 2011, the JCK aims to empower younger generations to address mental health issues in themselves and their communities. The JCK Foundation had no role in the design of the study, or collection, analysis, and interpretation of the data, or writing of the manuscript.

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RM and LR conceived and designed the study; EG and KK organized the dataset; AK analyzed the data and created the figure and tables; RM, LR, and AK interpreted the results; RM, LR, and AK drafted the manuscript; all authors read and approved the manuscript.

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Miles, R., Rabin, L., Krishnan, A. et al. Mental health literacy in a diverse sample of undergraduate students: demographic, psychological, and academic correlates. BMC Public Health 20 , 1699 (2020). https://doi.org/10.1186/s12889-020-09696-0

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SYSTEMATIC REVIEW article

Promoting university students' mental health: a systematic literature review introducing the 4m-model of individual-level interventions.

• 1 Guidance & Counseling Office, Student Services & Registration, Mohammed Bin Rashid University of Medicine and Health Sciences (MBRU), Dubai, United Arab Emirates
• 2 Strategy & Institutional Excellence, Mohammed Bin Rashid University of Medicine and Health Sciences (MBRU), Dubai, United Arab Emirates

Objective: The purpose of this study is to systematically review recently published individual student-level interventions aimed at alleviating the burden of mental health challenges faced by the students and/ or at equipping them with coping mechanism that will foster their resilience.

Methods: This study relied on a systematic literature review. PubMed dataset was used; the search was confined to the following period: July 2016-December 2020.

Results: A total of 1,399 records were identified by the electronic search, out of which 40 studies were included in this study. The authors inductively identified four overlapping categories of interventions across all included articles, and coded them as follows: Mindfulness, Movement, Meaning, and Moderator. Accordingly, each study was linked to at least one of four overlapping categories based on the nature of the intervention(s) under investigation, leading to differing assortments of categories.

Conclusions: The 4M-Model generated by this study encourages focusing on devising holistic, university-based interventions that embrace the individuality of students to improve their mental health through elements of mindfulness, movement, meaning, and moderator. Through this focused approach, university counselors are enabled to design interventions that address students' physical, psychological, emotional, and social needs.

Introduction

There has been a positive paradigm shift in the way our world and its citizens are perceiving the concept of mental health. Mental health is a state of well-being that allows individuals to enjoy and maintain relationships as well as handle stress in a healthy manner without compromising on productivity ( 1 ).

A large body of literature on tertiary education students highlights the importance of maintaining mental health with evidence relating it to educational attainment and productivity ( 2 ), social relationships, engagement on campus, and quality of life ( 3 ), and placement performance ( 4 ). Poor mental health has also been linked with lower retention within a programme, grade point averages, and graduation rates among university students ( 5 ). Counseling, psychoeducation, and mental health services on campuses are no longer deemed as merely supportive but rather an integral component necessary to empower students. These services are integral to help students develop skills such as psychological flexibility ( 6 ) which in turn influences mental health ( 1 ).

The current generation of university students is vastly different from previous generations, especially in their attitudes and beliefs toward their mental health needs. Well-being is a dynamic concept of interlinked physical, social, and psychological dimensions which is constantly changing depending on intrinsic and extrinsic environments and motivations ( 7 ). It is not only the demographics of the current generation of university students that has changed considerably from the past ( 8 ), but so have their attitudes and beliefs toward their needs, including mental health ( 3 ). This population is considered high risk because most mental health problems are triggered before the age of 24 ( 9 ). There is enough evidence to link personal and academic stressors to mental health ( 10 – 12 ). Contemporary tertiary education is striving to attain and maintain cultures of excellence, similar to traditional universities in the past ( 13 ). However, there has been a shift to turn modern day campuses into high stakes competitive testing environments with well-intended emphasis on preparing students to become part of the global economy. This change has influenced the context in which modern universities function. There are a set of challenges that contemporary universities face that extend beyond the earlier tertiary educational institutions and there is an assumption that students are coming to college “overwhelmed and more damaged than those of previous years” ( 14 ).

Although good citizenship has always been an important foundation of all educational institutions, with the dynamic social landscape that the universities are set within, there seems to be a tendency to lead students to fixate on extrinsic factors such as: results and Grade Point Averages, over intrinsic interest such as innovative learning, and expansion of lateral thinking ( 13 ). When the priority is grades, it manifests itself in excessive hours of focused studying, and in negative coping behaviors, such as: inadequate sleep and addictive behaviors, which could potentially affect the well-being of the student. Often, in this pursuit of academic excellence, there is the danger of ignoring the social, emotional, and psychological problems that modern students are now increasingly facing.

There is enough research that indicates that students are experiencing more mental health disorders in contemporary times and are less resilient than students in the past ( 8 ), with lower levels of frustration tolerance ( 15 ). Anxiety and depression are most prevalent among tertiary students ( 16 ). There is a rise in the number of college students with a diagnosable psychological disorder ( 17 ) with some students at greater risk than others of experiencing stress and mental health problems ( 18 ). There has been also a shift in the severity of the problems by students seeking counseling services over the past decade. It is no longer just presenting challenges of adjustment and individuation ( 19 ), or benign hormonal developmental problems associated with the age that prompts students to seek counseling. Students are presenting with severe psychological problems ( 20 ) with a sizeable number of them on psychiatric medication to help them function better on campus ( 15 ).

A common narrative through an exhaustive body of literature highlights the barriers to seeking help for mental health problems by students on campus due to stigma ( 21 ), scepticism about treatment efficacy ( 22 ), and a belief that their emotional problems will not be completely understood. This leads to a sense of social isolation as the students restrain from reaching out for help ( 21 ). Two contributing factors to inadequate help-seeking are the stigma of having a mental health problem and the personal characteristics of the individual student ( 20 ). A fear of negative consequences on academic records ( 23 ) is another common barrier among university students. Interestingly, students resist seeking help because they do not perceive their condition to require intervention or do not perceive it as a priority among their other commitments. They also have the tendency to normalize stress as part of university life, expecting it “will go away with time,” and prefer to handle their problems on their own ( 24 ).

More recent research indicates that students also rely on informal sources of help-seeking from non-professionals, particularly peer groups ( 25 ). Students report having no inhibitions about having open discussions about their mental health problems via social-networking websites ( 26 ). This resonates with the network episode model of help-seeking that emphasizes the social network as an integral, contemporary support in enhancing knowledge and attitudes toward seeking help ( 27 ). However, there is also a significant increase in the number of students with major psychological problems seeking counseling services on campus ( 3 ) challenging the stigma connected with help-seeking. The newer generation's familiarity with psychosocial support services and openness toward seeking them are putting mental health at the core of self-care, much like diet and exercise ( 26 ).

Along with rapid social changes and expectations, the dilution of traditional family anchors (that is the changes to family systems which include busy yet isolated lifestyles, social media pressures, a living free from parental influence which is very common to this age group, and forced separation from families in the pursuit of dream destinations for education) all compounding to the considerable degree of stress that students report upon ( 18 ). Considering all these transitions, focusing on the support that is available to young people on campus is increasingly becoming a necessity. This is not only a personal benefit for students but a national and international investment that could also result in considerable economic benefit ( 28 ) as these students stand to become contributors to the global economy.

A wealth of research exists which highlights the effectiveness of changing organizational factors that influence mental health ( 29 , 30 ). However, there is limited research on person-centric mental health strategies used in university settings ( 31 ). A Systematic Literature Review that was conducted by Fernandez et al. focused on evaluating the effect of setting-based interventions that stimulated and improved the mental health and well-being of university students and employees ( 32 ). That review constitutes an asset for universities seeking to adopt setting-based strategies that were proven efficacious. Yet, given the highspeed in which the higher education ecosystem has been evolving, there is an evident need for a more up-to-date review. Also, despite the importance of modifying the environment for it to become more nurturing for university students' mental health, this needs to be in conjunction with embracing the individuality of each student. Accordingly, the purpose of this study is to bridge this gap through providing a review of the literature on recently published individual student-level interventions that aim to alleviate the burden of mental health challenges faced by the students and/or help them with coping mechanisms that will foster their resilience.

We conducted a systematic review following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines ( 33 ). The protocol of the systematic review was published in PROSPERO, a database of prospectively registered systematic reviews in health and social care (CRD42021227862).

Search Strategy

To complement the work of Fernandez et al., focusing on the recent literature, the search period was confined to July 2016 through December 2020 ( 32 ). PubMed database was used. The search strategy used, with its key words and Boolean logic, is available as an online resource. It was structured as follows:

• Subjects: student or resident.

• Location: higher education, university, college, or tertiary education.

• State-of-being : mental health.

• Challenges faced by subjects : psychosocial, anxiety, depression, burnout, stress, peer-pressure, social media pressure, bullying, eating disorder, perfectionism, or learning difficulties.

• Intervention to address the challenges : psychotherapy, mindfulness, Counseling, support group, yoga, breathing, art therapy, awareness, resilience, gratitude, affirmations, or peer-Counseling.

Pure qualitative studies were excluded. We included all quantitative studies, so long as they contained information on the impact of the intervention. These included those using experimental (i.e., randomized controlled trials) or observational (i.e., controlled trials without randomization, and pre-post and time series) approaches. Duplicated papers were excluded. Studies were screened for inclusion in three phases:

1. BN and FO went over all the abstracts, together, to remove the articles that certainly did not meet the inclusion criteria.

2. The full text of all the remaining abstracts were reviewed independently by BN and FO. The results were discussed. Any discrepancies were investigated and reflected upon until reaching consensus.

3. Finally, all remaining articles were thoroughly reviewed for summarizing purposes based on a preset template: research study objective, context, design, method, sample, intervention, and main conclusion.

Articles were included if:

a) Empirical/applied (i.e., theoretical studies or systematic reviews, and studies using secondary data were excluded),

b) Conducted in one or more university,

c) Aimed at evaluating, the immediate or long-term effect of an intervention on the mental health status of students,

d) Included global measures of mental health and well-being,

e) Had the university counselor involved in the intervention,

f) Involved full-time students, and

g) Was written in English.

Quality Assessment

The quality of each of the included articles was evaluated considering the internal and external validity. For the internal validity (risk of bias), each study's methodological quality was assessed using the criteria introduced by Jadad et al. ( 34 ). As for the external/ ecological validity of the included studies, it was assessed using the criteria developed by Green and Glasgow ( 35 ). This quality assessment was not used to exclude articles. Yet, the results of the assessment were thoroughly reflected upon as an evaluative measure of the review output.

Data Analysis

The interventions referred to in the included studies were analyzed by the researchers using the framework of Braun and Clarke ( 36 ). The intention was to inductively build a general interpretation of all included studies, in alignment with the paradigm of constructivism ( 37 , 38 ). The assumption was that reality is socially-constructed. This required thoroughly reflecting upon the interventions investigated in the included studies. The process of exploratory reflection adapted was spiral, where the researchers' observations kept getting revisited which culminated into the development of an evidence-driven model. Since the constructivism paradigm gives precedence to thoroughness and insightfulness over extensiveness and generalizability ( 39 ), the decision was made upfront, as abovementioned, for this search to be limited to a single database ( 40 ). As for the purpose of the qualitative meta-synthesis, it was to create a dynamic individual-level intervention framework that is holistic and context-specific ( 41 ). All articles were categorized based on the nature of the intervention(s) under investigation. It is all narratively presented in the results section.

A total of 1,399 records were identified by the electronic search. Two researchers (BN and FO) reviewed all the abstracts of the resulting papers to identify ones that fitted the inclusion criteria. Based on that, a total of 1,178 articles were excluded. The full text of all remaining 220 articles were extracted and thoroughly reviewed by the two researchers (110 by each). Accordingly, 133 articles were excluded. The remaining 87 articles underwent another round of assessment by both researchers together. Out of these 87 articles, 47 papers were excluded: four studies did not meet the eligibility criteria of having an intervention in them, 31 studies did not include assessing the effectiveness of an intervention,10 studies were not exclusively on university students, and 1 was not on full-time students. Also, one study was excluded because it was not counselor-led but outsourced. Out of the initially identified 1399 articles, 40 articles were finally included in the study ( Figure 1 ).

Figure 1 . PRISMA flow-diagram. Promoting university students' mental health: a systematic literature review introducing the 4M-Model of individual-level interventions, Dubai, United Arab Emirates, 2020.

Of the 40 studies, nine studies were conducted in USA, eight in United Kingdom, four in Canada, three in Australia, five in Germany, four in China, and one in each of Turkey, Hungary, Israel, Ireland, Japan, South Korea and Netherlands. The quality of evidence is very high in terms of internal validity because most of the studies ( 25 ) employed RCT, five studies used a quasi-experimental method, two had a cross sectional design, and eight studies utilized a pre-post design without a control group.

The external validity of the papers could be considered low/ moderate. Since most of the studies indicated the experience of only one institution; generalization of the findings is limited. The only exceptions were one study that was conducted in Israel which included three institutions and one conducted in UK which included eight universities. After thoroughly reflecting upon the interventions under investigation across all 40 resulting studies, the authors qualitatively synthesized a holistic framework. This involved inductively identifying four overlapping categories of interventions. Each category was in turn coded with a label that appeared to be most fit to the encapsulated interventions and that is in harmony with the codes of the rest of the categories (i.e., alliteration).

Accordingly, each study was linked to at least one of four overlapping categories based on the nature of the intervention(s) under investigation ( Table 1 ). The first category, coded as Mindfulness, included individual-level interventions that used mindfulness as a strategy to promote mental health. Mindfulness, in this context, refers to any intervention that aims to promote living in the moment or “now” and adopting acceptance and a non-judgmental attitude to guide action. The popular Mindfulness Based Stress Reduction (MBSR) curriculum was used in four studies ( 8 , 42 – 45 ). Mindfulness Based Cognitive Therapy (MBCT) which focuses on reframing thoughts along with becoming aware of the nature and quality of them was found to also be effective in two studies ( 46 , 47 ). In three studies, the intervention(s) made use of imagery and self-guidance ( 48 – 51 ), whereas two other studies explored the effectiveness of Acceptance and Commitment Therapy (ACT) ( 6 ) to improve the psychological flexibility, school engagement, and mental health among University students.

Table 1 . Distribution of the output of the systematic literature review depending on the nature of the intervention(s) under investigation.

The second category of studies was coded as Movement and included individual-level interventions which have a predominant physical element and solicit change in bodily sensations including but not limited to yoga, fitness, dance, kickboxing, and aerobics and breathing exercises. While Tong et al. ( 52 ) exclusively looked at the effect of Yoga and Fitness on mental health, five sets of researchers ( 8 , 42 , 43 , 45 , 46 ) looked at breathing and simple yoga as part of their mindfulness course. Sleep was studied in connection to mental health in two studies ( 53 , 54 ) as it has been found to be a precursor to many mental health problems with insomnia and the quality of sleep put on top of the list affecting sleep hygiene. Behavioral activation, a personalized therapeutic tool mainly used in the treatment of depression targeting behaviors that feed into the condition, was found to be effective in three studies that were reviewed ( 55 – 57 ) involving students with mild depression. The goal of Behavioral Activation is engaging in enjoyable activities with a part of the process focusing on getting past obstacles that may impede that enjoyment. One study included peer-led support ( 56 ) and online delivery of the course ( 57 ), where both appeared to be efficacious. Only one study by Chalo et al. ( 58 ) used Biofeedback intervention, that involved measuring students' quantifiable bodily functions to convey information to them in real-time as a solution to help students manage their physiological response to anxiety and stress.

The third category was coded as Meaning and included studies that investigate individual-level interventions that focus on the counselor addressing connections and associations between variables and enabling the student to reframe cognitions. Psychoeducation was widely utilized with cognitive training as the most common ( 54 , 59 – 63 ). Eustis et al. ( 49 ) focused their study on the student's self-awareness, while Demir and Ercan ( 64 ) explored communication techniques among students. In addition, three studies explored the feasibility of having courses embedded within the curriculum ( 38 , 48 , 50 ) to improve the mental health of students, while nine studies explored the effect of elective courses that aimed at stress reduction ( 18 , 43 , 50 , 56 , 58 , 65 – 69 ).

The last category of studies was coded as Moderator which referred to any element of support that was deployed in conjunction with the counselor, in an individual-level intervention, that acts as a moderator between the student and the counselor. Pet therapy was explored in three studies ( 70 – 72 ) to assess well-being, and an extensive use of the computer to deliver courses such as ACT, Psychoeducation, and Cognitive Behavior Therapy (CBT) which are all traditionally effective in psychotherapy, were found to be efficacious online in 10 studies ( 44 , 50 , 57 , 61 , 73 – 78 ) highlighting the significance of the potential of web-based interventions to impart psychotherapy to a wider audience.

This literature review showed that elements of Mindfulness were a major part of the 23 studies, Meaning was predominant in 24 studies, while Movement was an important feature in 17 studies. An element of support complementary to the therapist, either in the form of a pet (canine) or a web/phone application (i.e., Moderator), was part of 16 interventions. Commonly used approaches were Mindfulness based therapies, ACT, Cognitive Behavior Therapy, and Psychoeducation. The duration of the interventions investigated in the included studies ranged between 1 and 12 weeks, with most of the studies spanning between 6 and 8 weeks. Nine studies had just one element, and only one study ( 49 ) had all the four elements included ( Figure 2 ), which the authors perceived as a “lucky find.”

Figure 2 . The 4M-Model generated from this study's qualitative synthesis, visually illustrated as a four-leaf clover which is a symbol of luck. Promoting university students' mental health: a systematic literature review introducing the 4M-Model of individual-level interventions, Dubai, United Arab Emirates, 2020.

Thirty-one studies had overlapping elements indicating that these elements are not mutually exclusive and rather interlinked and are blended with the intention of enhancing the effectiveness of a program.

The output of this Systematic Literature Review revealed diverse interventions. Most of these interventions were hybrid versions of existing evidence-based interventions. A few of the identified articles reflected upon contextualized home-grown interventions. There appeared to be a lack of consensus on a common model/ approach to effectively improve the mental health and wellness of university students ( 61 ) who are known to have their own set of challenges. Hence, this paper provides an outline of practices that have been deployed in this direction, illustrating them from a holistic perspective. Elements of mindfulness, meaning, movement, and use of a moderator were seen to overlap in the studies. The blending of these elements was proven to be effective in improving metacognitive awareness, emotional regulation ( 79 ), concentration, and mental clarity ( 80 ), and decreasing emotional reactivity ( 81 ) and rumination (through disengagement with persistent negative thoughts) ( 82 ) and in turn reducing depression, stress, and anxiety ( 83 ). It has also shown to foster social connectedness and the ability to express oneself in various social situations ( 84 ) thereby reducing stress and anxiety and increasing patience, gratitude, and body awareness ( 85 ). With so many elements that need to be taken into consideration, the researchers have attempted to comprehend the output of this review from the field theory point-of-view where the “organism and environment are perceived as part of an interacting field” ( 86 ).

Moreover, Counseling strategies and interventions are meant to emphasize on the growth of an individual. The human potential for self-actualization, a concept understood by Abraham Maslow as a change process that aims at making a person “aware of what is going on inside himself” [Maslow, as cited in Seaman ( 87 ), p. 3] is core to Counseling interventions, which is where the four elements blend to become crucial to the process of self-awareness and eventually self-growth.

The results of the study indicate that self-awareness through mindfulness is an important foundation upon which all other elements build up to improve mental health of students. This was not a surprising find because this is in alignment with the results of many previously conducted studies ( 88 , 89 ). Mindfulness seems to be the new mantra and has been intensively researched ( 90 ). However, despite a substantial amount of theoretical work conducted to merge Buddhist and Western conceptual viewpoints to psychotherapy ( 91 ), there is minimal literature on how it can translate to practice making this review an important addition to the limited knowledge around the topic of psychological interventions that have been found to be effective among university students. MBSR has proven to reduce stress and anxiety among university students by fostering insight and concentration along with physiologic relaxation ( 92 ). Teaching students to live in the present moment by reframing thoughts (i.e., MBCT) has been found to be effective in reducing depression ( 93 ). It also lessens the risk of relapse with comparable efficacy to antidepressant medication ( 94 ) which, in itself, is a breakthrough for psychotherapy. ACT which focuses on acceptance has been found to improve coping, self-regulation, psychological flexibility, and school engagement ( 6 ). Counseling young adults, in particular students at the university level, would benefit by basing it on Engel's biopsychosocial viewpoint which includes taking into consideration the hormonal changes (biological), identity crisis, and the challenges arising from intimacy and isolation (psychological) which have been hypothesized in Eric Erickson's psychosocial stages of development for this age group. The new age technological challenges of peer-pressure over social media sites and the demands of fitting in and changing family dynamics (sociological) also need to be taken into consideration when conceptualizing a Counseling program for this target group.

Moreover, this transition stage between adolescence and adulthood, also referred to as “emerging adulthood” ( 95 ), is considered to be a period of accepting responsibility for one's actions and livelihood, developing belief systems and values independent of parental and external influences, and establishing relationships with parents on equal grounds. Young university students who are still financially dependent and living with parents during this period are arbitrarily considered to be adolescents if adult responsibilities are not yet accessed. These intangible markers gradually develop. The entailed process could last many years until the corresponding responsibilities are effectively adopted. As such, the range between adolescence and adulthood becomes wider than typically defined, stretching from the beginning of puberty to the early twenties ( 96 ).

Counseling has been traditionally associated as a profession that requires the physical presence of a minimum of two people in a professional relationship to talk through and process experiences to gain insight and understanding. However, in this review, it is evident that web-based interventions seem to produce an equally effective result ( 97 ) as observed in 16 studies of the literature review which could be utilized as a complementary medium widening the scope of practice of counselors and psychotherapists. This could also help in minimizing the stigma associated with getting undesirably labeled and help in reducing psychological self-restraint which has been termed as ‘online disinhibition effect' ( 98 ). Web-based mental health interventions also are becoming a preferred medium for students to gain services and information ( 99 ) as they accommodate their busy schedules ( 100 ).

Another observation was that even though most of the interventions were conducted only for a short period of time, the effectiveness of the interventions was established. Embedding interventions within the curriculum has been suggested ( 101 ) which makes this review even more pertinent for innovations in curriculum planning. This may also help in alleviating the stigma that is attached to Counseling services which is often a barrier that prevents students from reaching out for help ( 102 ). This aligns with Vygotsky's notion of Zone of Proximal Development ( 103 ) which refers to pedagogical support being beneficial for activities, in this context, psychoeducation of positive behaviors that facilitate help seeking behaviors before they can start using them independently.

The above observations prompted the researchers to recognize that the four identified elements when combined would result in a holistic approach of addressing the individual from a biopsychosocial point-of-view. This was depicted in the form of the 4M-Model to guide counselors to develop and implement university-level interventions that could help to reduce stress, anxiety, and depression as well as improve emotion regulation and self-awareness to address the mental health needs of young adults. It would be worthwhile for future research studies to validate the suggested 4M-Model through a similar systematic review of the literature relying on a combination of databases ( 104 ). The analysis in this case would be deductive where the model conceived from this study can be used as a preset template. Also, for validation purposes, it is recommended to conduct follow-up studies aimed at evaluating the efficaciousness of a tailor-made assortment of interventions that can be linked to all elements of the 4M-Model. For that purpose, it would be useful to adapt a mixed methods approach to research, where quantitative and qualitative findings will be integrated to obtain a holistic perspective of the output, outcome, and impact of such university-based, individual-student level mental health initiatives.

Findings of this review reveal the 4M-Model that happen to address all aspects of holistic well-being: physical, psychological, emotional, and social. Effectiveness of the varied interventions that have been reviewed in this study indicate that if a comprehensive approach toward intervention including mindfulness, movement, moderator, and meaning is adapted, then it would not only help students to be supported in a holistic manner but would help counselors plan and execute their programs in a focused approach to address the needs of any university student population who are increasingly overwhelmed and burned out with the stressors from their outside worlds as well as from within. The findings from the review add to the growing evidence for the urgent need of an intervention model that can serve as a directive for counselors and students.

Data Availability Statement

The original contributions presented in the study are included in the article/supplementary material, further inquiries can be directed to the corresponding author/s.

Author Contributions

BN and FO conceptualized the study, conducted the review, performed the qualitative meta-synthesis, and prepared and approved the manuscript. Both authors contributed to the article and approved the submitted version.

Conflict of Interest

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Acknowledgments

The authors would like to extensd their gratitude to three of their colleagues: Dr. Lisa Jackson, Dr. Leigh Powell, and Ms. Mersiha Kovacevic, for their active role, and valuable reflections and feedback in reviewing the complete manuscript.

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PubMed Abstract | CrossRef Full Text

Keywords: mental health, health and well-being, holism, university students, mindfulness, higher education, student support

Citation: Nair B and Otaki F (2021) Promoting University Students' Mental Health: A Systematic Literature Review Introducing the 4M-Model of Individual-Level Interventions. Front. Public Health 9:699030. doi: 10.3389/fpubh.2021.699030

Received: 22 April 2021; Accepted: 31 May 2021; Published: 25 June 2021.

Reviewed by:

Copyright © 2021 Nair and Otaki. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY) . The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

*Correspondence: Bhavana Nair, bhavana.nair@mbru.ac.ae

† ORCID: Bhavana Nair orcid.org/0000-0002-3381-8293 Farah Otaki orcid.org/0000-0002-8944-4948

Disclaimer: All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher.

• DOI: 10.35631/ijepc.954032
• Corpus ID: 271260659

REVIEWING THE INFLUENCE OF MENTAL HEALTH AND COPING STRATEGIES ON ACADEMIC PERFORMANCE

• Noraida Saidi , Nik Zam Nik Wan , +4 authors Normaizatul Akma Saidi
• Published in International Journal of… 30 June 2024
• Psychology, Education

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• Open access
• Published: 22 June 2023

Social media and mental health in students: a cross-sectional study during the Covid-19 pandemic

• Abouzar Nazari   ORCID: orcid.org/0000-0003-2155-5438 1 ,
• Maede Hosseinnia   ORCID: orcid.org/0000-0002-2248-7011 2 ,
• Samaneh Torkian 3 &
• Gholamreza Garmaroudi   ORCID: orcid.org/0000-0001-7449-227X 4  

BMC Psychiatry volume  23 , Article number:  458 ( 2023 ) Cite this article

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Social media causes increased use and problems due to their attractions. Hence, it can affect mental health, especially in students. The present study was conducted with the aim of determining the relationship between the use of social media and the mental health of students.

Materials and methods

The current cross-sectional study was conducted in 2021 on 781 university students in Lorestan province, who were selected by the Convenience Sampling method. The data was collected using a questionnaire on demographic characteristics, social media, problematic use of social media, and mental health (DASS-21). Data were analyzed in SPSS-26 software.

Shows that marital status, major, and household income are significantly associated with lower DASS21 scores (a lower DASS21 score means better mental health status). Also, problematic use of social media (β = 3.54, 95% CI: (3.23, 3.85)) was significantly associated with higher mental health scores (a higher DASS21 score means worse mental health status). Income and social media use (β = 1.02, 95% CI: 0.78, 1.25) were significantly associated with higher DASS21 scores (a higher DASS21 score means worse mental health status). Major was significantly associated with lower DASS21 scores (a lower DASS21 score means better mental health status).

This study indicated that social media had a direct relationship with mental health. Despite the large amount of evidence suggesting that social media harms mental health, more research is still necessary to determine the cause and how social media can be used without harmful effects.

Peer Review reports

• Social media

Social media is one of the newest and most popular internet services, which has caused significant progress in the social systems of different countries in recent years [ 1 , 2 ]. The use of the Internet has become popular among people in such a way that its use has become inevitable and has made life difficult for those who use it excessively [ 3 ]. Social media has attracted the attention of millions of users around the world owing to the possibility of fast communication, access to a large amount of information, and its widespread dissemination [ 4 ]. Facebook, WhatsApp, Instagram, and Twitter are the most popular media that have attractive and diverse spaces for online communication among users, especially the young generation [ 5 , 6 ].

According to studies, at least 55% of the world’s population used social media in 2022 [ 7 ]. Iranian statistics also indicate that 78.5% of people use at least one social media. WhatsApp, with 71.1% of users, Instagram, with 49.4%, and Telegram, with 31.6% are the most popular social media among Iranians [ 8 , 9 ].

The use of social media has increased significantly in all age groups due to the origin of the COVID-19 pandemic [ 10 ] .It affected younger people, especially students, due to educational and other purposes [ 11 , 12 ]. Because of the sudden onset of the COVID-19 pandemic, educational institutions and learners had to accept e-learning as the only sustainable education option [ 13 ]. The rapid migration to E-learning has brought several challenges that can have both positive and negative consequences [ 14 ].

Unlike traditional media, where users are passive, social media enables people to create and share content; hence, they have become popular tools for social interaction [ 15 ].The freedom to choose to participate in the company of friends, anonymity, moderation, encouragement, the free exchange of feelings, and network interactions without physical presence and the constraints of the real world are some of the most significant factors that influence users’ continued activity in social media [ 16 ]. In social media, people can interact, maintain relationships, make new friends, and find out more about the people they know offline [ 17 ]. However, this popularity has resulted in significant lifestyle changes, as well as intentional or unintentional changes in various aspects of human social life [ 18 ]. Despite many advantages, the high use of social media brings negative physical, psychological, and social problems and consequences [ 19 ], but despite the use and access of more people to the Internet, its consequences and crises have been ignored [ 20 ].

Use of social media and mental health

Spending too much time on social media can easily become problematic [ 21 ]. Excessive use of social media, called problematic use, has symptoms similar to addiction [ 22 , 23 ]. Problematic use of social media represents a non-drug-related disorder in which harmful effects emerge due to preoccupation and compulsion to over-participate in social media platforms despite its highly negative consequences [ 24 , 25 , 26 ], which leads to adverse consequences of mental health, including anxiety, depression, lower well-being, and lower self-esteem [ 27 , 28 , 29 ].

Mental health & use of social media

Mental health is the main pillar of healthy human societies, which plays a vital role in ensuring the dynamism and efficiency of any society in such a way that other parts of health cannot be achieved without mental health [ 30 ]. According to World Health Organization’s (WHO) definition, mental health refers to a person’s ability to communicate with others [ 31 ]. Some researchers believe that social relationships can significantly affect mental health and improve quality of life by creating a sense of belonging and social identity [ 32 ]. It is also reported that people with higher social interactions have higher physical and mental health [ 33 ].

Scientific evidence also shows that social media affect people’s mental health [ 34 ]. Social studies and critiques often emphasize the investigation of the negative effects of Internet use [ 35 ]. For example, Kim et al. studied 1573 participants aged 18–64 years and reported that Internet addiction and social media use were associated with higher levels of depression and suicidal thoughts [ 36 ]. Zadar also studied adults and reported that excessive use of social media and the Internet was correlated with stress, sleep disturbances, and personality disorders [ 37 ]. Richards et al. reported the negative effects of the Internet and social media on the health and quality of life of adolescents [ 38 ]. There have been numerous studies that examine Internet addiction and its associated problems in young people [ 39 , 40 ], as well as reports of the effects of social media use on young people’s mental health [ 41 , 42 ].

A study on Iranian students showed that social media leads to depression, anxiety, and mental health decline [ 25 ]. A study on Iranian students showed that social media leads to depression, anxiety, and mental health decline [ 25 ]. But no study has investigated the effects of social media on the mental health of students from a more traditional province with lower individualism and higher levels of social support (where they were thought to have lower social media use and better mental health) during the COVID-19 pandemic. As social media became more and more vital to university students’ social lives during the lockdowns, students were likely at increased risk of social media addiction, which could harm their mental health. University students depended more on social media due to the limitations of face-to-face interactions. In addition, previous studies were conducted exclusively on students in specific fields. However, in our study, all fields, including medical and non-medical science fields were investigated.

The present study was conducted to determine the relationship between the use of social media and mental health in students in Lorestan Province during the COVID-19 pandemic.

Study design and participants

The current study was descriptive-analytical, cross-sectional, and conducted from February to March 2022 with a statistical population made up of students in all academic grades at universities in Lorestan Province (19 scientific and academic centers, including centers under the supervision of the Ministry of Health and the Ministry of Science).

Sample size

According to the convenience sampling method, 781 people were chosen as participants in the present study. During the sampling, a questionnaire was created and uploaded virtually on Porsline’s website, and then the questionnaire link was shared in educational and academic groups on social media for students to complete the questionnaire under inclusion criteria (being a student at the University of Lorestan and consenting to participate in the study).

The research tools included the demographic information questionnaire, the standard social media use questionnaire, and the mental health questionnaire.

Demographic information

The demographic information age, gender, ethnicity, province of residence, urban or rural, place of residence, semester, and the field of study, marital status, household income, education level, and employment status were recorded.

Psychological assessment

The students were subjected to the Persian version of the Depression Anxiety Stress Scale (DASS21). It consists of three self-report scales designed to measure different emotional states. DASS21 questions were adjusted according to their importance and the culture of Iranian students. The DASS21 scale was scored on a four-point scale to assess the extent to which participants experienced each condition over the past few weeks. The scoring method was such that each question was scored from 0 (never) to 3 (very high). Samani (2008) found that the questionnaire has a validity of 0.77 and a Cronbach’s alpha of 0.82 [ 43 ].

Use of social media questionnaire

Among the 13 questions on social media use in the questionnaire, seven were asked on a Likert scale (never, sometimes, often, almost, and always) that examined the problematic use of social media, and six were asked about how much time users spend on social media. Because some items were related to the type of social media platform, which is not available today, and users now use newer social media platforms such as WhatsApp and Instagram, the questionnaires were modified by experts and fundamentally changed, and a 22-item questionnaire was obtained that covered the frequency of using social media. Cronbach’s alpha was equal to 0.705 for the first part, 0.794 for the second part, and 0.830 for all questions [ 44 ]. Considering the importance of the problematic use of the social media, six questions about the problematic use were measured separately.

To confirm the validity of the questionnaire, a panel of experts with CVR 0.49 and CVI 0.70 was used. Its reliability was also obtained (0.784) using Cronbach’s alpha coefficient. Finally, the questionnaire was tested in a class with 30 students to check the level of difficulty and comprehension of the questionnaire. Finally, a 22-item questionnaire was obtained, of which six items were about the problematic use of social media and the remaining 16 questions were about the rate and frequency of using social media. Cronbach’s alpha was 0.705 for the first part, including questions about the problematic use of the social media, and 0.794 for the second part, including questions about the rate and frequency of using the social media. The total Cronbach’s alpha for all questions was 0.830. Six questions about the problematic use of social media were measured separately due to the importance of the problematic use of social media. Also, a separate score was considered for each question. The scores of these six questions on the problematic use of the social media were summed, and a single score was obtained for analysis.

Statistical analysis

Data were analyzed using the Statistical Package for Social Sciences (SPSS) version 26.0 (SPSS Inc., Chicago, IL, USA). The normal distribution of continuous variables was analyzed using the Kolmogorov-Smirnov test, histogram, and P-P diagram, which showed that they are not normally distributed. Descriptive statistics were calculated for all variables. Comparison between groups was done using Mann-Whitney and Kruskal-Wallis non-parametric tests. Multiple linear regression analysis was used to investigate the relationship between mental health, problematic use of social media, and social media use (The result of merging the Frequency of using social media and Time to use social media). Generalized Linear Models (GLM) were used to assess the association between mental health with the use of social media and problematic use of social media. Due to the high correlation (r = 0.585, p = < 0.001) between the use of social media and problematic use of social media, collinearity, we run two separate GLM models. Regression coefficients (β) and adjusted β (β*) with 95% CI and P-value were reported.

A total of 781 participants completed the questionnaires, of which 64.4% were women and 71.3% were single. The minimum age of the participants was 17 years, the maximum age was 45 years, and about half of them (48.9%) were between 21 and 25 years old. A total of 53.4% of the participants had bachelor’s degrees. The income level of 23.2% of participants was less than five million Tomans (the currency of Iran), and 69.7% of the participants were unemployed. 88.1% were living with their families and 70.8% were studying in non-medical fields. 86% of the participants lived in the city, and 58.9% were in their fourth semester or higher. Considering that the research was conducted in a Lorish Province, 43.8% of participants were from the Lorish ethnicity.

The mean total score of mental health was 12.30 with a standard deviation of 30.38, and the mean total score of social media was 14.5557 with a standard deviation of 7.74140.

Table  1 presents a comparison of the mean problematic use of social media and mental health with demographic variables. Considering the non-normality of the hypothesis H0, to compare the means of the independent variables, Mann-Whitney non-parametric tests (for the variables of gender, the field of study, academic semester, employment status, province of residence, and whether it is rural or urban) and Kruskal Wallis (for the variables age, ethnicity, level of education, household income and marital status). According to the obtained results, it was found that the score of problematic use of social media is significantly higher in women, the age group less than 20 years, unemployed, non-native students, dormitory students, and students living with friends or alone, Fars students, students with a household income level of fewer than 7 million Tomans(Iranian currency), and single, divorced, and widowed students were higher than the other groups(P < 0.05).

By comparing the mean score of mental health with demographic variables using non-parametric Mann-Whitney and Kruskal Wallis tests, it was found that there is a significant difference between the variable of poor mental health and all demographic variables (except for the semester variable), residence status (rural or urban) and education level. (There was a significant relationship (P < 0.05). In such a way that the mental health condition was worse in women, age group less than 20 years old, non-medical science, unemployed, non-native, and dormitory students. Also, Fars students, divorced, widowed, and students with a household income of fewer than 5 million Tomans (Iranian currency) showed poorer mental health status. (Table  1 ).

The final model shows that marital status, field, and household income were significantly associated with lower DASS21 scores (a lower DASS21 score means better mental health status). Being single (β* = -23.03, 95% CI: (-33.10, -12.96), being married (β* = -38.78, 95% CI: -51.23, -26.33), was in Medical sciences fields (β* = -8.15, 95% CI: -11.37, -4.94), and have income 7–10 million (β* = -5.66, 95% CI: -9.62, -1.71) were significantly associated with lower DASS21 scores (a lower DASS21 score means better mental health status). Problematic use of social media (β* = 3.54, 95% CI: (3.23, 3.85) was significantly associated with higher mental health scores (a higher DASS21 score means worse mental health status). (Table  2 )

Age, income, and use of social media (β* = 1.02, 95% CI: 0.78, 1.25) were significantly associated with higher DASS21 scores (a higher DASS21 score means worse mental health status). Marital status and field were significantly associated with lower DASS21 scores (a lower DASS21 score means better mental health status). Age groups < 20 years (β* = 6.36, 95% CI: 0.78, 11.95) and income group < 5 million (β* = 6.58, 95% CI: 1.47, 11.70) increased mental health scores. Being single (β* = -34.72, 95% CI: -47.06, -38.78), being married (β* = -38.78, 95% CI: -51.23, -26.33) and in medical sciences fields (β* = -8.17, 95% CI: -12.09, -4.24) decreased DASS21 scores. (Table  3 )

The main purpose of this study was to determine the relationship between social media use and mental health among students during the COVID-19 pandemic.

University students are more reliant on social media because of the limitations of in-person interactions [ 45 ]. Since social media has become more and more vital to the social lives of university students during the pandemic, students may be at increased risk of social media addiction, which may be harmful to their mental health [ 14 ].

During non-adulthood, peer relations and approval are critical and social media seems to meet these needs. For example, connection and communication with friends make them feel better and happier, especially during the COVID-19 pandemic and national lockdowns where face-to-face communication was restricted [ 46 ]. Kele’s study showed that the COVID-19 pandemic has increased the time spent on social media, and the frequency of online activities [ 47 ].

Because of the COVID-19 pandemic, e-learning became the only sustainable option for students [ 13 ]. This abrupt transition can lead to depression, stress, or anxiety for some students due to insufficient time to adjust to the new learning environment. The role of social media is also important to some university students [ 48 ].

Staying at home, having nothing else to do, and being unable to go out and meet with friends due to the lockdown measures increased the time spent on social media and the frequency of online activities, which influenced their mental health negatively [ 49 ]. These reasons may explain the findings of previous studies that found an increase in depression and anxiety among adolescents who were healthy before the COVID-19 pandemic [ 50 ].

According to the results, there was a statistically significant relationship between social media use and mental health in students, in such a way that one Unit increase in the score of social media use enhanced the score of mental health. These two variables were directly correlated. Consistent with the current study, many studies have shown a significant relationship between higher use of social media and lower mental health in students [ 45 , 51 , 52 , 53 , 54 ].

Inconsistent with the findings of the present study, some previous studies reported the positive effect of social media use on mental health [ 55 , 56 , 57 ]. The differences in findings could be attributed to the time and location of the studies. Anderson’s study in France in 2018 found no significant relationship between social media use and mental health. This may be because of the differences between the tools for measuring the ability to detect fake news and health literacy and the scales of the research [ 4 ].

The present study showed that the impact of using social media on the mental health of students was higher than Lebni’s study, which was conducted in 2020 [ 25 ]. Also, in Dost Mohammad’s study in 2018, the effect of using social media on the mental health of students was reported to be lower than in the present study [ 58 ]. Entezari’s study in 2021, was also lower than the present study [ 59 ]. It seems that the excessive use of social media during the COVID-19 pandemic was the reason for the greater effects of social media on students’ mental health.

The use of social media has positive and negative characteristics. Social media is most useful for rapidly disseminating timely information via widely accessible platforms [ 4 ]. Among the types of studies, at least one shows an inverse relationship between the use of social media and mental health [ 53 ]. While social media can serve as a tool for fostering connection during periods of physical isolation, the mental health implications of social media being used as a news source are tenuous [ 45 ].

The results of the GLM analysis indicated that there was a statistically significant relationship between the problematic use of social media and mental health in students in such a way that one-unit increase in the score of problematic use of social media enhanced the mental health score, and it was found that the two variables had a direct relationship. Consistent with our study, Boer’s study showed that problematic use of social media may highlight the potential risk to adolescent mental health [ 60 ]. Malaeb also reported that the problematic use of social media had a positive relationship with mental health [ 61 ], but that study was conducted on adults and had a smaller sample size before the COVID-19 pandemic.

Saputri’s study found that excessive social media use likely harms the mental health of university students since students with higher social media addiction scores had a greater risk of experiencing mild depression [ 62 ]. A systematic literature review before the COVID-19 pandemic (2019) found that the time spent by adolescents on social media was associated with depression, anxiety, and psychological distress [ 63 ]. Marino’s study (2018) reported a significant correlation between the problematic use of social media by students and psychological distress [ 64 ].

Social media has become more vital for students’ social lives owing to online education during the COVID-19 pandemic. Therefore, this group is more at risk of addiction to social media and may experience more mental health problems than other groups. Lebni also indicated that students’ higher use of the Internet led to anxiety, depression, and adverse mental health, but the main purpose of the study was to investigate the effects of such factors on student’s academic performance [ 25 ]. Previous studies indicated that individuals who spent more time on social media had lower self-esteem and higher levels of anxiety and depression [ 65 , 66 ]. In the present study, students with higher social media addiction scores were at higher mental health risk. Such a finding was consistent with research by Gao et al., who found that the excessive use of social media during the pandemic had adverse effects on social health [ 14 ]. Cheng et al. indicated that using the Internet, especially for communication with people, can harm mental health by changing the quality of social relationships, face-to-face communication, and changes in social support [ 24 ].

A reason for the significant relationship between social media use and mental health in students during the COVID-19 pandemic in the present study was probably the students’ intentional or unintentional use of online communication. Unfortunately, social media published information, which might be incorrect, in this pandemic that caused public fear and threatened mental health.

During the pandemic, social media played essential roles in learning and leisure activities. Due to electronic education, staying at home, and long leisure time, students had more time, frequency, and opportunities to use social media in this pandemic. Such a high reliance on social media may threaten student’s mental health. Lee et al. conducted a study during the COVID-19 pandemic and confirmed that young people who used social media had higher symptoms of depression and loneliness than before the COVID-19 pandemic [ 67 ].

The present study showed that there was a significant positive relationship between problematic use of social media and gender, so that women were more willing to use social media, probably because they had more opportunities to use social media as they stayed at home more than men; hence, they were more exposed to problematic use of social media. Consistent with our study, Andreassen reported that being a woman was an important factor in social media addiction [ 68 ]. In contrast to our study, Azizi’s study in Iran showed that male students use social media significantly more than female students, possibly due to differences in demographic variables in each population [ 69 ].

Moreover, there was a significant relationship between age and problematic use of social media in that people younger than 20 were more willing to use social media in a problematic way. Consistent with the present study, Perrin also indicated that younger people further used social media [ 70 ].

According to the findings, unemployed students used social media more than employed ones, probably because they had more time to spend in virtual space, leading to higher use and the possibility of problematic use of social media [ 71 ].

Moreover, non-native students were more willing to use the social media probably because students who lived far away from their families used social media problematically due to the lack of family control over hours of use and higher opportunities [ 72 ] .

The results showed that rural students have a greater tendency to use social Medias than urban students. Inconsistent with this finding, Perrin reported that urban people were more willing to use the social media. The difference was probably due to different research times and places or different target groups [ 70 ].

According to the current study, people with low household income were more likely to use social media, most likely because low-income people seek free information and services due to a lack of access to facilities and equipment in the real world or because they seek assimilation with people around them. Inconsistent with our findings, Hruska et al. reported that people with high household income levels made much use of social media [ 73 ], probably because of cultural, economic, and social differences or different information measurement tools.

Furthermore, single, divorced, and widowed students used social media more than married students. This is because they spend more time on social media due to the need for more emotional attention, the search for a life partner, or a feeling of loneliness. This also led to the problematic use of social media [ 74 ].

According to the results, Fars people used social media more than other ethnic groups, but this difference was insignificant. This finding was consistent with Perrin’s study, but the population consisted of people aged 18 to 65 [ 70 ].

In the current study, there was a significant relationship between gender and mental health, so that women had lower mental health than men. The difference was in health sociology. Consistent with the present study, Ghasemi et al. indicated that it appeared necessary to pay more attention to women’s health and create an opportunity for them to use health services [ 75 ].

The findings revealed that unemployed students had lower mental health than employed students, most likely because unemployed individuals have lower mental health due to not having a job and being economically dependent on others, as well as feeling incompetent at times. Consistent with the present study, Bialowolski reported that unemployment and low income caused mental disorders and threatened mental health [ 76 ].

According to this study, non-native students have lower mental health than native students because they live far from their families. The family plays an imperative role in improving the mental health of their children, and mental health requires their support. Also, the economic, social, and support problems caused by being away from the family have endangered their mental health [ 77 ].

Another important factor of the current study was that married people had higher mental health than single people. In addition, divorced and widowed students had lower mental health [ 78 ]. Possibly due to the social pressure they suffer in Iranian society. Furthermore, they received lower emotional support than married people. Therefore, their lower mental health seemed logical [ 79 , 80 , 81 ]. A large study in a European population also reported differences in the likelihood of mood, anxiety, and personality disorders between separated/divorced and married mothers [ 82 ].

A key point confirmed in other studies is the relationship between low incomes with mental health. A meta-analysis by Lorant indicated that economic and social inequalities caused mental disorders [ 83 ]. Safran also reported that the probability of developing mental disorders in people with low socioeconomic status is up to three times higher than that of people with the highest socioeconomic status [ 84 ]. Bialowolski’s study was consistent with the current study but Bialowolski’s study examined employees [ 76 ].

The present study was conducted during the COVID-19 pandemic and therefore had limitations in accessing students. Another limitation was the use of self-reporting tools. Participants may show positive self-presentation by over- or under-reporting their social media-related behaviors and some mental health-related items, which may directly or indirectly lead to social desirability bias, information bias, and reporting bias. Small sample sizes and convenience sampling limit student population representativeness and generalizability. This study was based on cross-sectional data. Therefore, the estimation results should be seen as associative rather than causative. Future studies would need to investigate causal effects using a longitudinal or cohort design, or another causal effect research design.

The findings of this study indicated that the high use of social media affected students’ mental health. Furthermore, the problematic use of the social media had a direct relationship with mental health. Variables such as age, gender, income level, marital status, and unemployment of non-native students had significant relationships with social media use and mental health. Despite the large amount of evidence suggesting that social media harms mental health, more research is still necessary to determine the cause and how social media can be used without harmful effects. It is imperative to better understand the relationship between social media use and mental health symptoms among young people to prevent such a negative outcome.

Data Availability

The datasets used and/or analyzed during the current study are available from the corresponding author on reasonable request.

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The authors would like to express their gratitude to all academic officials of Lorestan universities and Mr. Mohsen Amani for their cooperation in data collection.

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Abouzar Nazari and Maedeh Hossennia designed the study, collected the data and drafted the manuscript. Samaneh Torkian performed the statistical analysis and prepared the tables. Gholamreza Garmaroudi, as the responsible author, supervised the entire study. All authors reviewed and edited the draft manuscript and approved the final version.

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Nazari, A., Hosseinnia, M., Torkian, S. et al. Social media and mental health in students: a cross-sectional study during the Covid-19 pandemic. BMC Psychiatry 23 , 458 (2023). https://doi.org/10.1186/s12888-023-04859-w

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Prevalence of anxiety, depression, and post-traumatic stress disorder among paramedic students: a systematic review and meta-analysis

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• Adnan Alzahrani   ORCID: orcid.org/0000-0001-9234-9426 1 , 2 ,
• Chris Keyworth 1 ,
• Khalid Mufleh Alshahrani 1 , 3 ,
• Rayan Alkhelaifi 4 &
• Judith Johnson 1 , 5 , 6  

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There are elevated mental health concerns in paramedic students, but estimates vary between studies and countries, and no review has established the overall prevalence. This systematic review addressed this by estimating the global prevalence of common mental health disorders, namely anxiety, depression, and post-traumatic stress disorder (PTSD), in paramedic students internationally.

A systematic search of six databases, including MEDLINE, EMBASE, PsycINFO, CINAHL, Scopus, and medRxiv, was conducted to identify studies relating to mental health among paramedicine students. The search encompassed studies from inception until February 2023. To be considered for inclusion in the review, the studies had to report prevalence data on at least one symptom of anxiety, depression, or PTSD in paramedicine students, using quantitative validated scales. The quality of the studies was assessed using Joanna Briggs Institute (JBI) Checklist, which is a specific methodological tool for assessing prevalence studies. Subgroup analyses were not conducted due to insufficient data.

1638 articles were identified from the searches, and 193 full texts were screened, resulting in 13 papers for the systematic review and meta-analysis. The total number of participants was 1064 from 10 countries. The pooled prevalence of moderate PTSD was 17.9% (95% CI 14.8–21.6%), anxiety was 56.4% (95% CI 35,9–75%), and depression was at 34.7% (95% CI 23.4–48.1%).

This systematic review and meta-analysis has found that paramedicine students globally exhibit a high prevalence of moderate PTSD, anxiety, and depression. The prevalence of these mental health conditions surpasses those among paramedic providers and the general population, as indicated by previous reviews. Further research is therefore warranted to determine appropriate support and interventions for this group.

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Introduction

Mental health disorders are common in the general population, with anxiety affecting around 301 million (4% of the global population) according to the Global Burden of Disease Study in 2019 [ 18 ]. Similarly, depression affecting around 280 million [ 52 ]. The underlying causes of mental health disorders are complex, but evidence suggests that risk of these is elevated in occupational groups who experience potentially stressful events in the course of their work [ 57 , 59 , 57 ]. One such high-risk group is paramedics [ 20 ]. Several studies have found a higher rate of mental health issues (e.g., depression, PTSD, stress) among paramedics than in the general population [ 4 , 5 , 29 , 36 , 47 ]. For example, in Saudi Arabia, the prevalence of anxiety and depression among the general population is between 12.4% and 12.7% respectively [ 1 , 2 ]. However, for paramedics and paramedic students, the rates of anxiety are 19.3% [ 3 ] and 24.3% [ 6 ].

Paramedics are a fundamental part of the healthcare system, enacting clinical and non-clinical roles in a variety of unscheduled and dynamic settings (e.g., prehospital; [ 13 , 54 ]). Thus, they face innumerable challenges as they must handle different cases in unpredictable contexts [ 10 , 26 ] and be ready to make life-or-death decisions in a limited time frame. Some of the greatest burdens to paramedics’ mental health are found in their daily tasks and work environments, including attending to traumatic cases (e.g., death, severe trauma), lack of resources, and long shifts [ 4 , 5 ], 58 , 20 ] [ 33 ]. These burdens pose significant challenges, including related physical and mental demands, and so it is unsurprising that the risk of common mental health disorders is elevated in this group [ 4 , 5 , 24 , 40 ].

Internationally, the training for paramedics involves practical clinical placements [ 14 ]. As such, paramedic students also face similar challenges to qualified paramedics [ 16 ]. Furthermore, paramedic students encounter additional challenges related to academic requirements and training placements [ 7 , 16 , 26 ]. A limited number of studies have examined the mental wellbeing of paramedic students and their findings have suggested that mental health disorders are more prevalent among paramedic students than the general population [ 6 , 16 , 36 ]. However, the global prevalence of mental health problems among paramedic students is unclear. Compared to pharmacy, medicine, and nursing students [ 27 , 46 , 48 ], respectively), paramedicine is an understudied major health speciality in tertiary education, with no current systematic review investigating the prevalence of mental health issues among the paramedic student population [ 19 ]. Quantifying the global rate of mental health disorders among paramedic students could highlight the extent to which addressing this should be prioritised by policymakers, researchers, clinicians, and tertiary academicians to understand the mental health needs of paramedic students [ 19 ].

Accordingly, this systematic review aimed to estimate the prevalence of common mental health disorders (i.e., anxiety, depression, PTSD) among paramedic students internationally [ 30 , 53 ].

The current systematic review followed the PRISMA statement and the Institute of Medicine’s Standards for Systematic Reviews [ 42 , 34 ]. A protocol was registered in the PROSPERO International Register of Systematic Reviews (Registration No: CRD42022303570). To identify relevant studies of mental health issues among paramedic students and associated variables, major health databases were searched from inception to January 30, 2022, with the search updated on February 12, 2023.

Search strategy

To identify relevant citations for inclusion, six databases were searched: CINAHL (EBSCOhost), EMBASE (ELSEVIER), Medline (Ovid), PsycINFO, Scopus, medRxiv (grey literature and pre-prints from bioRxiv and medRxiv). To identify relevant studies with data on mental health disorders among paramedic students and associated variables, the databases were searched from inception to January 30, 2022, with the search updated on February 12, 2023. The search strategy included Medical Subject Headings (MeSH) terms and keywords/phrases describing the population and the outcome; a language restriction was also placed on potentially relevant records. Further, the researchers manually searched reference lists and citation chaining of the included articles, which helped identify additional relevant articles. The search results from each database were exported, and the duplicates were removed. Only articles in the English language were included. All searches employed two main search blocks: mental health (anxiety, depression, and PTSD) and paramedic students.

Eligibility criteria

The criteria for studies to be eligible for inclusion regarding population were if they only included participants enrolled in a paramedicine academic training programme and if they excluded qualified paramedics and volunteers. No interventions or comparators were applied in the review, and all quantitative study designs were included. Where studies reported more than one measurement of the outcome variables of interest (i.e., in the case of cohort/intervention studies), we included baseline measurements in our analysis. Additionally, mixed-method studies with quantitative data were also considered. The inclusion criteria included studies that measured anxiety, depression, or PTSD symptoms using any type of quantitative design, including grey literature. The exclusion criteria included qualitative studies without any quantitative element and studies that did not use validated questionnaires to measure outcome variables. The review’s primary outcomes were the prevalence of anxiety, depression, and PTSD among paramedic students, and there were no secondary outcomes.

Study selection

The search results from each database were exported to Endnote X8.2 (Clarivate Analytics, Philadelphia, United States), and all duplicates were removed. The study selections were completed in two stages: in the first stage, the titles and abstracts of the identified studies were screened; in the second stage, the full texts of the retained studies were accessed and further screened according to the eligibility criteria. A percentage of titles/abstracts (10%) was screened independently by two reviewers to check for agreement (KA and RA). To estimate the level of agreement, we calculated the Kappa score, which indicated good agreement (k = 0.739). The remaining screening of titles/abstracts against the selection criteria was undertaken by two reviewers (AA and RA). Three independent reviewers each undertook the full-text screening (AA, KA, and RA). All disagreements were resolved through discussion; there was 100% agreement between reviewers on the second review.

Data extraction

A data extraction form was devised in Excel 2016 16.7 (Microsoft Inc.) and piloted with five randomly selected studies. The quantitative data for the meta-analysis were extracted in a separate Excel file. The following descriptive information was extracted from the eligible studies: (1) study (country, recruitment methods, research design), (2) participants (age, gender, sample size, setting), (3) outcome variables (assessments to measure anxiety, depression, and/or PTSD and the reported prevalence of each outcome). The data were extracted by AA and reviewed by CK, JJ, KA, and RA.

Quality assessment

The quality of the studies was assessed independently by two reviewers using the Joanna Briggs Institute (JBI) Critical Appraisal Checklist for Studies Reporting Prevalence Data [ 60 ]. Through this instrument, study quality was assessed across nine domains: the suitability of the sample to represent the target population, the recruitment methods, the sample size, the identification of the sample and the subjects, the data analysis approach used for the sample, the methods chosen to identify the outcome, the measurement of the condition, the appropriateness of the statistical findings, and the adequacy of the response rate. The nine items can be answered with ‘Yes’, ‘No’, ‘Unclear’, or ‘Not Applicable’. All disagreements between authors were resolved through discussion.

Data analysis

All studies included in this project are described in a narrative review, including a table that quantifies our primary outcomes, design, and participant characteristics (see Table  1 ). The methods of the included studies varied, with different scales and cut-off scores implemented to identify the prevalence of anxiety, depression, and PTSD. To ensure an accurate interpretation, the prevalence of the selected mental health disorders was estimated using the moderate and above cut-off levels recommended on each of the scales.

PTSD, anxiety and depression studies included in the meta-analysis were examined using comprehensive meta-analysis (CMA) software. A random-effects meta-analysis was conducted using pooled mean prevalence estimates and expressed as an event rate. The results were calculated using a 95% confidence interval (CI) and p -value. A high heterogeneity was expected, given the probable levels of heterogeneity. The random effect is preferred in such cases; however, the fixed model is favoured for prevalence studies to maintain the weight of studies. Therefore, both the random and fixed effects were displayed in the results (M. [ 12 , 35 ]). Where appropriate, heterogeneity factors were assessed using the Higgins inconsistency test (I 2 ) and p -value. A p-value below 0.05 was considered statistically significant [ 25 ]. The risk of publication bias was examined through Egger’s test and Begg’s funnel plot, which were prepared using CMA software [ 9 , 15 ]. See Appendix 1, 2, and 3C. No subgroup analyses were performed due to insufficient data available for analysis.

Study characteristics

A total of 1638 articles from six databases were identified (See Fig.  1 ). After removing duplicates, 1,081 studies remained. During the title and abstract screening phase, 850 studies were excluded as they did not match the current systematic review criteria; 193 studies were screened fully. Only 38 studies met the inclusion criteria, and a further 23 of these were excluded as the researchers could not obtain the relevant data, even after contacting the study authors. Thus, 13 studies were included in the systematic review [ 6 , 8 , 13 , 16 , 21 , 22 , 32 , 34 , 37 , 38 , 39 , 51 , 55 , 56 ], and met the criteria for meta-analysis. Of these 13 studies, six were included in the final set for PTSD, seven for anxiety, and six for depression. Please refer to Fig.  1 for the PRISMA diagram.

“PRISMA 2020 Flow Diagram” [ 42 ]

Articles were primarily excluded in the first and second screening stages due to the study population (n = 626), outcomes (n = 234), design (n = 137), and publication type (n = 10). During the eligibility stage, articles were primarily excluded because the rate of each disorder of interest among paramedic students could not be identified, a lack of detailed results provided for each scale, and reporting of the mean results only.

A total of 1623 participants were included in the review; from this sample, 1064 paramedic students from 13 studies conducted across 10 countries were included in the meta-analyses. The included studies were published between 1996 and 2022, with the number of studies increasing with time.

Six studies were cross-sectional, including a prevalence-based study; two were mixed methods; two were longitudinal, including a study that provided outcomes from two different collection points as well as baseline prevalence data for the second dataset; three were cohort studies; and two used alternative study designs. Regarding the sampling techniques, 12 studies used non-random methods (purposeful sampling and convenience sampling), while the remaining three used random or census methods. If the sample methods were not mentioned, they were listed as non-random methods.

Regarding gender, 56% of the participants were male and 43% were female. In two studies, no gender information was listed. All the studies used self-report scales to identify the prevalence of mental health conditions, and no study used a clinical diagnostic interview. For further information, see Appendix 2, 3, 4B.

Mental health outcomes

Prevalence of posttraumatic stress disorder.

Six studies reported symptoms of PTSD among paramedic students. These symptoms were assessed using the following four scales: the PTSD Checklist for DSM-5 (PCL-5), the Posttraumatic Stress Diagnostic Scale (PDS), the Davidson Trauma Scale (DTS), and Keane’s MMPI scale (PK) for PTSD. The pooled prevalence estimate of moderate PTSD was 17.9% (95% CI, 14.8–21.6%; see Appendix Table E), with a range of 5–22%. The heterogeneity was low (I2 = 1%, p < 0.001), reflecting variance in true effects rather than sampling error. This was evidenced through the Q-value, which was 6.055 with six degrees of freedom and p 0.417. The pooled estimate of mild PTSD was not presented due to a lack of available data for four studies.

Prevalence of anxiety

Seven studies reported symptoms of anxiety among paramedic students. Five scales were used in these studies, including the seven-item Generalised Anxiety Disorder Scale (GAD-7), Depression Anxiety Stress Scales (DASS-21), Westside Test Anxiety Scale (WTA), Trait Anxiety Inventory (TAI), and State-Trait Anxiety Inventory (STAI). The pooled estimated prevalence of moderate anxiety was found to be 56.4% (95% CI 35.9%, 75%). While the prevalence of mild anxiety, according to the analysis of four studies, was estimated at 27.1% (95% CI 15.8%, 42.4%). The estimated range of moderate anxiety on each study varied between 24.3 and 94%. The statistical analysis revealed high heterogeneity (I 2  = 96%, p  < 0.001) among the studies, indicating a difference in true effects rather than sampling error. The Q-value was 155.907 with seven degrees of freedom and p  < 0.001. Subgroup analyses were not conducted due to insufficient studies for comparison.

Prevalence of depression

Six studies reported symptoms of depression among paramedic students. These studies used six scales: the Beck Depression Inventory and Revised Beck Depression Inventory (BDI & BDI-II), the DASS-21, the Center for Epidemiological Studies Depression Scale (CES-D), the nine-item Patient Health Questionnaire (PHQ-9), and the Kessler Psychological Distress Scale (K10). Based on six scales, the prevalence of moderate depression was estimated at 34.7% (95% CI 0.234–0.481). The range of prevalence estimates across the studies was between 8 and 56.2%. However, there was a high level of heterogeneity between the studies, with an I 2 of 83%, indicating a difference in true effects rather than sampling error. The Q-value is 28.616 with 5 degrees of freedom and p  < 0.001. Unfortunately, the pooled estimate of mild depression could not be presented due to the lack of available data. Further, subgroup analyses were not conducted as there was insufficient data to make comparisons.

Publication bias

Various methods were used to evaluate publication bias. For PTSD, Begg’s funnel plot indicated symmetry (see graph 1c), while Egger’s test showed non-significance with an intercept (B0) of  – 1.685 and a 95% confidence interval ( – 3.99623, 0.62586) and a p -value of 0.0598. The null hypothesis was not rejected with a criterion alpha of 0.100, as the actual effect size varied among the studies. The prediction interval was estimated to be between 13.8 and 23%, with the true effect size falling within this range for 95% of similar populations. For anxiety, Begg’s funnel plot suggested publication bias (see graph 2c). Still, Egger’s test did not provide any significant evidence, with an intercept (B0) of 5.71895, a 95% confidence interval ( – 3.22881, 14.66671), and a p-value of 0.08443. The null hypothesis was rejected with a criterion alpha of 0.100, as the true effect size differed in all studies. The prediction interval was estimated to be between 6.3 and 96.1%, with the true effect size in 95% of all comparable populations falling in this range. For depression, while there was possible publication bias due to a slightly asymmetric Begg’s funnel plot, Egger’s test ( p  = 0.18) found no significant evidence of bias, with an intercept (B0) of  – 2.19777, a 95% confidence interval (-8.28963, 3.89409), and a p -value of 0.18659. The null hypothesis was rejected with a criterion alpha of 0.100, as the true effect size differed in all studies. The prediction interval was estimated to be between 8.2 and 75.9%, with the true effect size in 95% of all comparable populations falling within this range.

Sensitivity analyses

In order to test sensitivity, the leave-one-out method was used, as described by Higgins et al. [ 61 ]. The prevalence of PTSD remained unchanged as a result of the application, with minor changes ranging from 0.06% to 13.5% in six studies and remaining significant. This suggests that a single study did not influence the findings, as two studies showed an increase of 2.3% and a decrease of 5.3%, respectively. For anxiety, the prevalence changed in three studies, while it increased from 5.4% to 10% in four studies. The remaining three studies showed an increase of 3.9–5.6%, although the relative weight remained almost the same in five studies. Regarding depression, the prevalence remained unchanged as a result of the application, with slight changes ranging from 0.07% to 3% in four studies. However, in only two studies, the difference was between 3 and 7%, indicating that two to four studies influenced the results for anxiety and depression.

To our knowledge, this is the first systematic review and meta-analysis examining the prevalence of anxiety, depression, and post-traumatic stress disorder among the paramedic student population. Accordingly, the current project presents a major contribution to the literature as it illustrates the prevalence of mental health conditions using 15 studies from 10 countries examining a total of 1,392 paramedic students. The prevalence demonstrated high rates of moderate-to-high anxiety (56%), depression (34%), and PTSD (17.9%). These findings are consistent with a systematic review of paramedics, which reported lower rates of PTSD than other mental health conditions [ 43 ].

The pooled estimate for mental health disorders among paramedicine students was higher than those found in similar reviews of qualified paramedics [ 17 , 28 , 41 , 43 ]. It is possible that this is due to stressors related to the experiences involved in paramedicine training programmes. The clinical training for paramedicine varies by country and university,some students are sent to prehospital providers and different hospital departments, while others receive further training facilities. This diversity of experiences adds to the complexity of their training and the challenges they face. Furthermore, some programs send students for clinical training as early as their first month of the program. The training focuses on monitoring the field and caring for patients in time-sensitive situations, in a limited space, and with several cases and challenges encountered. It is also worth noting that the current prevalence of mental health conditions among paramedic students is higher than in other student populations, indicating the need for collective attention and action to prevent adverse effects on paramedicine student wellbeing [ 7 , 23 , 44 ] and educational outcomes [ 31 ].

The results of our systematic review have shown that paramedic students are more likely to experience anxiety than other mental health conditions. This is consistent with wider trends in mental health disorder occurrence, which highlight anxiety as the most common mental health disorder [ 18 ]. This could also be attributed to the COVID-19 pandemic, which was initially associated with an increase in anxiety worldwide [ 56 ]. However, more recent meta-analyses comparing mental health symptoms before and after the COVID-19 pandemic suggests any initial differences in mental health symptoms in the general population have since reduced to pre-pandemic levels, with only a slight maintained increase in healthcare providers [ 45 , 49 , 50 ].

The findings revealed substantial heterogeneity among all the mental health outcomes. It was particularly important to consider the high heterogeneity between anxiety, depression, and PTSD when interpreting the estimated pooled prevalence in our meta-analysis of the percentage of variability (I 2 ). Each disorder had between six and six to seven studies with eight intakes, such as PTSD. Generally, estimates of heterogeneity based on fewer than 10 studies are unreliable [ 11 ]. As a result of the limited data available, a subgroup analysis could not be performed to test for evidence related to content or screening tools. Furthermore, we could not fully explain the high heterogeneity, particularly given the limited number of studies and the different scales used.

Regarding PTSD, studies that used the PCL-5 showed a similar prevalence rate (i.e., between 16 and 17%). However, the sample size and the date of the study showed no significance. Regarding depression, no scales showed any similar patterns to anxiety and PTSD. The studies published since the COVID-19 pandemic reported higher rates of depression than those published before, but it should be noted that all included studies were conducted during earlier phases of the pandemic and wider trends suggest that rates of depression have since returned to pre-pandemic levels [ 45 , 49 , 50 ].

Strengths and limitations

The primary strength of this systematic review is that it focuses on an international population with no limits to specific geographic areas or academic systems. Further, the study was registered on Prospero and followed the PRISMA guidelines to ensure methodological rigour. Two reviewers screened all the studies in the title and abstract stages, with a third reviewer conducting a full review for the data extraction.

However, there are several limitations to the employed methodology. The majority of the studies in the review used non-random sampling methods, which could generate selection bias. Some studies may have been missed as only articles written in English were included in the systematic review. Additionally, while preprint study was included to gather as much data as possible, the results of such studies could change from preprint to publication but that was not the case in the studies included.

The findings revealed substantial heterogeneity among all the mental health outcomes. It was particularly important to consider the high heterogeneity between anxiety, depression, and PTSD when interpreting the estimated pooled prevalence in our meta-analysis of the percentage of variability (I 2 ). Each disorder had between six to seven studies with eight intakes, such as anxiety. Generally, estimates of heterogeneity based on fewer than 10 studies are unreliable [ 11 ]. As a result of the limited number of studies available to be included in the review, it was not possible to conduct subgroup analyses or meta-regression to investigate moderating effects or to compare for differences according to factors such as screening tools used [ 64 , 65 ]. Furthermore, we could not fully explain the high heterogeneity, particularly given the limited number of studies and the different scales used. This issue was particularly evident in studies from countries with unconventional paramedicine training systems, such as India and Iran. Further, although the researchers attempted to contact study authors who did not list their full outcomes, many did not respond, despite being contacted over three times in a six-month period.

Further, the samples used in the studies were limited, with some being from one setting and one university only. Thus, the approach lacked randomisation. Begg’s funnel plots revealed signs of slight-to-high publication bias, but Egger’s test results did not reflect the same bias. The limited sample and lack of available data undoubtedly contributed to these discrepancies.

The present systematic review and meta-analyses provide the most comprehensive information on the prevalence of anxiety, depression, and PTSD among international paramedic students to date. Results suggest that paramedic students are at risk for common mental health conditions, particularly anxiety. This review can guide future research on the mental health of paramedic students internationally, a population that faces numerous and varied challenges and stressors with long-term negative effects. All parties involved, from academic administrators to service providers, need to take decisive action to meet the needs and address the concerns of paramedic students before they enter the field. Globally, universities must implement more support initiatives and improve existing mental health interventions in paramedicine programmes, particularly in collaboration with paramedic students.

Availability of data and materials

The datasets generated and/or analysed during the current study are publicly available in published studies.

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Acknowledgements

The authors appreciate all the respected researchers whose work was included in our reviews.

This research was funded by King Saud University in Saudi Arabia.

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Adnan Alzahrani, Chris Keyworth, Khalid Mufleh Alshahrani & Judith Johnson

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Adnan Alzahrani (A.A.), Chris Keyworth (C.K.), and Judith Johnson (J.J.) were responsible for designing and implementing the research, analysing the results, and writing the manuscript. Khalid Mufleh Alshahrani(K.A.) and Rayan Alkhelaifi(R.A.) assisted in study design, screening and data extractions and critically revised the manuscript. All authors read and approved the final manuscript.

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Appendix: 1e meta-analysis table for ptsd studies.

Appendix: 1C Funnel plot for PTSD studies

Appendix: 1F Data extraction PTSD

• PCL PTSD Checklist. PTDS Posttraumatic Stress Diagnostic Scale. PDS Posttraumatic Stress Diagnostic Scale. N Number of participant See the study coding in Appendix 1
• a Scale of Posttraumatic Stress Symptoms. DTS Davidson Trauma Scale

Appendix 2E Meta-analysis table for anxiety studies

Appendix: 2C Funnel plot for anxiety studies

Appendix: 2F Data extraction anxiety

• GAD-7 7-item Generalised Anxiety Disorder Scale, DASS Depression Anxiety Stress Scales, WTA Westside Test Anxiety Scale, TAI Trait Anxiety Inventory, STAI state-trait anxiety inventory

Appendix 3E Meta-analysis table for Depression studies

Appendix: 3C Funnel plot for depression studies

Appendix: 3F Data extraction depression

• aBDI Beck Depression Inventory, BDI-II Beck Depression Inventory, DASS Depression Anxiety Stress Scales, CES-D Centre for Epidemiological Studies Depression Scale, PHQ-9 The Nine items Patient Health Questionnaire, K10 The Kessler Psychological Distress Scale

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Alzahrani, A., Keyworth, C., Alshahrani, K.M. et al. Prevalence of anxiety, depression, and post-traumatic stress disorder among paramedic students: a systematic review and meta-analysis. Soc Psychiatry Psychiatr Epidemiol (2024). https://doi.org/10.1007/s00127-024-02755-6

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College students’ mental health improving, more finding support

• Kim North Shine

The latest annual Healthy Minds Study , which surveyed 100,000-plus college students from 200 universities across the United States, has good news to report: There are decreases in symptoms of anxiety, depression and thoughts of suicide, and increases in receiving mental health care and support.

In general, the latest report from the Healthy Minds Network found that college students seem to be flourishing more but mental illness and related issues for this age group remain a pressing concern.

“Mental health problems continue to be highly prevalent in college student populations, but the reports from students for this year’s study are promising,” said Justin Heinze of the University of Michigan, one of four principal investigators along with Daniel Eisenberg of UCLA, Sarah Ketchen Lipson of Boston University and Sasha Zhou of Wayne State University.

The study data, which was gathered through confidential online surveys taken by undergraduate and graduate students randomly selected by each school’s administrations, boiled down the students’ responses on: depressive symptoms, anxiety, eating disorders, diagnoses of mental illness, suicidal thoughts and nonsuicidal self-injury, history of mental illness, use of therapy or counseling, and stigma.

Some 104,000 students’ responses were used for the 2023-24 study. The emailed, web-based surveys are timed to avoid the first two weeks of the term, the final week of the term and holidays. This is the 15th year of the study and report, which is produced by the Healthy Minds Network. More than 850,000 students at 600-plus colleges and universities have participated.

Relative to previous years, students’ responses this year showed:

• A decrease in severe depressive symptoms from 23% in 2022 and 20% in 2023 to 19% in 2024.
• Moderate depressive symptoms decreased from 44% in 2022 and 42% in 2023 to 38% in 2024.
• After remaining unchanged at 14% in 2022 and 2023, reports of eating disorders dropped 1%.
• Nonsuicidal self-injury dropped to 13% in 2024, 2% less than 2022 and 1% less than last year.
• Among students with depressive or anxiety symptoms, more students (61%) are using mental health therapy or counseling. In 2022, the number was 60% and in 2023 the number dropped to 59%.
• More students reported taking psychiatric medication: 31% this year vs. 29% in 2022 and 2023.
• Attitudes about mental health remain generally positive. Only 7% of students agree that they would think less of someone who has received mental health treatment, a slight uptick from 6% in prior years. However, the number who reported that others would think less of someone who received mental health treatment was 41%, the same as last year and a percentage point higher than two years ago.

“For the first time in roughly 15 years of collecting Healthy Minds data, we have seen two consecutive years of improved outcomes from fall 2022 through spring 2024,” said Ketchen Lipson, BU associate professor of health law, policy and management.

The improvements might also be related to students bouncing back from the effects of the COVID-19 pandemic.

“This positive trend probably reflects more stability and social connection after the pandemic, as well as institutions’ greater efforts to support student mental health,” said Eisenberg, UCLA professor of health policy and management. “One of our major goals in the coming years is to help clarify which population-level strategies are most effective for supporting student mental health.”

The detailed picture of mental health and related issues provided by the Healthy Minds Study is typically used by schools to identify needs and priorities, benchmark against peer institutions, evaluate programs and policies, plan for services and programs, and advocate for resources.

“The Healthy Minds Study serves as a barometer for student mental health across the nation,” said Heinze, associate professor of health behavior and health equity in U-M’s School of Public Health. “While we’re excited to see this progress, higher education institutions need to continue to prioritize their students’ mental well-being and ensure they have the support services they need to succeed.”

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Factors That Predispose Undergraduates to Mental Issues: A Cumulative Literature Review for Future Research Perspectives

Distress and mental health issues among college students is an emerging topic of study. The aim of this research work is to illustrate academic and social risk factors and how they prove to be predictors of anxiety and depressive disorders. The methodology used is a cumulative literature review structured over 10 systematic phases, and is replicable. Showing considerable potential for cumulative research, the relevance of this study reflects the concern of the academic community and international governments. The articles selected range from categorization of disorders in relation to mental health, to reporting the condition of rhinestones and difficulties of students in university contexts. In conclusion, the research focusses upon predisposing, concurrent or protective factors relating to the mental health of university students, so that institutions can act on concrete dynamics or propose targeted research on this topic.

Introduction

Mental health and mental health-related issues have been a matter of concern for quite a long time earning little regard and interest from the respective healthcare facilities and systems. Governments have put inadequate measures to ensure that citizens' mental challenges are handled rightfully to achieve high levels of mentally healthy people. The perpetuated issue has also developed in various sectors of society. The current situation in a learning institution is worth raising eyebrows, and therefore it deserves serious attention. Most of the undergraduate students and yet to graduate college students depict high levels of mental illness among the students, thus, depicting discomfort of the students and the level of neglect the health sector is faced with. The majority of today's people who are suffering from mental issues in society constitute college and university students ( 1 ). College students endorse high rates of mental health problems. While many colleges offer on-campus services, many students who could benefit from mental health services do not receive car. Indeed, nearly half of students who screen positive for depression, for example, do not receive treatment ( 2 ).

Adverse consequences are synonymous with undergraduate students with mental distress. The victims are likely to experience challenges such as impaired functioning in cognition, substance abuse, poor performance in their school work, and learning disabilities. They are likely to abuse drugs such as tobacco, alcohol, cigarette smoking, and other hard drugs that impair normal body functioning ( 3 ). Most of these drugs are associated with various risk behaviors, depression, and anxiety ( 3 ). This suggests that emotional discomfort raises the likelihood of developing additional mental health issues. For this reason, the prevalence of mental illnesses among university students is higher compared to people in other environments. The situation is almost similar in most colleges since they are predisposed to similar conditions and forms of livelihood. This inherent condition puts the future generation, which is inherently composed of the schooling individuals, at more risk in line with mental health and other health conditions that may arise due to the mental disorders.

Several factors have contributed to the mental distress and discomfort associated with undergraduates. For instance, sex has a significant contribution to the mental illnesses that people experience in learning institutions. The prevalence of the conditions tends to be a notch higher among female students than male students ( 4 ). Some students lack interest in fieldwork which affects their mental health in the long run. Introvert students are also more likely to fall victims and students who face various social challenges such as poverty ( 4 ). Most of the learning institutions have tight schedules and continuous sequences of study, which affects the students' performance and their mental well-being. Challenges and the predisposing factors that affect the students are bound to result from their school environment or their history; therefore, the growth environment and interaction play a significant role in determining one's health. Some of the predisposing factors are avoidable, while others are accustomed and tied to the students. Therefore, it is prudent to come up with measures to ensure control and regulation of the inherent situation of the undergraduate students who make up the future and continuity of our current society.

Common Mental Illnesses Among Undergraduates

Undergraduate students face many mental issues; however, the prevalence of some of the health conditions is a bit higher than others. Experts and researchers use terminology like “crisis” and “epidemic” to describe American college student's mental health issues today. Mood disruptions are only one of the many mental health problems that college students face. Suicide, addiction, and eating disorders are examples of significant issues ( 5 ). Although mental health specialists emphasize the need to talk about such concerns, students often regard these pressures as a typical livelihood in learning institutions. In other circumstances, individuals may be unable to seek help due to a lack of time, energy, will, or financial resources ( 5 ). It is, therefore, a challenge in coming up with a satisfactory solution to the challenges of problems. Drawing the students' goodwill and desire to have their mental issues fixed is also a challenge as some of them may feel shy or mentally healthy, and that there is no need to go through medication. Similarly, identifying the deserving students and coming up with radical measures to satisfactorily come up with a solution is also challenging since acquiring the required resources is quite expensive. However, solving the problem is arguably easy through addressing some of the major health conditions that most undergraduate students experience.

Below, we investigate some of the most common mental illnesses among college students, such as depression, anxiety, suicidal thoughts, eating disorders, and addiction.

Depression is a widespread chronic medical illness that can affect thoughts, mood, and physical health. It is characterized by low mood, lack of energy, sadness, insomnia, and an inability to enjoy life ( 6 ). Victims of the condition tend to develop varying episodes of discomfort and displeasure that destruct them from their normative activities. Students may grow poor performance and the inability to fit in with their schoolmates in co-curricular and curriculum activities. According to the ACHA's 2018 poll, 40% of American students had at least one significant depressive episode that same year ( 5 ). A person may also feel sad, hopeless, powerless, and get overwhelmed with life situations and challenges that one may be facing. Trouble in completing assignments, challenges in paying attention, and reading are also synonymous with depression among undergraduates ( 5 ). It might be challenging to spot these concerns in others since students often minimize or refuse to discuss issues that are bothering them.

In ICD-10, Generalized anxiety disorder includes anxiety neurosis, anxiety reaction, and anxiety state, but excludes neurasthenia. ICD-10 also proposes diagnostic criteria for research: (i) at least 6 months with prominent tension, worry, and feelings of apprehension about everyday events and problems; and (ii) at least four symptoms out of a list of 22 items, of which at least one item is from a list of four items of autonomic arousal (palpitations/accelerated heart rate, sweating, trembling/shaking, dry mouth).

Anxiety was identified as a significant student mental disorder by 61 percent of survey respondents in the University of Pennsylvania study published by Locke et al. ( 7 ). Anxiety disorder symptoms are frequently misdiagnosed as everyday stress or dismissed as someone overly concerned. Panic attacks might be misinterpreted as a medical ailment, like a tension headache or heart attack, depending on how your body responds to high amounts of specific chemicals ( 7 ). Since each person's symptoms present differently, what sighs the existence of anxiety to one person may not be similar in another ( 7 ). Consequently, the causes of anxiety differ from one person to another; however, some causes are common among campus students. For instance, stress, life experiences, genetics, and brain chemicals commonly cause anxiety in people ( 7 ). It, therefore, requires adequate measures of utmost keenness to ensure that the condition gets eliminated from the learners' livelihood.

The APA defines completed suicide as a self-injurious act that results in death and attempted suicide as a non-fatal, self-inflicted, potentially harmful act that is intended to result in death but may or may not result in injury ( 8 ).

Approximately 20% of university students in the United States were reported to be suicidal in 2018 ( 9 ). Therefore, it implies that the mental condition is rampant and makes up one of the major mental illnesses common among American students. According to the Los Angeles Times' Healstaff ( 10 ) report, teenagers and young adults record the highest suicide cases in America. Since the population inherently dominates the composition of the universities, it insinuates that undergraduate students register the highest number of suicide cases. Many students experience dissatisfaction and doubt, but these feelings can spiral out of control, leading some to consider suicide seriously. Suicidal ideation manifests itself in a variety of ways. Speech, temperament, and behavior are all examples of common warning indicators ( 10 ). Persons may describe themselves as stuck, burdening others, as if they have no reason to live and have no purpose to live. Suicidal ideation causes a wide range of emotions: anxiety, impatience, loss of interest in previously appreciated activities, shame, rage, and melancholy ( 11 ). People may engage in certain activities, such as giving up valued items, withdrawing from family and friends, unexpectedly visiting someone to say bye, and searching the internet for ways to commit suicide ( 11 ). They also may sleep poorly or excessively, act rashly, show anger, and increase their drug and alcohol use ( 11 ). Whenever one is seen with the symptoms, a bold and patient approach should help the victim seek medical attention from a psychiatrist and facilitate the healing process.

Eating disorders are a group of illnesses characterized by significant changes in one's eating habits and a preoccupation with a person's shape or body. Eating disorders (EDs), including anorexia nervosa, bulimia nervosa, and binge-eating disorder, constitute a class of common and deadly psychiatric disorders ( 12 ). The health conditions can entail binge eating and deprivation of food, which sometimes results in purging. According to 2018 estimates from the National Eating Disorders Association, 10–20% of female college students suffer from an eating disorder, with rates continuing to grow ( 13 ). Male students have a lower incidence rate of 4–10% ( 13 ). The typical eating disorders among undergraduates include bulimia nervosa, anorexia nervosa, and binge eating disorder. Emaciation is a specific symptom of anorexia nervosa, characterized by an excessive preoccupation with thinness, a disordered body image, and anxieties about gaining weight ( 14 ). Constant desires that occur at any time of day and lead to binge eating characterize binge eating disorder ( 14 ). This condition is frequently linked to low self-esteem and a negative body image. Bulimia nervosa is a form of binge eating condition characterized by recurrent and frequent bouts of eating abnormally large amounts of food, followed by compensatory behaviors such as purging, fasting, or excessive exercise ( 14 ). The symptoms and indications of eating preconditions differ from person to person and condition to condition, and many are dependent on the mental state of the person suffering from the problem ( 14 ). Many college students fail to seek treatment for their eating disorders since they do not have an awareness that they have one.

Alcohol and recreational substances are commonly used by college students, which can be troublesome ( 15 ). Addiction is a psychological or physical dependency pattern on one or more substances, characterized by strong cravings and substance abuse despite knowing risks and consequences ( 16 ). Alcohol is the leading cause of many disorders and deaths for campus students, while some abuse drugs to induce their studying habits ( 17 ). The recreational activities that undergraduates use alcohol and other drugs for result in addiction which causes many diseases. Besides alcohol, students also abuse marijuana, cocaine, ecstasy, and benzodiazepines ( 17 ). The dire need and desire to abuse drugs for various purported gains may lead to health complications resulting in death and body organs' failure.

Mental Illness Prevalence Among Undergraduates

Mental health disorders are common among students, with a higher incidence than in the general population. Statistically, more than half of the students in American public universities suffer from depression and anxiety ( 18 ). Similarly, a poll of undergraduate students at Coventry University in the United Kingdom found that many students had suffered mental health disorders such as anxiety and depression in 2006 ( 19 ). Maser et al. ( 20 ) showed that the prevalence of mental health disorders such as anxiety and depression cases are a notch higher in medical school compared to the general non-student community of the same age, which supports these findings. Over the last two decades, these investigations have shown that the frequency of Seasonal Affective Disorder (SAD) amongst students has remained more significant than the general population.

SAD is not only common, but it is also persistent among students. Zivin et al. ( 18 ) found that more than half of students maintain their higher anxiety and sadness over time by performing a 2-year follow-up survey research and study of students. This phenomenon could be related to a lack of SAD therapy or the persistence of pre-existing risk factors.

Methodology

The cumulative literature review, a new and rigorous research method, is divided into 10 phases ( 21 ):

• Selection of key concepts (especially of independent and dependent variables and the relationships between them).
• Creation of a search string (in addition to selecting the keywords, it is necessary to include and exclude the studies found through the criteria used). The final goal of this phase of the research is to find a manageable number of studies through the following procedure: (1) query two or three search engines or databases; (2) use keywords in combination with “and/or”; (3) use filters to manage the enormity of the results (comparison with a second researcher as in this study would be desirable).
• Export of the results from the databases and a merging of all the transcribed results in the form of a bibliography on a single worksheet.
• Selection of primary sources by eliminating duplicates and excluding irrelevant studies based on titles. This step is necessary to create a separate list of systematic reviews on the topic. It is also essential for drawing up a list of the individual choices of the cumulative review.
• Verification of the secondary bibliography, by checking the bibliographies of all the included studies. Studies that cite primary sources, such as other systematic reviews on the topic, must therefore be included under the studies not found in the initial search.
• Data extraction (produced by the reviewers' work), in which the characteristics of the selected studies are extrapolated. These characteristics include key variables, type of research project, context, results, year of publication, etc. The exclusion criteria are also cumulative; i.e., they are formulated on the basis of the time available and the studies retrieved from the databases.
• Updating of the results on the basis of recent publications, which may prompt an update regarding the initial work carried out. This must be done before the conclusion of the cumulative review.
• Verification by the second reviewer, who checks the included studies.
• Writing of the last phase of the report.
• Exercising due care in the publicization of the revision. This involves making the data collection work explicit within the format of the paper: keywords, extracted data, results, etc.

Each phase is illustrated below, retracing the steps taken to carry out the cumulative review, in order to make the study replicable.

In this study, research, which was based on the cumulative literature review model, followed the ten-phase model set out in the previous paragraph. Specifically, the following keywords were selected: mental disease, risk factors, university, students (phase 1). Scopus, WoS and Google Scholar were selected as search engines. The search yielded 797 results that were selected, based on comparison by researchers, using the following inclusion-exclusion criteria: inclusion of all literature reviews in the 2011–2020 period, related studies on risk factors toward mental disorders of university students (phase 2), with exclusion based on primary source titles. The raw research data was transcribed on a spreadsheet, in order to enable a global view of the studies located and to start the selection work (phase 3). The file was “cleaned up,” in order to remove duplicate contributions and create a second list of systematic reviews of the literature ( n = 4), one book, and one book chapter (phase 4). In the first file named “primary sources,” significant studies were selected and placed based on the title. The cleaned file contained n = 33 papers. For the second file containing the systematic reviews of the literature, the secondary bibliography included was consulted, and the studies already present in the first file of the present research were eliminated. In this case, 67% of the studies had already been identified in the comparison of the cumulative literature reviews. It would be desirable to build a reliability index of the cumulative review that took into account this value, i.e., the degree of replicability of the systematic studies already conducted (phase 5). Construction of a grid ( Table 1 ) was carried out, using the results of the research and data extraction by the researchers who analyzed the key variables (key variables, type of research project, context, results, year of publication, etc.), by selecting as reported in the table, only the fields relevant to the research (phase 6). The research carried out in the first months of 2021 has been updated with more recent publications that have introduced a surveys studies of mental illness among university students (effects of the COVID emergency in terms of physical, cognitive and relational consequences). On the basis of the inclusion-exclusion criteria, other ( n = 2) papers were included (phase 7). The complete file, containing the studies considered significant for the purposes of the construction of this work, was analyzed by the second researcher, in order to avoid errors in the research (phase 8). Steps 9 and 10 resulted in the production of this research paper.

Summary of the results.

It is clear from the selected articles that the idea present in the introduction is confirmed: the highest number of studies were on mental disorders, as well as on alimentary disorders. On the contrary, technology and other new addictions among university students are still little studied. They were therefore excluded from this study ( Table 1 ).

Risk Factors

From the analysis of the literature, several risk factors emerge that are involved in the development of mental problems in students. In particular, it is possible to classify the main factors in: academic factors, social factors, psychological risk factors, lifestyle factors and physiological factors.

Among the academic factors, the inverse correlation between time spent in study and poor results emerges. Academic results are, in fact, correlated with job placement and other higher education programs. It follows that, at times, this can be detrimental to students' mental health. In addition, elements such as loneliness and social isolation can often induce worry and melancholic states that play a major role in learning. One example is the pandemic situation that has forced millions of students into a scarcity of relationships for a very long time. Additional pivotal factors are those of a psychological nature: disappointments, stress, and perceived anxiety can have a major impact on academic performance; in addition, abuse and mistreatment negatively affect cognitive, emotional, and social development.

The period of change characterized by entry into college often involves changes in lifestyle as well: there may be a tendency to increase intake of drugs, alcohol, and various substances that, if abused, can alter functioning patterns. One of the pivotal factors, however, is the biological makeup of the individual: genetic history and health status have high implications in mental health.

Academics Factors

SAD can get caused by a variety of university-related academic pressures. The degree's subject is one of these strongly prevalent factors. When compared to their non-medical colleagues, nursing, medical and health-related students have a greater prevalence of depression and anxiety ( 23 ). Medical and nursing students, who have both theoretical and patient-related responsibilities, typically have an enormous workload among undergrads and, as a result, experience higher anxiety and despair ( 24 ). Furthermore, students majoring in psychology and philosophy, like medical and nursing students, are more likely than others to acquire depression during their studies ( 34 ). Medical and nursing students who work with people's health may develop melancholy and anxiety due to their worries about making mistakes that could hurt them or their patients ( 23 ). Students whose degrees include practical components may travel to new locations for fieldwork and job experience, adding to their anxiety and stress ( 23 ). However, it's essential to determine whether students with underlying mental health issues are more prone to pick disciplines like philosophy or psychology or subjects that lead to caring careers like nursing and medicine.

Furthermore, some prospective students, particularly those studying nursing and medical, often lack explicit knowledge of the workload and curriculum associated with their field of study before enrolling in university, and as a result, they may become disillusioned once they begin their studies ( 23 ). It's worth noting that not all research discovered a link between the study's subject and the development of SAD ( 35 ). Variances can explain this phenomenon in sample type and size, resulting in disparities in workload and curriculum, such as courses taught in different universities across the world.

Studying for a degree at the university level can be a challenging endeavor that necessitates mental work. Mastery of the subject has been shown to negatively affect anxiety, self-esteem, and depression among college and university students, with those who have a mastery of the subject displaying less stress and anxiety ( 32 ). Additionally, students studying in a foreign environment where there is a use of a non-native language sigh high levels of anxiety and sadness during their freshman year, with their stress levels decreasing with time ( 32 ). This is due to the fact that students studying in a foreign language are typically people who have moved abroad and thus take a while in adjusting to their new form of livelihood. Domestic and international students' depression and anxiety levels can be linked to the year of study, with newcomers entering university. On the other hand, final-year students experience the highest levels of anxiety and depression, and various risk factors ( 32 ). First-year students experience SAD due to difficulties adjusting to university life, negative family experiences in the past, social isolation, and a lack of friends. Final-year students report unpredictability about their years ahead, prospective work opportunities, university debt repayment, and adjusting to life after school as major risk factors for SAD ( 32 ). As a result, as students go through their degrees and learning process, there is a change in SAD potential risk themes.

Students spend a large percentage of time engaged in academic pursuits at university, and poor academic performance can harm their mental health. Receiving worse grades during their studies can have a severe impact on student's mental health, leading to the development of SAD ( 28 ). Academic achievement throughout undergraduate education can influence degree categorization, affecting students' opportunities, including job placement or entrance to postgraduate programs. On the other hand, both the cases of students suffering from mental problem symptoms and the severity of their SAD increase during test time, indicating a direct link between academic stress and students' psychological health states ( 38 ). However, there is no direct correlation that is well-established. There are chances that depression and other related disorders such as momentary memory loss and lack of concentration are causes of bad academic marks, or that students get anxious and depressed due to their poor exam performance ( 39 ). Grades and mental health can have a reciprocal relationship, with poor mental health causing students to receive poorer grades ( 40 ), creating a vicious loop of academic performance and mental health. Interestingly, students' social connection and coherence to the campus community during exam periods decreased ( 38 ). This phenomenon can be explained by students' lower participation in university social events and clubs and a higher sense of competitiveness among their peers. Furthermore, students interact with lecturers, instructors, tutors, and other staff members both directly and indirectly; as a result, the interaction between academic staff and students can impact students' mental health. Another factor that contributes to SAD among undergrads is a bad and abusive interaction with teachers and mentors.

Part-time students are more likely to be emotionally stable and free from mental illnesses compared to full-time students. Students enrolled for part-time studies are more likely to be employed, and therefore they have a constant flow of income. Similarly, they are less likely to experience some social predisposes that may induce mental illnesses due to their schedule. Unlike full-time students, they are free-wheel and do not have a limited and timed duration to complete their courses. Their financial advantage puts them in a better position; however, they are also likely to experience other forms of predisposing factors. The negative predisposes that are more likely to cut across all students, for this reason, include the pressure accrued from school workload, phobia of performing poorly. They also entail the wrong expectations built on the courses and institutions of learning, a student's year of study, poor relationship with the staff with which a student interacts at the university.

Social Factors

In human livelihood, everyone is exposed to society and that an individual and society are two inseparable entities. Society has a significant influence on a person's thought ideology and self-actualization. Naturally, a person's description and identification of oneself gets determined by society. For this reason, society dramatically influences a person's state of mental health. Whenever a person coexists with others in a relatively fair environment or at par with the majority fortunate, the individual's mental health state is likely to be boosted. The case is dissimilar when a person belongs to a few unfortunate members of the community. Some of the social predisposes are therefore likely to perpetuate disorders in undergraduate students or otherwise breed them.

Loneliness and social isolation are a matter of concern among students, especially due to the advent of online learning, which discourages interaction. In modern society, especially after the COVID-19 pandemic, most institutions of higher learning have adopted online learning to facilitate the continuity of education and the learning process. This form of learning has hindered students' possibility of interaction with their peers in a classroom environment. This phenomenon has perpetuated the inherent social condition and situations of some students, especially introverts. According to Loades et al. ( 33 ), young adults, who make up the undergraduate population, are prone to experiencing high depression rates, which can also cause anxiety. The isolation and limitation of interaction among the young population require mitigation to ensure that the issue gets resolved at the early stages of inception ( 33 ). Self-solation and loneliness are also associated with having few friends, thus putting one at risk of experiencing mental illnesses in college. More often than not, loneliness can lead to low self-esteem and confidence, which breeds anxiety.

Social disadvantages such as poor housing and poverty pose more risk of mental disorders among students. Among learners, poverty is associated with poor performance in school in line with behavior, cognition, and attention-related issues ( 22 ). Therefore, it is associated with anxiety, schizophrenia, depression, delinquency, and other mental health disorders that are synonymous with young adults. Additionally, poverty increases one's risk of getting traumas and abuse, especially during childhood, and losing crucial family members ( 22 ). High-income inflow in a home setup reduces chances and risk of domestic violence. It, therefore, goes without saying that when the condition is otherwise, the students are likely to get exposed to unbearable environments at home, which yields mental conditions. Similarly, students coming from poor backgrounds have instilled internal pressure and desire to evict themselves from poverty. The fear of poverty and the desire to become wealthy gives students discomfort and pressure since they always think that it is likely to cost them severely ( 22 ). Students who live in poor housing facilities are also likely to develop low self-esteem and confidence. They view themselves as inferior to other classes of students ( 22 ). Other students may also discriminate and underrate them, thus brewing mental conditions that are stringent and adverse. Therefore, it is wise and socially acceptable that students should not let their social situation of poverty and poor housing ruin their idea and sense of self-esteem and confidence.

Bullying and social discrimination impose mental health conditions that may affect the students' performance and cause long-term health conditions. Bullying, especially in the school environment, affects both the victims and the perpetrators in different ways ( 41 ). It may cause trauma, behavior, and bodily implications and affect one's identity. Contemporary cyberbullying is also characterized by imposing anxiety, low self-esteem, and depression among young adults ( 41 ). The psychological discomforts and distress may yield a personal thought toward a person, thus harming oneself. The individuals are likely to behave in a manner that can trigger suicide attempts and other forms of self-harm ( 41 ). As a result of low self-esteem, a person may also become an introvert, thus interfering with one's potential to interact with other people. Perpetrators are likely to have interaction problems and the inability to socialize with their fellow students since they have instilled fear. The situation is almost similar when one experiences various forms of discrimination. Discriminated individuals end up with low self-esteem and confidence, as well as the desire to rise above their perpetrators ( 29 ). This state breeds anxiety and depression among the victims.

Psychological Risk Factors

University and college students also get exposed to various psychological stressors and displeasures that negatively impact their mental health and performance. Some social predisposes are also likely to cause psychological discomfort and resulting mental illnesses in a university or college setup. Some early childhood preconditions are also likely to impact a person psychologically, even at the tertiary level of education ( 44 ). For instance, childhood trauma, abuse, and neglect are likely to be more disastrous when a person reaches the university or college level. Trauma greatly impacts a person's thoughts and feelings about oneself and how they relate with other people in society. Students, especially females, who have gone through a traumatic experience are likely to develop mental illnesses and conditions such as post-traumatic stress disorder (PTSD), depression, or anxiety ( 45 , 46 ). Childhood maltreatment has a negative impact on cognitive, social development, and emotional development leading to problems with interaction and communication, as well as making people more prone to negative emotions in general and noticeable behavior problems like emotional maladjustment and anxiousness, hyperactivity, antisocial traits, and delinquent behaviors ( 45 ). Mistreatment during childhood is also likely to cause poor emotional intelligence, inhibited until college or university. Social support and refraining from mistreatment lead to mitigation of long-term adverse conditions such as depression and emotional self-regulation among children. Whenever the mitigation measures are not implemented, the victims are affected in adulthood. The instances are more severe among university and college students.

Long-term and severe stress is synonymously associated with causing mental illnesses among graduates. When stress becomes overwhelming and prolonged, the risks for mental health problems and medical problems increase. Long-term stress increases the risk of mental health problems such as anxiety and depression, substance use problems, sleep problems, pain, and bodily complaints such as muscle tension. Research indicates that stressful events cause significant psychological such as anxiety, distress, and depression ( 27 ). Similarly, severe and long-term academic stress leads to loss of welfare of the victims. Students suffering from academic stress are likely to perform poorly in their schoolwork ( 27 ). Poor performance perpetuates stress in the long run, as many students are accustomed to fearing academic failure and poor performance. Undergraduates may also get challenged by stressful life instances, such as breaking the law, which can cause mental discomfort and disorder. Its severity is also likely to cause other health conditions such as hypertension and asthma. It is, therefore, a predisposing factor that may inherently dominate a person's livelihood in the university.

Poor performance in school work leaves undergraduate students in thought which breeds mental illnesses. Whenever one performs poorly, there are chances that the person will get challenged mentally and develop the desire to work toward changing their results. However, failure for the same can cause a mental disorder due to the inherent academic expectations a person may develop. Similarly, mental illnesses affect a student's performance; therefore, the two risk factors are reversible, hence pausing the risk of cycle perpetuation. Attention to the students performing poorly in colleges and universities is essential in ensuring the cases of mental ill-health and continual unfolding of situations causing a cycle is fixed. This motive will help improve the learners' performance and work toward preventing some mental conditions that are likely to be incurred due to poor academic performance.

Lifestyle Factors

Moving away from family and starting a new life necessitates adaptability and flexibility for one to acclimatize to a new way of life. Most undergraduate students change their behavior and lifestyles as they leave their family setting and start a new life alongside their colleagues, friends, and classmates. SAD can be influenced by various lifestyle factors like alcohol intake, tobacco use, food habits, fitness, and drug usage. Students with mental problems consume a lot of alcohol ( 26 ). Alcohol is the most abused by undergraduates. It is synonymous with a series of mental disorders that they face. Alcohol is also addictive, and that when students overuse it, they are likely to experience various addiction disorders.

Another risk factor linked to SAD is tobacco smoking. It is widespread among students, particularly those from Eastern developing and developed nations like Japan, China, and South Korea ( 47 ). As a result of social bonding, many of the learners, especially male undergraduates, smoke, and the rate of social smoking is directly connected with SAD ( 47 ). Social smokers are less likely to give up their habit and are more likely to continue doing so, resulting in long-term detrimental psychological and physical health implications ( 47 ). Another key component in mental health among young individuals is illegal substance misuse ( 36 ). Academic stress and the social milieu in university dorms and student housing can lead students to take illegal drugs, smoke cigarettes, or consume excessive amounts of alcohol as a coping strategy, causing mental disorders ( 42 ). Students who felt supported by their university were less stressed and were less likely to engage in substance abuse, demonstrating the importance of social support in preventing and treating depression symptoms ( 42 ). It is especially important since a new social behavior or habit formed early in life might persist for a long time. Additionally, students who do not live a healthy lifestyle may experience shame, which can exacerbate their SAD symptoms ( 36 ). Rosenthal et al. ( 37 ) discovered negative behaviors associated with alcohol consumption, such as missing the next day's class, careless actions, self-harm, physical fight or verbal argument, the indulgence of unwanted sexual acts, shame, and regrets. The quantity of alcohol consumed can be the cause of depression and anxiety.

In universities and colleges, graduates adopt diverse sleeping habits that may yield mental illnesses and disorders. Many young people do not get enough sleep, causing sleep deprivation, a serious risk factor for depression and low mood ( 37 ). Students in the United States frequently report significant stress levels and inadequate sleep ( 43 ). The majority of undergraduates strive for academic brilliance, financial security, and the preservation of their lifestyle, which leads to poor sleep. Inadequate sleep can create a vicious cycle in which academic stress causes sleep deprivation. Insufficient sleep causes stress due to poor academic performance, as sleep quality and quantity are linked to academic performance ( 26 ). In general, poor sleeping habits are linked to lower learning ability, anxiety, and stress, leading to depression. Inadequate sleep, therefore, is likely to perpetuate a person's mental illness or otherwise fuel its inception.

In contrast with the predisposing factors, engaging physical exercise among students in colleges and universities is essential in protecting against mental dysfunctions. Students who claim to have limited time and fixed schedules may fail to engage in physical exercise and workouts. The development of SAD symptoms characterizes such students. Engagement in physical exercise and workouts makes the mind occupied and can also free off one's thoughts, which may cause mental illnesses. It also increases a person's interaction and enhances the social capabilities of interaction, which helps prevent some conditions. Physical exercise is also a form of therapy that requires one to exert physical exercise on the activity.

Physiobiological Factors

Physiobiological factors entail the factors that get affected directly and are related to the victim's biological composition, genetic history, and other health factors. For example, the mental health of an individual is inseparable from the family's history. Common disorders tied to an individual's family history include bipolar disorders, schizophrenia, dementia, depression, and anxiety ( 25 ). The genetic makeup determines the vulnerability of a person toward mental issues ( 25 ). People whose predecessors are associated with a certain mental illness are more likely to experience the same based on their genetic composition. Similarly, if one's family has a history of mental illness, one has likely been exposed to stressful conditions at some point in life. Growing up in a challenging environment or being abused by a parent or relative raises the risk of getting depression or anxiety ( 25 ). Epigenetics habits can also alter a person's emotions and habits, influencing people's biological composition, and it is likely to get passed to the next generation ( 30 ). Stress caused by mental health issues in great-grandparents, grandparents, or parents changes one's DNA, making them more vulnerable to difficulty ( 30 ). Furthermore, if a person's ancestors ate bad diets, had exposure to environmental pollutants, living with chronic stress, or did not receive proper prenatal nutrition, their genes—and thus an individual's—got altered, making them more likely to show mental illness health disorders.

Other biological factors such as pregnancy and birth complications, brain injury, chronic diseases, alcohol consumption, and drug abuse, as well as poor nutrition, are likely to predispose a victim to mental conditions. Some students have a history of complications during birth. Such students may inhibit the health conditions till the university or college level of study, and they are likely to cause mental disorders ( 31 ). Brain trauma and injury are also significant factors that may cause disorders in undergraduates. Some students have chronic illnesses such as diabetes and cancer, which expose them to discrimination, depression, anxiety, and low self-esteem. The diseases may also cause brain impairments, leaving the students mentally unwell ( 31 ). Usage of drugs and alcoholic drinks also influences the health status of an individual. Some drugs, such as marijuana, are associated with paranoia, resulting in adverse mental illnesses ( 31 ). Too much usage of drugs can also impair a person's eating habits which affect the learner's nutrition. It is, therefore, yields various eating disorders.

Mental health-related issues and social well-being predisposing factors are a matter of concern in the community, especially among undergraduates. The prevalence of mental disorders is a notch higher among college and university students, raising the alarm on establishing some of the causes of the phenomenon. The predisposing factors include social, psychological, biological, lifestyle-based factors and academic factors. Academic excellence pressure and exerts various emotional feelings among students. The emotions and failure to meet their expectations land students into mental conditions that may perpetuate for a while. Change of environment and desire to adjust to a new form of livelihood in the university also causes a resultant change in lifestyle. More often than not, students commence drug and substances abuse which puts them at risk. A person's history of the family's genetic composition, chronic illnesses, and injuries of the brain also causes brain challenges ( 48 ). Interaction and other socio-economic factors are also crucial to a student's mental health that, when neglected, may result in disorders. Therefore, it is wise for the community to make haste and limit instances of the unfolding of the predisposing factors to achieve high standards of mental health among the undergraduates. This move will help in creating a future society that is mentally healthy.

Author Contributions

PL: introduction. GT: methodology and conclusion. Both authors contributed to the article and approved the submitted version.

Conflict of Interest

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Publisher's Note

All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.

Positive Education and Student Wellbeing: A Review of Relationship between Gifted and Non-Gifted Students' Wellbeing and High Achievement

• Jophus Anamuah-Mensah University of Winneba
• Gladys Ami Allotey 116 Street to 133 West McCarthy Hills, Accra, Ghana. Queensland University of Technology

In the pursuit of fostering creativity and technology for innovative economies, students' wellbeing has grown globally. Positive education, which emphasises nurturing strengths for wellbeing and peak performance, plays a crucial role. Yet, research on its impact in disciplines, especially STEM areas, is limited. This article reviews 57 studies limited to gifted and non-gifted students, including STEM subjects, to analyse the relationship between positive education and gifted student achievements. Examining literature from 1999 to 2023, the study highlights the significant connection between wellbeingfocused education and academic success. Findings reveal that not only individuals' character traits, constitute inward restorative defenses against mental health issues across all age groups but also the gifted, particularly gifted males, are more susceptible to mental disorders compared to their nongifted and normal or average-intelligence counterparts. The research highlights the importance of identifying gifted students early, utilising their potential for wellbeing and improved outcomes, especially in interdisciplinary fields such as STEM. Incorporating gifted education and wellbeing into preservice teacher education through holistic institutional approaches is crucial, particularly in the context of developing African nations. The study also suggests socio-emotional development for advancing academics, especially in STEM. This research suggests future exploration into the intersection of positive education and students' academic accomplishment.

How to Cite

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© College of Education Studies, University of Cape Coast, Ghana.

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