Medical vs Non-Medical Student Mental Health in Pakistan: A 602-Student Study

Medical students are often treated as the university group most vulnerable to depression and anxiety, but new evidence from 602 undergraduate students in Lahore, Pakistan, suggests a more complicated picture. In this cross-sectional study, non-medical students reported higher depressive symptoms on the PHQ-9 and higher depression and anxiety scores on the DASS-21 after adjustment for measured characteristics. Stress scores, however, did not differ significantly by academic discipline. The results suggest that student mental health support should not be designed around the assumption that medical education automatically identifies the students at greatest psychological risk.

By Taimoor Asghar

Why compare medical and non-medical student mental health in Pakistan?

University is a period of substantial psychological and social change. Students may simultaneously face academic competition, financial pressure, uncertainty about employment, changing relationships, altered sleep patterns, greater independence and expectations from family. These pressures are not confined to any single academic discipline.

Medical education receives particular attention because medical students face demanding examinations, large curricula, clinical responsibilities and exposure to illness and suffering. This has understandably produced a large body of research on medical-student wellbeing. An unintended consequence, however, is that students studying engineering, business, social sciences, humanities and other disciplines may receive comparatively less attention in discussions of university mental health.

That distinction matters in Pakistan. Academic pathways can be associated with different expectations, career prospects, financial pressures and social environments. Assuming that one discipline is inherently more psychologically vulnerable can obscure the broader factors associated with depression, anxiety and stress across an entire student population.

Our recently published BMC Psychology study addressed this issue by directly comparing medical and non-medical undergraduates while also examining how two widely used mental-health questionnaires performed in the same population. The BMC Psychology study on PHQ-9 and DASS-21 symptom profiles among Pakistani university students included 602 participants from universities in Lahore.

What did the 602-student study examine?

The study used a cross-sectional survey design involving 602 undergraduate students. Of these participants, 424 were medical students and 178 were non-medical students. Participants completed two established self-report instruments: the Patient Health Questionnaire-9, commonly known as the PHQ-9, and the 21-item Depression Anxiety Stress Scales, or DASS-21.

The analysis went substantially beyond simply calculating average questionnaire scores. The study incorporated descriptive analyses, comparisons between medical and non-medical students, multivariable regression, confirmatory factor analysis, item response theory and symptom network analysis. It also examined whether the measurements behaved sufficiently similarly across academic-discipline groups to support meaningful comparisons.

This distinction is important because comparing two groups is much more informative when there is evidence that the questionnaire is measuring the underlying construct in a comparable way in both groups. The study reported support for measurement invariance across discipline, strengthening the interpretation of the medical versus non-medical comparisons.

Non-medical students reported higher depressive symptoms

One of the most notable findings was that non-medical students did not show better mental-health scores than their medical counterparts. On the PHQ-9, the median score was 10 among non-medical students and 9 among medical students.

The difference also persisted in adjusted analysis. Academic discipline was associated with PHQ-9 scores after accounting for variables included in the regression model, with non-medical students having scores approximately 1.43 points higher than medical students. The reported p-value was 0.004.

A similar pattern appeared when depression was measured using the DASS-21. Non-medical students had higher adjusted DASS Depression scores, with an estimated difference of approximately 1.82 points and a p-value of 0.003.

These results do not establish that studying a non-medical subject causes depression. A cross-sectional study measures variables at one period rather than following students over time, so it cannot establish the temporal sequence required for a causal conclusion. Nevertheless, the consistency across two measures of depressive symptoms makes the comparison worth taking seriously.

What happened with anxiety and stress?

The discipline-related pattern was not identical across every psychological domain. Non-medical students also reported higher DASS Anxiety scores in the adjusted analysis. The estimated difference was approximately 2.31 points, with a p-value of 0.001.

Stress produced a different result. Although the adjusted estimate also pointed toward higher scores among non-medical students, the difference did not meet the study’s conventional threshold for statistical significance. The reported estimate was approximately 0.89 points with a p-value of 0.089.

This distinction illustrates why depression, anxiety and stress should not automatically be treated as interchangeable outcomes. Students can show different patterns depending on which dimension is being assessed, and a difference observed in depression cannot simply be assumed to exist for stress.

Academic discipline explained only a small part of the picture

The headline comparison between medical and non-medical students is interesting, but one of the most important findings is less dramatic: academic discipline explained relatively little of the overall variation in mental-health scores.

The regression models had low R-squared values, ranging approximately from 0.029 to 0.041. In practical terms, the measured predictors in these models accounted for only a small proportion of the differences in symptoms between individual students.

This prevents an overly simplistic interpretation of the findings. The study does not support replacing the stereotype that medical students have the worst mental health with a new stereotype that non-medical students do. Rather, it indicates that discipline is only one characteristic within a much larger network of influences on student wellbeing.

Two students in the same degree programme can have very different financial circumstances, sleep habits, social support, previous mental-health histories, family expectations and coping resources. A university mental-health strategy based predominantly on faculty labels would therefore risk missing many students who need support.

Gender was consistently associated with symptom scores

Another notable result involved gender. Female students had higher scores across the mental-health domains examined in the adjusted models, with all reported associations having p-values below 0.001.

These findings identify an association within this sample rather than a biological or causal explanation. Gender-related differences in self-reported psychological symptoms can reflect numerous interacting influences, including social pressures, exposure to stressors, differences in reporting, cultural expectations and other unmeasured variables.

For universities, the practical implication is not to assume that all female students require clinical intervention. Instead, institutions should recognise that population-level differences may help identify groups for whom accessible prevention, screening and support services deserve particular attention.

Sleep was associated with PHQ-9 depression scores

Sleep also emerged as a relevant correlate. Each additional hour of sleep was associated with an approximately 0.37-point lower PHQ-9 score in the adjusted model, with a p-value of 0.010.

Again, the study design cannot determine direction. Poor sleep may contribute to emotional difficulties, depressive symptoms can disrupt sleep, and both can arise from common factors such as academic pressure or irregular routines. The result therefore should not be interpreted as evidence that adding a specific number of sleep hours will produce a predictable reduction in depression.

What the association does show is that sleep belongs in conversations about student mental health. Universities considering wellbeing programmes may benefit from addressing scheduling, sleep education and unhealthy academic routines alongside more traditional counselling services.

Previous depression treatment was an especially strong marker

Prior treatment for depression showed the strongest association with PHQ-9 scores among the reported predictors, with an estimated coefficient of 4.15 and a p-value below 0.001.

This finding is clinically understandable but should be interpreted carefully. Previous treatment identifies students who have already experienced mental-health difficulties; it does not mean treatment worsens depression. Cross-sectional data cannot distinguish the many reasons why someone with a treatment history may continue to report symptoms.

For student-support systems, a history of mental-health care may nevertheless be relevant when considering continuity of support. Students entering or progressing through university may need ways to maintain access to appropriate professional care rather than restarting the process of seeking help whenever their academic circumstances change.

How well did the PHQ-9 and DASS-21 perform?

The study was not limited to prevalence or group comparisons. A major component examined the psychometric performance of the PHQ-9 and DASS-21 when administered concurrently.

Internal consistency estimates were acceptable, with Cronbach’s alpha values ranging from 0.82 to 0.88 across the assessed scales. The confirmatory factor analysis of the DASS-21 also showed adequate overall fit for its three-factor structure. Reported indices included a comparative fit index of 0.954, Tucker-Lewis index of 0.948 and root mean square error of approximation of 0.052.

However, there was an important qualification. Correlations between the latent DASS-21 factors were extremely high. The reported depression-stress correlation was 0.939, while anxiety-stress was 0.949.

Those correlations suggest substantial overlap between the constructs in this student sample. The three DASS domains can still be scored separately, but researchers should be cautious about interpreting small differences between them as evidence of completely independent psychological processes.

Which symptoms provided the most information?

Item response theory allowed the researchers to move beyond total questionnaire scores and examine how individual symptoms contributed to measurement. Within the PHQ-9, items concerning self-worth, concentration, feeling down and appetite demonstrated comparatively high discrimination. The interest or anhedonia item showed the lowest discrimination parameter in the reported analysis, at 0.468.

This does not mean that loss of interest is clinically unimportant. The result concerns how that particular item functioned psychometrically within this dataset. Clinical importance and statistical discrimination are related but fundamentally different concepts.

The broader message is that questionnaire totals can hide meaningful variation at the symptom level. Two students can receive the same overall depression score while reporting very different problems. One may primarily experience concentration difficulties and negative self-evaluation, while another may report sleep, appetite or energy problems.

What did the symptom network reveal?

The study also used symptom network analysis to explore relationships among individual PHQ-9 and DASS-21 items. Self-worth, concentration and downheartedness emerged among the most central symptoms in the estimated network.

Network findings can help researchers generate hypotheses about how symptoms cluster and interact, but they should not automatically be interpreted causally. A central symptom in a cross-sectional network is not necessarily the symptom that causes other difficulties, nor does statistical centrality prove that targeting it will produce the greatest treatment benefit.

The reported stability coefficients ranged from 0.31 to 0.44, providing another reason to interpret the network results as exploratory rather than as a direct clinical treatment map.

What does this mean for medical versus non-medical students?

The study challenges a common mental model of university wellbeing. Medical students certainly face substantial pressures, and nothing in these findings suggests that their mental-health needs should receive less attention. What the findings demonstrate is that focusing predominantly on medical students can produce an incomplete picture of psychological distress on university campuses.

In this sample, non-medical students actually reported higher depression and anxiety scores after adjustment. At the same time, the small amount of variance explained by the models indicates that degree type is not an adequate substitute for individual assessment.

A more defensible approach is therefore population-wide support with additional attention to empirically identified risk markers rather than assumptions about which faculty should be considered vulnerable.

Implications for universities in Pakistan

The findings point toward several practical considerations for institutions developing student mental-health services.

• Make services university-wide. Mental-health programmes should be accessible to students from medical, science, business, engineering, humanities and other faculties rather than concentrating resources solely in programmes traditionally considered stressful.
• Use validated screening tools appropriately. Instruments such as the PHQ-9 and DASS-21 can help quantify symptoms in research or screening settings, but questionnaire scores are not equivalent to a psychiatric diagnosis.
• Pay attention to sleep and daily routines. The observed relationship between sleep duration and PHQ-9 scores supports treating sleep as part of the wider student-wellbeing environment.
• Provide continuity for students with previous mental-health difficulties. A history of depression treatment may identify students who would benefit from straightforward routes to professional support.
• Look beyond total scores. Concentration difficulties, negative self-worth and other individual symptoms can affect academic functioning even when two students have similar total questionnaire scores.

Important limitations of the study

Several limitations should shape interpretation. First, the study was cross-sectional, meaning exposure and outcome variables were measured within the same general period. It can identify associations but cannot establish whether academic discipline, sleep or another measured characteristic caused the observed symptoms.

Second, the data came from university students in Lahore. The results should not automatically be generalised to every university in Pakistan, to students in other provinces, or to young people who are not enrolled in higher education.

Third, both the PHQ-9 and DASS-21 are self-report measures. They quantify reported symptoms but do not provide a clinical diagnosis by themselves.

Fourth, the medical and non-medical groups were unequal in size, with 424 medical and 178 non-medical participants. Finally, the low R-squared values indicate that substantial variation in student mental health remained unexplained by the measured variables. Factors not captured in the analysis may be highly relevant.

The broader lesson from the 602-student study

The most useful conclusion is not that one academic discipline has definitively worse mental health than another. The stronger message is that assumptions about who is at risk can be misleading.

Among these 602 Pakistani university students, non-medical participants reported higher depression and anxiety scores than medical participants, while stress did not differ significantly after adjustment. Female gender, sleep duration and previous depression treatment were also associated with symptom levels, and academic discipline explained only a small fraction of overall variation.

For researchers, the results highlight the value of studying students across multiple disciplines rather than treating medical students as representative of university mental health. For universities, they support broad, accessible mental-health strategies that recognise distress wherever it occurs. For students, they reinforce an equally important point: the name of a degree programme does not determine whether psychological difficulties deserve attention.

Frequently asked questions

Were medical students more depressed than non-medical students in this study?

No. Non-medical students had a higher median PHQ-9 score and higher adjusted depression scores in both the PHQ-9 and DASS-21 analyses.

Did non-medical students also report more anxiety?

Yes. Non-medical students had higher adjusted DASS Anxiety scores in the study. This was an association within the sampled population and does not demonstrate that studying a non-medical subject causes anxiety.

Was stress significantly different between the two groups?

No statistically significant discipline difference was reported for DASS Stress after adjustment. The reported p-value was 0.089.

Can PHQ-9 or DASS-21 scores diagnose depression or anxiety?

No. These questionnaires measure self-reported symptoms and can support screening and research, but they do not replace an appropriate clinical assessment when diagnosis or treatment decisions are required.

What factors besides academic discipline were associated with mental-health scores?

Female gender was associated with higher scores across the examined domains. Longer sleep duration was associated with lower PHQ-9 scores, while previous depression treatment was a strong marker of higher PHQ-9 scores. These are associations and should not be interpreted as proof of causation.

What is the main implication for Pakistani universities?

The findings support mental-health services that are accessible across academic disciplines. Universities should avoid assuming that psychological distress is primarily a medical-student problem and should consider broader student-level factors when designing support systems.

Medical disclaimer: This article is for educational and research communication purposes only. The PHQ-9 and DASS-21 are not substitutes for an individual clinical assessment. Anyone experiencing persistent or severe depression, anxiety, significant impairment, thoughts of self-harm or other concerning mental-health symptoms should seek assessment from an appropriately qualified healthcare professional or appropriate urgent services when necessary.