Depression in University Students: The Surprising Findings From Our Pakistan Study

Depression in university students is often discussed as if certain academic disciplines are automatically at greater risk than others. Our recent study of 602 undergraduate students in Lahore, Pakistan, challenges that assumption. Non-medical students reported slightly higher depressive symptoms than medical students, and the difference persisted after statistical adjustment. Yet perhaps the more important finding was that academic discipline explained only a small fraction of the overall variation in mental-health symptoms. In other words, whether a student studied medicine or another subject mattered less than the broader picture of individual vulnerability, previous mental-health history, gender, sleep and other influences.

These findings come from our 2026 BMC Psychology study, Psychometric properties and symptom profiles of the PHQ-9 and DASS-21 among medical and non-medical university students, which examined 424 medical and 178 non-medical students in Lahore. Rather than asking only how common depressive symptoms were, we also compared academic groups, examined predictors of symptom severity and evaluated how two widely used psychological questionnaires performed in this population.

Depression in university students may not follow the pattern we expect

Medical education has a well-established reputation for being demanding. Long study hours, examinations, clinical responsibilities and exposure to illness can make medical students an obvious focus for university mental-health research. That concern is reasonable, but it can lead to an unintended assumption: if medical students face particularly visible academic pressures, they must necessarily have worse depression than students in other disciplines.

Our findings did not support that simple hierarchy. The median PHQ-9 score among non-medical students was 10, compared with 9 among medical students. Statistical modelling also indicated higher PHQ-9 scores among non-medical students after adjustment for measured covariates. The same general pattern appeared for the depression and anxiety domains of the DASS-21, although the difference in DASS stress scores was not statistically significant.

That does not mean medical students are protected from depression. Nor does it establish that being a non-medical student causes depressive symptoms. The study was cross-sectional, meaning exposures and symptoms were measured at one point in time. What it does show is that universities should be cautious about assuming that one highly visible academic group represents the entire student mental-health problem.

What did the Pakistan study examine?

The study included 602 undergraduate students from universities in Lahore, Pakistan. Of these participants, 424 were medical students and 178 were studying non-medical disciplines. Participants completed two established self-report measures: the Patient Health Questionnaire-9, commonly known as the PHQ-9, and the 21-item Depression Anxiety Stress Scales, or DASS-21.

The PHQ-9 is a nine-item questionnaire designed to measure the severity of depressive symptoms. Its original validation study found it useful as a brief measure of depression severity, and it has subsequently become one of the most widely used depression questionnaires in clinical care and research. Importantly, however, a questionnaire score is not equivalent to an individual clinical diagnosis. Assessment of depression in a person requires appropriate clinical evaluation when indicated.

Our analysis went beyond a simple comparison of average scores. It included descriptive statistics, group comparisons, multivariable regression, confirmatory factor analysis, item response theory and symptom network analysis. This allowed us to explore not only whether medical and non-medical students differed, but also which symptoms appeared particularly informative and whether the measurement tools behaved adequately within the sample.

The first surprising finding: non-medical students reported more depressive symptoms

The most immediately counterintuitive result concerned academic discipline. Non-medical students had a PHQ-9 median of 10 compared with 9 in medical students. In adjusted modelling, academic group remained associated with PHQ-9 scores. Non-medical students also had higher adjusted scores for the DASS-21 depression and anxiety domains.

It would be easy to turn this into the headline that non-medical students are more depressed than medical students. That interpretation would go too far. The observed difference was relatively modest, the study involved students from one Pakistani city, and a cross-sectional design cannot establish causation.

More importantly, the statistical models explained only a small proportion of the total variation in symptom scores. Model R-squared values were approximately 0.029 to 0.041. Put simply, the variables included in those models accounted for only a limited amount of why one student reported more symptoms than another.

This may be one of the study’s most useful messages. Academic discipline can be statistically associated with mental-health scores without being the dominant explanation for student mental health.

Why might non-medical students report higher scores?

The study was not designed to determine the causal mechanism behind the difference, so any explanation must remain tentative. Different groups of students may experience different combinations of academic uncertainty, employment concerns, financial pressure, family expectations, social support, institutional resources or career-related stress. There may also be differences between universities, courses and student populations that were not captured by the variables available in our survey.

The appropriate conclusion is therefore not that one academic pathway is inherently psychologically worse than another. It is that universities should examine mental health across their full student population rather than allocating attention according to assumptions about which disciplines appear most stressful.

The second important finding: female students reported higher symptoms across domains

Gender showed a more consistent pattern in our models. Female students had higher scores across the measured depression, anxiety and stress domains, with statistically significant associations across the models.

This does not mean that every female student is at greater risk than every male student, nor does it mean that male students require less mental-health support. Group-level associations cannot be used to predict the needs of a particular person. However, a consistent association can help universities identify populations that may warrant closer attention when designing inclusive screening, prevention and support services.

The finding also reinforces why university mental health cannot be reduced to academic discipline. Students bring different social circumstances, personal histories and vulnerabilities into the same educational environment. Two people studying the same degree may experience that environment very differently.

Sleep was associated with depressive symptoms

Another practically relevant finding involved sleep. Each additional hour of sleep was associated with a lower PHQ-9 score in the adjusted analysis. The estimated coefficient was -0.37 points per additional hour of sleep.

Again, the cross-sectional design matters. We cannot say from these data that increasing sleep by one hour will produce a particular reduction in depression scores. Depression itself can disturb sleep, and the relationship between sleep and mental health can operate in both directions. Other factors may also influence both.

Nevertheless, the association is meaningful from a university-health perspective. Sleep is closely connected to daily student routines, academic timetables, late-night study, social activities and digital habits. Universities discussing student wellbeing should therefore consider sleep health alongside counselling and psychological services rather than treating mental health as an issue that begins only after severe symptoms appear.

Previous treatment for depression was a strong predictor

A history of previous treatment for depression was the strongest predictor identified in the reported regression analysis, with a coefficient of 4.15 for PHQ-9 scores. This association is clinically understandable: students who have previously required treatment may represent a group with a history of more substantial or recurrent depressive symptoms.

However, previous treatment should not be interpreted as causing current symptoms. It is better understood as a marker of prior mental-health history. From a service-planning perspective, universities may benefit from ensuring that students with existing or previous mental-health needs can access continuity of support when they enter or continue higher education.

Not every depression symptom contributed equally

One feature that distinguished our study from many student mental-health surveys was the examination of individual questionnaire items. Item response theory suggested that some symptoms were more informative for distinguishing levels of depressive symptom severity than others.

Items involving self-worth, concentration, feeling down and appetite showed comparatively high discrimination in the PHQ-9 analysis. The loss-of-interest or anhedonia item showed lower discrimination in this particular sample. Symptom network analysis similarly highlighted self-worth, concentration and downheartedness as relatively central features of the observed symptom structure.

These findings should be interpreted carefully. They do not mean that other symptoms are unimportant or that screening should simply discard them. Depression is heterogeneous, and individual patients can experience very different symptom profiles. Network centrality also does not demonstrate that one symptom causes another.

What the findings do suggest is that examining the structure of symptoms may reveal information that is hidden when researchers report only total questionnaire scores.

The questionnaires worked reasonably well, but there was an important measurement warning

The PHQ-9 and DASS-21 demonstrated acceptable internal consistency in the study, with Cronbach’s alpha values ranging from 0.82 to 0.88. Measurement invariance across academic discipline was also supported, strengthening the basis for comparing medical and non-medical students within the study.

The DASS-21 confirmatory factor analysis showed adequate overall fit. However, correlations between some of its latent dimensions were extremely high. The reported correlations were 0.939 between depression and stress and 0.949 between anxiety and stress.

This matters because the DASS-21 is commonly interpreted as providing distinct depression, anxiety and stress subscale scores. When latent factors are extremely highly correlated in a particular population, it raises a measurement question: how clearly are these constructs being distinguished?

Our results do not invalidate the DASS-21. They instead illustrate why researchers should evaluate psychometric performance rather than assuming that a questionnaire behaves identically in every cultural or educational population.

Screening scores are not psychiatric diagnoses

This distinction is essential when discussing depression in university students. A PHQ-9 or DASS-21 score represents self-reported symptoms measured using a structured questionnaire. It does not, by itself, establish a diagnosis of major depressive disorder or another psychiatric condition.

The PHQ-9 was developed as a brief measure of depressive symptoms and can be useful for screening and severity assessment, but interpretation still depends on context. Clinical diagnosis involves professional assessment, including symptom history, functional impairment, possible alternative explanations and safety concerns.

This is especially important when research findings are communicated to the public. Statements such as “X percent of students have depression” can become misleading when a study actually measured the proportion crossing a questionnaire threshold rather than the proportion receiving a structured clinical diagnosis.

What the findings mean for universities in Pakistan

The strongest practical lesson may be that student mental-health systems should be broad rather than discipline-specific. Universities understandably develop programs around groups believed to be at high risk, but mental-health support should remain accessible across faculties.

A more comprehensive approach could include:

• making counselling and psychological support available to students across academic disciplines;
• providing clear routes for students with previous mental-health treatment to obtain appropriate ongoing support;
• including evidence-based mental-health education during student orientation and throughout university life;
• addressing sleep health and realistic study routines as part of wellbeing initiatives;
• training relevant university staff to recognize concerning changes and refer students appropriately;
• protecting confidentiality so fear of stigma does not discourage help-seeking;
• evaluating local student data rather than relying entirely on assumptions imported from other countries or academic settings.

The final point is especially important in Pakistan. Mental-health evidence from universities in North America or Europe can provide valuable context, but educational structures, family systems, financial pressures, cultural expectations and access to professional care differ between settings. Local data are therefore necessary for locally appropriate decisions.

What this study cannot tell us

Every research result becomes more useful when its limitations are stated clearly. Our study was cross-sectional, so it cannot establish the direction of causal relationships. For example, the association between sleep and depression could reflect effects in either or both directions.

The participants were undergraduate students recruited from universities in Lahore. The findings should not automatically be generalized to every university student in Pakistan, particularly students from different provinces, rural settings, postgraduate programs or institutions with substantially different educational and socioeconomic environments.

The mental-health measures were self-reported questionnaires rather than structured psychiatric diagnostic interviews. Self-report data may be influenced by recall, interpretation, willingness to disclose symptoms and cultural factors.

The medical and non-medical groups were also unequal in size, with 424 medical and 178 non-medical students. Although statistical methods can account for unequal group sizes, broader and more diverse replication would strengthen confidence in the observed academic-discipline differences.

Finally, the low proportion of variance explained by the regression models indicates that many influences on student mental health were not captured. Future studies could examine factors such as financial strain, academic workload, social support, loneliness, family expectations, physical activity, substance use, living arrangements and access to mental-health services.

Why the “surprising” result may actually be the most useful one

The most memorable finding is that non-medical students reported somewhat higher depressive symptoms than medical students. But the deeper lesson is not a competition between faculties over which students have worse mental health.

The data point toward a more nuanced conclusion: depression in university students cannot be adequately understood from degree type alone. Academic discipline showed an association, but individual and contextual differences remain substantial. Female students reported higher symptoms across several domains, sleep was associated with PHQ-9 scores, prior depression treatment identified a particularly relevant group, and individual symptoms differed in their measurement characteristics.

For researchers, the results support more careful measurement and greater attention to symptom-level information. For universities, they support inclusive mental-health strategies. And for students, the findings reinforce that psychological distress is not restricted to a particular faculty or type of degree.

Where research should go next

Future Pakistani university mental-health research would benefit from multicentre studies involving institutions from multiple regions and a wider range of disciplines. Longitudinal research could follow students over time and help determine whether changes in sleep, academic conditions, finances or social circumstances precede changes in depressive symptoms.

Researchers could also investigate why academic groups differ rather than simply documenting that a difference exists. If non-medical students repeatedly show higher symptom scores in independent samples, the next question would be which factors account for that pattern.

Qualitative research could complement questionnaire studies by exploring how students themselves describe academic pressure, career uncertainty, family expectations, stigma and access to psychological care. Combining these approaches may provide a richer picture than any single depression score.

Final perspective

Depression in university students is a whole-campus issue. Our Pakistan study challenges the expectation that medical students necessarily report the greatest psychological burden. In this sample, non-medical students reported slightly higher depression and anxiety scores, but academic discipline explained relatively little of the overall variation between students.

That finding shifts the conversation away from asking which faculty is “most depressed” and toward a more useful question: how can universities identify and support students who need help, regardless of what they study?

Mental-health research is most useful when it makes our assumptions more precise rather than replacing one stereotype with another. These results suggest that universities should look beyond degree labels, pay attention to individual vulnerability and previous mental-health history, consider factors such as sleep, and make support systems accessible across the entire student community.

Medical disclaimer: This article provides educational information about population-level research and is not intended to diagnose depression or provide individualized medical advice. Screening questionnaires such as the PHQ-9 and DASS-21 do not replace assessment by a qualified healthcare professional. Anyone experiencing persistent depressive symptoms, substantial impairment, thoughts of self-harm or other urgent mental-health concerns should seek appropriate professional or emergency care.