Understanding Depression and Anxiety Among Pakistani University Students Using PHQ-9 and DASS-21

Depression and anxiety among Pakistani university students cannot be understood simply by assuming that one academic group is more vulnerable than another. A 2026 study of 602 undergraduate students in Lahore found that non-medical students reported somewhat higher depressive and anxiety symptoms than medical students, while female students, prior depression treatment, and sleep were also associated with symptom levels. Just as importantly, the study tested how well two widely used instruments—the Patient Health Questionnaire-9 (PHQ-9) and Depression Anxiety Stress Scales-21 (DASS-21)—performed in this population.

Byline: Taimoor Asghar

Published on taimoorasghar.com

Why depression and anxiety among Pakistani university students deserve closer attention

University life is often associated with academic opportunity, independence, and professional development, but it can also coincide with considerable psychological pressure. Students may face examinations, competitive grading, financial concerns, uncertainty about employment, disrupted sleep, relocation away from family, changing social relationships, and pressure to meet expectations from themselves or others.

These experiences do not automatically constitute a mental disorder. Feeling worried before an examination or temporarily discouraged after a setback can be part of ordinary life. The challenge for researchers and university health systems is to distinguish transient distress from patterns of symptoms that may warrant greater attention.

This is where standardized questionnaires can be useful. Instead of relying only on broad questions such as whether a student feels stressed, validated symptom scales provide a structured way to quantify specific experiences. Two instruments commonly used in mental-health research are the PHQ-9 and DASS-21.

The 2026 BMC Psychology study, Psychometric properties and symptom profiles of the PHQ-9 and DASS-21 among medical and non-medical university students, examined both student symptom patterns and the measurement properties of these instruments in a Pakistani university population.

What was investigated in the Pakistani study?

The cross-sectional study included 602 undergraduate students recruited from universities in Lahore, Pakistan. Of these participants, 424 were medical students and 178 were studying non-medical disciplines.

Students completed the PHQ-9 and DASS-21. Rather than limiting the analysis to a comparison of average questionnaire scores, the researchers used several complementary statistical approaches.

• Descriptive statistics were used to characterize symptom distributions.
• Medical and non-medical students were compared using non-parametric statistical testing.
• Multivariable regression was used to examine whether academic discipline and other factors were associated with PHQ-9 and DASS-21 scores.
• Confirmatory factor analysis assessed whether the expected underlying structure of the questionnaires was supported by the data.
• Item response theory examined how individual questionnaire items performed across different levels of symptoms.
• Symptom network analysis explored which symptoms occupied more central positions within the observed symptom network.
• Measurement invariance testing assessed whether the instruments behaved sufficiently similarly across medical and non-medical students to support meaningful comparisons.

This broader psychometric approach matters because a questionnaire may be internally consistent without necessarily separating psychological constructs as cleanly as researchers expect. Understanding both symptom scores and measurement behavior therefore provides a more informative picture.

Understanding the PHQ-9

The Patient Health Questionnaire-9 is a nine-item self-report measure designed to assess depressive symptoms. Its items correspond closely to core symptom domains associated with depression, including reduced interest or pleasure, low mood, sleep disturbance, low energy, appetite changes, negative feelings about oneself, concentration problems, psychomotor changes, and thoughts related to death or self-harm.

The PHQ-9 asks about symptoms over the preceding two weeks. Responses can be combined into a total score representing increasing depressive symptom severity.

Importantly, a PHQ-9 score is not equivalent to a psychiatric diagnosis. A questionnaire can identify symptom burden and help determine who may benefit from further assessment, but diagnosis requires appropriate clinical evaluation, including consideration of symptom duration, functional impairment, medical conditions, substance use, differential diagnoses, and the individual’s broader circumstances.

The original validation work by Kroenke, Spitzer, and Williams established the PHQ-9 as a useful brief measure of depression severity, contributing to its widespread use in both research and healthcare.

Understanding the DASS-21

The DASS-21 contains 21 items divided into three seven-item domains: depression, anxiety, and stress. It therefore provides a broader assessment of negative emotional symptoms than a depression-specific instrument alone.

DASS-21 depression

The depression domain focuses on experiences such as low positive affect, hopelessness, reduced interest, lack of enthusiasm, and feelings that life lacks meaning. Although these concepts overlap with depression measured by the PHQ-9, the two questionnaires are not interchangeable because their item content and conceptual structures differ.

DASS-21 anxiety

The anxiety domain assesses symptoms associated with anxious arousal and fear. These may include autonomic sensations, trembling, panic-like experiences, and apprehension.

DASS-21 stress

The stress domain focuses more on persistent tension, difficulty relaxing, irritability, agitation, and feeling overwhelmed.

The DASS family of scales has been investigated across numerous populations, and psychometric research has generally supported its usefulness for measuring dimensions of depression, anxiety, and stress. At the same time, the three domains often correlate strongly, reflecting the substantial overlap between forms of psychological distress.

What did the study find about medical and non-medical students?

One of the study’s most relevant findings challenges the common assumption that medical students necessarily carry the greatest mental-health burden within a university.

The median PHQ-9 score was 10 among non-medical students compared with 9 among medical students. After adjustment for other variables in the regression analysis, non-medical students also had higher scores on the PHQ-9, DASS-21 depression domain, and DASS-21 anxiety domain.

The adjusted difference in DASS-21 stress scores did not reach conventional statistical significance.

This finding should not be interpreted as evidence that medical education protects students from psychological distress. Medical students face well-documented academic and professional pressures. Rather, the results suggest that mental-health programs should not concentrate exclusively on medical faculties while assuming students in other disciplines are at comparatively low risk.

The researchers also found that the statistical models explained only a small proportion of the overall variation in symptoms. Academic discipline therefore represented only one piece of a much larger picture.

Academic discipline is not the whole explanation

The study’s low model R-squared values are particularly useful for interpreting the medical versus non-medical comparison. Even when group differences are statistically significant, academic discipline alone does not explain why one individual student develops substantial symptoms while another does not.

Mental health is influenced by interacting biological, psychological, social, educational, and environmental factors. Potential influences can include financial strain, family circumstances, interpersonal difficulties, academic workload, chronic illness, previous mental-health problems, social isolation, sleep disruption, traumatic experiences, substance use, and access to support.

Cross-sectional university surveys generally cannot establish the complete causal pathway behind these relationships. Their strength is identifying associations and population patterns that can guide further investigation.

Female students reported higher symptom scores

Female gender was associated with higher scores across the symptom domains examined in the study. This association remained statistically significant in the adjusted analyses reported by the authors.

Such a finding should be interpreted at the group level rather than applied deterministically to individual students. It does not mean that every female student experiences worse mental health than every male student, nor does it establish why the difference occurred.

Possible explanations for gender differences in mental-health surveys can involve numerous social, cultural, biological, economic, and reporting-related mechanisms. Determining which of these mechanisms operate within Pakistani university populations would require targeted longitudinal and qualitative research rather than assumptions based solely on questionnaire scores.

Nevertheless, the result supports ensuring that university mental-health services are attentive to gender-related patterns and barriers to seeking support.

Sleep emerged as another relevant factor

Sleep duration showed a significant association with PHQ-9 scores. Each additional hour of sleep was associated with a lower PHQ-9 score in the adjusted model.

This result is clinically and practically interesting because sleep disturbance and depressive symptoms frequently occur together. However, the cross-sectional study design cannot determine which direction the relationship operated.

Shorter sleep could contribute to mood difficulties through fatigue, impaired concentration, emotional dysregulation, and reduced resilience. Conversely, depression, anxiety, academic stress, irregular routines, or other problems may disrupt sleep. Both processes can also occur simultaneously.

For universities, the finding supports considering sleep health as one component of broader student well-being initiatives rather than treating psychological health solely as a counseling issue.

Previous depression treatment was strongly associated with current symptoms

Among the variables examined, prior treatment for depression showed a particularly strong association with current depressive symptom scores. Students reporting previous depression treatment had substantially higher PHQ-9 scores in the adjusted analysis.

This is not surprising: a history of treatment may identify students who have previously experienced clinically meaningful depressive symptoms and who may remain vulnerable to recurrence or persistent symptoms.

However, the association should not be interpreted to mean that treatment causes higher symptom levels. Cross-sectional observational data cannot support such a conclusion. Prior treatment is better understood as a marker of previous mental-health burden in this context.

How reliable were PHQ-9 and DASS-21 in this sample?

Reliability describes the consistency with which items within a scale measure related aspects of a construct. In the Pakistani study, Cronbach’s alpha values ranged from 0.82 to 0.88 across the PHQ-9 and DASS-21 scales.

These results indicate good internal consistency within this study population. In practical terms, the items within each scale showed sufficiently coherent relationships to support their use as symptom measures in the sample.

Reliability, however, is only one component of measurement quality. A questionnaire can be reliable yet still have limitations in construct validity, factor separation, or interpretation across populations. This is why the authors also performed confirmatory factor analysis, item response theory, and measurement invariance testing.

What did the DASS-21 factor analysis show?

The confirmatory factor analysis of the DASS-21 produced generally adequate model-fit statistics. The study reported a comparative fit index of 0.954, Tucker-Lewis index of 0.948, root mean square error of approximation of 0.052, and satisfactory related fit indicators.

Yet another result deserves particular attention: correlations between the latent DASS-21 factors were extremely high. The reported depression-stress latent correlation was 0.939, while anxiety and stress correlated at 0.949.

These values suggest that although the expected domains could be statistically modeled, the constructs overlapped very strongly in this sample.

That does not make the DASS-21 unusable. Instead, it raises a more nuanced measurement question: how confidently should researchers interpret small differences between the individual depression, anxiety, and stress subscales when the underlying factors are so closely related?

In some university populations, the DASS-21 may capture both specific symptom dimensions and a broader common component of psychological distress. Researchers should therefore examine psychometric performance in the population being studied rather than assuming that results from one country or setting automatically transfer to another.

Which symptoms appeared especially informative?

The study also examined individual questionnaire items using item response theory. Certain symptoms were particularly effective at distinguishing between students with different underlying levels of psychological distress.

Items involving self-worth, concentration, feeling down, and appetite showed comparatively high discrimination. In contrast, the PHQ-9 interest or anhedonia item showed lower discrimination in this sample.

Item discrimination is a statistical concept. It does not mean that a lower-discrimination symptom is clinically unimportant. Anhedonia remains a central feature of depressive disorders. Instead, discrimination indicates how strongly a particular questionnaire item differentiated participants at different levels of the latent trait within this specific dataset.

This distinction is essential when translating psychometric results into practical conclusions.

What did symptom network analysis add?

Traditional questionnaire scoring combines multiple symptoms into a total or subscale score. Network analysis approaches the problem differently by examining symptoms as interconnected elements.

In the Pakistani study, self-worth problems, concentration difficulties, and downheartedness emerged among the more central symptoms in the network. These findings broadly complemented the item-level analyses, which also highlighted cognitive and self-evaluative symptoms.

Network centrality should nevertheless be interpreted cautiously. A symptom appearing central in a cross-sectional network does not prove that it causes other symptoms. In addition, the reported network stability coefficients ranged from approximately 0.31 to 0.44, suggesting that some centrality estimates were more stable than others.

The results are therefore better regarded as useful clues about symptom organization than as evidence for targeting one specific symptom as the causal driver of student depression or anxiety.

Can PHQ-9 and DASS-21 scores be compared across academic disciplines?

An important methodological result was support for measurement invariance across medical and non-medical students.

Measurement invariance asks whether a questionnaire measures the same underlying construct in sufficiently comparable ways across groups. Without such evidence, an apparent difference in scores could partly arise because questionnaire items function differently in one group rather than because the groups actually differ in symptoms.

Support for invariance therefore strengthens the interpretation of the medical versus non-medical comparisons reported in the study, although it does not remove the other limitations associated with observational cross-sectional research.

PHQ-9 versus DASS-21: what does each contribute?

The two questionnaires overlap but answer somewhat different questions.

• PHQ-9: provides a concise assessment focused specifically on depressive symptoms over the previous two weeks.
• DASS-21: provides separate symptom scores for depression, anxiety, and stress and can capture a broader range of negative emotional experiences.
• Using both: can provide a richer psychometric picture in research, particularly when investigators want to compare depression-specific findings with broader emotional distress.

The Pakistani findings suggest that both instruments performed adequately overall, while the high correlations among DASS-21 domains also demonstrate why researchers should not treat depression, anxiety, and stress scores as completely independent phenomena.

What should Pakistani universities learn from these findings?

The most practical implication is that student mental-health strategies should be university-wide rather than concentrated only in programs traditionally regarded as highly stressful.

Medical students certainly warrant support, but this study found higher depressive and anxiety scores among non-medical participants after adjustment for measured variables. Universities should therefore build services around student need rather than assumptions about which faculty is most vulnerable.

A comprehensive approach might include accessible counseling and referral pathways, confidential screening where appropriate, faculty awareness, clear procedures for responding to students experiencing significant distress, anti-stigma initiatives, academic support, attention to sleep and workload, and mechanisms for identifying students whose symptoms substantially interfere with daily functioning.

Screening programs also require appropriate follow-up. Administering PHQ-9 or DASS-21 questionnaires without a pathway for assessment, support, and referral risks turning measurement into an administrative exercise rather than meaningful care.

Important limitations when interpreting the study

Several limitations are essential for understanding what these results can and cannot tell us.

The study was cross-sectional

Exposure variables and mental-health symptoms were measured at one point in time. Therefore, associations involving sleep, gender, academic discipline, previous treatment, and symptom scores cannot by themselves establish cause and effect.

The sample came from Lahore

Pakistan has considerable educational, cultural, economic, and geographic diversity. Findings from undergraduate students recruited in Lahore should not automatically be generalized to every university student in the country.

Symptoms were self-reported

PHQ-9 and DASS-21 scores represent reported symptoms rather than diagnoses confirmed through structured psychiatric interviews.

Group membership explained limited variance

Although statistically significant differences were detected between medical and non-medical students, discipline accounted for only a modest component of the overall variability in mental-health symptoms.

Psychological constructs overlapped substantially

The very high correlations among DASS-21 latent factors suggest that depression, anxiety, and stress may be difficult to separate completely in this population using the subscales alone.

What future research could investigate

The study opens several useful directions for future Pakistani research. Longitudinal studies could follow students over multiple semesters to determine whether changes in sleep, academic workload, finances, examination periods, social circumstances, or other exposures precede changes in symptoms.

Multi-university studies involving several provinces could test whether the psychometric findings replicate across different languages, socioeconomic backgrounds, public and private universities, and academic disciplines.

Clinical validation studies could compare PHQ-9 and DASS-21 results with structured diagnostic interviews. Qualitative studies could also explore why certain students experience psychological distress, how they understand their symptoms, and what prevents them from seeking professional support.

Finally, intervention studies are needed to determine which campus-level strategies actually improve student outcomes rather than merely increasing awareness.

Key message

The evidence from this 602-student Pakistani study shows why student mental health requires both broad attention and careful measurement. Non-medical students reported higher depression and anxiety scores than medical students in this sample, but academic discipline explained only a small part of the variation in symptoms. Female students reported higher scores across multiple domains, shorter sleep was associated with higher PHQ-9 scores, and previous depression treatment was strongly associated with current symptom burden.

The PHQ-9 and DASS-21 demonstrated good internal consistency and generally adequate psychometric performance. At the same time, the strong overlap among DASS-21 depression, anxiety, and stress factors reminds researchers that mental-health questionnaires simplify complex and interconnected psychological experiences.

For Pakistani universities, the implication is not to identify a single ‘highest-risk’ faculty. It is to develop accessible, evidence-informed mental-health support for the entire student population while paying attention to groups and circumstances associated with greater symptom burden.

Frequently asked questions

What is the PHQ-9 used for?

The PHQ-9 is a nine-item questionnaire used to measure the severity of depressive symptoms over the preceding two weeks. It is widely used in research and healthcare but should not be treated as a stand-alone psychiatric diagnosis.

What does the DASS-21 measure?

The DASS-21 measures symptoms across three domains: depression, anxiety, and stress. Each domain contains seven items. The scales can help quantify psychological distress, although substantial overlap can occur among the three dimensions.

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

No. In this sample, non-medical students had a higher median PHQ-9 score and higher adjusted PHQ-9, DASS depression, and DASS anxiety scores than medical students. However, academic discipline explained only a small proportion of overall symptom variability.

Does a high PHQ-9 or DASS-21 score mean someone has a mental disorder?

Not necessarily. These questionnaires assess symptoms and can help identify people who may benefit from further evaluation. Diagnosis requires appropriate professional assessment and consideration of the person’s clinical and social context.

Why was sleep important in the study?

Longer sleep duration was associated with lower PHQ-9 scores after adjustment for other measured factors. Because the study was cross-sectional, it cannot establish whether shorter sleep contributed to depressive symptoms, depressive symptoms disrupted sleep, or both processes were occurring.

Can the study’s findings be applied to all Pakistani students?

No. The study provides valuable evidence from 602 undergraduate students in Lahore, but further multi-center and longitudinal research is needed before assuming the same patterns apply to every university population across Pakistan.

Medical disclaimer: This article is for educational and research communication purposes only. PHQ-9 and DASS-21 results do not replace assessment by a qualified healthcare professional. Anyone experiencing persistent psychological distress, major impairment in daily functioning, or thoughts of self-harm should seek appropriate professional or urgent medical support according to the seriousness of the situation. Medication or treatment should not be started, stopped, or changed solely on the basis of information in this article.