BMC psychology · 2026
Psychometric properties and symptom profiles of the PHQ-9 and DASS-21 among medical and non-medical university students: a cross-sectional study in Pakistan.
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Asghar Taimoor, Hassan Ali, Sahar Ifrah, Tahir Muhammad, Shahid Bilal, Komal Komal
Аннотация
BACKGROUND: Depression is a leading cause of disability among university students. While medical students are often assumed to be at highest risk, cross-disciplinary comparisons in South Asia remain scarce. This study examined depressive symptom differences between medical and non-medical students in Pakistan and evaluated the concurrent psychometric performance of the PHQ-9 and DASS-21.
METHODS: A cross-sectional survey of 602 undergraduate students (424 medical, 178 non-medical) was conducted at universities in Lahore, Pakistan. Measures included the PHQ-9 and DASS-21. Analyses comprised descriptive statistics, Wilcoxon rank-sum tests, multivariable linear regression (separate models for PHQ-9 and each DASS-21 domain), confirmatory factor analysis, item response theory using a graded response model, and symptom network analysis with stability testing.
RESULTS: Non-medical students had higher PHQ-9 scores than medical students (median 10.0 vs. 9.0). In adjusted models, non-medical students scored higher on PHQ-9 (β = -1.43, p = 0.004), DASS Depression (β = -1.82, p = 0.003), and DASS Anxiety (β = -2.31, p = 0.001); the DASS Stress difference was non-significant (β = -0.89, p = 0.089). Female gender predicted higher scores across all domains (all p < 0.001). Each additional hour of sleep was associated with lower PHQ-9 scores (β = -0.37, p = 0.010). Prior depression treatment was the strongest predictor (β = 4.15, p < 0.001). DASS-21 confirmatory factor analysis showed adequate fit (CFI = 0.954, TLI = 0.948, RMSEA = 0.052), but latent factor correlations were very high (Depression-Stress r = 0.939; Anxiety-Stress r = 0.949). Cronbach's α ranged 0.82-0.88 across scales. Item response theory indicated that self-worth, concentration, down, and appetite items showed the highest discrimination; interest (anhedonia) showed the lowest (a = 0.468). In network analysis, self-worth, concentration, and downheartedness were the most central nodes; stability coefficients ranged 0.31-0.44. Measurement invariance across discipline was supported. Model R² values were low (0.029-0.041).
CONCLUSIONS: Non-medical students reported higher depressive and anxiety symptoms than medical students in this Pakistani sample, although academic discipline explained only a small proportion of variance. Both instruments performed adequately, though the DASS-21's near-unity latent correlations may raise questions about subscale distinguishability in this population. Cognitive and self-worth symptoms emerged as the most informative for screening purposes. Campus mental health strategies should address the whole student population, with particular attention to female students and sleep health.
METHODS: A cross-sectional survey of 602 undergraduate students (424 medical, 178 non-medical) was conducted at universities in Lahore, Pakistan. Measures included the PHQ-9 and DASS-21. Analyses comprised descriptive statistics, Wilcoxon rank-sum tests, multivariable linear regression (separate models for PHQ-9 and each DASS-21 domain), confirmatory factor analysis, item response theory using a graded response model, and symptom network analysis with stability testing.
RESULTS: Non-medical students had higher PHQ-9 scores than medical students (median 10.0 vs. 9.0). In adjusted models, non-medical students scored higher on PHQ-9 (β = -1.43, p = 0.004), DASS Depression (β = -1.82, p = 0.003), and DASS Anxiety (β = -2.31, p = 0.001); the DASS Stress difference was non-significant (β = -0.89, p = 0.089). Female gender predicted higher scores across all domains (all p < 0.001). Each additional hour of sleep was associated with lower PHQ-9 scores (β = -0.37, p = 0.010). Prior depression treatment was the strongest predictor (β = 4.15, p < 0.001). DASS-21 confirmatory factor analysis showed adequate fit (CFI = 0.954, TLI = 0.948, RMSEA = 0.052), but latent factor correlations were very high (Depression-Stress r = 0.939; Anxiety-Stress r = 0.949). Cronbach's α ranged 0.82-0.88 across scales. Item response theory indicated that self-worth, concentration, down, and appetite items showed the highest discrimination; interest (anhedonia) showed the lowest (a = 0.468). In network analysis, self-worth, concentration, and downheartedness were the most central nodes; stability coefficients ranged 0.31-0.44. Measurement invariance across discipline was supported. Model R² values were low (0.029-0.041).
CONCLUSIONS: Non-medical students reported higher depressive and anxiety symptoms than medical students in this Pakistani sample, although academic discipline explained only a small proportion of variance. Both instruments performed adequately, though the DASS-21's near-unity latent correlations may raise questions about subscale distinguishability in this population. Cognitive and self-worth symptoms emerged as the most informative for screening purposes. Campus mental health strategies should address the whole student population, with particular attention to female students and sleep health.