Are the PHQ-9 and GAD-7 Suitable for Use in India? A Psychometric Analysis
Bibliographic record
Abstract
BACKGROUND: Cross-cultural evidence on the factorial structure and invariance of the PHQ-9 and the GAD-7 is lacking for South Asia. Recommendations on the use of unit-weighted scores of these scales (the sum of items' scores) are not well-founded. This study aims to address these contextual and methodological gaps using data from a rural Indian population. METHODS: with diabetes = 202). 1,007 participants were surveyed over 2 years using the PHQ-9 and the GAD-7. Bifactor-(S - 1) modeling and multigroup confirmatory factor analysis were used. RESULTS: Factor analysis supported the existence of a somatic and cognitive/affective subcomponent for both scales, but less explicitly for the GAD-7. Hierarchical omega values were 0.72 for the PHQ-9 and 0.76 for the GAD-7. Both scales showed full scalar invariance and full or partial residual invariance across age, gender, education, status of diabetes and over time. Effect sizes between categories measured by unit-weighted scores versus latent means followed a similar trend but were systematically higher for the latent means. For both disorders, female gender and lower education were associated with higher symptom severity scores, which corresponds with regional and global trends. CONCLUSIONS: For both scales, psychometric properties were comparable to studies in western settings. Distinct clinical profiles (somatic-cognitive) were supported for depression, and to a lesser extent for anxiety. Unit-weighted scores of the full scales should be used with caution, while scoring subscales is not recommended. The stability of these scales supports their use and allows for meaningful comparison across tested subgroups. CLINICAL TRIAL REGISTRATION: Australia and New Zealand Clinical Trials Registry: ACTRN12611000262909http://www.anzctr.org.au/Trial/Registration/TrialReview.aspx?id=336603&isReview=true.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".