Psychometric analysis of the Edinburgh Postnatal Depression Scale and Pregnancy Related Anxiety Questionnaire in Pakistani pregnant women
Bibliographic record
Abstract
BACKGROUND: The Edinburgh Postnatal Depression Scale (EPDS) and the Pregnancy-Related Anxiety Scale (PRAQ) are frequently used perinatal mental health scales. OBJECTIVE: To identify the factor structure of the Urdu language versions of EPDS and PRAQ in 280 Pakistani pregnant women. METHOD: The tools were administered at 12-19 weeks' and 22-29 weeks' gestational age (GA). Exploratory factor analyses were undertaken on data collected at 12-19 weeks' GA, to assess both scales. Results obtained at the second time point were used to examine test-retest reliability. The correlation between the scales was computed. RESULTS: A two-factor model yielded the best fit for both scales, which is consistent with findings from previous studies. For the EPDS, acceptable reliability was attained for the overall score (α = 0.77) and for the factor related to depressive symptoms (α = 0.73), but not for the factor related to anhedonia/suicide (α = 0.64). For the PRAQ, acceptable reliability was attained for the overall score (α = 0.83) and for the factor related to pregnancy concerns (α = 0.84), but not for the factor related to childbirth (α = 0.64). Test-retest reliability was acceptable for both overall scales EPDS: r = 0.50; PRAQ: r = 0.45; both p < .001). The Pearson correlation between the EPDS and PRAQ were r = 0.145, p < .05. CONCLUSION: Analysis of the tools confirmed a two-factor structure for both depression and anxiety among Pakistani pregnant women. A weak correlation was found between the EPDS and PRAQ. Further research is required to develop screening instruments for perinatal mental disorders that are applicable to cultural contexts.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 source (direct Gemma or distilled Codex), 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".