Validating a Shortened Depression Scale (10 Item CES-D) among HIV-Positive People in British Columbia, Canada
Bibliographic record
Abstract
OBJECTIVE: To establish the reliability and validity of a shortened (10-item) depression scale used among HIV-positive patients enrolled in the Drug Treatment Program in British Columbia, Canada. METHODS: The 10-item CES-D (Center for Epidemiologic Studies Depression Scale) was examined among 563 participants who initiated antiretroviral therapy (ART) between August 1, 1996 and June 30, 2002. Internal consistency of the scale was measured by Cronbach's alpha. Using the original CES-D 20 as primary criteria, comparisons were made using the Kappa statistic. Predictive accuracy of CES-D 10 was assessed by calculating sensitivity, specificity, positive predictive values and negative predictive values. Factor analysis was also performed to determine if the CES-D 10 contained the same factors of positive and negative affect found in the original development of the CES-D. RESULTS: The correlation between the original and the shortened scale is very high (Spearman correlation coefficient =0.97 (P<0.001). Internal consistency reliability coefficients of the CES-D 10 were satisfactory (Cronbach α=0.88). The CES-D 10 showed comparable accuracy to the original CES-D 20 in classifying participants with depressive symptoms (Kappa=0.82, P<0.001). Sensitivity of CES-D 10 was 91%; specificity was 92%; and positive predictive value was 92%. Factor analysis demonstrates that CES-D 10 contains the same underlying factors of positive and negative affect found in the original development of the CES-D 20. CONCLUSION: The 10-item CES-D is a comparable tool to measure depressive symptoms among HIV-positive research participants.
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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 | 0.002 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 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".