Comparison of the PHQ-9 and CES-D depression scales in systemic sclerosis: internal consistency reliability, convergent validity and clinical correlates
Bibliographic record
Abstract
OBJECTIVE: The reported rates of depressive symptoms in patients with SSc are high. The Center for Epidemiologic Studies Depression Scale (CES-D) is the only measure of depressive symptoms validated for SSc patients. The objective of this study was to assess the internal consistency reliability, convergent validity and strength of association with clinical correlates of the 9-item version of the Patient Health Questionnaire depression scale (PHQ-9) compared with the CES-D in SSc. METHODS: We conducted a cross-sectional, multicentre study of 566 SSc patients who were assessed with the PHQ-9 and CES-D scales, and through clinical histories and medical examinations. Internal consistency reliability was assessed with Cronbach's alpha, convergent validity with Pearson's correlation and the relationship of socio-demographic and clinical variables with the PHQ-9 and CES-D scores using multiple linear regression. RESULTS: Scale reliability was good for the PHQ-9 (alpha = 0.87) and similar to the CES-D (alpha = 0.90). Correlations of the PHQ-9 total score were -0.68 with mental health, -0.43 with physical health, 0.44 with disability, 0.40 with pain and 0.79 with fatigue, which were all in the expected direction and similar to the results with the CES-D. Regression coefficients of clinical correlates did not differ significantly between models using the PHQ-9 and CES-D. CONCLUSION: The PHQ-9 is reliable and valid for use as a measure of depressive symptom severity in patients with SSc and performs similarly to the CES-D. However, the PHQ-9 is advantageous because it is half the length of the CES-D, easily administered and scored, and is increasingly used across many patient groups for assessment in research and clinical settings.
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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 | 0.009 | 0.019 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| 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".