Screening for Anxiety and Depressive Symptoms in Type 2 Diabetes Using Patient-Reported Outcome Measures: Comparative Performance of the EQ-5D-5L and SF-12v2
Bibliographic record
Abstract
Objective. To evaluate the performance of EQ-5D-5L (EuroQol Five-Dimension, Five-Level Questionnaire) and SF-12-v2 (12-item Medical Outcomes Health Survey–Short Form, Version 2) in screening for anxiety and depressive symptoms in adults with type 2 diabetes. Methods. Cross-sectional data from a population-based study of type 2 diabetes in Alberta, Canada, were used. Anxiety symptoms (using the 2-item Generalized Anxiety Disorder questionnaire) were categorized into absent (<3) versus present (≥3). Depressive symptoms (using the 8-item Patient Health Questionnaire) were categorized according to two severity cut-points: absent (<10) versus mild (≥10), and absent (<15) versus moderate-severe (≥15). The performance of the measures in screening for anxiety and depressive symptoms was evaluated using receiver operating curve (ROC) analysis. Results. Average age of participants ( N = 1,391) was 66.8 years (SD 10.2), and 47% were female. Seventeen percent of participants screened positive for mild and 5.9% for moderate-severe depressive symptoms, and 11.3% for anxiety symptoms. For comorbid symptoms, 8.6% screened positive for anxiety and any depressive symptoms, and 4.6% for anxiety and moderate-severe depressive symptoms. The EQ-5D-5L anxiety/depression dimension and the SF-12 mental composite summary score had the best performance in screening for anxiety (area under ROC: 0.89, 0.89, respectively), depressive symptoms (any: 0.88, 0.92; moderate-severe: 0.90, 0.90), and comorbid anxiety and depressive symptoms (any: 0.92, 0.91; moderate-severe: 0.92, 0.90). These were followed by SF-12 feeling downhearted/depressed item (range = 0.83–0.85), while the lowest performance was for the EQ-5D-5L index score (0.80–0.84) and the SF-12 mental health domain (0.81–0.82). Conclusion. The EQ-5D-5L and the SF-12 are suitable tools for screening for anxiety and depressive symptoms in adults with type 2 diabetes. These tools present a unique opportunity for a standardized approach for routine mental health screening within the context of routine outcome measurement initiatives, where screening is recommended.
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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 | 0.016 | 0.024 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 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".