A collaborative, computer-assisted, psychoeducational intervention for depressed patients with chronic disease at primary care: protocol for a cluster-randomized controlled trial
Bibliographic record
Abstract
Introduction Depression treatment recommendations seldom include chronic illness comorbidity. Objectives To describe the rationale and methods for a cluster-randomized trial (CRT) in primary care clinics (PCC) comparing a computer-assisted psychoeducational (CAPE) intervention to usual care (UC) for depressed patients with hypertension or diabetes. Methods Two-arm, single-blind CRT in Santiago, Chile. Eight PCC will be randomly assigned to the intervention or UC. A total of 360 depressed individuals aged 18 or older PHQ-9 scores ≥ 15 and hypertension or diabetes will be recruited. Patients with alcohol/substance abuse; current treatment for depression, bipolar disorder, or psychosis; illiteracy; severe impairment; and residents in long-term care facilities will be excluded. Patients in the intervention will receive eight CAPE sessions by trained therapists, structured telephone calls to track progress, and usual medical care for chronic diseases. Psychologists and psychiatrists will regularly supervise therapists. To ensure continuity of care, the PCC team will meet monthly with a research team member. Patients in UC will receive standard medical and depression treatment. Three, six, and twelve months after enrollment, outcomes will be assessed. The primary outcome will be a 50% reduction in baseline PHQ-9 scores at six months. Intention-to-treat analyses will be used. Results A previous, small-scale pilot study provided valuable insights for study design. Conclusions This study will provide first-hand evidence on the effectiveness of a CAPE for depressed patients with chronic diseases at PCC in a Latin American country. Disclosure No significant relationships.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 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) | 0.001 | 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 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".