Depressive Symptoms Moderated the Effect of Chronic Illness Self-Management Training on Self-Efficacy
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Bibliographic record
Abstract
BACKGROUND: Identifying moderators of the effects of self-efficacy enhancing interventions could facilitate their refinement and more targeted, cost-effective delivery. Current theories and data concerning the potential moderating effect of depressive symptoms on interventions to enhance patient chronic illness self-management self-efficacy are conflicting. OBJECTIVES: To explore the moderating effect of depressive symptoms on the effect of an intervention to enhance patient self-efficacy for self-managing chronic illness. RESEARCH DESIGN: Regression analyses using baseline and postintervention (6 weeks) data from an ongoing randomized controlled trial. SUBJECTS: Patients (N = 415) aged >or=40 years recruited from a primary care network in Northern California with arthritis, asthma, chronic obstructive pulmonary disease, congestive heart failure, depression, and/or diabetes mellitus, plus impairment in >or=1 basic activity, and/or a score of >or=4 on the 10-item Center for Epidemiologic Studies Depression Scale (CES-D). MEASURES: Stanford self-efficacy scale, self-reported depression, CES-D, and Medical Outcomes Study Short Form health status questionnaire (SF-36) Mental Component Summary score. RESULTS: Regression analyses revealed the intervention was effective primarily in those with self-reported depression (interaction effect F = 8.24, P = 0.0003), highest CES-D score category (F = 5.68, P = 0.0037), and lowest (most depressed) Mental Component Summary-36 tercile (F = 4.36, P = 0.0135). CONCLUSIONS: Individuals with more depressive symptoms seem more likely to experience self-efficacy gains from chronic illness self-management training than individuals with less depressive symptoms. Future self-management training studies should stratify subjects within study groups by depressive symptom level to further explore its potential moderating effect.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it