Activation and Self-Efficacy in a Randomized Trial of a Depression Self-Care Intervention
Bibliographic record
Abstract
OBJECTIVES: In a sample of primary care participants with chronic physical conditions and comorbid depressive symptoms: to describe the cross-sectional and longitudinal associations of activation and self-efficacy with demographic, physical and mental health status, health behaviors, depression self-care, health care utilization, and use of self-care tools; and to examine the effects of a depression self-care coaching intervention on these two outcomes. Design/Study Setting. A secondary analysis of activation and self-efficacy data collected as part of a randomized trial to compare the effects of a telephone-based coached depression self-care intervention with a noncoached intervention. Activation (Patient Activation Measure) was measured at baseline and 6 months. Depression self-care self-efficacy was assessed at baseline, at 3 months, and at 6 months. PRINCIPAL FINDINGS: In multivariable cross-sectional analyses (n = 215), activation and/or self-efficacy were associated with language, birthplace, better physical and mental health, individual exercise, specialist visits, and antidepressant nonuse. In longitudinal analyses (n = 158), an increase in activation was associated with increased medication adherence; an increase in self-efficacy was associated with use of cognitive self-care strategies and increases in social and solitary activities. There were significant improvements from baseline to 6 months in activation and self-efficacy scores both among coached and noncoached groups. The self-care coaching intervention did not affect 6-month activation or self-efficacy but was associated with quicker improvement in self-efficacy. CONCLUSIONS: Overall, the results for activation and self-efficacy were similar, although self-efficacy correlated more consistently than activation with depression-specific behaviors and was responsive to a depression self-care coaching intervention.
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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 | 0.004 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.007 | 0.001 |
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".