Examining the effects of an Educational Person-centered Intervention on Compensatory Strategies (EPICS) in older adults living with frailty: A mixed-methods pilot trial
Bibliographic record
Abstract
This study aimed to explore effects of a two-session Educational Person-centered Intervention on Compensatory Strategies (EPICS) designed to increase knowledge of strategies, reduce barriers, and improve accomplishment of meaningful leisure activities (MLA) and well-being in older adults living with frailty. Using a double-blind concurrent mixed-methods design, 36 community-dwelling older adults were assigned to the experimental (EPICS) or control (friendly visits) group through a covariate adaptive randomization. Questionnaires were administered prior to the intervention and ± two months post-intervention. Individual semi-structured interviews conducted at the end of the study furthered the authors’ understanding of the effects of the intervention. Quantitative analysis revealed significant increase in knowledge of compensatory strategies and reduction of barriers for the experimental group only. Qualitative analysis (purposive sample, n = 8) showed enhanced well-being and self-activation. Discussions about barriers to accomplishment may be sufficient to trigger self-activation in someolder adults living with frailty to improve participation in MLA and well-being.
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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 | 0.003 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".