Client Adherence with Home Programs after Discharge from a Campus-Based Occupational Therapy Adult Clinic
Bibliographic record
Abstract
This retrospective, descriptive study used the Ecological Model of Adherence to examine how client, provider, intervention, and contextual factors are associated with client adherence with home programs, two months after discharge from a campus-based occupational therapy clinic. Twelve participants (M = 60.67 years, SD = 13.68, range: 30-78 years) were interviewed and occupational therapy clinic records were reviewed. The reported rate of adherence with home programs was 25% (n = 4). Point-biserial correlations and Phi coefficient cross-tabulations were calculated between 10 variables and client-reported adherence with home programs, two of which were high, positive, and statistically significant: the correlations between client-reported adherence and the inclusion of client-identified occupational performance problems in the home program (rj(1) = .63, p = .028) and the time required to perform the home program (rj(1) = .82, p = .017). These findings suggest that home programs that explicitly included clients’ occupational performance problems and required a greater investment of time were strongly associated with higher levels of adherence, two months after discharge. Results should be interpreted with caution due to the low power of the study. Although the results of this study did not demonstrate sufficient support for the Ecological Model of Adherence, further investigation of the mechanisms that influence client adherence with home programs could improve occupational therapists’ understanding of these factors.
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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 | 0.002 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".