The Role of Theory in Increasing Adherence to Prescribed Practice
Bibliographic record
Abstract
PURPOSE: The purpose of this article is to apply theoretical frameworks to adherence behaviour and to guide the development of an intervention to increase adherence to prescribed home programmes. SUMMARY OF KEY POINTS: Delivering an effective intervention requires establishing one that is evidence based and of adequate dosage. Two-thirds of patients who receive home exercise prescriptions do not adhere to their home programme, which may contribute to their physiotherapy's being ineffective. The mediating concepts of self-efficacy (SE) and outcome expectations (OE) are common to the five relevant theories used to explain adherence to exercise: the health belief model, protection motivation theory, theory of reasoned action, theory of planned behaviour, and social cognitive theory. CONCLUSION/RECOMMENDATIONS: Few intervention studies with any theoretical underpinning have examined adherence to exercise. Even fewer have been designed to affect and measure change in the theoretical mediators of SE and OE in patient populations. Physiotherapists must consider increasing adherence as a component of effective physiotherapy. Ongoing research is needed to increase our understanding of adherence to prescribed home programmes and to design interventions to affect theoretical mediators for increasing adherence.
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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 | 0.021 | 0.051 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.001 |
| Science and technology studies | 0.002 | 0.012 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.005 | 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".