Understanding barriers and facilitators of exercise adherence after total-knee arthroplasty
Bibliographic record
Abstract
PURPOSE: The purpose of this qualitative study is to understand the perceived patient barriers and facilitators of post-surgical exercise adherence in patients undergoing TKA. MATERIAL AND METHODS: We used an interpretive description approach. Data was gathered using semi-structured qualitative interviews. Participants were interviewed at 8 weeks post-operatively to capture physical, psychological, social and contextual changes and information. Topics that were explored included participants' experience with physical activity and exercise, motivation to perform physical activity, beliefs that exercise will reduce pain, factors that limit their ability to engage in exercise, and the importance of self-regulation in exercise adherence. RESULTS: This study identified 4 themes within the WHO adherence framework: patient-related factors, condition-related factors, health care system, and social support. In particular, self-regulation, knowledge of exercise, post-operative complications, comorbidities, social support, and lack of guidance from health care providers were identified as personal and environmental characteristics that influence exercise adherence. CONCLUSION: Exercise adherence is a multidimensional, interconnected construct and future research should focus on understanding the factors, particularly health care system, that impact adherence.IMPLICATIONS FOR REHABILITATIONRehabilitation therapists should aim to foster competence and confidence in post-operative rehabilitation by implementing strategies such as positive-reinforcement, goal setting, and increased education regarding the benefits of exercise.Clinical strategies to improve exercise adherence should be implemented both pre-and-post-operatively.Health care providers should clearly discuss post-operative outcomes and expectations (e.g., complications, etc.) with patients prior to surgery.
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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 | 0.011 | 0.024 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.003 | 0.003 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".