Understanding physiotherapists’ perspectives on promoting adherence to exercise rehabilitation for low back pain through a SDT lens
Bibliographic record
Abstract
Low back pain is a significant problem worldwide affecting 1 in 5 adults. Exercise-based physiotherapy has been shown to be an effective treatment; however, adherence is a major challenge in this population. Using Self-Determination Theory (SDT) as a guiding framework, this study examined physiotherapists’ perspectives on factors affecting, and strategies to improve, adherence to exercise-based rehabilitation among those living with low back pain. Six semi-structured interviews with practicing physiotherapists explored the role autonomy, social relatedness, and competence play in rehabilitation. Reflexive thematic analysis revealed 338 meaning units mapping onto 34 codes under 14 main themes. Participants highlighted that autonomy, competence, and social relatedness were all important factors influencing patient adherence. In terms of strategies to improve adherence, autonomy was targeted by providing patients with choice relating to what exercises they did and when they completed them, while competence was addressed by making sure patients understood their exercises. Specific to social relatedness, it was highlighted that the rapport between providers and patients was key in promoting adherence. Further, participants agreed that while valuable, group exercise in a clinical setting is difficult to achieve. Participants reported that if strategies were effective, patients moved from introjected to identified regulatory states during the rehabilitation process. These findings suggest that SDT provides an effective framework for (a) understanding strategies clinical physiotherapists use to improve adherence to exercise-based rehabilitation among low back pain patients and (b) in shaping future rehabilitation interventions within this patient population.
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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 | 0.019 | 0.022 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.007 | 0.013 |
| Scholarly communication | 0.009 | 0.004 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.003 | 0.006 |
| 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".