Self-determination theory in physiotherapy practice: A rapid review of randomized controlled trials and systematic reviews
Bibliographic record
Abstract
Background The self-determination theory (SDT) is a theory on motivation proposing to support needs of autonomy, competence, and relatedness to improves autonomous motivation, which leads to adherence and compliance. Little is known about how SDT-driven physiotherapy interventions are implemented. Objectives The objectives of this rapid review were to identify the type of physiotherapy contexts in which SDT is being used and describe how SDT-based physiotherapy interventions are being measured. Methods The Cochrane Rapid Review Methods was followed to synthesize evidence from systematic reviews (SR) and randomized controlled trials (RCTs) on the use of SDT-related research in physiotherapy. We conducted a search on four databases between 1990 and September 17th, 2024. Two reviewers independently screened titles and abstracts, one reviewer completed the full-text screening while another screened all excluded full-text to ensure consensus. Findings were synthesized narratively following the review objectives. Results Of 184 identified SR or RCT, we included 8 RCTs and 1 SR targeting various health conditions. Physiotherapy interventions included strength and aerobic exercise, therapeutic modalities, yoga or tai chi, virtual therapy, coaching, and equine-assisted therapy. SDT interventions included communication training, autonomy supportive feedback, education and goal setting, provision of choices, and intrinsic motivation with the use of virtual reality, robotics, circus-themed games, music, and behaviour change strategies. The impact of SDT-driven physiotherapy interventions was most assessed for physical activity levels. Conclusion Our rapid review suggests that SDT-driven physiotherapy is being used across a broad range of health conditions, using various physiotherapy and SDT principles derived from the theory.
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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 | 0.063 | 0.213 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.017 | 0.014 |
| Bibliometrics | 0.020 | 0.020 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.007 | 0.008 |
| Open science | 0.004 | 0.004 |
| Research integrity | 0.004 | 0.003 |
| Insufficient payload (model declined to judge) | 0.008 | 0.001 |
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".