Physiotherapists supporting self-management through health coaching: a mixed methods program evaluation
Bibliographic record
Abstract
PURPOSE: To evaluate a program in support of chronic disease self-management (CDSM) that is founded on a health coaching (HC) approach, includes supervised exercise and mindfulness-based stress reduction components and is delivered within a private practice physiotherapy setting. METHODS: An explanatory mixed method design, framed by theory-based program evaluation, was employed to evaluate an eight-week group-based program. Standardized self-rated and performance measures were evaluated pre- and post intervention. Additionally, participant focus groups were conducted following the intervention period. An inductive thematic approach was undertaken to analyze the qualitative data. FINDINGS: Seventeen participants (N = 17) completed the study. Improvements were seen in both self-report and performance outcomes. Participants explained how and why they felt the program was beneficial. Six themes were generated: (1) group dynamic; (2) learning versus doing; (3) holism and comprehensive care; (4) self-efficacy and empowerment; (5) previous solutions versus new management strategies; and (6) healthcare provider support. CONCLUSIONS: This study established that a group program in support of CDSM founded on a HC approach demonstrated potential value from participants as well as favorable outcomes. A pragmatic randomized control trial is required to determine efficacy of this intervention.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.011 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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 teacher head, 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".