A clinical reasoning model focused on clients’ behaviour change with reference to physiotherapists: its multiphase development and validation
Bibliographic record
Abstract
BACKGROUND AND PURPOSE: A biopsychosocial approach and behaviour change strategies have long been proposed to serve as a basis for addressing current multifaceted health problems. This emphasis has implications for clinical reasoning of health professionals. This study's aim was to develop and validate a conceptual model to guide physiotherapists' clinical reasoning focused on clients' behaviour change. METHODS: Phase 1 consisted of the exploration of existing research and the research team's experiences and knowledge. Phases 2a and 2b consisted of validation and refinement of the model based on input from physiotherapy students in two focus groups (n = 5 per group) and from experts in behavioural medicine (n = 9). RESULTS: Phase 1 generated theoretical and evidence bases for the first version of a model. Phases 2a and 2b established the validity and value of the model. The final model described clinical reasoning focused on clients' behaviour change as a cognitive, reflective, collaborative and iterative process with multiple interrelated levels that included input from the client and physiotherapist, a functional behavioural analysis of the activity-related target behaviour and the selection of strategies for behaviour change. CONCLUSIONS: This unique model, theory- and evidence-informed, has been developed to help physiotherapists to apply clinical reasoning systematically in the process of behaviour change with their clients.
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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 | 0.043 | 0.076 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.003 |
| Bibliometrics | 0.004 | 0.002 |
| Science and technology studies | 0.003 | 0.005 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.004 | 0.003 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 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".