A clinical exploration of the Process of Transformation Model with rehabilitation therapists
Bibliographic record
Abstract
Background/Aims: Clients in rehabilitation services often undergo a process of personal change following a diagnosis of a chronic illness or a traumatic accident. One of the changes they experience could be that of a change in their meaning perspectives – that is, their beliefs, values, feelings, and attitudes towards their illness, their new life, and themselves. The Process of Transformation Model was developed through a metasynthesis of studies that relate to this transformation from clients' perspectives. Methods: To study the model from therapists' perspectives, a qualitative exploratory study was conducted with four expert rehabilitation therapists. Using focus groups and participant diaries, participants provided insights and interpretation of the model in their practice. Data collection and analysis was conducted concurrently. Results: Therapists are able to recognise clients in the initial trigger phase. They are also able to recognise certain outcomes of change; however, they have difficulty identifying the complex internal meaning perspectives' transformations that occur during the changing phase. Conclusions: While clients experience these critical reflective phases throughout their rehabilitation, therapists are relatively unaware of them. By recognising what phase their clients could be in, therapists would be prepared to adapt to their clients' needs and develop therapy plans accordingly, including providing patient education.
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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 | 0.038 | 0.035 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.006 | 0.018 |
| Scholarly communication | 0.011 | 0.014 |
| Open science | 0.003 | 0.010 |
| Research integrity | 0.003 | 0.005 |
| Insufficient payload (model declined to judge) | 0.004 | 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".