Working alliance development in occupational therapy: A cross‐case analysis
Bibliographic record
Abstract
BACKGROUND: Despite reverence afforded the therapeutic relationship construct in occupational therapy, many occupational therapists feel ill equipped to use themselves therapeutically to enhance the relationship with their clients. Furthermore, although occupational therapists often link the strength of the therapeutic relationship to therapy outcomes, related occupational therapy specific research has been limited. According to the psychotherapy literature, the working alliance is one element of the therapeutic relationship which has in fact been linked to therapy outcomes. METHODS: A mixed-methods, prospective, multiple case study approach was used to compare the experiences of the working alliance by both occupational therapists and clients across four therapeutic dyads. RESULTS: Several key elements were identified in this study's qualitative data as shaping the process of alliance development in occupational therapy including: the fostering of an interpersonal connection; the use of humour as therapeutic modality; an impetus to act that leads to functional enhancements; a shared sense of success and a positive feedback mechanism created through successfully attaining clearly delineated, client-centred therapy goals. CONCLUSIONS: By considering these identified elements, occupational therapists may focus upon tangible considerations towards enhanced therapeutic use-of-self in the development of sound working alliance with their clients potentially improving therapy outcomes.
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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 | 0.008 | 0.016 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.005 | 0.002 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.002 | 0.002 |
| 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 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".