Evidence-based practice in Therapeutic Recreation : An examination of clinical decision-making in mental health
Bibliographic record
Abstract
There are repeated calls for evidence-based practice (EBP) in therapeutic recreation (TR) as a means to improve client outcomes, ensure consistency and communication among professionals, create protocols and criteria for client assessments, and increase recreation therapists' (RTs) research capacity. The purpose of this study was to understand what influences RTs' clinical decision-making in a mental health setting. A qualitative research approach with ethnographic techniques was used. The study consisted of two phases: journaling and a focus group. A systematic, inductive approach guided analysis of the data from 10 RTs located in different workplaces within one Canadian health region. Findings suggested that while RTs had a common practice philosophy, their use of research evidence in decision-making was limited. A lack of infrastructure supporting service provision including minimal clinical leadership, few opportunities for mentorship, and contextual factors such as limited resources influenced clinical decision-making. Implications for research and practice are provided.
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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 | 0.233 | 0.384 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.008 | 0.008 |
| Science and technology studies | 0.008 | 0.022 |
| Scholarly communication | 0.019 | 0.009 |
| Open science | 0.004 | 0.012 |
| Research integrity | 0.004 | 0.006 |
| Insufficient payload (model declined to judge) | 0.002 | 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".