Development of a KT intervention to promote the use of dance as a therapeutic modality in rehabilitation
Bibliographic record
Abstract
Background: Dance is a modality of choice in rehabilitation, because it combines the benefits of aerobic exercise with an enjoyable social activity. Despite the scientific evidence supporting the use of dance in rehabilitation, this treatment modality is rarely used in rehabilitation settings. As with other evidence-based interventions in rehabilitation, the implementation of scientific results from research to practice remains a challenge. Objective: This thesis aims to answer the following research question: What knowledge translation (KT) strategy will enable professionals working in rehabilitation to implement a specific dance intervention as a therapeutic modality? To answer this question, the two manuscripts presented in this thesis will address the following specific research objectives: 1) To determine the factors influencing the implementation of a dance intervention in a rehabilitation setting, 2) To identify the preferred format for a KT strategy based on clinicians’ perceptions of their needs for specific knowledge. Methods: Using a descriptive qualitative study design, this research project was based on the Knowledge-to-Action Process. Three focus groups were conducted with allied health-care professionals from three purposefully selected rehabilitation centers of the Centre for Interdisciplinary Research in Rehabilitation of the Greater Montreal (CRIR). Two members of the research team independently analyzed the transcripts using thematic content analysis. Results: Fourteen clinicians across three sites (six occupational therapists, six physiotherapists and two social workers) participated in this study. Four main factors supporting or limiting the implementation of a dance intervention emerged from the analysis: Clinician’s knowledge and skills, Interest towards using dance as a potential intervention and personal beliefs, Support from the organization of the institution, and Available resources. Although each site was different, the personal and organizational factors influencing the implementation of a potential dance intervention were similar for all three sites. Moreover, the participants corroborated the need for a simple and user-friendly KT strategy, designed for busy clinicians. Discrepancies were noted on which type of KT strategy would be most useful to ensure the implementation of dance interventions between sites currently using dance or those not using it. In an institution where dance was already implemented, direct mentoring was perceived as the ideal format to disseminate knowledge. In an institution where dance was not used, the best perceived format was a combination of active strategies in various formats: a web-supported platform with videos and written documentation. In all three groups, the structure of a dance class, the dance exercises and the therapists’ skills were described as important components of this multi-component tool. Conclusion: Consistent with the Knowledge-to-Action Process, this research project accomplished two actions: Assess Barriers to Knowledge Use and Adapt Knowledge to Local Context. The identification of the barriers to implement a dance intervention and the preferred format and content of KT strategy are a necessary precursor to developing effective KT strategies tailored to the need of clinicians working in rehabilitation centers. It can ultimately contribute to facilitate the implementation a dance intervention in rehabilitation settings.
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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 | 0.014 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| 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".