Adapting Dance to Complex Clinical Contexts: A Methodology Model
Bibliographic record
Abstract
BACKGROUND: While the content of health-related dance interventions is still relatively undocumented in the literature, the processes of adapting dance to specific situations are even less so, and rarely seem to be based on theoretical or practical guidelines. Yet the description of these processes could guide the adaptation of other interventions. PURPOSE: This study aimed to document the process of adapting a dance intervention in a complex clinical setting, in order to propose a methodology that could inspire the development of other interventions in specific clinical contexts. METHODS: The adaptation methodology described in this article is part of an embedded single-case study, where the case unit was the adaptation process of a dance group intervention and the subunits of analysis were the intervention's clinical and theoretical premises, content, and pedagogy. Participants were rehabilitation therapists (n=21), patients (n=6), relatives (n=4), and rehabilitation assistants (n=4). Data were collected through various techniques (focus groups, situational observation, pilot dance sessions, interviews, critical incidents, research journals, template for intervention description and replication/TIDieR checklist, and video recordings) to allow an iterative adaptation process. Data were analyzed using inductive qualitative analysis. RESULTS: Adaptations were made prior to and throughout the intervention, taking into account relevant scientific and disciplinary knowledge, as well as the different actors' implicit and explicit experiences. The intervention pedagogy focused on adapting the dance content to meet the participants' needs while inviting them to self-adapt this content. The resulting methodology model includes four stages: preliminary design, validation with rehabilitation therapists, specific tailoring, and ongoing tailoring. Conclusion: Optimizing the adaptation of dance and ensuring its complementarity within a complex clinical context requires collaboration with the different disciplinary clinicians in order to offer synergistic coherence and ensure dance's contribution to therapeutic objectives.
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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 | 0.052 | 0.038 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.005 | 0.004 |
| Science and technology studies | 0.003 | 0.008 |
| Scholarly communication | 0.007 | 0.006 |
| Open science | 0.005 | 0.004 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".