‘Unalloyed, Uncomplicated Joy’: A Qualitative Study to Understand Dementia Care Partners’ Experiences of Dance/Movement Therapy
Bibliographic record
Abstract
Care partners who have a loved one living with dementia are at risk for psychological distress and burden. As a result, a variety of programs to support dementia care partners have been designed, but dance/movement therapy (DMT) remains underexplored for care partner well-being. As such, the purpose of this study was to understand the experience of a novel DMT intervention designed to promote resilience among carers. Semi-structured interviews were conducted with 9 female care partners who took part in a pilot study. Reflective journals and interviews were transcribed and then thematically analyzed with an inductive approach. Three themes emerged pertaining to participants’ experiences of the DMT program. Holistic engagement theme emphasized the powerful impact which the body-mind approach of had for carers, above and beyond verbal therapy. Liberation theme highlighted how beneficial movement was to enable carers to feel “free” to express themselves. Connection to others theme demonstrated the impact of movement to foster supportive relationships between carers. Participants suggested that future iterations of this program should have more sessions with time to process DMT activities in-depth. Overall, results suggest that DMT is a promising approach to support care partner well-being holistically, by providing creative opportunities for them to move, process, and connect. These findings can be built upon in future creative-arts therapy interventions for care partners.
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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 | 0.013 | 0.019 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.013 | 0.012 |
| Scholarly communication | 0.005 | 0.005 |
| Open science | 0.003 | 0.008 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.004 | 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".