The impacts of dance/movement therapy on dementia caregivers’ burden and resilience: A mixed-methods exploration
Why this work is in the frame
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Bibliographic record
Abstract
Many interventions have been explored which aim to support dementia caregivers. However, the traditional approaches focus on cognitive strategies to reduce negative psychological outcomes (e.g., burden). Presently, there is a lack of strengths-based programs designed to enhance positive aspects of caregiver health. Although the benefits of dance/movement therapy (DMT) have been shown with other populations, it is underexplored for caregivers apart from their loved one with dementia. For the current study, ten women participated in the first DMT program for dementia caregivers, which was evaluated with a convergent mixed-methods design. Caregiver burden and resilience was assessed at baseline and follow-up, and therapeutic factors of DMT were assessed at three time points immediately following DMT (week 3, 4, and 5). Quantitative analyses showed that caregiving burden was significantly reduced, and resilience did increase, but not significantly. Qualitative findings from journal entries and semi-structured interviews revealed that DMT enhanced coping through bolstering resilience factors such as self-efficacy and cognitive reframing. Together, these findings suggest that DMT shows promise as an intervention which can meaningfully decrease burden and enhance resilience factors for caregivers. More research is needed which measures outcomes and mechanisms of DMT for caregivers in the context of dementia care. • This study describes a novel DMT intervention for informal dementia caregivers. • The impacts of the intervention were explored with a mixed-methods approach. • Participants’ caregiving burden significantly decreased after the DMT program. • Qualitative findings revealed that DMT enhanced coping and resilience factors.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it