Mouvement de passage: Creating connections through movement among persons with dementia
Bibliographic record
Abstract
One of the challenging consequences of dementia is the change in relationships that can co-occur with the progression of this condition. Despite this well-documented change, few arts-based interventions target the relational dimension of dementia. This study aims to explore the effects of one arts-based relational intervention: a movement program designed to foster connections within a group of persons with dementia. We used ethnographic methods-including participant observations and informal interviews-to understand the relational effects of this program conducted by two dancers and a musician. The movement sessions were video recorded, and participant movement trajectories were analyzed for different ways in which they created connections. We identified two types of connections-nonreciprocal and reciprocal-and four subtypes of connections-connection to exercise/music, connection to participant, interpersonal connection, and group connection-that participants engaged in during the movement program. Despite most participants not remembering the previous movement sessions, they experienced increasing numbers of connections over the course of the program, particularly reciprocal interpersonal connections. Participants explored new forms of moving and creatively transformed the movement structures proposed by the dancers. The results demonstrate the effectiveness of this program in augmenting connections and fostering exploration and creativity in individuals with dementia, providing a template for further developments of interventions targeting the relational dimensions of dementia. This study also highlights the potential of combining ethnographic methods and video analysis to include the perspectives of persons with dementia in research.
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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 | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.005 | 0.005 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.001 | 0.001 |
| 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".