The Virtualization of a Movement and Social Group-Activity Intervention for Older Adults and Their Caregivers
Bibliographic record
Abstract
Abstract COVID-related safety concerns mandated suspension of our ongoing trial testing the effects of movement and social engagement in older adults with early-stage dementia and their caregivers (dyads). Participant vulnerability and the requirement for group social interaction complicated intervention resumption. We present results from a successful pilot to rapidly and iteratively optimize study interventions for remote delivery targeting intervention mediators (social connection, movement) based on participant feedback. Three-dyad groups (n=6 individuals) completed cycles of intervention via Zoom immediately followed by an interview with open-ended and quantitative feedback. Cycles were repeated until no new information was solicited, then repeated with new participants. Optimization revealed needs for technological support, more intensive movement, and social connection. Specifically, the inability to make eye contact, see others’ full body, and technology-associated timing asynchronies impeded social connection in the movement group. We will present practical tips for crafting remote group interventions for caregiver/person living with dementia dyads.
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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 | 0.006 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".