‘Now I can bend and meet people virtually in my home’: The experience of a remotely supervised online chair yoga intervention and visual socialisation among older adults with dementia
Bibliographic record
Abstract
BACKGROUND: Little research has been conducted on telehealth-based interventions in older adults. There has been no study of the use of telehealth-based online chair yoga (CY) to improve physical activity and manage dementia symptoms and socialisation for older adults with dementia who are socially isolated. OBJECTIVES: The study identified benefits, challenges and facilitators in participating in remotely supervised online CY from the perspective of older adults with dementia and their caregivers, including what would help them to participate in online interventions. METHODS: In a qualitative descriptive design, four online focus groups (two pre-intervention and two post-intervention) conducted via videoconference explored the benefits, challenges and facilitators in participating in a remotely supervised twice-weekly, 8-week online CY intervention. A total of 17 participants (eight people with dementia and nine family caregivers) attended the focus groups. The data were subjected to thematic analysis. RESULTS: Thematic analysis of data identified three themes from the perspectives of older adults with dementia and their caregivers: (a) benefits (e.g. sleep and relaxation, emotional regulation, flexibility, muscle strength, convenience, caregiver-participant connection), (b) challenges (e.g. technological setup) and (c) lessons learned (e.g. inclusion of caregiver, yoga instructor, visual cues, socialisation, safety). The online intervention was beneficial to participants, who reported that they wanted to continue home-based online CY practice. CONCLUSION: Convenience was the major advantage for the participant to continue to practice online CY. The online intervention offered virtual socialisation, which could be significant for motivating older adults to continue the CY program. IMPLICATIONS FOR PRACTICE: Gerontological nurses could add CY as a nonpharmacological component of a treatment plan and monitor older adults' progress during the online intervention. The home-based online CY intervention should be prioritised to promote health and wellness in socially isolated older adults with dementia.
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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 | 0.012 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.006 | 0.004 |
| Scholarly communication | 0.003 | 0.004 |
| Open science | 0.002 | 0.007 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 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".