Dementia- and mild cognitive impairment-inclusive exercise: Perceptions, experiences, and needs of community exercise providers
Bibliographic record
Abstract
PURPOSE: For persons who are at risk for, or living with, dementia exercise is recommended, yet many become or remain inactive. Exercise providers play a vital role in promoting and facilitating exercise in these groups by recognizing and being responsive to the needs of persons with mild cognitive impairment (MCI) or dementia in exercise programming. The objective of this study was to explore the experiences, perceptions, and needs of community exercise providers regarding dementia. MATERIALS & METHODS: Five focus groups were held with community exercise providers (n = 30) who deliver exercise to older adults (≥55 years) in municipal, non-profit, for profit, or academic settings. RESULTS: Three themes were developed: (1) Unique experiences and diverse perceptions: suggests unique personal experiences with MCI and dementia inform distinct perceptions of dementia; (2) Dementia-Inclusive Practices: learning as you go and adapting for the individual: reflects exercise providers' approaches to recognizing and accommodating individuals' unique abilities and preferences; (3) Training and Best Practices, with Flexibility: identifies exercise providers' desires for MCI- and dementia-specific knowledge and training strategies, which need to recognize dementia heterogeneity between and within persons over time. CONCLUSIONS: These findings highlight a willingness of exercise providers to support dementia-inclusive exercise, but recognize they have minimal training and lack educational resources to do so. Formal training resources may enhance exercise accessibility and participation for persons with MCI or 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 | 0.003 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.003 |
| 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".