An Outdoor Walking Program for Immigrant Muslim Older Adults: A Community‐Based Participatory Intervention
Bibliographic record
Abstract
AIM: To explore Muslim immigrant older adults' experiences of a modified community-based outdoor walking program and identify factors that facilitate or hinder program acceptance and participation. DESIGN: An exploratory qualitative description single-group pilot study was designed and implemented in three phases: (1) pre-intervention focus group interviews; (2) intervention implementation with tracking of physical activity levels using personal activity monitors; and (3) postintervention individual interviews. METHODS: Participants were recruited using a convenience sampling strategy in a mosque in Edmonton, Canada, in June 2019. After focus group discussions with participants, walking sessions were conducted for 10 weeks in a local accessible park with required amenities such as benches and restrooms. A fitness instructor delivered the weekly program that was followed by individual semistructured interviews to explore participants' satisfaction and program acceptance. Content analysis was used for qualitative data and sociodemographic, health and physical activity level (via step counts) data was documented for all participants. RESULTS: Thirteen participants with a mean age of 66.9 years completed the program. The majority of participants led a sedentary lifestyle. Participants identified three motivators that increased program satisfaction, which were socialising with peers, having a fitness instructor, and using Fitbit activity trackers. Difficulties with transportation and lack of appropriate educational components were areas for improvement that could enhance acceptability of the program. CONCLUSIONS: This study suggests that early incorporation of older immigrants' preferences increases acceptance of physical activity programs. IMPLICATIONS: Nurses' engaging in healthy lifestyle support for older immigrants can identify the influences on positive uptake of physical activity programs in this population. IMPACT: Immigrant Muslim older adults lack access to evidence-based physical activity programming that meets their cultural and religious preferences. This study provides some insights into ways to engage this population in similar programs. PATIENT OR PUBLIC CONTRIBUTION: Community-dwelling older adults who participated in this study completed focus groups and interviews and engaged in the 10-week pilot intervention. Their input informed the modifications to the intervention.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".