Motivation, Satisfaction and Perceived Benefits of Volunteering With the Cardiovascular Health Awareness Program (CHAP): A Survey of French-speaking Volunteers in Quebec
Bibliographic record
Abstract
Abstract Background: Locally recruited and trained volunteers are a vital component of the Cardiovascular Health Awareness Program (CHAP), a community-based cardiovascular disease prevention program that has been implemented across different settings and targeting different populations. As part of expanding and adapting CHAP to new settings, we conducted a pragmatic cluster randomized controlled trial to implement CHAP targeting elderly residents of subsidized social housing buildings in Québec and Ontario. As there is some evidence that the culture of volunteering might be different for English-speakers than their French-speaking counterparts, our objective was to generate a profile of French-speaking CHAP volunteers and to compare it with English-speaking volunteers in Ontario who participated in an earlier community-based CHAP program and with volunteers in Canada as reported in the Statistics Canada's General Social Survey on Giving, Volunteering and Participating (CSGVP). Methods: A cross-sectional survey was administered online or by telephone to volunteers who participated in at least one CHAP session held in subsidized social housing in Montérégie (Québec, Canada) between March 2018 and June 2019. Results: The response rate was 79% (30/38), majority were female (87%, 26/30), retired or semi-retired (83%; 25/30), almost two-thirds (63%, 19/30) had previous work experience in the healthcare field, and 40% (12/30) had more than 10 years of volunteering experience. These characteristics were similar both to those of general profile of volunteers in Canada and to English-speaking volunteers in Ontario who participated in an earlier pharmacy-based CHAP program. The top 5 reasons for volunteering among French-speaking CHAP volunteers were identical to those reported in CSGVP: making a contribution to the community; using one’s skills and experience; improving one’s sense of well-being or health; exploring one’s own strengths; and networking with or meeting people. The majority of French-speaking CHAP volunteers, like their English counterparts in Ontario, reported a high level of satisfaction with their participation in the program, enjoyed their interaction with participants, and gained new knowledge. Conclusions: French-speaking CHAP volunteers in Quebec share many similarities with English-speaking CHAP volunteers in Ontario and volunteers in Canada in terms of background, motivation, satisfaction and perceived benefits of volunteering.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 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".