The Physical Activity–Related Barriers and Facilitators Perceived by Men Living in Rural Communities
Bibliographic record
Abstract
Men, especially those living in rural areas, experience chronic disease at higher rates than the general population. Physical activity is a well-established protective factor against many chronic diseases; however, only a small fraction of men are meeting national guidelines for physical activity. The purpose of this study was to examine the perceived physical activity-related barriers and facilitators experienced by men living in rural areas in Canada. Participants completed a paper-and-pencil or online survey and asked to select personally relevant physical activity-related barriers and facilitators from a list of 9 and 10 choices, respectively. A total of 149 men completed the survey (50.3% between the ages of 18 and 55 years; 43.0% older than 55 years). Participants were predominantly from rural areas and smaller communities. Overall, the response options "I'm too tired," "I don't have enough time," and "I think I get enough exercise as work" were the three most frequently cited barriers to regular physical activity. The response options "Personal motivation to be healthy," "I enjoy it," and "Support from family and/or friends" were the three most often cited facilitators to physical activity. Results are similar to those shown in other populations. Results can be used to inform the development of policies and programs that aim to increase the physical activity levels of men living in rural areas and small communities.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".