Individual, social, environmental, and physical environmental correlates with physical activity among Canadians: a cross-sectional study
Bibliographic record
Abstract
BACKGROUND: The identification of various individual, social and physical environmental factors affecting physical activity (PA) behavior in Canada can help in the development of more tailored intervention strategies for promoting higher PA levels in Canada. This study examined the influences of various individual, social and physical environmental factors on PA participation by gender, age and socioeconomic status, using data from the 2002 nationwide survey of the Physical Activity Monitor. METHODS: In 2002, 5,167 Canadians aged 15-79 years, selected by random-digit dialling from household-based telephone exchanges, completed a telephone survey. The short version of the International Physical Activity Questionnaire was used to collect information on total physical activity. The effects of socio-economical status, self-rated health, self-efficacy, intention, perceived barriers to PA, health benefits of PA, social support, and facility availability on PA level were examined by multiple logistic regression analyses. RESULTS: Self-efficacy and intention were the strongest correlates and had the greatest effect on PA. Family income, self-rated health and perceived barriers were also consistently associated with PA. The effects of the perceived health benefits, education and family income were more salient to older people, whereas the influence of education was more important to women and the influence of perceived barriers was more salient to women and younger people. Facility availability was more strongly associated with PA among people with a university degree than among people with a lower education level. However, social support was not significantly related to PA in any subgroup. CONCLUSION: This study suggests that PA promotion strategies should be tailored to enhance people's confidence to engage in PA, motivate people to be more active, educate people on PA's health benefits and reduce barriers, as well as target different factors for men and women and for differing socio-economic and demographic groups.
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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 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.005 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| 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".