Assessing the social climate of physical (in)activity in Canada
Bibliographic record
Abstract
BACKGROUND: Ecological models suggest that a strategy for increasing physical activity participation within a population is to reconstruct the "social climate". This can be accomplished through 1) changing norms and beliefs, 2) providing direct support for modifying environments, and 3) implementing policies to encourage physical activity. Nevertheless, surveillance efforts have paid limited attention to empirical assessment of social climate. This study responds to this gap by assessing the social climate of physical activity in Canada. METHODS: = 49.1 ± 16.3 years) completed an online survey asking them to assess social climate dimensions including social norms of physical (in)activity, perceptions of who causes physical inactivity and who is responsible for solving physical inactivity, and support for physical activity-related policy. Descriptive statistics (frequencies) were calculated. Multinomial logistic regressions were constructed to identify whether demographic variables and physical activity participation associated with social climate dimensions. RESULTS: Physical inactivity was considered a serious public health concern by 55% of the respondents; similar to unhealthy diets (58%) and tobacco use (57%). Thirty-nine percent of the respondents reported that they often see other people exercising. Twenty-eight percent of the sample believed that society disapproves of physical inactivity. The majority of respondents (63%) viewed the cause of physical inactivity as both an individual responsibility and other factors beyond an individuals' control. Sixty-seven percent of respondents reported physical inactivity as being both a private matter and a public health matter. Strong support existed for environmental-, individual-, and economic-level policies but much less for legislative approaches. The social climate indicators were associated with respondents' level of physical activity participation and demographic variables in expected directions. CONCLUSION: This study is the first known attempt to assess social climate at a national level, addressing an important gap in knowledge related to advocating for, and implementing population-level physical activity interventions. Future tracking will be needed to identify any temporal (in)stability of these constructs over time and to explore the relationship between physical activity participation and indicators of the national social climate of physical activity.
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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 | 0.003 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 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".