Factors Associated With the Intention to Begin Physical Activity Among Inactive Middle-Aged and Older Adults
Bibliographic record
Abstract
Factors that affect physical activity (PA) behavior change are well established. Behavioral intention is a strong psychological predictor of behavior; however, there is less research on the factors that affect the intention to increase PA participation specifically, especially among adults in mid and later life who are inactive. Using data from the Canadian Community Health Survey, which was informed by the transtheoretical model (TTM), this study investigated the relationships between a range of demographic and biopsychosocial factors with the intention to become physically active among 1,159 inactive adults aged 40 years and older. Comparisons were made between participants reporting the intention to begin PA in the next 30 days (TTM Preparation; n = 610), 6 months (TTM Contemplation; n = 216), or not at all (TTM Precontemplation; n = 333). First, multinomial logistic regression identified age, sex, ethnicity, education, restriction of activities, self-perceived health, and community belonging as factors significantly associated with 30-day PA intention, while age and ethnicity were significantly associated with 6-month PA intention, compared with those reporting no intention. Second, binary logistic regression revealed that education was the only factor that differentially associated with intention timeframe as participants with lower levels of education were less likely to report PA intention in 30 days compared with 6 months. Findings demonstrate key demographic, biopsychosocial, and temporal factors that warrant consideration for tailored PA promotion programs that aim to effectively address the constraints and barriers that negatively influence PA intention among middle-aged and older adults.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".