Environmental and psychosocial correlates of objectively measured physical activity among older adults.
Bibliographic record
Abstract
OBJECTIVE: Neighborhood environments can support or hinder physical activity especially as health declines with age. This study puts psychological theories of health behavior change in context with built environment research to better understand the interplay of environmental and psychosocial characteristics impacting older adults' sedentary behavior and physical activity. METHOD: The Active Streets, Active People study recruited 193 older adults living in a highly walkable neighborhood in Vancouver, British Columbia, Canada. Participants completed questionnaires on attitudes toward walking, behavioral control for walking, and perceived built environment variables. To assess behavior, participants wore an ActiGraph GT3X + accelerometer for 7 consecutive days. Regression-based path analysis was conducted to examine whether the link between the perceived environment and behavior is mediated by psychosocial variables. RESULTS: In total, 174 participants had valid accelerometry data (Mage = 70.3, SD = 7.2) and demonstrated a daily average of 525.7 min of sedentary behavior (SD = 65.1) as well as high levels of total physical activity (M = 254.3, SD = 65.1 min/day). Mediation analysis revealed that perceived street connectivity and diversity of land use were negatively related to sedentary behavior, but only indirectly through behavioral control. Similarly, effects of street connectivity and diversity of land use on physical activity were mediated by behavioral control. CONCLUSIONS: Results highlighted that the perceived built environment is important for physical activity and sedentary behavior, largely because these environmental perceptions are positively linked to older adults' confidence in walking. By integrating environmental and psychosocial correlates of preventive health behaviors within a theoretical structure, the psychosocial mechanisms through which the environment affects activity can be better understood. (PsycINFO Database Record
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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 | 0.000 | 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) | 0.001 | 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".