Abstract 13362: Socio-ecological Variables Influenced Moderate-to-vigorous Intensity Physical Activity Levels Amongst Hospital-based Nurses: A Multi-site Study
Bibliographic record
Abstract
Introduction: Previous research has shown that nurses are not meeting recommended moderate-to-vigorous intensity PA (MVPA) guidelines (≥150 minutes/week) for optimal cardiovascular disease risk reduction. Socio-ecological approaches have been used to explore the determinants of PA levels. We examined personal, social and environmental factors associated with the MVPA levels of Canadian nurses. Methods: Secondary analysis of data from a multi-site cross-sectional study was undertaken. Nurses were recruited from 14 hospitals in Ontario, Canada. An accelerometer (ActiGraph GT3X) was used to measure MVPA levels (minutes/day). Socio-ecological variables were derived from sociodemographic, anthropometric and cardiometabolic data, and questionnaires assessing determinants of PA (Table 1). Multivariate generalized estimating equations (GEE) were used to explore associations between socio-ecological variables and MVPA levels while accounting for hospital sites. Variables were selected for multivariate analyses if they were significant ( p <0.05) in univariate analyses. Results: A total of 257 nurses (42±12 years) had complete accelerometer (≥10 hours of wear time for ≥4 days) and questionnaire data. Of these nurses, 54% were overweight/obese and 6% were smokers. Multivariate analyses showed positive associations between MVPA levels and high perceived capability to exercise despite common barriers (e.g. poor weather; β=0.13, p =0.02) and feeling connected to their exercise peers (β=1.34, p =0.01). Greater shiftwork associated daytime sleepiness and/or insomnia were inversely associated with MVPA levels (β=-4.87, p <0.01). Conclusion: Future endeavors to accentuate nurses’ PA levels should address modifiable socio-ecological variables such as encouraging exercise despite common barriers, and with peers to whom they feel connected. Nurses should consider increasing time spent engaging in MVPA to minimize the negative effects of shiftwork.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| 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".