Work-related factors predict changes in physical activity among nurses participating in a web-based worksite intervention: A randomized controlled trial
Bibliographic record
Abstract
BACKGROUND: Despite the numerous benefits associated with physical activity (PA), most nurses are not active enough and few interventions have been developed to promote PA among nurses. A secondary analysis of raw data from a single-centre, three-arm parallel-group randomized controlled trial was conducted to assess whether work-related characteristics and general mood states predict changes in total weekly moderate-to-vigorous intensity PA (MVPA) and average daily step-count among nurses participating in a 6-week web-based worksite intervention. METHODS: : 46.1 ± 11.2 years) were randomized to an individual-, friend-, or team-based PA challenge. Participants completed questionnaires pre- and post-intervention assessing work-related characteristics (i.e., shift schedule and length, number of hours worked per week, work role) and general mood states (i.e., tension, depression, anger, confusion, fatigue, vigour). Participants received a PA monitor to wear before and during the 6-week PA challenge, which was used to assess total weekly MVPA minutes and average daily step-count. Data were analyzed descriptively and using multilevel modeling for repeated measures. RESULTS: Change in total weekly MVPA minutes, but not change in average daily step-count, was predicted by shift schedule (rotating vs. fixed) by time (estimate = - 17.43, SE = 6.18, p = .006), and work role (clinical-only vs. other) by time (estimate = 18.98, SE = 6.51, p = .005). General mood states did not predict change in MVPA or change in average daily step-count. CONCLUSIONS: Given that nurses who work rotating shifts and perform clinical work showed smaller improvements in MVPA, it may be necessary to consider work-related factors/barriers (e.g., time constraints, fatigue) and collaborate with nurses when designing and implementing MVPA interventions in the workplace. TRIAL REGISTRATION: ClinicalTrials.gov: NCT04524572 . August 24, 2020. This trial was registered retrospectively. This study adheres to the CONSORT 2010 statement guidelines.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.000 | 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 | 0.001 |
| 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".