Determinants and Benefits of Physical Activity Maintenance in Hospital Employees
Bibliographic record
Abstract
This study investigated whether the positive behavioral and anthropometric outcomes of a pedometer-based physical activity 8-week challenge were maintained 6 months after the end of the program. It further investigated the motivational profile of those who maintained their physical activity levels in the months following the end of the program and of those who did not. Hospital employees from a university-affiliated multisite health care center in Canada participated using a questionnaire. Of the 235 participants who completed the 8-week challenge, 157 questionnaires were returned 6 months later. Paired-samples t tests were conducted between the baseline and follow-up scores as well as between the postprogram and follow-up scores to detect significant differences between the measurement points. This study shows that the pedometer-based physical activity helped hospital employees maintain a high level of physical activity as well as maintain a healthy body mass index after 6 months. The results demonstrated that during maintenance the high physical activity group obtained higher scores for identified regulation and intrinsic regulation compared with the other groups. The results of the study revealed that identified and intrinsic regulations are important contributors to maintaining physical activity among hospital employees.
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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 | 0.003 |
| 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) | 0.001 | 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".