Selected Barriers and Incentives for Worksite Health Promotion Services and Policies
Bibliographic record
Abstract
PURPOSE: To assess employees'attitudes toward potential barriers to and incentives for their likely use of worksite health promotion services. METHODS: Data from the 2004 HealthStyles Survey, a volunteer mail survey, were used to examine selected barriers to, incentives for, and potential use of worksite health promotion programs among adults employed full-time or part-time outside the home (n = 2337). RESULTS: Respondents were 72.7% white and 52.1 % female; 36.5 % were college graduates, 30.7% had a body mass index of at least 30, and 35.6% were regularly active. The most common reported barriers to use of worksite services were no time during the workday (42.5 %) and no time before or after work (39.4%). More than 70% of employees responded that the following incentives would promote their interest in participating in a free worksite wellness program: convenient time, convenient location, and employer-provided paid time off during the workday. Preferred health promotion services reported by respondents were fitness centers (80.6%), weight loss programs (67.1 %), and on-site exercise classes (55.2 %). Policy practices of paid time to exercise at work and healthy vending or cafeteria food choices were preferred by almost 80% of employees. CONCLUSIONS: These HealthStyles Survey data, in combination with needs data from an employer's own workforce, may help employers design wellness programs to include features that attract 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 | 0.013 | 0.034 |
| 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 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".