Worksite Health Promotion: The Value of the Tune Up Your Heart Program
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Successful wellness initiatives at DaimlerChrysler Canada Incorporated (DCCI) led to a unique partnership between key stakeholders that allowed implementation of Tune Up Your Heart, a program aimed at improving workforce cardiovascular disease (CVD) risk. Volunteers were screened and stratified according to their CVD risk. Interventions were tailored to risk level and included goal setting, monitoring progress, and company-wide education programs. Outcome data (CVD risk and components of risk) were collected at study entry and after 18 months. The economic impact of the program was determined using a model based on subject movement across risk categories and historical claims data for life insurance, short- and long-term disability, prescription drugs, and casual absenteeism. Intervention participants (N = 343) demonstrated a significant (P = .0113) relative CVD risk reduction of 12.7%; 36% of participants lost weight, and average body mass index decreased from 28.4 to 28.2 (P = .0419). Average systolic and diastolic blood pressure significantly decreased (P < .0001 and P = .0221, respectively). Subjects reported increased adherence to recommended exercise and diet regimens, and the number of smokers decreased by 14%. The majority of subjects reported satisfaction with the program. Annual savings were estimated at Can$793 for the intervention group and Can$18,461 when projected to the entire workforce (N = 13,629). Savings were sensitive to cost weighting when subjects moved to a lower risk class but more robust to other parameters. The Tune Up Your Heart program significantly improved employee CVD risk profile, and was associated with savings for DCCI.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.004 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.003 | 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 it