A Prospective Programmatic Cost Analysis of Fuel Your Life
Bibliographic record
Abstract
OBJECTIVE: An accounting of the resources necessary for implementation of efficacious programs is important for economic evaluations and dissemination. METHODS: A programmatic costs analysis was conducted prospectively in conjunction with an efficacy trial of Fuel Your Life (FYL), a worksite translation of the Diabetes Prevention Program. FYL was implemented through three different modalities, Group, Phone, and Self-study, using a micro-costing approach from both the employer and societal perspectives. RESULTS: The Phone modality was the most costly at $354.6 per participant, compared with $154.6 and $75.5 for the Group and Self-study modalities, respectively. With the inclusion of participant-related costs, the Phone modality was still more expensive than the Group modality but with a smaller incremental difference ($461.4 vs $368.1). CONCLUSIONS: This level of cost-related detail for a preventive intervention is rare, and our analysis can aid in the transparency of future economic evaluations.
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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 | 0.014 | 0.037 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".