The cost-effectiveness of a back education program for firefighters: a case study.
Bibliographic record
Abstract
SUMMARY OF BACKGROUND DATA: Low Back Pain (LBP) is one of the most common causes of disability in the working population, and its impact on industry is enormous. The high financial costs of LBP and its apparent relationship with working conditions have led to efforts to prevent this condition. Several reviews have suggested that there is considerable potential for multimodal preventive interventions to cost-effectively reduce the overall burden of illness. OBJECTIVES: The objectives of this study were to assess the feasibility of implementing a multi-faceted back injury prevention program in the community, and to assess the effectiveness of this program. STUDY DESIGN: A case study involving 92 firefighters from a suburb north of Toronto, Ontario, Canada. METHODS: A back education program, called the Back Informed Program, was conducted on-site by a trained chiropractor. It offered employees job-specific education, ergonomic advice, exercises and pain management, as well as hands-on practice sessions. Data on absenteeism due to back injury, and cost of lost work days due to back injury were collected between January 1995 and December 1996. Data were compared to a municipality that received no such program during the same time period. Secondary outcomes, including information attained among the workers were qualitatively assessed. Absenteeism and financial data were used to demonstrate the potential efficacy of such a program. RESULTS: The results showed a significant decrease in the number of days lost due to back injuries in the year following implementation of the program. Upon implementation of the Back Informed program, there was a reduction of 72.4% in days lost reported over the two year period of program implementation. The rate of days lost per worker was 0.64 prior to program implementation and dropped to 0.13 two years later. This resulted in substantial cost-savings in both direct and indirect costs to the municipality. CONCLUSIONS: This study suggests that a multi-faceted, occupation-specific back education program may help reduce back injuries and reduce injury-related costs.
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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 | 0.002 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 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".