Workplace health promotion through health coaching on styrian farms: outcomes from project evaluation
Bibliographic record
Abstract
Farmers and their families are at risk for health stressors related to working and living conditions on farms. Since Ottawa 1986, Workplace Health Promotion (WHP) aims to enhance health and well-being at work by improving the working environment. WHP is less implemented and evaluated on farms in Austria. In 2015 health coaching as a method of WHP was conducted and evaluated on 13 farms (49 participants; time period of coaching: 1 year) in Styria to facilitate the initiation of WHP on farms. Questions were: What are health topics for farmers? Does health coaching support sustainable integration of WHP on farms? A mixed-methods approach was used for qualitative and quantitative evaluation. 67 reflection sheets of health coaching sessions, two focus group discussions with project team members, 10 interviews and 58 Recovery-Stress-Questionnaires (31 at project start; 27 at project end) with farmers were analysed. Main health topics are: structure of farming families, conflicts between generations, time management, organisation of work and recovery-time, working environment and equipment, financial pressure, qualification and future perspectives. Farmers and health coaches report positive impact of health coaching related to raised awareness, changed mind-sets and gained methods on how to shape working environment. Results from Recovery-Stress-Questionnaire show no differences between stress figures at project start and end. Recovery figures are slight better after project duration. Health coaching is solution-oriented, if participants are able to think innovative and appreciate each other. Negative impacts on coaching are lack of time and calm as well as conflicts within the family and financial pressure. Participating farmers can be seen as role models for future approaches and need to be advised further on. Sustainable WHP on farms requires a strategy, supporting structures in public insurance companies and allocation of financial and personal resources. Key messages: Health coaching is a method to raise awareness, change mind-sets of farmers and show up ways to improve the working environment on farms Workplace health promotion on farms requires a strategy for holistic health promotion, supporting structures in public insurance companies and allocation of financial and personal resources
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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 | 0.020 | 0.017 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".