Mental Health and Wellbeing Helplines for Farmers: A Scoping Review of Usage, Acceptability, and Effectiveness of Those Currently in Operation Around the World
Bibliographic record
Abstract
OBJECTIVES: Farmers have higher risk of suicide than the general working population but are less likely to seek help from mainstream mental health services. Farmer-focused sources of support such as farmer helplines may be a viable alternative, and several currently operate internationally. However, it is unclear whether these specialized helplines collectively tend to be used and are acceptable or effective in reducing farmers' distress. This review aimed to fill this important knowledge gap. METHODS: The PRISMA 2020 guidelines, in consultation with the extension for scoping reviews, guided the review process. The search included 13 academic databases and grey literature via Google. RESULTS: The database search yielded 1,337 initial results and a Google search strategy resulted in 620 links to investigate. Data extraction was sought from 28 papers and 332 online links. We identified 35 unique helplines operating across Canada, the United States, the United Kingdom, Ireland, Australia, India, and Austria. Farmers do use helplines when experiencing stress; however, we found little empirical evidence of the acceptability or effectiveness of helplines. Anecdotal evidence suggested farmers are more likely to trust telephone support services operated by people who understand the farming way of life. CONCLUSION: Research in this area is scant but promising. Farmers and farming communities will use farmer helplines in times of elevated stress. However, there is a pressing need for more rigorous evaluation studies to determine their effectiveness in this at-risk group. Further, when designing farmer helplines, careful consideration should be given to the extent to which those answering calls understand farming.
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How this classification was reachedexpand
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 | 0.003 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".