“The Hill in Front of You”: A Qualitative Study of the Mental Health Impact of Livestock Diseases and Depopulation on Farmers
Bibliographic record
Abstract
BACKGROUND: Livestock disease outbreaks are challenging to control and often lead to animal deaths, sometimes necessitating the mass euthanasia of an entire herd or flock, a process known as depopulation. Depopulation is essential for safeguarding animal welfare, human health, and economic stability, as well as preventing the further spread of disease. While significant advancements have been made in the surveillance, detection, and disposal of affected farm animals, less attention has been given to the impact of livestock diseases and depopulation on farmers' mental health. This study explored the mental health effects of these events on farmers and identified strategies to enhance their resilience in coping with such stress. METHODS: Using a qualitative study, 20 farmers, veterinarians, and industry experts were recruited to describe the experience of livestock diseases and depopulation in Alberta, Canada through semi-structured, one-on-one interviews. All had experience with livestock diseases, and 18 had direct depopulation experience. To capture a broad spectrum of the impact on farmers, we gathered feedback from those raising cattle, swine, poultry, deer and elk, sheep, goats, and bees. The interviews were analyzed using a thematic approach to identify common themes. RESULTS: Five themes and five sub-themes emerged from the analysis: emotional distress (with sub-themes of shock and helplessness, anxiety and hypervigilance, despondency and waning motivation, fear of judgment and stigma, and contextual variables), threats to identity, economic burden, distrust and frustration with authorities, resilience and adaptation. Using our findings, we adapted the Emergency Management Framework to show what activities could be integrated to support farmers' mental health needs before, during, and after a depopulation event. CONCLUSION: Farm animal diseases threaten the livelihoods and well-being of farmers as well as pose a significant threat to Canada's food security and national economy. Our findings indicate farmers who experience livestock diseases and depopulation may be at risk for poor mental health. Implications for education and training, as well as changes to policy to support the mental health and well-being of farmers is discussed.
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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 | 0.007 | 0.011 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.016 | 0.014 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.002 | 0.003 |
| 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".