Computerized Cognitive Behavioral Therapy for Anxiety and Depression in Farming Communities: Mixed Methods Feasibility Study of Participant Use and Acceptability
Bibliographic record
Abstract
BACKGROUND: Farmers have higher rates of depression than nonfarmers and higher rates of suicide than the general population. Several barriers to help seeking have been identified in farmers, which may be overcome by offering web-based mental health support. Computerized cognitive behavioral therapy (cCBT) is an effective intervention used to prevent and treat mild to moderate depression but has not been evaluated in the farming community. OBJECTIVE: This study explored the feasibility of delivering a cCBT course tailored to farmers using a mixed methods approach. METHODS: Farmers (aged ≥18 years) with no, minimal, or moderately severe depressive symptoms (Patient Health Questionnaire-9 [PHQ-9] score <20) were recruited using web-based and offline advertisements and given access to a cCBT course consisting of 5 core modules and automated and personalized email support. Depression (PHQ-9), anxiety (General Anxiety Disorder-7), and social functioning (Work and Social Adjustment Scale) were measured at baseline and the 8-week follow-up. Wilcoxon signed rank tests assessed changes in scores for all outcome measures over time. Telephone interviews focusing on participant use and satisfaction with the course were analyzed using thematic analysis. RESULTS: Overall, 56 participants were recruited; 27 (48%) through social media. Overall, 62% (35/56) of participants logged into the course. At baseline, almost half of the participants reported experiencing minimal depressive symptoms (25/56, 45%) and mild anxiety (25/56, 45%), and just over half (30/56, 54%) reported mild to moderate functional impairment. Posttreatment data were available for 27% (15/56) of participants (41/56, 73% attrition rate). On average, participants experienced fewer depressive symptoms (P=.38) and less functional impairment (P=.26) at the 8-week follow-up; these results were not statistically significant. Participants experienced significantly fewer symptoms of anxiety at the 8-week follow-up (P=.02). Most participants (13/14, 93%) found the course helpful and easy to access (10/13, 77%) and the email support helpful (12/14, 86%). Qualitative interviews identified heavy workloads and mental health stigma within the farming community as barriers to help seeking. Participants thought that web-based support would be helpful, being convenient and anonymous. There were concerns that older farmers and those with limited internet connections may have difficulty accessing the course. Improvements regarding the layout and content of the course were suggested. Dedicated support from someone with farming knowledge was recommended to improve retention. CONCLUSIONS: cCBT may be a convenient way of supporting mental health within farming communities. However, challenges in recruiting and retaining farmers may indicate that cCBT supported only by email may not be an acceptable mode of mental health care delivery for many; however, it was valued by respondents. Involving farming organizations in planning, recruitment, and support may address these issues. Mental health awareness campaigns targeting farming communities may also help reduce stigma and improve recruitment and retention.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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".