Depression, Social Factors, and Farmworker Health Care Utilization
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
PURPOSE: Farmworkers frequently live in rural areas and experience high rates of depressive symptoms. This study examines the association between elevated depressive symptoms and health care utilization among Latino farmworkers. METHODS: Data were obtained from 2,905 Latino farmworkers interviewed for the National Agricultural Workers Survey. Elevated depressive symptoms were measured using the Center for Epidemiologic Studies Depression short-form. A dichotomous health care utilization variable was constructed from self-reported use of health care services in the United States. A categorical measure of provider type was constructed for those reporting use of health care. RESULTS: Over 50% of farmworkers reported at least 1 health care visit in the United States during the past 2 years; most visits occurred in a private practice. The odds of reporting health care utilization in the United States were 45% higher among farmworkers with elevated depressive symptoms. Type of provider was not associated with depressive symptoms. Women were more likely to seek health care; education and family relationships were associated with health care utilization. CONCLUSIONS: Latino farmworkers who live and work in rural areas seek care from private practices or migrant/Community Health Clinics. Farmworkers with elevated depressive symptoms are more likely to access health care. Rural health care providers need to be prepared to recognize, screen, and treat mental health problems among Latino farmworkers. Outreach focused on protecting farmworker mental health may be useful in reducing health care utilization while improving farmworker quality of life.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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 it