The Effects of AgrAbility on the Mental/Behavioral Health of Farmers and Ranchers with Functional Limitations: A Comparison Study
Bibliographic record
Abstract
Background: While research on the quality of life (QOL) levels of farmers and ranchers with disabilities is growing, research focused on interventions that improve their behavioral health is almost nonexistent. The AgrAbility Project, a USDA initiative, offers practical solutions to increase farmers and ranchers with disabilities’ QOL and independent living and working (ILW) levels. Aim of the Study: The objectives of the current study are threefold: first, to assess overall pretest-posttest changes in the ILW and QOL levels of AgrAbility participants; second, to focus on the behavioral health changes of AgrAbility participants; and third, to compare those changes in a group of AgrAbility participants to those of a no-treatment comparison group. Methods: AgrAbility treatment group participants (N = 273) included farmers and ranchers from 14 states with various disabilities who participated in AgrAbility and no-treatment comparison group participants (N = 100) from 17 states. Both groups completed ILW and McGill Quality of Life surveys. Results: Paired samples t-tests indicated that AgrAbility participants’ ILW and QOL improved with large or larger than typical effect sizes. Paired samples t tests indicated that AgrAbility participants’ behavioral health improved significantly with medium effect sizes. Independent samples t tests reported significantly higher gain scores on all three behavioral health subscales for AgrAbility participants compared with the group of non-participants. Conclusions: These results show that participation in the AgrAbility Project was associated with significant improvements in behavioral health when compared to the no-treatment group which experienced no significant change in their behavioral health. The current study makes an initial contribution to the search for an evidence-based intervention for improving the physical and behavioral health of farmers and ranchers with functional limitations.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| 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".