Associations Between Diet Quality and Psychosocial and Environmental Factors in Rural Adults
Bibliographic record
Abstract
OBJECTIVE: Assess relationships between diet quality and healthy eating motivation, confidence, social support, and food environment. METHODS: The study sample of a community-randomized controlled intervention trial responded at baseline to sociodemographic, diet, diet-related psychosocial factor (motivation, confidence, social support), and environment (healthy food availability, food shopping motivation) questions. Linear regression was used to analyze cross-sectional associations between dietary intake (diet quality, fruit and vegetable, fiber, ultraprocessed food) and psychosocial and environmental factors. RESULTS: Data from 2420 rural adults were analyzed. Psychosocial factors were positively associated with fruit and vegetable and fiber consumption and diet quality. Psychosocial factors were negatively associated with ultraprocessed food consumption frequency, except for social support from friends. Fruit and vegetable availability was positively associated with fruit and vegetable and fiber consumption and overall diet quality. Food shopping motivation was positively associated with fruit and vegetable intake and overall diet quality. CONCLUSIONS AND IMPLICATIONS: These findings contribute insights into ways psychosocial and environmental factors influence diet quality within rural studies.
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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 | 0.002 |
| 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) | 0.002 | 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".