Social determinants of health in rural Indian women & effects on intervention participation
Bibliographic record
Abstract
The social determinants of health have become an increasingly crucial public health topic in recent years and refer to the non-medical factors that affect an individual's health outcomes. Our study focuses on understanding the various social and personal determinants of health that most affect women's wellbeing. We surveyed 229 rural Indian women through the deployment of trained community healthcare workers to understand their reasons for not participating in a public health intervention aimed to improve their maternal outcomes. We found that the most frequent reasons cited by the women were: lack of husband support (53.2%), lack of family support (27.9%), not having enough time (17.0%), and having a migratory lifestyle (14.8%). We also found association between the determinants: women who had lower education levels, were primigravida, younger, or lived in joint families were more likely to cite a lack of husband or family support. We determined through these results that a lack of social (both spousal and familial) support, time, and stable housing were the most pressing determinants of health preventing the women from maximizing their health outcomes. Future research should focus on possible programs to equalize the negative effects of these social determinants to improve the healthcare access of rural women.
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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 | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".