Binational utilization and barriers to care among Mexican American border residents with diabetes.
Bibliographic record
Abstract
OBJECTIVE: To assess whether U.S.-Mexico border residents with diabetes 1) experience greater barriers to medical care in the United States of America versus Mexico and 2) are more likely to seek care and medication in Mexico compared to border residents without diabetes. METHODS: A stratified two-stage randomized cross-sectional health survey was conducted in 2009 - 2010 among 1 002 Mexican American households. RESULTS: Diabetes rates were high (15.4%). Of those that had diabetes, most (86%) reported comorbidities. Compared to participants without diabetes, participants with diabetes had slightly greater difficulty paying US$ 25 (P = 0.002) or US$ 100 (P = 0.016) for medical care, and experienced greater transportation and language barriers (P = 0.011 and 0.014 respectively) to care in the United States, but were more likely to have a person/place to go for medical care and receive screenings. About one quarter of participants sought care or medications in Mexico. Younger age and having lived in Mexico were associated with seeking care in Mexico, but having diabetes was not. Multiple financial barriers were independently associated with approximately threefold-increased odds of going to Mexico for medical care or medication. Language barriers were associated with seeking care in Mexico. Being confused about arrangements for medical care and the perception of not always being treated with respect by medical care providers in the United States were both associated with seeking care and medication in Mexico (odds ratios ranging from 1.70 - 2.76). CONCLUSIONS: Reporting modifiable barriers to medical care was common among all participants and slightly more common among 1) those with diabetes and 2) those who sought care in Mexico. However, these are statistically independent phenomena; persons with diabetes were not more likely to use services in Mexico. Each set of issues (barriers facing those with diabetes, barriers related to use of services in Mexico) may occur side by side, and both present opportunities for improving access to care and disease management.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".