Determinants of Health Service Utilization Among Adults at High Risk of Developing Type 2 Diabetes in Kerala, India
Bibliographic record
Abstract
The purpose of this study was to examine the determinants of health service utilization in a population at high risk of developing type 2 diabetes mellitus in India. Using Andersen's behavioral model of healthcare utilization, multivariate logistic regression analysis was performed on baseline data of the Kerala Diabetes Prevention Program. We examined the association between predisposing, enabling, and need factors with outpatient health service use in the past four weeks and inpatient health service use in the past 12 months. More than a quarter (27.9%) and 12.9% of 1007 participants used outpatient services and inpatient services, respectively. Men were less likely to use outpatient services (odds ratio [OR] = 0.56). Outpatient service utilization was positively associated with low social support (OR = 1.69), low general health status (OR = 5.71), and time off from work due to illness (OR = 8.01). Higher educational status (OR = 0.63), low general health status (OR = 3.59), and time off from work due to illness (OR = 1.21) were associated with increased utilization of inpatient services. Although gender, educational status, and social support had important roles, health service utilization in this study population was largely dependent on general health status and presence of illness.
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How this classification was reachedexpand
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 | 0.005 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".