Structural Equation Modeling of Oral Stomatitis and Its Determinants among the Sundanese Ethnic Group: Evidence from IFLS-5
Bibliographic record
Abstract
Background: Oral stomatitis is an inflammation of the mucosa in various oral structures such as cheeks, gums, tongue, lips, palate, and floor of the mouth that commonly occurs in communities, including among the Sundanese ethnic group. Risk factors affecting stomatitis incidence in the Sundanese population need to be analyzed for developing more effective prevention programs. Aim: To analyze risk factors for stomatitis among the Sundanese population using panel data from the Indonesian Family Life Survey (IFLS). Method: This was an analytical observational study using secondary data from IFLS-5. The research design employed structural equation modelling (SEM) analysis examining variables including age, gender, education, residential area classification, general health status, and smoking habits. Results: The study revealed that age and general health variables had significant associations with stomatitis occurrence (p<0,001). Ages below 25 years and suboptimal health conditions proved to be significant factors influencing increased stomatitis incidence. Meanwhile, gender, education level, residential area classification, and smoking habits showed no significant correlation. Conclusion: Age and general health status are the main risk factors for stomatitis occurrence among the Sundanese population, which can serve as a reference for prevention program development.
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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 | 0.004 | 0.009 |
| 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 | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".