Determinants of Gastritis Occurrence in The Working Area of Telaga Dewa Health Center, Bengkulu City in 2024
Bibliographic record
Abstract
Intoduction: According to the World Health Organization (WHO), the highest prevalence of gastritis occurrence in the world is found in Canada at 35%. Based on the health profile of Indonesia in 2019, Indonesia ranks third in the highest cases of gastritis in Asia, after India and Thailand, with a fairly high prevalence of gastritis at 274,396 cases or 40% of the population of 238,452,952 people. From the data of the Bengkulu Provincial Health Office in 2022,there were still many cases of gastritis recorded as the third most common disease in Bengkulu Province, with a total of 51,069 cases. The Telaga Dewa Health Center reported the highest incidence of gastritis, with 1,689 cases recorded from patient visits in 2022.The purpose of this study is to determine the relationship between dietary patterns, stress, and knowledge with the occurrence of gastritis in the working area of Telaga Dewa Health Center, Bengkulu City in 2024. Method: The method used is a descriptive correlational research design with a cross-sectional approach, using purposive sampling technique. Data were collected by distributing questionnaires to 90 individuals representing all respondents in the working area of Telaga Dewa Health Center, Bengkulu City, based on inclusion and exclusion criteria. Result and Discussion: The results of the study showed that there is a relationship between dietary patterns and the occurrence of gastritis with a p-value of 0.000, a relationship between stress and the occurrence of gastritis with a p-value of 0.001, and a relationship between knowledge and the occurrence of gastritis with a p-value of 0.000. Conclusion: his study concludes that there is a relationship between dietary patterns, stress, and knowledge with the occurrence of gastritis in the working area of Telaga Dewa Health Center, Bengkulu City.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 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".