Assessment of gastroesophageal reflux disease signs, symptoms, and food behaviors concerning mental health in Herat, Afghanistan: A descriptive study
Bibliographic record
Abstract
Abstract Background and Aims Gastroesophageal reflux disease (GERD) is a highly prevalent gastrointestinal disorder with modifiable risk factors that are associated with considerable health and economic burdens. The current study was conducted to assess the signs and symptoms, food behaviors, depression, anxiety, and stress related to GERD in Herat, Afghanistan. Methods A descriptive study was conducted between August 29 and October 20, 2020, among patients with GERD symptoms, who provided informed verbal consent at the Mowaffaq Clinic and Sehat Hospital in Herat, Afghanistan. The minimum sample size was 384. Data were collected using a three‐domain questionnaire and Depression, Anxiety, and Stress Scale 42 standard questionnaire. SPSS version 27 was used to perform descriptive statistics and χ2 tests. Results The sample consisted of 396 patients, with the majority being female (67.9%), married (78.5%), and illiterate (34.8%). Heartburn (88.1%) and regurgitation (84.3%) were the most common symptoms reported by participants. Tomato consumption (60.1%) was the most frequent type of eating behavior. Most patients reported severe anxiety (45.9%) and showed statistically significant differences in age, sex, education level, and cigarette usage. This study also found that certain demographic status, eating behaviors, and symptoms were associated with significantly different depression, anxiety, and stress scores among patients with GERD. Conclusion Our study demonstrates the association between GERD and various modifiable risk factors in Herat, Afghanistan. Public health initiatives focusing on preventive measures and raising awareness can potentially alleviate the burden of GERD. Moreover, further research and targeted interventions are essential to improve health outcomes, particularly among patients with GERD, who may experience psychological comorbidities.
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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 | 0.001 | 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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".