Determinants of Community Distrust of Drugs Deliverers in the Catchment Areas of Waihaong and Air Salobar Health Centers, Ambon
Bibliographic record
Abstract
Lymphatic Filariasis (LF) is a chronic infectious disease caused by worms from the nematode group.Mass drug administration (MDA) for LF is carried out in endemic communities to eliminate lymphatic filariasis.Previous analysis shows that one of the factors associated with community compliance with taking LF drugs was the community's trust towards LF drug deliverers during MDA.This study examined factors associated with community distrust of LF drugs deliverers in the 2018 MDA in the catchment areas of Waihaong and Air Salobar Health Centers, Ambon City.Data used in this study were derived from a cross-sectional study conducted in January 2019 in the catchment areas of Waihaong and Air Salobar Health Centers.The survey involved 964 respondents aged 18-70 living in the study sites.Potential predictors of community distrust of drug deliverers in this analysis were categorized into: (1) Socio-demographic characteristics, i.e., respondents' age, gender, education, occupation, living area, and household income, and (2) Internal factors, i.e., respondents' level of knowledge of lymphatic filariasis and MDA, and sense of obligation to take LF drugs.Logistic regression analysis was employed to examine factors associated with the community's distrust of LF drug deliverers during the 2018 MDA.Our analysis showed that 8.8% of respondents distrust drug deliverers.The odds of distrusting LF drug deliverers amongst respondents with low knowledge of LF and MDA was almost ten times the odds in those with a high level of knowledge (aOR = 9.91, 95%CI: 2.31-42.42,p = 0.002).The odds were also significantly higher in those who did not feel obliged to take LF drugs than in those with a strong sense of obligation (aOR = 3.86, 95%CI: 2.02-7.39,p < 0.001).Our findings show that interventions are still required to improve the community's knowledge of LF and MDA through different health promotion activities.Efforts to enhance the community's sense of responsibility and mutual obligation to take LF drugs will be beneficial to improve community trust in drug deliverers in MDA and support the goal of LF elimination in Ambon 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 | 0.001 | 0.003 |
| 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 | 0.001 |
| 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".