Kepatuhan Minum Obat Pencegahan Filariasis di Wilayah Kerja Puskesmas Waihaong dan Air Salobar Kota Ambon
Bibliographic record
Abstract
Background: Lymphatic Filariasis (LF) is an infectious disease caused by filarial worms and transmitted by mosquitoes. Mass drug administration (MDA) for LF is used in endemic areas to stop transmission and prevent disability due to LF. This study aims to identify factors associated with overall compliance with the MDA in 2018 in the catchment areas of Waihaong and Air Salobar Health Centers, Ambon. Method: This analysis used data derived from a survey conducted by the Faculty of Medicine Pattimura University, Ambon, in January 2019. We used information from 745 subjects who received LF drugs in both study areas. Logistic regression analysis was employed to determine factors associated with community compliance with taking filariasis drugs. Results: Our study found that only 67% of the community swallowed LF drugs (60,3% in Waihaong and 72,6% in Air Salobar). Higher compliance with swallowing the LF drugs was found in respondents living in the catchment area of Air Salobar Health Center (OR=2,01, 95%CI:1,42-2,86, P-value<0,001);with a high level of knowledge (OR=1,91, 95%CI:1,34-2,74, P-value<0,001 and with a high sense of trust towards the drugs deliverers (OR=4,93, 95%CI:2,17-11,22, Pvalue<0,001). Furthermore, respondents who felt a high moral obligation to take the drugs (OR=2,39, 95%CI:1,15-4,94, P-value=0,019); and received social support to take the drugs (OR=5,12, 95%CI:3,18-8,23, P-value<0,001) were also more likely to comply with treatment. This study shows that health promotion interventions to increase community awareness and knowledge are still required in Ambon City despite many rounds of mass drug administration. Various educational media and efforts to increase knowledge and capabilities of the drug deliverers are essential to improve community compliance with taking LF drugs.
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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 | 0.000 |
| 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) | 0.006 | 0.001 |
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".