Determinants of Fulfillment of Requirements for Hand Washing Facilities with Soap
Bibliographic record
Abstract
The behavior of Washing Hands with Soap (CTPS) and running water is carried out as an effort to protect yourself and others in the prevention of infectious diseases. However, the practice of CTPS in Banyumas Regency is still low. One of the causes is the limitation of CTPS supporting facilities and infrastructure which results in ineligible facilities. The purpose of the study is to analyze factors related to the fulfillment of CTPS facility requirements. A type of observational analytical research with the crosssectional method. The population in this study is houses that have CTPS facilities in Baturraden District. The number of samples was 325 houses with the sampling technique of cluster random sampling. Data collection techniques through interviews and observations. Data analysis uses chi-square statistical ui and logistic regression. Factors related to the fulfillment of the CTPS facility requirements were the respondent's education level (p-value ≤ 0.05; OR=1,855; CI95%=1,123-3,064). income (P-value ≤ 0.05; OR=1,855; CI95%=1,123-3,064), counseling (p-value ≤ 0.05; OR=2,116; CI95%=1,273-3,518 knowledge (p-value ≤ 0.05; OR=2,187; CI95%=1,137-4,207), and attitudes (p-value ≤ 0.05; OR=2,187; CI95%=1,137-4,207). The dominant factors related to the fulfillment of CTPS facility requirements are counseling, knowledge and attitude. The Primary Health Center of Baturraden I needs to actively conduct counseling to increase public knowledge and attitudes regarding the importance of fulfilling the requirements of CTPS facilities.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".