Effectiveness of Health Coaching through TB Cards on Prevention of Tuberculosis Transmission
Bibliographic record
Abstract
Tuberculosis is the biggest infectious disease killer in the world and has long been faced by various countries, including Indonesia. Many TB prevention control programs have been implemented, but public compliance with preventing TB transmission is still low. The research aims to determine the effectiveness of health coaching through TB cards in preventing TB transmission. Quasi-experimental quantitative research design pre-post-test with control group. Purposive sampling technique. The number of respondents in the control and treatment groups was 15 each. Data analysis to measure the significance of the average difference between the 2 groups used the non-parametric Wilcoxon test and the Mann Whitney test. The results of statistical tests show that knowledge p value = 0.000, attitude p value = 0.000 and action p value = 0.000 (p < 0.005). Overall, the research shows that health education through TB cards is effective in increasing TB prevention behavior in the community. Structured and easily accessible information via the TB Card helps the public understand TB transmission, symptoms and preventive measures. Health guidance through TB cards also contributes to community empowerment.
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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 | 0.004 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".