Doktor Muda Competencies: Self-efficacy and Hand Washing Demonstration Skill among School Children in Malaysia
Bibliographic record
Abstract
INTRODUCTION: “Doktor Muda” (DM) programme was developed by the Ministry of Health (MOH), Malaysia to train a group of pupils as peer educator for change in motivating and assisting their peers to adopt healthy practices especially in hand washing through good knowledge, positive attitude, high self-efficacy and skill to deliver health messagesAIM: This study aims to identify the association of socio demographic, knowledge, attitude, and practices with self-efficacy in proper hand washing.METHODS: A cross-sectional study using a self-administered questionnaire and observation checklists for hand washing demonstration skills.RESULT: This study showed that the subjects` knowledge (16.7%), practice (23.8%) and self-efficacy (41.7) in proper hand washing were low. Significant association were found between gender (p=0.004), academic achievements (p=0.038) and practices (p=0.003) with self-efficacy in proper hand washing.CONCLUSION: Various strategies are needed to strengthen DM role as peer educators and health change agents in school as levels of their knowledge, practice and self-efficacy were low.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 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".