Online Health Education Program to Prevent Tobacco Use for Student Teachers during COVID-19 Pandemic in Thailand: Design, Challenges, and Outcomes
Bibliographic record
Abstract
This study developed an online health education program by applying the Health Belief Model with social support to prevent tobacco use by student teachers and evaluated the effectiveness of the program during the COVID-19 pandemic in Thailand. This involved mixed method research divided into 2 phases, with phase 1 combining an online focus group discussion (n=8) and a literature review to develop an online health education program to prevent tobacco use, while phase 2 involved evaluating the effectiveness of the program. Phase 2 used a randomized pretest-posttest control group design consisting of an intervention group (n=30) and a control group (n=30) selected by simple random sampling for both groups from student teachers in academic years 1–5 in the Faculty of Education, Kasetsart University, Bangkok, Thailand. The result from phase 1 for the proposed program for the intervention group involved 8 weeks of online activities, including exercise, meditation, music, games and lectures by experts in public health, health education, and experiences shared by ex-smokers. Leaflets were provided to all participants in both the intervention and control groups. The results from phase 2 showed significant differences in knowledge (p < 0.000; p < 0.007), attitude (p < 0.000; p < 0.034) and risk behavior to tobacco use (p < 0.004; p < 0.025) for both the intervention and control groups at 8 weeks post-intervention compared to pre-intervention, respectively. The program could support, guidance, and contributions of the many individuals and organizations that have been involved in the online process.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".