College students’ knowledge, attitude, and practices on COVID-19 prevention post e-health education program
Bibliographic record
Abstract
This study explored if significant improvements in knowledge, attitude, and practices among college students will be observed post E-health education program on COVID-19 prevention. The study reports a pre-post quantitative research on 178 college students. The participants received nine sessions of e-health education developed using the Communicable Disease Control Health Education Curriculum Analysis Tool (HECAT) through Zoom. The adapted and modified questionnaire was developed from previously published literature regarding viral epidemics related to MERS-CoV disease, infection prevention, and control measures for COVID-19 by World Health Organization and the Communicable Disease Control and Prevention guidelines. The first phase gathers the relevant profile and background of the participants, and the last phase comprises post-evaluation. The data were analyzed using SPSS version 27. The results indicate above-average means for knowledge on COVID-19 prevention in the pretest (17.75±2.27) and the posttest (17.60±2.95). Moreover, the participants were aware of the importance of vaccination, social distancing measures, following health protocols, and the essentiality of compliance with government agencies' guidelines. However, the participants were not practicing some of these health measures, as evidenced by the low means in the pretest (1.75±0.97) and posttest (1.66±1.08). All tests for significant differences of pretest and posttest means of knowledge (p=0.46), attitude (p=0.12), and practices (p=0.41) on COVID-19 prevention were all insignificant. Our study provides evidence that the online health education program improved college students' knowledge and attitude toward COVID-19 prevention. Still, they did not adhere to or practice some of the health measures to prevent its transmission.
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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 | 0.014 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 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".