Effectiveness of a Participatory and Culturally Tailored Learning Program for Coronavirus Prevention in Muslim Older Adults With Hypertension and Diabetes: Quasi-Experimental Study
Bibliographic record
Abstract
Background: Respiratory infections have increased globally over time, with older adults being the most susceptible demographic. Programs based on cultures and experiences strongly correspond with useful, real-world applications. Objective: This study evaluated a participatory and culturally based learning program's effect on awareness, knowledge, and preventive behaviors regarding coronavirus and health care among Muslim older adults with hypertension and diabetes in Thailand. Methods: The quasi-experimental study used a 2-group pretest-posttest design with participants aged 60-80 years with hypertension and diabetes. The sample included 35 in the experimental group and 32 in the control group. An interactive 6-week learning program focusing on coronavirus prevention and health care was developed by incorporating Muslim cultural perspectives and Kolb experiential learning model, alongside standard care. The control group received only standard care. Data were collected via a questionnaire covering general information, awareness, knowledge, and preventive behaviors related to coronavirus prevention and health care. The content validity indices of sections II, III, and IV were 0.98, 0.99, and 0.96, respectively. The Cronbach α coefficients of awareness and behaviors were 0.89 and 0.86, respectively, while the KR-20 for knowledge was 0.86. Data analysis was conducted using the t test, Mann-Whitney U test, and Wilcoxon signed-rank test. Results: The results indicated that, after participating in the program, the awareness, knowledge, and preventive behaviors related to coronavirus and health care among older adults in the experimental group significantly improved compared to their preprogram levels and to those in the control group, with a P value <.01. Conclusions: The program effectively improved coronavirus prevention and health care among Muslim older adults. It could be broadly applied in similar contexts and to other severe respiratory diseases.
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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 | 0.005 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".