Assessment of Awareness and Knowledge About Rickets in Primary Health Care Centers in Saudi Arabia Based on Health Belief Model and Social Cognitive Theory
Bibliographic record
Abstract
BACKGROUND: Rickets is considered a significant health issue affecting children especially infants and toddlers. Despite the development affordable and accessible of a health care system in Saudi Arabia, Saudi children had a high prevalence of rickets. This study aims to assess knowledge and awareness of mothers about rickets after short interventional program based on the health belief model and social cognitive theory. METHODS: A Quasi-experimental design pre-posttest type was carried out by using self-administered questionnaire. A sample size of 180 mothers who attended the well-baby clinic in primary health care centers in Riyadh and Medina Region were consented and then enrolled in the study. The questionnaire focused on 7 domains; demographic information and the other 6 domains based on health believe model and social cognitive theory. RESULTS: The mean scores of knowledge, self-efficacy, and health belief model constructs (susceptibility, severity, benefits) significantly increased. The mean score and the percentages of knowledge and health belief model constructs show changes between pretest and post test result with statistical significant (27.9% in knowledge and self-efficacy, 34.9% in perceived susceptibility, 54.5% in perceived severity, 25.9% in perceived benefits, 11.7% in perceived barriers and 5.4% in cues to action) all were with a p-value of less than 0.05. CONCLUSION: Educational intervention based on social cognitive theory and health belief model were effective in improving knowledge, awareness and practice related to preventive behaviors of rickets.
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 | 0.002 | 0.004 |
| 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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".