Parental Knowledge Attitudes and Practice Towards Headaches Among Elementary School-Aged Children in Al-Baha, Saudi Arabia
Bibliographic record
Abstract
Aim: To evaluate parental knowledge, attitudes, and practices regarding childhood headaches in Al-Baha, Saudi Arabia, and identify gaps that could inform targeted educational interventions. Methods: A cross-sectional online survey was administered to 399 parents residing in Al-Baha. The survey assessed parental understanding, behavior, and perceptions concerning pediatric headaches. Data analysis was conducted using SPSS version 27.0, applying descriptive statistics, Mann–Whitney U, Kruskal–Wallis, and Spearman’s correlation tests. Results: Among the respondents, 52.4% were female (N = 209) and 47.6% male (N = 190), with a mean age of 42.56 years. Female participants exhibited significantly higher knowledge scores than their male counterparts. The most frequently reported headache triggers were sleep disturbances (79.4%), vision problems (61.7%), and psychological factors (52.1%), whereas malnutrition was identified by only 48.9% of respondents. Symptom monitoring practices varied: 46.1% of parents reported observing symptoms before seeking medical care, while 23.0% considered headaches an emergency. Notably, 57.4% sought professional consultation when symptoms persisted, yet 32.1% administered painkillers without medical advice. Knowledge scores were positively correlated with both attitude scores (r = 0.151, p = 0.002) and practice scores (r = 0.336, p < 0.001). Conclusion: The findings indicate that parental understanding of childhood headaches is often limited, particularly concerning nutritional triggers and evidence-based management strategies. This underscores the urgent need for targeted educational initiatives to enhance awareness, promote appropriate health-seeking behavior, and reduce the risk of mismanagement.
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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 | 0.001 | 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 | 0.000 |
| 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".