Knowledge and Attitude of Mothers Towards Childhood Vaccination in Taif, Saudi Arabia
Bibliographic record
Abstract
Background: Misconceptions and inadequate knowledge about vaccination represent an important barrier against adherence to vaccination schedules. Objectives: To assess the knowledge and attitude of mothers of children under five years of age with regard to standard childhood vaccination. Subjects and methods: A cross-sectional study was conducted at Taif Children’s Hospital (a subsidiary of the Ministry of Health), Saudi Arabia, among a sample of mothers of children aged below five years attending the hospital’s outpatient clinics during the study period of May-July 2021. A valid questionnaire was utilised for data collection, comprising demographic questions as well as an assessment of respondents’ knowledge and attitude towards childhood vaccination. Results: The study included 397 mothers, more than half of whom (53.9%) were aged between 20 and 30 years. Overall, the total knowledge score ranged between 5 and 10, with an arithmetic mean of 9.03 and standard deviation of (± 1.25). Higher-educated mothers (university or above) were more knowledgeable about childhood vaccination than lesser-educated mothers (mean ranks were 200.44 and 123.35, respectively), p=0.020. Overall, the total score for attitude towards childhood vaccination ranged between 5 and 10, with an arithmetic mean of 9.15 and standard deviation of (± 0.48). Married mothers expressed a more positive attitude towards childhood vaccination than divorced mothers (mean ranks were 200.83 and 144.81, respectively), p=0.014. Conclusion: The knowledge about, and attitude towards, childhood vaccination among mothers in Taif, Saudi Arabia are excellent. However, some misconceptions require correction
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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 | 0.000 | 0.002 |
| 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) | 0.002 | 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".