Knowledge of Amblyopia among Primary Health Care Physicians and Family Medicine Residents: A Cross-Sectional Study in the Qassim Region of Saudi Arabia
Bibliographic record
Abstract
Background: Amblyopia is a serious visual impairment resulting from abnormal visual stimulation during early childhood. Early detection of childhood visual abnormalities will reduce adult visual impairment. This study aimed to assess the knowledge of Amblyopia among primary Health Care (PHC) physicians and Family Medicine Residents (FMA) in Qassim Region. Methods: A cross-sectional study enrolled 197 PHC physicians and residents from FMA. Data were collected through an online questionnaire with variables on physicians’ knowledge about amblyopia based on the Canadian Pediatric Society Recommendations for Vision Screening at Infant and Well Child Visits. The data was analyzed using SPSS version 21. Results: The respondent’s average age was 35 (SD ± 8.00). Males were 103(52.3%); the majority were Saudi 120 (60.9%). Most of them, 189 (96%) knew the definition of amblyopia. But the majority of physicians, 138 (70%) had not seen or diagnosed any case of amblyopia before . The overall knowledge of the family medicine residents and PHC physicians regarding amblyopia’s prevalence rate, causes, examination, and treatment was good at 178 (90.4%). However, their knowledge of referral criteria for amblyopia cases still needed more updating. No statistical relationship was identified between the participant’s demographic characteristics and their level of knowledge. Conclusions: This study highlighted a good knowledge level regarding amblyopia among primary health care physicians and family medicine residents. However, strategies to improve vision screening are necessary. Early intervention is crucial to prevent treatable causes of vision loss in children. Keywords: Amblyopia; vision screening; Primary health Care; Qassim; Saudi Arabia
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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 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".