Practice patterns in the management of amblyopia among optometrists in Ghana
Bibliographic record
Abstract
Despite internationally recognized guidelines, amblyopia management varies among eye care professionals worldwide. Hence, we sought to investigate the practice patterns of amblyopia management and the factors associated with the decision to treat amblyopia among optometrists in Ghana. A cross-sectional survey was conducted among registered optometrists in Ghana from January 2020 to October 2020. Data collection was done through the administration of online questionnaires via e-mail (google form). The structured questionnaires included demographic information, mode, and scope of practice, diagnostic criteria, examination procedures, treatment modalities, and prognosis. A p value of less than 0.05 was deemed statistically significant. The mean (±SD) age of all the 168 respondents was 32.6 (±6.1) years (range: 24-50 years). The majority of the optometrists (64.9%) treated amblyopia in their practice; with the most prevalent being refractive amblyopia (68.2%), followed by strabismic amblyopia (27.1%), then form-deprivation amblyopia (4.7%). Most (76.1%) amblyopic patients presented with symptomatic squinting. The most common ocular and medical history was anisometropia (90.0%), and the most common diagnostic procedures were patient history, visual acuity, and refraction. Optical correction (88.3%) was mainly prescribed for amblyopia treatment, followed by patching (58.5%). Nearly half of the respondent (45.0%) reported good prognosis after amblyopia treatment. After statistical adjustment, female optometrists were significantly associated with decreased odds of treating amblyopia (AOR = 0.36, p = .004). Refractive amblyopia is the main type of amblyopia managed by optometrists in Ghana. Hence, optical correction is the primary treatment regime. Current amblyopia management practice among optometrists adhere to recommended guidelines and our findings demonstrate uniformity in the standard of care.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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) | 0.001 | 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".