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Record W2768681298 · doi:10.1093/pch/pxx148

Paediatric vision screening in the primary care setting in Ontario

2017· article· en· W2768681298 on OpenAlexafffundabout
Tran D. Le, Rana Arham Raashid, Linda Colpa, Jason Noble, Asim Ali, Agnes Wong

Bibliographic record

VenuePaediatrics & Child Health · 2017
Typearticle
Languageen
FieldMedicine
TopicOphthalmology and Visual Impairment Studies
Canadian institutionsHospital for Sick ChildrenUniversity of Toronto
FundersCanadian Institutes of Health ResearchHospital for Sick ChildrenCanada Foundation for Innovation
KeywordsMedicineFamily medicineReimbursementIntervention (counseling)Primary carePediatricsNursingHealth care

Abstract

fetched live from OpenAlex

OBJECTIVES: Early intervention is critical to prevent treatable causes of vision loss in children. The objectives of the current study are: (1) to assess how well primary care physicians in Ontario follow the vision screening guidelines for children as recommended by the Canadian Paediatric Society and the Rourke Baby Record and (2) to identify barriers to vision screening in the primary care setting. DESIGN: Cross-sectional survey. METHODS: A 19-question survey was mailed out to 1000 randomly selected family physicians (family MDs), 1000 general practitioners (GPs) and 1000 paediatricians in Ontario as listed in the 2013 Canadian Medical Directory. RESULTS: A total of 719 completed surveys were included in the analysis (449 from family MDs/GPs and 270 from paediatricians). Vision screening was reported to be performed by 65% of family MDs/GPs and 52% of general paediatricians at every well child visit. While red reflex was reported to be checked by 94% of all physicians in children under 3, it was only performed by 25% of respondents for children over 3. Thirty seven percent of all physicians reported never performing a visual acuity test in any age group. When asked about the obstacles preventing them from performing vision screening, lack of training (family MDs/GPs: 50%, paediatricians: 42%), time constraints (family MDs/GPs: 42%; paediatricians: 40%) and inadequate reimbursement (family MDs/GPs: 17%; paediatricians: 15%) were the most commonly cited reasons. CONCLUSIONS: Strategies to improve vision screening are necessary given that early intervention is crucial to prevent treatable causes of vision loss in children.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.027
Threshold uncertainty score0.993

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.031
GPT teacher head0.353
Teacher spread0.321 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations33
Published2017
Admission routes3
Has abstractyes

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