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Record W3044006808 · doi:10.1177/1362361320942091

Vision care among school-aged children with autism spectrum disorder in North America: Findings from the Autism Treatment Network Registry Call-Back Study

2020· article· en· W3044006808 on OpenAlexaboutno aff
Olivia J. Lindly, James Chan, Rachel M. Fenning, Justin G. Farmer, Ann M. Neumeyer, Paul P. Wang, Mark W. Swanson, Robert A. Parker, Karen Kuhlthau

Bibliographic record

VenueAutism · 2020
Typearticle
Languageen
FieldMedicine
TopicOphthalmology and Visual Impairment Studies
Canadian institutionsnot available
FundersAgency for Healthcare Research and QualityMassachusetts General Hospital
KeywordsAutism spectrum disorderAutismPsychologyPsychiatryMedicineClinical psychology

Abstract

fetched live from OpenAlex

Children with autism spectrum disorder have a high risk of vision problems yet little is known about their vision care. This cross-sectional survey study, therefore, examined vision care among 351 children with autism spectrum disorder ages 6–17 years in the United States or Canada who were enrolled in the Autism Treatment Network Registry. Vision care variables were vision tested with pictures, shapes, or letters in the past 2 years; vision tested by an eye care practitioner (e.g. ophthalmologist, optometrist) in the past 2 years; prescribed corrective eyeglasses; and wore eyeglasses as recommended. Covariates included sociodemographic, child functioning, and family functioning variables. Multivariable models were fit for each vision care variable. Though 78% of children with autism spectrum disorder had their vision tested, only 57% had an eye care practitioner test their vision in the past 2 years. Among the 30% of children with autism spectrum disorder prescribed corrective eyeglasses, 78% wore their eyeglasses as recommended. Multivariable analysis results demonstrated statistically significant differences in vision care among children with autism spectrum disorder by parent education, household income, communication abilities, intellectual functioning, and caregiver strain. Overall, study results suggest many school-aged children with autism spectrum disorder do not receive recommended vision care and highlight potentially modifiable disparities in vision care. Lay Abstract Children with autism are at high risk for vision problems, which may compound core social and behavioral symptoms if untreated. Despite recommendations for school-aged children with autism to receive routine vision testing by an eye care practitioner (ophthalmologist or optometrist), little is known about their vision care. This study, therefore, examined vision care among 351 children with autism ages 6–17 years in the United States or Canada who were enrolled in the Autism Treatment Network Registry. Parents were surveyed using the following vision care measures: (1) child’s vision was tested with pictures, shapes, or letters in the past 2 years; (2) child’s vision was tested by an eye care practitioner in the past 2 years; (3) child was prescribed corrective eyeglasses; and (4) child wore eyeglasses as recommended. Sociodemographic characteristics such as parent education level, child functioning characteristics such as child communication abilities, and family functioning characteristics such as caregiver strain were also assessed in relationship to vision care. Although 78% of children with autism had their vision tested, only 57% had an eye care practitioner test their vision in the past 2 years. Among the 30% of children with autism prescribed corrective eyeglasses, 78% wore their eyeglasses as recommended. Differences in vision care were additionally found among children with autism by parent education, household income, communication abilities, intellectual functioning, and caregiver strain. Overall, study results suggest many school-aged children with autism do not receive recommended vision care and highlight potentially modifiable disparities in vision care.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.004
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.249
Threshold uncertainty score0.495

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.002
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.014
GPT teacher head0.284
Teacher spread0.270 · 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 source (direct Gemma or distilled Codex), 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

Citations17
Published2020
Admission routes1
Has abstractyes

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