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Record W2611773869 · doi:10.1002/aur.1806

Identifying the clinical needs and patterns of health service use of adolescent girls and women with autism spectrum disorder

2017· article· en· W2611773869 on OpenAlexafffund
Ami Tint, Jonathan A. Weiss, Yona Lunsky

Bibliographic record

VenueAutism Research · 2017
Typearticle
Languageen
FieldPsychology
TopicFamily and Disability Support Research
Canadian institutionsUniversity of TorontoYork UniversityCentre for Addiction and Mental Health
FundersCanadian Institutes of Health ResearchHealth CanadaSinneave Family FoundationAutism Speaks
KeywordsAutism spectrum disorderAutismPsychologyDevelopmental psychologyService (business)PsychiatryClinical psychologyMedicine

Abstract

fetched live from OpenAlex

Girls and women in the general population present with a distinct profile of clinical needs and use more associated health services compared to boys and men; however, research focused on health service use patterns among girls and women with Autism Spectrum Disorder (ASD) is limited. In the current study, caregivers of 61 adolescent girls and women with ASD and 223 boys and men with ASD completed an online survey. Descriptive analyses were conducted to better understand the clinical needs and associated service use patterns of girls and women with ASD. Sex/gender comparisons were made of individuals' clinical needs and service use. Adolescent girls and women with ASD had prevalent co-occurring mental and physical conditions and parents reported elevated levels of caregiver strain. Multiple service use was common across age groups, particularly among adolescent girls and women with intellectual disability. Overall, few sex/gender differences emerged, although a significantly greater proportion of girls and women accessed psychiatry and emergency department services as compared to boys and men. Though the current study is limited by its use of parent report and small sample size, it suggests that girls and women with ASD may share many of the same high clinical needs and patterns of services use as boys and men with ASD. Areas for future research are discussed to help ensure appropriate support is provided to this understudied population. Autism Res 2017, 10: 1558-1566. © 2017 International Society for Autism Research, Wiley Periodicals, Inc.

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)0.007
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 score0.029
Threshold uncertainty score0.982

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0070.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0010.001
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 head0.302
GPT teacher head0.497
Teacher spread0.194 · 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

Citations49
Published2017
Admission routes2
Has abstractyes

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