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Record W4283165002 · doi:10.1177/13623613221100787

Predictors of expert providers’ familiarity with intervention practices for school- and transition-age youth with autism spectrum disorder

2022· article· en· W4283165002 on OpenAlexaff
Chelsea M. Cooper, Tamara E. Rosen, kim hyunsik, Nicholas R. Eaton, Elizabeth Cohn, Amy Drahota, Lauren J. Moskowitz, Matthew D. Lerner, Connor M. Kerns

Bibliographic record

VenueAutism · 2022
Typearticle
Languageen
FieldNeuroscience
TopicAutism Spectrum Disorder Research
Canadian institutionsUniversity of British Columbia
FundersNational Institute of Mental HealthHealth Resources and Services AdministrationEunice Kennedy Shriver National Institute of Child Health and Human DevelopmentSimons Foundation
KeywordsPsychologyAutism spectrum disorderIntervention (counseling)AutismIntellectual disabilityDelphi methodMedical educationCognitionService providerClinical psychologyApplied psychologyDevelopmental psychologyPsychiatryMedicine

Abstract

fetched live from OpenAlex

Understanding the types of intervention practices familiar to transdisciplinary autism spectrum disorder providers may be critical to characterize and optimize “usual care” for common clinical concerns (e.g. internalizing, externalizing, and social challenges) among school- and transition-age autistic youth. We assessed if there is an underlying factor structure to expert providers’ familiarity with such practices, and if characteristics of experts (discipline, years’ experience, and school setting) and/or their clients (age and intellectual disability) predicted these factors. Fifty-three expert providers rated their familiarity with 55 practices via an online Delphi poll. Exploratory structural equation modeling identified latent factors of familiarity, which were regressed onto provider and client variables to identify predictors. Four factors emerged: two approaches (cognitive and behavioral) and two strategies (engagement and accessibility). Cognitive approaches were associated with practicing outside school settings and treating clients without intellectual disability, behavioral approaches with practicing in schools and the disciplines of clinical psychology and behavior analysis, engagement strategies with practicing outside school settings, and accessibility strategies with more years in practice. Findings suggest expert transdisciplinary autism spectrum disorder providers are familiar with many of the same approaches and that differences in knowledge are predicted by their discipline, treatment setting, experience, and work with youth with intellectual disabilities. Lay abstract School-age children, adolescents, and young adults with autism spectrum disorder encounter many different types of providers in their pursuit of treatment for anxiety, behavior problems, and social difficulties. These providers may all be familiar with different types of intervention practices. However, research has not yet investigated patterns in expert providers’ familiarity with different practices nor how these patterns are related to the characteristics of providers (years in practice, academic discipline, setting) and the youth (age and intellectual disability) they typically support. A panel of 53 expert transdisciplinary providers rated their familiarity with 55 intervention practices (derived from research and expert nominations) via an online Delphi poll. Advanced statistical methods were used to identify types of intervention practices with which providers were familiar, which included two approaches (cognitive and behavioral) and two strategies (engagement and accessibility). Providers who practiced outside a school setting or treated clients without intellectual disability were more familiar with cognitive approaches. Clinical psychologists, behavior analysts, and school-based providers were more familiar with behavioral approaches. Providers practicing outside school settings were also more familiar with engagement strategies, and providers with more years in practice were more familiar with accessibility strategies. These results may help families and researchers to better anticipate how services may vary depending on the types of autism spectrum disorder providers seen and work to reduce disparities in care that may result.

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)0.000
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.423
Threshold uncertainty score0.829

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
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 head0.292
Teacher spread0.262 · 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

Citations3
Published2022
Admission routes1
Has abstractyes

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