MétaCan
Menu
Back to cohort
Record W3177900528 · doi:10.1080/15021149.2021.1946371

Enriched supervision to increase quality of early intensive behavioral intervention in autism: a pragmatic randomized controlled pilot study

2021· article· en· W3177900528 on OpenAlexaff
Ulrika Långh, Élodie Cauvet, Adrienne Perry, Svein Eikeseth, Sven Bölte

Bibliographic record

VenueEuropean Journal of Behavior Analysis · 2021
Typearticle
Languageen
FieldNeuroscience
TopicAutism Spectrum Disorder Research
Canadian institutionsYork University
FundersSällskapet BarnavårdStiftelsen Kempe-Carlgrenska FondenStiftelsen Frimurare Barnhuset i StockholmVetenskapsrådet
KeywordsIntervention (counseling)Autism spectrum disorderAutismApplied behavior analysisRandomized controlled trialPsychologyQuality assuranceQuality (philosophy)Clinical psychologyNursingMedicinePsychiatry

Abstract

fetched live from OpenAlex

Methods to enhance the quality of delivered Early Intensive Behavioral Intervention (EIBI) for children with autism spectrum disorder (ASD) have received surprisingly little attention in previous research. In a pragmatic randomized controlled pilot study, we studied the feasibility and effects of enriched supervision (using detailed video feedback) on EIBI quality compared to regular supervision only, over a period of 4–6 months. EIBI was conducted in 30 children with ASD by preschool staff, where 18 received enriched, and 12 regular supervisions. EIBI quality was evaluated using the York Measure of Quality of Intensive Behavioural Intervention. The enriched supervision was deemed feasible and compared to staff receiving regular supervision. Preschool staff who received enriched supervision improved on overall quality of EIBI delivery, as well as specifically regarding goal-directedness, organization and efficiency of the EIBI. Findings support the significance of adequate education and supervision of EIBI providers for intervention quality assurance.

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)0.011
metaresearch head score (Gemma)0.008
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 score0.531
Threshold uncertainty score0.933

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0110.008
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0030.001
Bibliometrics0.0020.003
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
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 head0.067
GPT teacher head0.380
Teacher spread0.313 · 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

Citations2
Published2021
Admission routes1
Has abstractyes

Explore more

Same venueEuropean Journal of Behavior AnalysisSame topicAutism Spectrum Disorder ResearchFrench-language works237,207