MétaCan
Menu
Back to cohort
Record W3014735150 · doi:10.1177/0145445520915671

Effects of an Interactive Web Training to Support Parents in Reducing Challenging Behaviors in Children with Autism

2020· article· en· W3014735150 on OpenAlexafffund
Stéphanie Turgeon, Marc J. Lanovaz, Marie‐Michèle Dufour

Bibliographic record

VenueBehavior Modification · 2020
Typearticle
Languageen
FieldNeuroscience
TopicAutism Spectrum Disorder Research
Canadian institutionsUniversité de Montréal
FundersFonds de Recherche du Québec - SantéUniversité de Montréal
KeywordsAutismAutism spectrum disorderPsychologyIntervention (counseling)Psychological interventionAttritionRandomized controlled trialClinical psychologyParent trainingDevelopmental psychologyMedicinePsychiatry

Abstract

fetched live from OpenAlex

Many children with autism spectrum disorder (ASD) engage in challenging behaviors, which may interfere with their daily functioning, development, and well-being. To address this issue, we conducted a four-week randomized waitlist control trial to examine the effects of a fully self-guided interactive web training (IWT) on (a) child engagement in challenging behaviors and (b) parental intervention. After 4 weeks, parents in the treatment group reported lower levels of challenging behaviors in their children and more frequent use of behavioral interventions than those in the waitlist groups. Furthermore, within-group analyses suggest that these changes persisted up to 12 weeks following completion of the IWT. Our results highlight the potential utility of web training, but our high attrition rate and potential side effects prevent us from recommending the training as a standalone treatment.

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)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Non-randomized trial · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.068
GPT teacher head0.344
Teacher spread0.276 · 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 designNon-randomized trial
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

Citations27
Published2020
Admission routes2
Has abstractyes

Explore more

Same venueBehavior ModificationSame topicAutism Spectrum Disorder ResearchFrench-language works237,207