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Record W4328048637 · doi:10.1177/15394492231159903

A Telehealth Delivered Toilet Training Intervention for Children with Autism

2023· article· en· W4328048637 on OpenAlexaboutno aff
Lauren Little, Anna Wallisch, Winnie Dunn, Scott Tomchek

Bibliographic record

VenueOTJR Occupational Therapy Journal of Research · 2023
Typearticle
Languageen
FieldPsychology
TopicFamily and Disability Support Research
Canadian institutionsnot available
FundersAmerican Occupational Therapy Foundation
KeywordsToiletingAutismTelehealthToiletCoachingIntervention (counseling)PsychologyPsychological interventionClinical psychologyPhysical therapyMedicineActivities of daily livingDevelopmental psychologyPsychiatryTelemedicinePsychotherapist

Abstract

fetched live from OpenAlex

BACKGROUND: Independence in toileting is a vital skill, yet toilet-training interventions for children with autism are limited. OBJECTIVES: We investigated the acceptability and preliminary efficacy of a hybrid telehealth intervention that used synchronous individualized coaching sessions and asynchronous online educational materials to support parents in toilet training their children with autism. METHOD: Participants included 34 families of children with autism ages 2 to 8 years. Measures were administered at pre- and postintervention (10-12 weeks) and included the Toileting Behavior Questionnaire, Goal Attainment Scaling, and Canadian Occupational Performance Measure. RESULTS: Twenty-five families completed all intervention procedures. Parents found the intervention highly acceptable and reported significant improvements in child toileting behaviors; however, families accessed the asynchronous intervention materials at a low rate. CONCLUSION: A parent coaching model delivered through telehealth may be a promising method to increase toileting independence among families of young children with autism.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.500
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0070.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.292
GPT teacher head0.520
Teacher spread0.228 · 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.

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

Citations14
Published2023
Admission routes1
Has abstractyes

Explore more

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