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Record W4312141122 · doi:10.3390/children9121971

Effects of Integrative Autism Therapy on Multiple Physical, Sensory, Cognitive, and Social Integration Domains in Children and Adolescents with Autism Spectrum Disorder: A 4-Week Follow-Up Study

2022· article· en· W4312141122 on OpenAlexaboutno aff
Yunhwan Kim, Mi-Kyoung Kim, Chanhee Park, Joshua H. You

Bibliographic record

VenueChildren · 2022
Typearticle
Languageen
FieldNeuroscience
TopicAutism Spectrum Disorder Research
Canadian institutionsnot available
FundersKorea Health Industry Development Institute
KeywordsAutismAutism spectrum disorderChildhood Autism Rating ScaleAnalysis of variancePsychologyRepeated measures designSensory processingRating scaleClinical psychologyOccupational therapyPhysical therapySensory systemMedicineDevelopmental psychologyPsychiatry

Abstract

fetched live from OpenAlex

This study aimed to compare the effects of conventional autism therapy (CAT) and integrative autism therapy (IAT) in children and adolescents with autism spectrum disorder (ASD). A convenience sample of 24 children with ASD was recruited and underwent either CAT or IAT for 60 min/day, twice a week, for 20 sessions over 10 weeks. Outcome measures included the following: (1) physical domain (pediatric balance scale, PBS), (2) sensory domain (short sensory profile), (3) cognitive domains (functional independence measure, FIM; and childhood autism rating scale), and (4) social integration domain (Canadian occupational performance measure, COPM; short falls efficacy scale; and pediatrics quality of life questionnaire). Two-way repeated analysis of variance (ANOVA) was used to determine the intervention-related changes in the four domains across the pre-test, post-test, and follow-up test at p < 0.05. ANOVA showed significant interaction effects on the PBS, FIM, and COPM (p < 0.05) variables. Moreover, time main effects (p < 0.05) were observed in all four domain variables, but no group main effect was noted. This study provides promising evidence that IAT is more effective than CAT for managing children and adolescents with ASD.

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 score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0010.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.001
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 head0.012
GPT teacher head0.265
Teacher spread0.254 · 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

Citations8
Published2022
Admission routes1
Has abstractyes

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