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Record W2108009709 · doi:10.1177/0008417413520440

Optimizing participation of children with autism spectrum disorder experiencing sensory challenges: A clinical reasoning framework

2014· article· en· W2108009709 on OpenAlexvenueno aff
Jill Ashburner, Sylvia Rodger, Jenny Ziviani, Elizabeth A. Hinder

Bibliographic record

VenueCanadian Journal of Occupational Therapy · 2014
Typearticle
Languageen
FieldNeuroscience
TopicAutism Spectrum Disorder Research
Canadian institutionsnot available
Fundersnot available
KeywordsAutism spectrum disorderPsychological interventionCoachingAutismPsychologyIntervention (counseling)Remedial educationSensory systemSensory processingDevelopmental psychologyApplied psychologyCognitive psychologyPsychotherapistPsychiatry

Abstract

fetched live from OpenAlex

BACKGROUND: Remedial sensory interventions currently lack supportive evidence and can be challenging to implement for families and clinicians. It may be timely to shift the focus to optimizing participation of children with autism spectrum disorders (ASD) through accommodation and self-regulation of their sensory differences. PURPOSE: A framework to guide practitioners in selecting strategies is proposed based on clinical reasoning considerations, including (a) research evidence, (b) client- and family-centredness, (c) practice contexts, (d) occupation-centredness, and (e) risks. KEY ISSUES: Information-sharing with families and coaching constitute the basis for intervention. Specific strategies are identified where sensory aversions or seeking behaviours, challenges with modulation of arousal, or sensory-related behaviours interfere with participation. Self-regulatory strategies are advocated. The application of universal design principles to shared environments is also recommended. IMPLICATIONS: The implications of this framework for future research, education, and practice are discussed. The clinical utility of the framework now needs to be tested.

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)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.367
Threshold uncertainty score0.604

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.158
GPT teacher head0.406
Teacher spread0.248 · 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

Citations63
Published2014
Admission routes1
Has abstractyes

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