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Record W2990265155 · doi:10.1177/0162643419888765

The Use of Technologies Among Individuals With Autism Spectrum Disorders: Barriers and Challenges

2019· article· en· W2990265155 on OpenAlexafffund
Parisa Ghanouni, Tal Jarus, Jill G. Zwicker, Joseph M. Lucyshyn

Bibliographic record

VenueJournal of Special Education Technology · 2019
Typearticle
Languageen
FieldNeuroscience
TopicAutism Spectrum Disorder Research
Canadian institutionsChild and Family Research InstituteSunny Hill Health Centre for ChildrenUniversity of British ColumbiaDalhousie University
FundersMichael Smith Health Research BC
KeywordsApprehensionThematic analysisAutismService providerAutism spectrum disorderPerceptionPsychologyEmerging technologiesKnowledge managementBusinessQualitative researchService (business)Computer scienceMarketingDevelopmental psychologySociology

Abstract

fetched live from OpenAlex

Despite the rapid growth in development of technology, such as software or hardware devices, its implementation among stakeholders working with individuals with autism spectrum disorder (ASD) is slow. This suggests that there might be a number of challenges that hinder technology adoption or its continued usage. The current project aimed to investigate stakeholders’ perceptions on potential barriers in adopting technology. We involved 17 stakeholders, including parents of children with ASD, service providers, and administrators of ASD organizations, in interviews. Thematic analysis yielded three themes: (a) making the right choice, (b) apprehension and concern about uptake, and (c) external obstacles to implementation. This project was the first study to involve key stakeholders to determine components that take place in utilization and adoption of technologies in the field of 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 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)0.000
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: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.223
Threshold uncertainty score0.523

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.027
GPT teacher head0.276
Teacher spread0.249 · 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 designTheoretical or conceptual
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

Citations19
Published2019
Admission routes2
Has abstractyes

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