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Record W4408197446 · doi:10.1080/17483107.2025.2472268

Parents’ attitudes towards using assistive technologies for children with ASD in Jordan

2025· article· en· W4408197446 on OpenAlexaff
Bara’ah A. Bsharat, Ahmad Hussein Al-Duhoun, Parisa Ghanouni, Raya Alhusban, Jasmine Begeske

Bibliographic record

VenueDisability and Rehabilitation Assistive Technology · 2025
Typearticle
Languageen
FieldHealth Professions
TopicAssistive Technology in Communication and Mobility
Canadian institutionsDalhousie University
Fundersnot available
KeywordsExpectancy theoryUnified theory of acceptance and use of technologyPsychologyAssistive technologyAutism spectrum disorderVariance (accounting)Developmental psychologyApplied psychologyAutismSocial supportSocial influenceClinical psychologySocial psychologyComputer scienceBusiness

Abstract

fetched live from OpenAlex

This study aimed to evaluate the acceptance and attitudes of Jordanian parents toward assistive technology (AT) for children with autism spectrum disorder (ASD) using the Unified Theory of Acceptance and Use of Technology (UTAUT). In this cross-sectional study, 130 parents participated, most female (73.8%) and over 34 (70.8%). The majority (89.6%) reported that their children used smartphones, with 68.5% using them several times daily. Smartphones (89.6%) and iPads (24%) were the most frequently used technologies, while talking books (4%) and smart boards (2.4%) had the lowest usage. UTAUT results showed moderate agreement in most factors: effort expectancy (68.7%), performance expectancy (58.7%), and attitudes toward technology (65%). Notably, 47.8% of parents reported low social support for using AT, likely due to limited awareness and financial constraints. Regression analysis revealed that technology usage explained 41% of the variance in performance expectancy, while parental factors accounted for 43% of the variance in effort expectancy. Significant positive relationships were found between AT usage, behavioral intention, and actual use. These findings suggest that increasing technology usage and social support may enhance the adoption of AT for children 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 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)0.005
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.031
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0010.005
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0010.001
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 head0.041
GPT teacher head0.420
Teacher spread0.379 · 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

Citations0
Published2025
Admission routes1
Has abstractyes

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