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Record W4386116219 · doi:10.1177/13623613231192870

Digital citizenship of children and youth with autism: Developing guidelines and strategies for caregivers and clinicians to support healthy use of screens

2023· article· en· W4386116219 on OpenAlexafffund
Yael Mayer, Mor Cohen‐Eilig, Janice Chan, Natasha Kuzyk, Armansa Glodjo, Tal Jarus

Bibliographic record

VenueAutism · 2023
Typearticle
Languageen
FieldSocial Sciences
TopicChild Development and Digital Technology
Canadian institutionsUniversity of British Columbia
FundersUniversity of HaifaMichael Smith Health Research BC
KeywordsAutismScreen timePsychologyPsychological interventionDelphi methodMedicineClinical psychologyPsychiatry

Abstract

fetched live from OpenAlex

Over the past few years, screen-based usage among children and youth has increased significantly, particularly among those with autism. Yet current screen time guidelines do not address the specific needs of autistic children and youth. Therefore, the objective of this study was to develop specific and clear guidelines and strategies that caregivers and expert clinicians agree upon to support the digital citizenship of children with autism. Using the Delphi method, 30 experts, including 20 clinicians and 10 caregivers, were invited to complete a series of three surveys. The experts had to rate their agreement levels on a series of statements that included possible guidelines and strategies. The final statements to be included in the guidelines were accepted by more than 75% of the panel. The final guidelines included six sections: (1) general principles, (2) considerations for timing and content of leisure screen time use, (3) strategies for caregivers and clinicians to monitor and regulate screen time use, (4) behaviors to monitor for screen time overuse, (5) additional guidelines for clinicians, and (6) resources. The agreed-upon guidelines developed in this study could be the stepping stones for clinical interventions targeting screen time overuse of children with autism, addressing the screen time challenges that many families are experiencing. Lay Abstract Children and youth with autism use screens in their daily lives and in their rehabilitation programs. Although parents and clinicians experience specific challenges when supporting positive screen time use of children and youth with autism, no detailed information for this group exists. Therefore, this study aimed to develop clear guidelines that are agreed by expert clinicians and parents of children and youth with autism. Using a method called Delphi, 30 experts—20 clinicians and 10 caregivers, who have experience working with or caring for children and youth with autism were invited to complete a series of three surveys. In each round, the experts had to rate their agreement with statements regarding screen time management. The agreement level was set to 75%. The final themes to be included in the guidelines were accepted by more than 75% of the panel. The final guidelines included six main sections: (1) general principles, (2) considerations for timing and content of leisure screen time use, (3) strategies for caregivers and clinicians to monitor and regulate screen time use, (4) behaviors to monitor for screen time overuse, (5) additional guidelines for clinicians, and (6) resources. The new guidelines developed in this study can provide potential guidance on how to further the development of digital citizenship for children and youth with autism and provide strategies to families to help manage screen time use.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.595
Threshold uncertainty score0.363

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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 integrity0.0000.000
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 head0.112
GPT teacher head0.346
Teacher spread0.234 · 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

Citations16
Published2023
Admission routes2
Has abstractyes

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