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Record W2580196347 · doi:10.2196/mental.6605

Social Skills Training for Adolescents With Autism Spectrum Disorder Using Facebook (Project Rex Connect): A Survey Study

2017· article· en· W2580196347 on OpenAlexvenueno aff
McLeod F. Gwynette, Danielle Morriss, Nancy J. Warren, James Truelove, Jennifer Warthen, Charles P. Ross, George Mood, Charlotte Anne Snook, Jeffrey J. Borckardt

Bibliographic record

VenueJMIR Mental Health · 2017
Typearticle
Languageen
FieldNeuroscience
TopicAutism Spectrum Disorder Research
Canadian institutionsnot available
FundersNational Institute of Mental Health
KeywordsNeurotypicalAutism spectrum disorderSocial mediaPsychologyPsychological interventionIntervention (counseling)Social skillsAutismThe InternetClinical psychologyDevelopmental psychologyPsychiatryWorld Wide WebComputer science

Abstract

fetched live from OpenAlex

BACKGROUND: Adolescents with autism spectrum disorder (ASD) spend more time using electronic screen media than neurotypical peers; preliminary evidence suggests that computer-assisted or Web-based interventions may be beneficial for social skills acquisition. The current generation of adolescents accesses the Internet through computers or phones almost daily, and Facebook is the most frequently used social media platform among teenagers. This is the first research study to explore the use of Facebook as a therapeutic tool for adolescents with ASD. OBJECTIVE: To study the feasibility and clinical impact of using a Web-based social platform in combination with social skills training for adolescents with ASD. METHODS: This pilot study enrolled 6 participants (all males; mean age 14.1 years) in an online social skills training group using Facebook. Data was collected on the participants' social and behavioral functioning at the start and conclusion of the intervention. Outcome measures included the Social Responsiveness Scale-2, the Social Skills Improvement System Rating Scale, and the Project Rex Parent Survey. Participants were surveyed at the conclusion of the intervention regarding their experience. RESULTS: No statistically significant differences in measurable outcomes were observed. However, the online addition of Facebook was well received by participants and their parents. The Facebook intervention was able to be executed with a careful privacy protocol in place and at minimal safety risk to participants. CONCLUSIONS: The utilization of Facebook to facilitate delivery of social skills training for adolescents with ASD appears to be feasible, although the clinical impact of such an addition is still unclear. It is important to note that social difficulties of participants persisted with the addition of the online platform and participants still required assistance to engage with peers in an online environment. A Web-based intervention such as the one utilized in this study has the potential to reach a mass number of patients with ASD and could address disparities in access to in-person treatment services. However, the complexity and evolving nature of Facebook's website and privacy settings leads to a number of unique online safety concerns that may limit its clinical utility. Issues encountered in our study support the development of an alternative and closed Web-based social platform designed specifically for the target audience with ASD; this platform could be a safer and more easily moderated setting for aiding in social skills development. Despite a small sample size with no statistically significant improvements of target symptoms, the use of electronic screen media as a therapeutic tool for adolescents with ASD is still a promising area of research warranting further investigation. Our study helps inform future obstacles regarding feasibility and safety.

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)0.002
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.003
Threshold uncertainty score0.012

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.001

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 head0.134
GPT teacher head0.446
Teacher spread0.312 · 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 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

Citations15
Published2017
Admission routes1
Has abstractyes

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