Comparison of Social Media Use Among Adolescents with Autism Spectrum Disorder and Non-ASD Adolescents
Bibliographic record
Abstract
Naseem Alhujaili,1,2 Elyse Platt,2 Sarosh Khalid-Khan,2 Dianne Groll2 1Division of Psychiatry, Department of Internal Medicine, Faculty of Medicine in Rabigh, King Abdulaziz University, Jeddah, Saudi Arabia; 2Department of Psychiatry, Queen’s University, Kingston, ON, CanadaCorrespondence: Naseem Alhujaili, Email nalhujaili@kau.edu.saBackground: It has been well documented that social media use among adolescents is rising. However, most research has focused on social media use among typically developing adolescents and less on its use among adolescents with autism spectrum disorder (ASD). The goal of this study was to compare the time spent as well as to identify the purpose of social media use in adolescents with ASD compared to non-ASD adolescents.Methods: This was a cross-sectional study of adolescents between ages 13– 18 who were attending a hospital-based child and adolescents psychiatry clinic. Participants completed a self-report 18-item questionnaire to assess the pattern and reasons for using social media sites. The sample size was 26 for ASD and 24 for the non-ASD group.Results: We found that the time spent on social media among adolescents with ASD was comparable to those without ASD diagnosis. However, participants with ASD differed from their non-ASD counterparts in both preferred social media sites as well as reasons for use. The most favourable social media site for ASD adolescents was YouTube. In contrast, the preferred social media site among adolescents without ASD was Snapchat. About 92.3% of participants without ASD reported using social media sites for primarily social interactions. In contrast, 59.1% of participants with ASD reported entertainment purposes as their primary reason for choosing a social media site.Conclusion: Although the current study is based on a small sample of participants, the findings suggest that the pattern of usage and reasons for using social media differ significantly between the two groups. There is, therefore, a definite need for further research with a larger sample size to examine the implications of these differences and to determine how social media could be used as a tool for learning social skills and its efficacy and safety in the ASD population.Keywords: autism, social media, adolescents, ASD and social networking sites
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".