Work

Cyber Dependent Crime May Be Predicted by Autism Diagnosis but Not Autistic Traits

Year: 2026

Type: article

Abstract: PURPOSE: Previous research has produced mixed findings on the question of whether autism or the degree of autistic traits influence the prevalence of cybercrime. Our objective was to resolve some of these inconsistencies by investigating the relationships between autism diagnosis, autistic traits, advanced computer skills and different types of cybercrime in adults. METHODS: Autistic (N = 138) and non-autistic (N = 206) adults completed (a) the 50-item Autism Spectrum Quotient to assess degree of autistic traits, (b) the Cyber-Dependent Crime Questionnaire and the Cyber Crime Index to measure the prevalence of cyber-dependent and cyber-enabled crime, and (c) the LiES and the BIDR-16 to permit control for any tendency of participants to lie and provide socially desirable responses. Participants who endorsed any engagement in cybercrime also described the activity to ensure that any disclosure of cybercrime was in fact criminal activity. RESULTS: Autism diagnosis, but not autistic traits, was a significant predictor of cyber-dependent crime. However, this relationship was not mediated by advanced digital skills or theory of mind. Furthermore, neither autism diagnosis nor autistic traits predicted engagement in cybercrime more broadly. CONCLUSION: Contrary to the view that autistic individuals are no more likely to become involved in criminal activity than non-autistic adults, our study indicates that autism may be a risk factor for involvement in cybercrime. However, whether autism diagnosis is the driving factor in this relationship, or there are other individual and socio-environmental factors that might be critical enabling factors, awaits further investigation.

Source: Journal of Autism and Developmental Disorders

DOI: 10.1007/s10803-026-07580-1

Authors: Alliyza Lim, Neil Brewer

Institution: Flinders University

Language: English

Topic: Cybercrime and Law Enforcement Studies

Subfield: Information Systems

Field: Computer Science

Domain: Physical Sciences

SDG: Good health and well-being

Open Access status: hybrid

Estimated APC paid: $3,190