Related Experiment Video
Updated: May 16, 2026

A Familiarization Protocol Facilitates the Participation of Children with ASD in Electrophysiological Research
Published on: July 31, 2017
Factors associated with participation in employment for high school leavers with autism
Hsu-Min Chiang1, Ying Kuen Cheung, Huacheng Li
1Intellectual Disability/Autism Program, Department of Health and Behavior Studies, Teachers College, Columbia University, Box 223, 525 West 120th St, New York, NY 10027, USA. hchiang@tc.columbia.edu
Abstract:
This study aimed to identify the factors associated with participation in employment for high school leavers with autism. A secondary data analysis of the National Longitudinal Transition Study 2 (NLTS2) data was performed. Potential factors were assessed using a weighted multivariate logistic regression. This study found that annual household income, parental education, gender, social skills, whether the child had intellectual disability, whether the child graduated from high school, whether the child received career counseling during high school, and whether the child's school contacted postsecondary vocational training programs or potential employers were the significant factors associated with participation in employment. These findings may have implications for professionals who provide transition services and post-secondary programs for individuals with autism.
More Related Videos
Related Concept Videos
Autism Spectrum Disorder
These core symptoms manifest differently among individuals, ranging from mild to severe. The disorder's complexity extends beyond its clinical presentation, encompassing a diverse range of biological, cognitive, and sociocultural influences.
Modeling in Therapy
Participant Modeling
Participant modeling involves therapists demonstrating calm and effective behaviors in situations...
Factors Influencing Attraction V: Social Skills
Attention-Deficit/Hyperactivity Disorder
Diagnostic Criteria and Symptoms
To diagnose ADHD, symptoms must manifest before age 12 and be evident across multiple settings.
Factorial Design

