Matthew J Smith1, Rogério M Pinto1, Leann Dawalt2,3, J D Smith4,5, Kari Sherwood1, Rashun Miles1, Julie Taylor6, Kara Hume7, Tamara Dawkins8,9, Mary Baker-Ericzén10, Thomas Frazier11, Laura Humm12, Chris Steacy12. 1. School of Social Work, University of Michigan, Ann Arbor, Michigan, USA. 2. School of Social Work, University of Wisconsin, Madison, Wisconsin, USA. 3. Waisman Center, University of Wisconsin, Madison, Wisconsin, USA. 4. Department of Psychiatry and Behavioral Sciences, Northwestern University Feinberg School of Medicine, Chicago, Illinois, USA. 5. Center for Prevention Implementation Methodology (Ce-PIM) for Drug Abuse and HIV, Northwestern University Feinberg School of Medicine, Chicago, Illinois, USA. 6. Department of Pediatrics, Vanderbilt University Medicine Center, Nashville, Tennessee, USA. 7. School of Education, University of North Carolina, Chapel Hill, North Carolina, USA. 8. TEACCH Autism Program, University of North Carolina School of Medicine, Chapel Hill, North Carolina, USA. 9. Department of Psychiatry, University of North Carolina School of Medicine, Chapel Hill, North Carolina, USA. 10. Child and Adolescent Services Research Center, Rady Children's Hospital, San Diego, California, USA. 11. Autism Speaks, New York, New York, USA. 12. SIMmersion, LLC, Columbia, MD, USA.
Abstract
BACKGROUND: Virtual Reality Job-Interview Training (VR-JIT) is an efficacious Internet-based intervention for adults with severe mental illness (SMI). Evaluations of VR-JIT have shown improved interview skill and access to employment in several cohorts of adults with SMI and with autism spectrum disorders (ASD). VR-JIT trains participants how to fill out job applications and handle job interviews through e-learning content and applied practice. Trainees receive feedback through in-the-moment nonverbal cues, critiques, and recommendations for improving performance. Our study sought to adapt VR-JIT for transition-age youth with ASD (TAY-ASD). METHODS: We recruited TAY-ASD and adult stakeholders from public and charter schools, transition programs, and community service providers. Participants provided feedback on VR-JIT to enhance its applicability to TAY-ASD. We used community-engaged methods to process and analyze data from TAY-ASD and stakeholders, presented their quantitative and qualitative responses to community and scientific advisory boards for review and recommendations, and adapted the intervention design and content. RESULTS: Our adaptations included adding diversity (gender; race/ethnicity) to the virtual hiring manager; shortening the interview by reducing response options; increasing social storytelling to enhance engagement with VR-JIT core components; adding employment opportunities more relevant to younger workers; reducing the reading level; and making the e-learning content more accessible by adding bullet points, voiceover, and imagery/video; and adding new learning goals. CONCLUSIONS: This study presents a rigorous and innovative community-engaged methodology for adapting VR-JIT to meet the needs of TAY-ASD. We review our engagement with TAY-ASD and stakeholders, and discuss the standardized coding scheme we used to adapt VR-JIT and the usefulness and limitations of employing this methodology in adapting other behavioral interventions.
BACKGROUND: Virtual Reality Job-Interview Training (VR-JIT) is an efficacious Internet-based intervention for adults with severe mental illness (SMI). Evaluations of VR-JIT have shown improved interview skill and access to employment in several cohorts of adults with SMI and with autism spectrum disorders (ASD). VR-JIT trains participants how to fill out job applications and handle job interviews through e-learning content and applied practice. Trainees receive feedback through in-the-moment nonverbal cues, critiques, and recommendations for improving performance. Our study sought to adapt VR-JIT for transition-age youth with ASD (TAY-ASD). METHODS: We recruited TAY-ASD and adult stakeholders from public and charter schools, transition programs, and community service providers. Participants provided feedback on VR-JIT to enhance its applicability to TAY-ASD. We used community-engaged methods to process and analyze data from TAY-ASD and stakeholders, presented their quantitative and qualitative responses to community and scientific advisory boards for review and recommendations, and adapted the intervention design and content. RESULTS: Our adaptations included adding diversity (gender; race/ethnicity) to the virtual hiring manager; shortening the interview by reducing response options; increasing social storytelling to enhance engagement with VR-JIT core components; adding employment opportunities more relevant to younger workers; reducing the reading level; and making the e-learning content more accessible by adding bullet points, voiceover, and imagery/video; and adding new learning goals. CONCLUSIONS: This study presents a rigorous and innovative community-engaged methodology for adapting VR-JIT to meet the needs of TAY-ASD. We review our engagement with TAY-ASD and stakeholders, and discuss the standardized coding scheme we used to adapt VR-JIT and the usefulness and limitations of employing this methodology in adapting other behavioral interventions.
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