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Employment outcomes for autistic 1 individuals are often poorer relative to their neurotypical (NT) peers, resulting in a greater need for other forms of financial and social support. While a great deal of work has focused on developing interventions for autistic children, relatively less attention has been paid to directly addressing the employment challenges faced by autistic adults. One key impediment to autistic individuals securing employment is the job interview. Autistic individuals often experience anxiety in interview situations, particularly with open-ended questions and unexpected interruptions. They also exhibit atypical gaze patterns that may be perceived as, but not necessarily indicative of, disinterest or inattention. In response, we developed a closed-loop adaptive virtual reality (VR)–based job interview training platform, which we have named Career Interview Readiness in VR (CIRVR). CIRVR is designed to provide an engaging, adaptive, and individualized experience to practice and refine interviewing skills in a less anxiety-inducing virtual context. CIRVR contains a real-time physiology-based stress detection module, as well as a real-time gaze detection module, to permit individualized adaptation. We also present the first prototype of the CIRVR Dashboard, which provides visualizations of data to help autistic individuals as well as potential employers and job coaches make sense of the data gathered from interview sessions. We conducted a feasibility study with 9 autistic and 8 NT individuals to assess the preliminary usability and feasibility of CIRVR. Results showed differences in perceived usability of the system between autistic and NT participants, and higher levels of stress in autistic individuals during interviews. Participants across both groups reported satisfaction with CIRVR and the structure of the interview. These findings and feedback will support future work in improving CIRVR’s features in hopes for it to be a valuable tool to support autistic job candidates as well as their potential employers.
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Design and Validation of a Stress Detection Model for Use with a VR Based Interview Simulator for Autistic Young Adults
Studies show that young autistic adults are under- or unemployed, with almost half never holding a paying job in their 20’s. Unemployment within this population leads to decreased personal growth and increased dependence on caregivers. Research suggests that the interview process is one of the largest barriers to employment for this population. Autistic individuals often struggle with emotion regulation, which can be exacerbated by the interview process. To address this, we propose the use of a stress detection model in conjunction with a virtual reality interview simulator. This combination will allow for the interview to adapt to the state of the participant to improve the skills and engagement of the user and positively influence their comfort level. Data regarding negative affective responses to categories of questions can also be used to inform employers on better interviewing techniques. A model was designed using data obtained from neurotypical participants completing a modified Computerized Paced Serial Addition Task (PASAT-C) and evaluated on a dataset obtained from Autistic participants who took part in a simulated interview. Agreement between the model and ground truth was compared based on Pearson correlation coefficients. It was found that was r(289) = 0.28, which was statistically significant (p < .001; CI: 0.17 to 0.38). Our preliminary results provide evidence for the validity of observer-based labeling of data captured using a wrist-worn physiological sensor.
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- PAR ID:
- 10293119
- Date Published:
- Journal Name:
- International Conference on Human-Computer Interaction (HCII)
- Volume:
- 12768
- Page Range / eLocation ID:
- 580-588
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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- Free Publicly Accessible Full Text
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Accepted Manuscript1.0
- Conference Paper:
- https://doi.org/10.1007/978-3-030-78092-0_40
