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Faustmann LL, Altgassen M. Practice is the best of all instructors-Effects of enactment encoding and episodic future thinking on prospective memory performance in high-functioning adults with autism spectrum disorder. Autism Res 2024. [PMID: 38800974 DOI: 10.1002/aur.3165] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/17/2023] [Accepted: 05/06/2024] [Indexed: 05/29/2024]
Abstract
Prospective memory (PM) is the ability to remember to carry out intended actions in the future. The present study investigated the effects of episodic future thinking (EFT) and enactment encoding (EE) on PM performance in autistic adults (ASD). A total of 72 autistic individuals and 70 controls matched for age, gender, and cognitive abilities completed a computerized version of the Dresden breakfast Task, which required participants to prepare breakfast following a set of rules and time restrictions. A two (group: ASD vs. controls) by three (encoding condition: EFT vs. EE vs. standard) between-subjects design was applied. Participants were either instructed to engage in EFT or EE to prepare to the different tasks prior to performing the Dresden breakfast or received standard instructions. Analyses of variance were conducted. Autism-spectrum-disorders (ASD) participants did not differ from control participants in their PM performance, regardless of which strategy they used. Compared to the standard condition, EE but not EFT improved time-based PM performance in all participants. This is the first study to find spared time-based PM performance in autistic individuals. The results confirm earlier results of beneficial effects of EE on PM performance. Findings are discussed with regards to the methodology used, sample composition as well as autistic characteristics.
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Affiliation(s)
- Larissa L Faustmann
- Department of Psychology, Johannes Gutenberg University Mainz, Mainz, Germany
| | - Mareike Altgassen
- Department of Psychology, Johannes Gutenberg University Mainz, Mainz, Germany
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Kim SI, Jang SY, Kim T, Kim B, Jeong D, Noh T, Jeong M, Hall K, Kim M, Yoo HJ, Han K, Hong H, Kim JG. Promoting Self-Efficacy of Individuals With Autism in Practicing Social Skills in the Workplace Using Virtual Reality and Physiological Sensors: Mixed Methods Study. JMIR Form Res 2024; 8:e52157. [PMID: 38206652 PMCID: PMC10811570 DOI: 10.2196/52157] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/05/2023] [Revised: 11/01/2023] [Accepted: 11/01/2023] [Indexed: 01/12/2024] Open
Abstract
BACKGROUND Individuals with autism often experience heightened anxiety in workplace environments because of challenges in communication and sensory overload. As these experiences can result in negative self-image, promoting their self-efficacy in the workplace is crucial. Virtual reality (VR) systems have emerged as promising tools for enhancing the self-efficacy of individuals with autism in navigating social scenarios, aiding in the identification of anxiety-inducing situations, and preparing for real-world interactions. However, there is limited research exploring the potential of VR to enhance self-efficacy by facilitating an understanding of emotional and physiological states during social skills practice. OBJECTIVE This study aims to develop and evaluate a VR system that enabled users to experience simulated work-related social scenarios and reflect on their behavioral and physiological data through data visualizations. We intended to investigate how these data, combined with the simulations, can support individuals with autism in building their self-efficacy in social skills. METHODS We developed WorkplaceVR, a comprehensive VR system designed for engagement in simulated work-related social scenarios, supplemented with data-driven reflections of users' behavioral and physiological responses. A within-subject deployment study was subsequently conducted with 14 young adults with autism to examine WorkplaceVR's feasibility. A mixed methods approach was used, compassing pre- and postsystem use assessments of participants' self-efficacy perceptions. RESULTS The study results revealed WorkplaceVR's effectiveness in enhancing social skills and self-efficacy among individuals with autism. First, participants exhibited a statistically significant increase in perceived self-efficacy following their engagement with the VR system (P=.02). Second, thematic analysis of the interview data confirmed that the VR system and reflections on the data fostered increased self-awareness among participants about social situations that trigger their anxiety, as well as the behaviors they exhibit during anxious moments. This increased self-awareness prompted the participants to recollect their related experiences in the real world and articulate anxiety management strategies. Furthermore, the insights uncovered motivated participants to engage in self-advocacy, as they wanted to share the insights with others. CONCLUSIONS This study highlights the potential of VR simulations enriched with physiological and behavioral sensing as a valuable tool for augmenting self-efficacy in workplace social interactions for individuals with autism. Data reflection facilitated by physiological sensors helped participants with autism become more self-aware of their emotions and behaviors, advocate for their characteristics, and develop positive self-beliefs.
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Affiliation(s)
- Sung-In Kim
- Department of Psychiatry, Seoul National University Bundang Hospital, Bundang, Republic of Korea
| | - So-Youn Jang
- Georgia Institute of Technology, Atlanta, GA, United States
| | - Taewan Kim
- Department of Industrial Design, Korea Advanced Institute of Science and Technology, Daejeon, Republic of Korea
| | - Bogoan Kim
- Department of Data Science, Hanyang University, Seoul, Republic of Korea
| | - Dayoung Jeong
- Department of Artificial Intelligence, Hanyang University, Seoul, Republic of Korea
| | - Taehyung Noh
- Department of Artificial Intelligence, Hanyang University, Seoul, Republic of Korea
| | - Mingon Jeong
- Department of Artificial Intelligence, Hanyang University, Seoul, Republic of Korea
| | - Kaely Hall
- School of Interactive Computing, Georgia Institute of Technology, Atlanta, GA, United States
| | - Meelim Kim
- Department of Preventive Medicine, Yonsei University College of Medicine, Seoul, Republic of Korea
- Herbert Wertheim School of Public Health and Human Longevity Science, University of California San Diego, San Diego, CA, United States
- The Design Lab, University of California San Diego, San Diego, CA, United States
- Center for Wireless & Population Health Systems Calit2's Qualcomm Institute, University of California San Diego, San Diego, CA, United States
| | - Hee Jeong Yoo
- Department of Psychiatry, Seoul National University Bundang Hospital, Seongnam, Republic of Korea
- Department of Psychiatry, Seoul National University College of Medicine, Seoul, Republic of Korea
| | - Kyungsik Han
- Department of Data Science, Hanyang University, Seoul, Republic of Korea
- Department of Artificial Intelligence, Hanyang University, Seoul, Republic of Korea
| | - Hwajung Hong
- Department of Industrial Design, Korea Advanced Institute of Science and Technology, Daejeon, Republic of Korea
| | - Jennifer G Kim
- Georgia Institute of Technology, Atlanta, GA, United States
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