Using Video-based Interventions with Individuals with Autism Spectrum Disorders: Introduction to the Special Issue

The development of high quality user-friendly video capture and editing equipment at relatively low costs has resulted in wonderful opportunities to incorporate video technology into behavioral interventions for individuals with Autism Spectrum Disorders (ASD) (Goldsmith & LeBlanc, 2004). The most common strategy for incorporating video into behavioral intervention is video modeling (VM), which involves having a learner watch a videotape (rather than a live demonstration) of a person correctly performing the target behavior followed by an opportunity to imitate (Delano, 2007). Other video-based behavioral interventions (VBIs) include video-based feedback and video-based discrimination training. In video feedback, a learner and teacher watch video footage of the learner's performance while the teacher provides consequences for appropriate exemplars (e.g., praise or other reinforcers) and for non-exemplars (e.g., corrective feedback and suggestion for alternative behavior) (Thiemann & Goldstein, 2001). In discrimination training, the learner watches video footage that may or may not show their own performance and determines which behavior or category of behavior is exemplified in each scene (e.g., rude or polite, friendly joke or bullying). In the past 20 years, a substantial research literature has amassed to document the beneficial effects of VM for teaching a wide variety of skills to individuals with ASD (Bellini & Akullian, 2007; Delano, 2007). Recently, my students and I coded approximately 40 published studies on VM with individuals with ASD during a 20-year time span (1987-2007) (Dillon, LeBlanc & Geiger, 2009). Over half of those studies targeted social behavior (including social language) (Charlop-Christy, Le & Freeman, 2000; Geiger, LeBlanc, Dillon, & Bates, 2010; Nikopoulos, & Keenan, 2003; Sherer, et al., 2001), with self-help/daily living skills (e.g., Charlop-Christy et al., 2000; Keen, Brannigan, & Cuskelly, 2007) as the second most frequently targeted area. Three of the studies in our special issue represent diversity in the skills targeted with individuals with ASD. Allen, Wallace, Renes, Bowen and Burke demonstrate how video modeling could be used to teach a vocational skill to a young adult with ASD. Allen et al. used a commercial video training tape to teach a man with ASD to effectively use a WalkAround[TM] to interact with customers in a retail warehouse as part of his employment preparation. Given the growing importance of focusing on transition to adulthood and employment opportunities, I am delighted to have the needs of adults with ASD represented in our special issue. Blum-Dimaya, Reeve, Reeve and Hoch also illustrate how video modeling can be used in conjunction with gaming technology to teach modern, age-appropriate leisure skills using a multi-component package. Blum-Dimaya et al. taught children with ASD to play Guitar Hero II[TM] and conceptualized the game-embedded visual displays as a form of simultaneous video modeling where the individual has the opportunity to imitate during, rather than after, the streaming video footage. Not only does this study demonstrate a strategy for teaching a very socially valid target, but it also illustrates that when we categorize our VM interventions using a functional rather than topographical approach, we may actually discover new tools for VBIs. Finally, Charlop, Dennis, Carpenter, and Greenberg demonstrate the effects of video modeling for teaching the most complex multi-component social behavior studied to date. Their participants were able to learn to emit social language responses that were accurate with respect to content, intonation, accompanying gesture, and accompanying facial expressions during their comments about ongoing events. In addition to demonstrating the effectiveness of video modeling, researchers have also examined the characteristics of the VM or the video presentation that are most important to facilitate skill acquisition (e. …