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History of Video Modeling

Video modeling (VM) has been used as a tool to support skill development in individuals with autism since the late 1990s. While the medium to record and deliver the video model has rapidly advanced over the past 30 years, driven by drastic changes in technology, the defining characteristics behind VM have remained relatively unchanged. Video modeling is defined as the modeling of a target behavior in a recorded format that results in a video representation via an electronic medium (Ayres and Langone 2005; Bellini and Akullian 2007).

One of the seminal studies involving VM and individuals with autism spectrum disorder (ASD) was designed to compare VM to live modeling, and it was designed to teach a variety of skills (Charlop-Christy et al. 2000). Participants included five children with autism ranging in age from 7 to 11 years. Children with differing functioning levels (e.g., different mental ages, language ages, play skills) were purposefully selected to determine whether VM would be effective across severity levels. All of the children reportedly watched television for at least 30–60 min/day. Different target behaviors were chosen for each child depending on his or her need, as determined by assessments he or she received as part of his or her enrollment in an after-school behavior therapy program. Target behaviors included expressive labeling of emotions, independent play, spontaneous greetings, conversational speech, self-help skills, oral comprehension, cooperative play, and social play. Tasks were randomly assigned to the VM or in vivo condition and ranked by trained college students to be of similar levels of difficulty. Adults who were familiar to the participants provided the model in both the video and live conditions. It is important to note that no prompts or tangible rewards were presented to children during the VM condition, whereas in the in vivo condition, prompts to pay attention and social praise for correct responses were provided.

A multiple baseline design across participants was utilized. Results indicated that children acquired skills faster in the VM condition. Children also generalized target behaviors after VM, but did not generalize target behaviors after live modeling (Charlop-Christy et al. 2000). The total time children spent in the VM condition was 170 min, whereas the total time spent in the live modeling condition was 635 min. In other words, the VM condition was more time- and cost-effective than the in vivo condition. The researchers concluded that VM is an effective technique that can support skill development in children with ASD. Since that time, VM has been used to teach a variety of skills to children, adolescents, and adults with autism across multiple contexts.

A meta-analysis analyzing the effectiveness of VM as an intervention tool for children with autism was conducted on 23 studies published between 1987 and 2005 (Bellini an Akullian 2007). A total of 73 participants, ranging in age from 3 to 20 years, were included. The average number of VM sessions conducted was 9.5 with the average duration of each clip being reported as 3 min. Percentage of non-overlapping data points (PND) were analyzed across the three dependent variable categories and revealed that the highest intervention effects were found for functional skills, followed by social communication skills and then behavioral skills (Bellini and Akullian 2007). The researchers concluded that VM is an effective intervention strategy to teach skills to children with ASD, and skills are both maintained and generalized after treatment is concluded (Bellini and Akullian 2007).

Video modeling has been demonstrated to be an effective technique in schools and the community. Research has indicated that educators can apply VM in school settings. Bellini and Akullian (2007) reported that the majority of the studies they reviewed took place in school settings. In school settings, VM has been used to increase academic skills (e.g., Delano 2007; Kinney et al. 2003; Hitchcock et al. 2003), decrease disruptive behaviors (Apple et al. 2005; Buggey 2005), and increase social interactions (e.g., Cihak et al. 2009; Nikopoulos and Keenan 2003; Wert and Neisworth 2003). In general, the focus on community applications of VM has included increasing appropriate behaviors and effective transitions (e.g., Schreibman et al. 2000), but community applications have also focused on daily living skills by helping individuals with ASD choose items to purchase at a store (Alacantara 1994; Haring et al. 1995) and independently purchase items (Mechling et al. 2005).

Video modeling is an effective strategy to promote skill acquisition in children with ASD because they (a) are partial to visual stimuli (e.g., Kinney et al. 2003), (b) can focus more efficiently on restricted fields due to issues with overselectivity (i.e., attending to non-relevant stimuli; e.g., Corbett 2003), (c) often have exceptional memories and are skilled echoers (e.g., Charlop and Milstein 1989), and (d) appear to avoid face-to-face interactions (e.g., Charlop-Christy et al. 2000). In addition, VM has several practical advantages for use as an intervention tool, such as (a) the capacity to present an assortment of examples, (b) concise control over the modeling process, (c) exact repetition and reuse of video clips, and (d) cost and time efficiency of intervention (Corbett 2003).

Theoretical Support for Video Modeling

As mentioned previously, VM has been used to teach a variety of skills to children with autism including imitation, play skills, self-help skills, and social skills (e.g., Ayres and Langone 2005; Cardon 2012; Cardon and Wilcox 2011; D’Ateno et al. 2003). It has been suggested that VM supports the development of observational learning, specifically the cognitive and behavioral changes humans experience as a result of watching or observing others involved in similar actions (Bandura 1977; Corbett 2003). According to Bandura, observational learning, or social learning theory, is critical to the development and survival of human beings as we learn what we should and should not do by observing events that occur around us. For observational learning to be successful, four components must be present: attention, retention, production, and motivation. We pay attention to activities that are modeled and then retain that information to utilize later. The actions that are observed can then be imitated (Bandura 1977). Although every action that is observed does not translate into perfect imitation, the awareness of the action has been created. Further, Bandura posited that the accuracy of imitative acts is reliant on positive reinforcement and continued input from others. The motivational factors that shape imitation in observational learning differentiate Bandura’s theory from Piaget’s in that Piaget attributes the desire to imitate to intrinsic needs as opposed to external factors.

A relatively new theory, proposed by researchers working at the Medical Investigation of Neurodevelopmental Disorders (MIND) Institute at UC Davis, implicates the visual attention differences present in children with autism (Vivanti et al. 2008). Researchers wanted to determine what children with autism look at when an imitative act is demonstrated. They believed that patterns in children’s visual attention could provide insight into how actions are encoded and ultimately which acts are imitated based on those patterns (Vivanti et al. 2008). The study included 18 children with autism and 13 children with typical development. It is important to note that all of the imitative acts presented to the participants were through prerecorded video clips. No live models were used. When controlling for the language level of the participants, researchers discovered that both groups more accurately imitated actions involving objects than those involving gestures. In addition, both groups visually attended to the action region (region where the action was performed) more during tasks that involved object imitation; however, differences were found between the two groups with regard to visual attention to the face region (area of the face of the demonstrator performing the action). Specifically, the children with autism looked at the face region less than half the time the typical children spent looking at the face region. The researchers proposed that the decreased attention to the face region could provide specific insight into the relationship between imitation deficits and social deficits present in children with autism. Future research into the visual attention skills of children with autism and the impact that visual attention has on imitation is necessary to determine the accuracy of the visual attention theory.

In summary, VM is thought to work as an intervention for children with autism because of several specific elements. When used as an intervention tool, VM capitalizes on the visual preferences (e.g., television watching, lining up toys to view them, repeatedly watching objects spin) exhibited in many children with autism (Corbett 2003; Kinney et al. 2003). Further, the screen offers a restricted field of vision and can therefore focus a child’s attention on relevant stimuli while decreasing their tendency to attend to irrelevant stimuli (e.g., Charlop-Christy et al. 2000; Corbett 2003). Screens are highly motivating, and reinforcement to attend to the task is built right in (Corbett 2003). And finally, children with autism attend for longer periods of time to screens as opposed to live presentations of information (Cardon and Azuma 2012; Vivanti et al. 2008).

Parameters of Video Modeling and Autism

As is evidenced by the numerous studies, VM is an effective intervention tool that can be used to teach play skills, language skills, self-help skills, social communication skills, functional daily living skills, academic skills, and appropriate behaviors. In addition, a number of reviews and meta-analyses have been conducted that identify the ability of children with ASD to maintain learned skills and to generalize those skills to new, previously undeveloped behaviors (Bellini and Akullian 2007; Ayres and Langone 2005; McCoy and Hermansen 2007; Gelbar et al. 2012). With regard to additional parameters of VM, however, there are several other components that should be considered.

Original research surrounding VM and autism looked at school-age and adolescent children to determine whether it was an effective intervention tool, particularly when targeting self-help skills or social skills (e.g., Charlop and Milstein 1989; Charlop-Christy et al. 2000; Nikopoulos and Keenan 2003). While seminal studies reported that older children with ASD responded positively to VM, more recent research has targeted younger children with ASD. In 2011, Cardon and Wilcox demonstrated that VM to teach object imitation was effective for children with ASD as young as 20 months of age. Further, very young children with ASD responded to VM used to teach object imitation, self-help skills, gestural imitation, and verbal imitation (Cardon 2012, 2013). Given the wide age ranges of children who respond to VM and the rapid response times that have been reported, introducing it as an early technique to support skill development is recommended.

In the home environment, emerging research has demonstrated that VM can be used by caregivers to teach a number of skills. Specifically, caregivers have been able to effectively create their own video models at home in order to teach fine motor skills (e.g., cutting with scissors and correct pencil grip), self-help skills (e.g., bed making), play skills (e.g., pretend play with a doll, puzzle completion), and social skills such as responding with, “No thank you” when offered an unpreferred food item (Cardon 2012). Similarly, VM has been utilized to teach children with autism how to interact with their siblings. Research conducted by Reagon et al. (2006) determined that children with ASD could be taught via VM to interact with their siblings during several different pretend play scenarios (e.g., cowboy dress-ups, playing teacher). It is recommended that VM be considered as a possible intervention technique across settings with a variety of individuals.

As described, VM can support skill development in both younger and older children across settings; however, there are some advanced parameters of the video model that should be considered. To begin with, some children have been able to successfully learn fine motor skills, such as cutting and tracing (Cardon 2012) using VM; however, recent research has indicated that the size of the screen may impact skill acquisition when attempting to learn fine motor tasks. Specifically, researchers analyzed screen size to determine whether the size of the screen used to present the video model impacted skill acquisition (Mechling and Ayres 2012; Mechling and Youhouse 2012). Results indicated that fine motor tasks increased regardless of screen size; however, more correct responses resulted from the use of a larger screen, particularly if an intellectual disability was present. It is important to note, however, that to date there is no research to indicate any significant differences between smartphones, tablets, or iPod touches with regard to skill acquisition and VM.

Another element of the video model that is helpful to consider is the use of a verbal description or a verbal narrative as an accompanying element of the video model. While this seems like an obvious parameter when teaching social communication skills via VM, it is also beneficial when teaching other target skills. For example, children learning pretend play skills, gestures, and self-help skills via VM have demonstrated increased verbal language skills after exposure to the video model (e.g., Boudreau and D’Entremont 2010; Cardon and Wilcox 2011; Cardon 2012; McDonald et al. 2005). Given that verbal language may be a pivotal component of VM intervention, it is recommended that verbal descriptions or narratives be included along with the video model.

It has been recognized that children with ASD respond well when increased levels of motivation are present (Koegel and Koegel 2006). It has also been suggested that the nature of VM increases motivation because of the presence of the electronic medium (i.e., tablet, smartphone; Corbett 2003) and that children may respond to VM because highly preferred items are being utilized during the intervention (Carr et al. 2000; Mechling et al. 2006). A recent study analyzed skill acquisition during VM when both preferred and non-preferred items were present (Robinson and Cardon 2012). Results indicated that participants imitated actions with both preferred and non-preferred objects and, contrary to the previous research, participants imitated actions with non-preferred items more consistently than preferred items. In other words, imitation occurred at high rates regardless of item preference. It may be beneficial to include novel actions and objects when implementing VM.

Often when describing the how-to aspects of VM, researchers take care to describe how to create videos that are free of visual and auditory distractions, but research on the specific requirements of the video model is limited. A recent study looked at one element of possible visual distractions that may be present in a video model (Gilbert and Cardon 2012). The researchers recorded models performing a target action with an object in front of a green screen. Three separate visual backgrounds were then embedded over the green screen: a plain background, a distracting background, and a moving background. In other words, the visual foreground of the video remained the same, while the background visually changed. Children with autism were shown the video clips in random order. All of the children that participated were able to imitate the target action with the object regardless of what background was present in the video. While further research is needed, the willingness that children with ASD have to imitate what they see on a video, be it preferred or non-preferred, and distracting or not, is an important component to take into consideration.

Video Modeling Implementation

In general, children with ASD that have shown a prior preference for visual stimuli or visual learning may respond better to VM as an intervention technique (Sherer et al. 2001). There are typically three types of VM that have been used to teach a variety of skills: classic video modeling, point of view, and video self-modeling.

Classic VM involves filming a model performing a target action. The video captures the model and the target action being completed correctly. The video is then presented to the child with autism. The child watches the video and is then given a chance to perform the task. As mentioned previously, classic VM has been used effectively to teach play skills, social skills, self-help skills, daily living skills, language skills, and academic skills.

Point of view video modeling (POVM) involves filming from the point of view of the model, often only showing their hands close-up as they complete a task. This type of VM has been effectively used to teach toy play to preschoolers (Hine and Wolery 2006), self-help skills, such as dressing (Norman et al. 2001), and daily living skills (Shipley-Benamou et al. 2002; Sigafoos et al. 2005). To some degree, POVM was helpful in supporting social behaviors in preschool and school-age children with ASD (Tetreault and Lerman 2010).

Video self-modeling (VSM) involves recording the child with autism performing the target skill multiple times and then editing the recordings to create a final product in which the child is shown to be demonstrating the skill correctly. The child only views the video of himself or herself performing the task correctly. VSM is more time-consuming and requires more technical skills because of the editing requirements; however, it has been found to be effective when teaching a variety of skills. Specifically, VSM can improve language and social skills, (e.g., Bellini and Akullian 2007; Lantz 2005), on-task behavior (Coyle and Cole 2004), and adherence to classroom expectations (e.g., Lang et al. 2009; Cihak 2011). A number of reviews and meta-analyses have been conducted to determine whether the type of VM used (i.e., classic vs. self versus point of view) impacts effectiveness. To date, no differences have been found and all types of VM have met criteria for evidence-based practice (Horner et al. 2005).

With regard to the age of the individual acting as the video model, research indicates that siblings, peers, and adults all make effective models (e.g., Bellini and Akullian 2007; Cardon 2012). That being said, working with more mature models may take less time and training, making it more cost-effective. While the majority of VM research focuses on a one-on-one session when showing the child with ASD the video model, there is emerging research that indicates that VM can be used effectively in group settings (Kroeger et al. 2007; Plavnick et al. 2013). The flexibility within VM as an intervention contributes to its usability and practicality.

While steps to creating a video model used to require a certain level of technical ability, with the introduction of smartphones and tablet computers, the technical skills to create a video model are almost universal. While these steps must be adapted to the type of device being used and the type of video model being created (i.e., classic vs. self vs. point of view), the basics steps are as follows:

  1. 1.

    Determine the target behavior you would like to focus on. The target behavior should be developmentally appropriate given the child’s age and stage.

  2. 2.

    Determine who you would like to film as the video model.

  3. 3.

    Determine how you would like to film the video (i.e., classic vs. self vs. point of view).

  4. 4.

    Have the model practice the target behavior several times. Creating a task analysis, or a list of the necessary steps, can be helpful. It is helpful to have the model verbalize, or describe, what they are doing. Or, think about what a child would say naturally when completing the task. Verbalizing during the video model is important because children often start to imitate what they hear and see!

  5. 5.

    Practice filming the model performing the target behavior with the video application on your smartphone or tablet.

  6. 6.

    Watch the video to make sure that you have captured every step of the target behavior and to make sure that the sound and picture quality is clear.

  7. 7.

    Present the video model to the child in an environment that is appropriate and conducive to their learning. Be sure to have any objects or materials that the child will need to complete the task nearby.

  8. 8.

    Play the video model for the child one time. If an object is required for the target behavior, have it sitting nearby where they can reach it or be sure to immediately hand them the item when the video is over.

  9. 9.

    If the child imitates, praise them! If the child does not imitate, play the video for them again.

  10. 10.

    If the child has three unsuccessful attempts, feel free to physically prompt the child to perform the target behavior. A physical prompt can help them understand what is required of them and may increase their level of success.

Children with ASD often like to watch the videos over and over again. As long as they are also performing the target behavior, watching the videos only reinforces the skill. They can watch the videos several times a day or several times a week. As mentioned previously, researchers have discovered that children can learn multiple skills via VM at the same time, so feel free to choose several target behaviors at once. Not all children respond to VM, but those that do tend to respond quickly (Charlop-Christy et al. 2000; Cardon 2012). If a child is struggling, you can always back off to one skill or review the video to see whether something needs to be rerecorded.

Video modeling is a well-researched intervention and can be used by caregivers and clinicians alike. It is a highly effective and efficient tool that supports a range of target behaviors in an assortment of environments. Over the past 30 years, VM has become more commonplace and it is a powerful tool that continues to enrich the lives of children with autism.