Video-based modeling: Differential effects due to treatment protocol
Highlights
► Meta-analysis of video based modeling (VBM) for individuals with disabilities. ► Differential effects do not exist based on the type of VBM implemented. ► The type of model utilized moderates the effect of VBM on targeted outcomes. ► Variations in procedural implementation of VBM appear to influence intervention effect size.
Introduction
Educational reform and recent legislation such as No Child Left Behind (NCLB; U.S. Department of Education, Office of the Deputy Secretary, 2001) and revisions to the Individuals with Disabilities Education Act (Individuals with Disabilities Education Improvement Act, 2004) obligate schools to utilize research-based teaching practices. Given the emphasis on isolating evidence based practices for individuals with disabilities, the literature base has been proliferated with seemingly efficacious and promising interventions (Odom, 2009). Video-based modeling (VBM) has received much attention as a practice with considerable potential for enhancing multiple skills for individuals with disabilities (Rayner et al., 2009, Shukla-Mehta et al., 2010). However, questions remain regarding the impact of variations in procedural implementation on the efficacy of the intervention (Shukla-Mehta et al., 2010).
VBM induces simulation of observed skills or behaviors by exposing the target individual to a model correctly demonstrating the target skill or behavior via a video-recording (Delano, 2007, Hitchcock et al., 2003). Additionally, VBM is an educational tool that allows for a precise enactment of the targeted skill that can be modeled to a number of students at numerous times and locations (Biederman and Freedman, 2007, Corbett and Abdullah, 2005). VBM provides a feasible and efficient means for capitalizing on the educational benefits of imitation and modeling as it allows for unlimited exposure to a variety of examples (Ayres, Maguire, & McClimon, 2009). Even if empirical evidence indicated statistically identical outcomes between in vivo and video-based modeling, VBM would be more valuable due to the additional advantages related to time and cost, as well as continuity across settings (Biederman and Freedman, 2007, Delano, 2007, Mechling et al., 2005, Rayner et al., 2009).
Two categories of VBM that will be discussed include video modeling with other as model (VMO) and video self-modeling (VSM). VMO involves the individual watching a video of another adult or peer, either known or unknown, demonstrating the desired skill with the expectation that the behavior will be imitated (Bellini and Akullian, 2007, Shukla-Mehta et al., 2010). VSM involves the target individual performing as the model for the creation of the video (Dowrick, 1999, Shukla-Mehta et al., 2010). VSM is comprised of two distinct subcategories including positive self-review and feedforward (Dowrick, 1999, McCoy and Hermansen, 2007). Feedforward involves video-recording the individual while he or she is being assisted in performing a skill to the best of his or her ability, with the implementation of additional interventions including coaching, instruction, and reinforcement, which ensure that each step or component of the skill is correctly demonstrated by the target individual, with or without prompts or cues (Dowrick, 1999, Dowrick et al., 2006, Hitchcock et al., 2003). The individual then views an edited video which has had the assistance and incorrect performances removed. Positive self-review, on the other hand, involves recording the individual engaged in natural activities and then editing out examples of undesired behavior or inaccurate performance (Dowrick et al., 2006, Hitchcock et al., 2004). The final video model is then a sample of the individual engaged in only positive exemplars of the targeted outcome (Dowrick, 1999, Hitchcock et al., 2003).
In addition to the two specific types of VBM, both have additional variations in protocol. First, recording can be conducted either from a third person or first-person perspective. The first-person perspective, referred to as point-of-view modeling, is filmed from the perspective of the viewer (Shukla-Mehta et al., 2010) without actually displaying the model, Additionally, VBM interventions have been implemented either alone, as a primary component of an intervention, or as part of an intervention package (Shukla-Mehta et al., 2010). Analysis of VBM with clear delineation between each type of VBM, and the variables for each type, as well as differentiation regarding effects based on whether the intervention was delivered alone or as part of a package continues to be a gap in the research (Bellini and Akullian, 2007, Shukla-Mehta et al., 2010).
Two meta-analyses (Baker et al., 2009, Bellini and Akullian, 2007) have previously evaluated the impact of VBM on targeted skills. Both meta-analyses utilized mean percent of non-overlapping data (PND) as the primary indicator of effectiveness across studies. Bellini and Akullian (2007) evaluated the impact of VMO and VSM, for increasing a variety of skills for individuals with autism spectrum disorder (ASD) whereas Baker et al. (2009) evaluated the use of VBM with participants with emotional disabilities as a primary diagnosis. Information about individual participant outcomes was not noted and the range of the reported mean PNDs, 29–100% (Bellini & Akullian, 2007) and 14–100% (Baker et al., 2009), indicated variable results. Utilizing Kruskall–Wallis, Bellini and Akullian (2007) indicated no statistically significant differences in results between VMO and VSM, types of targeted skills, and age groups. Baker et al. (2009) disaggregated the included studies based on targeted skill categories regardless of the type of VBM implemented, noting the majority of studies reviewed implemented video feedback. Neither meta-analyses evaluated differential effects that occur when VBM is implemented alone or with other components. The obtained range of results in both meta-analyses seem to indicate implementation factors may moderate the effectiveness of the intervention
Although these quantitative synthesis (Baker et al., 2009, Bellini and Akullian, 2007) provide useful information and do indicate VBM to be an effective intervention, several limitations exist. First, the inability to calculate p-values or confidence intervals with PND prevents meaningful comparison of results across studies and participants based on overlap (Kavale, 2010, Parker et al., 2009, Vannest et al., 2010a) and limits one of the benefits of meta-analysis, which is the ability to assess for variability based on study features (Kavale, 2010, Scruggs and Mastropieri, 1998).
Second, the reviews failed to evaluate differential effects that might occur due to variations in procedural implementation. Consideration as an evidence-based intervention that is transferable into practice requires explicit description of all components of the independent variable in order to promote replication both in future research and applied settings (Horner et al., 2005). Identifying “video modeling” as an effective intervention, is imprecise, as the term is used liberally to embody a wide variety of interventions employing the theory of modeling via video recordings (Delano, 2007). When VBMs are evaluated without segregating based on the type of VBM employed as well as the additional components included in the intervention, the comparisons cannot be considered equivalent (Shukla-Mehta et al., 2010). Bellini and Akullian (2007) acknowledged the grouping of VBM with other interventions as a limitation in terms of evaluating the benefits of VBM alone. Partitioning the current VBM literature according to variations in delivery of the intervention by model, presentation, and additional components will allow for analyses that identify differential effects due to procedural implementation variables.
The purpose of this meta-analysis is to quantitatively analyze studies utilizing VBM to provide specificity regarding the implementation factors that yield the greatest magnitude of change on targeted outcomes. The following questions are addressed: (a) Are there differential effects on participant outcomes based on the type of VBM? (b) Does the model influence the magnitude of effect on outcomes? (c) Are there differential effects based on whether VBM is used alone, with reinforcement, or as part of an intervention package?
Section snippets
Search method
Studies were identified through an electronic search utilizing the ERIC and PsycInfo database through the Cambridge Scientific Abstracts (CSA) database. Additionally, the Education Full Text database through the Wilson search engine was also utilized. The search was limited to peer-reviewed studies and the following Boolean string searches were conducted: modeling or “observational learning” and disability or autism or ADHD or “attention deficit hyperactivity disorder” or behavior disorder or “
Descriptive summary of studies
Of the 56 studies included in the analysis, 42 utilized VMO as the intervention and 18 included VSM. The total exceeds the total number of studies because four of the articles included both VMO and VSM (Cihak and Shrader, 2008, Marcus and Wilder, 2009, Sherer et al., 2001, Van Laarhoven et al., 2009). A total of 177 participants were included in the studies. The VMO studies included participants ranging in age from 2 to 72 with diagnoses of either ASD or intellectual disability. The VSM studies
Discussion
The current evidence base for VBM does not precisely identify the variation in treatment effect that occurs due to variations in procedural implementation (Bellini and Akullian, 2007, Delano, 2007, Shukla-Mehta et al., 2010). The purpose of this meta-analysis was to evaluate the evidence base for the use of VBM as an intervention for individuals with disabilities with a specific focus on the differential effects due to the type of VBM implemented and procedural variables. Overall results
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