Structured visual analysis of single‐case experimental design data: Developments and technological advancements

Abstract

Visual analysis is the primary method used to interpret single‐case experimental design (SCED) data in applied behavior analysis. Research shows that agreement between visual analysts can be suboptimal at times. To address the inconsistent interpretations of SCED data, recent structured visual‐analysis technological advancements have been developed. To assess the extent to which structured visual analysis is used to guide or supplement applied behavior analysts' interpretation of SCED graphs, a systematic review between the years of 2015 to 2020 in the Journal of Applied Behavior Analysis was conducted. Findings showed that despite recent efforts to develop structured visual‐analysis tools and criteria, these methods are rarely used to analyze SCED data. An overview of structured visual‐analysis tools is shared, their utility is delineated, common characteristics are brought to light, and future directions for both research and their clinical use are highlighted.

Quantification of behavioral data with effect sizes and statistical significance tests

“…The nature of our task (comparing statistical and visual analysis as fairly as we could) stopped the contextual information from being available, though a differently designed study could potentially further show the importance of the visual analysis by including that information (we take for granted that visual analysis is important and the primary method for analyzing single case research). A further limitation is that we did not ask the visual analysts to use any structured criteria for decision‐making as part of the study, while researchers have called for more use of such methods (Dowdy et al, 2022). A more carefully designed visual analysis task is a worthy extension for future research.…”

Reliability and validity of using structured visual‐inspection criteria to interpret latency‐based functional analysis outcomes

“…This would be especially ideal for latency-based FAs because these FA methods might be used for safety reasons when target behavior is severe or dangerous such that repeated emission of the behavior is undesirable (Thomason-Sassi et al, 2011). Further, the extent to which SVI methods can be used in clinical settings should be investigated (Dowdy et al, 2022).…”

“…To summarize, SVI methods have been found to be effective, reliable, and valid when compared to expert‐determined functions through visual inspection (Dowdy et al, 2022; Hagopian et al, 1997; Roane et al, 2013). There are several benefits of establishing SVI methods for interpreting FA outcomes including that (a) the rules may serve as an objective guide in the identification of behavioral functions (Hagopian et al, 1997), (b) agreement may be improved among researchers and clinicians (regardless of the rater's level of experience; Cox et al, 2021; Dowdy et al, 2022), and (c) they may aid in training others in accurate visual inspection of FA outcomes (Saini et al, 2018).…”

Extended alone and ignore assessments: A novel examination of factors that influence determination of an automatic function

“…Moreover, clinicians often rely on behavior characteristics (e.g., level, trend, variability) to make decisions regarding extended assessment outcome. When interpreting FA results, there are several tools that therapists may use to aid visual analysis, such as structured criteria (e.g., Dowdy et al., 2022; Hagopian et al., 1997; Lanovaz et al., 2019) and computerized programs (Zheng et al., 2021). These tools were developed for use with traditional single‐case designs (e.g., multi‐element) as opposed to a single series of consecutive sessions like extended assessments.…”