Meta-analyses and effect sizes in applied behavior analysis: A review and discussion

Extensions of open science for applied behavior analysis: Preregistration for single-case experimental designs

Open science practices are designed to enhance the utility, integrity, and credibility of scientific research. This article highlights how preregistration in open science practice can be leveraged to enhance the rigor and transparency of single-case experimental designs within an applied behavior analysis framework. We provide an overview of the benefits of preregistration including increased transparency, reduced risk of researcher bias, and improved replicability, and we review the specific contexts under which these practices most benefit the proposed framework. We discuss potential concerns with and unique considerations for preregistering experiments that use single-case designs, with practical guidance for researchers who are seeking to preregister their studies. We present a checklist as a tool for researchers in applied behavior analysis to use for preregistration and provide recommendations for our field to strengthen the contingencies for open science practices that include preregistration.

A Quantitative Systematic Literature Review of Combination Punishment Literature: Progress Over the Last Decade

This review evaluated single-case experimental design research that examined challenging behavior interventions utilizing punishment elements. Thirty articles published between 2013 and 2022 met study inclusion criteria. Study quality was also assessed. Through multiple levels of analysis (e.g., descriptive statistics, non-parametric statistics), we examined (a) participant and study trends, (b) differential outcomes related to temporal reinforcement approaches (antecedent, consequent, or combined reinforcement) applied alongside punishment element(s), (c) differential outcomes related to the punishment type (negative, positive) applied alongside reinforcement, and (d) effect sizes associated with study rigor across peer-reviewed and gray literature. Our results may tentatively suggest that, for certain situations, concurrently applying punishment with antecedent reinforcement approaches may coincide with significantly larger effect sizes compared to combined temporal reinforcement approaches, while positive punishment applied concurrently with reinforcement may coincide with larger but non-significant intervention effects. Most featured articles met rigor criteria, but larger effects were seen in peer-reviewed literature.

Generalized Linear Mixed Effects Modeling (GLMM) of Functional Analysis Graphical Construction Elements on Visual Analysis

Multielement designs are the quintessential design tactic to evaluate outcomes of a functional analysis in applied behavior analysis. Protecting the credibility of the data collection, graphing, and visual analysis processes from a functional analysis increases the likelihood that optimal intervention decisions are made for individuals. Time-series graphs and visual analysis are the most prevalent method used to interpret functional analysis data. The current project included two principal aims. First, we tested whether the graphical construction manipulation of the x-to-y axes ratio (i.e., data points per x- axis to y-axis ratio [DPPXYR]) influenced visual analyst's detection of a function on 32 multielement design graphs displaying functional analyses. Second, we investigated the alignment between board certified behavior analysts (BCBAs; N = 59) visual analysis with the modified visual inspection criteria (Roane et al., Journal of Applied Behavior Analysis, 46, 130-146, 2013). We found that the crossed GLMM that included random slopes, random intercepts, and did not include an interaction effect (AIC = 1406.1, BIC = 1478.2) performed optimally. Second, alignment between BCBAs decisions and the MVI appeared to be low across data sets. We also leveraged current best practices in Open Science for raw data and analysis transparency.

How Can Qualitative Methods Be Applied to Behavior Analytic Research: A Discussion and Suggestions for Implementation

Behavior analysts in research and clinical practice are interested in an ever-expanding array of topics. They are compelled to explore the social validity of the interventions they propose and the findings they generate. As the field moves in these important directions, qualitative methods are becoming increasingly relevant. Representing a departure from small-n design favored by behavior analysts, qualitative approaches provide analysts a unique set of tools to answer questions that prioritize voice, experience, and understandings in context. Despite recognition of the value of qualitative approaches in other disciplines, application of qualitative methods in behavior analysis remains limited. One likely explanation is that behavior analysts are not yet fluent in applying qualitative approaches within their clinical and research investigations. To address this issue, exploration of qualitative research approaches in behavior analytic literature is needed, alongside practical advice for analysts who are interested in using qualitative methods. This article briefly outlines qualitative literature which pertains to behavior analysts wanting to incorporate qualitative methods into their inquiries. Attention is primarily drawn to the need for coherence in designing and implementing a robust qualitative study that aligns with the behavior analyst's aims and perspective on knowing. A set of guiding questions are provided to orient behavior analysts to considerations in qualitative research and outline how analysts can conceptualize a strong qualitative study. This article aims to support increased application of qualitative methods by behavior analysts, where these methods best address the function of the behavior analytic investigation.

A Meta-Analysis of Anomia Treatment in Bilingual Aphasia: Within- and Cross-Language Generalization and Predictors of the Treatment Outcomes

PURPOSE

The present meta-analysis investigated the efficacy of anomia treatment in bilingual and multilingual persons with aphasia (BPWAs) by assessing the magnitudes of six anomia treatment outcomes. Three of the treatment outcomes pertained to the "trained language": improvement of trained words (treatment effect [TE]), within-language generalization of semantically related untrained words (WLG-Related), and within-language generalization of unrelated words (WLG-Unrelated). Three treatment outcomes were for the "untrained language": improvement of translations of the trained words (cross-language generalization of trained words [CLG-Tx]), cross-language generalization of semantically related untrained words (CLG-Related), and cross-language generalization of unrelated untrained words (CLG-Unrelated). This study also examined participant- and treatment-related predictors of these treatment outcomes.

METHOD

This study is registered in the International Prospective Register of Systematic Reviews (PROSPERO) under the number CRD42023418147. Nine electronic databases were searched to identify word retrieval treatment studies of poststroke BPWAs of at least 6 months postonset. Pre- and posttreatment single-word naming scores were extracted for each eligible participant and used to calculate effect sizes (within-case Cohen's d) of the six treatment outcomes. Random-effects meta-analyses were conducted to assess weighted mean effect sizes of the treatment outcomes across studies. Multiple linear regression analyses were used to examine the effects of participant-related variables (pretreatment single-word naming and comprehension representing poststroke lexical processing abilities) and treatment-related variables (type, language, and duration). The methodological quality of eligible studies and the risk of bias in this meta-analysis were assessed.

RESULTS

A total of 17 published studies with 39 BPWAs were included in the meta-analysis. The methodological quality of the included studies ranged from fair (n = 4) to good (n = 13). Anomia treatment produced a medium effect size for TE (M = 8.36) and marginally small effect sizes for WLG-Related (M = 1.63), WLG-Unrelated (M = 0.68), and CLG-Tx (M = 1.56). Effect sizes were nonsignificant for CLG-Related and CLG-Unrelated. TE was significantly larger than the other five types of treatment outcomes. TE and WLG-Related effect sizes were larger for BPWAs with milder comprehension or naming impairments and for treatments of longer duration. WLG-Unrelated was larger when BPWAs received phonological treatment than semantic and mixed treatments. The overall risk of bias in the meta-analysis was low with a potential risk of bias present in the study identification process.

CONCLUSIONS

Current anomia treatment practices for bilingual speakers are efficacious in improving trained items but produce marginally small within-language generalization and cross-language generalization to translations of the trained items. These results highlight the need to provide treatment in each language of BPWAs and/or investigate other approaches to promote cross-language generalization. Furthermore, anomia treatment outcomes are influenced by BPWAs' poststroke single-word naming and comprehension abilities as well as treatment duration and the provision of phonological treatment.

SUPPLEMENTAL MATERIAL

https://doi.org/10.23641/asha.25595712.

Rise of single-case experimental designs: A historical overview of the necessity of single-case methodology

ABSTRACTWindelband ([1894]1980) advocated that two approaches are used for accumulating scientific knowledge. The first is the idiographic approach that derives knowledge from a single unit, and the second is the nomothetic approach that accumulates knowledge of a group. Given these two approaches, the former matches case studies while the latter is more appropriate with experimental group studies. Scientists have criticized both methodologies for their various limitations. Later, the single-case methodology emerged as an alternative that potentially allays these limitations. In this context, this narrative review aims to describe the historical roots of single-case experimental designs (SCEDs) that have emerged to eliminate the tension of nomothetic and idiographic approaches over time. First, the review focuses on the emergence of SCEDs. Second, the strengths and challenges of SCEDs are reviewed, including those to address the limitations of group experimental and case studies. Third, the use and analyses of SCEDs are outlined, considering their current status. Fourth, this narrative review continues to delineate the dissemination of SCEDs in the modern scientific world. As a result, SCEDs can be evaluated as a method that has the potential to overcome the issues encountered in case description and group experimental research. Thus, that helps accumulate nomothetic and idiographic knowledge in determining evidence-based practices.

A comparison of parental attention and preferred items during tummy time: A consecutive controlled case series evaluation

Tummy time is an activity for infants to practice their early motor skills. Although most pediatricians recommend tummy time, parents may avoid the procedures due to indices of infant discomfort during this period. This consecutive controlled case series evaluation compared the effects of preferred items selected from a preference assessment with those of parental attention on head evaluation and negative vocalizations during tummy time. In addition, we directly evaluated parental choice by inviting parents to select which tummy time treatment they wanted to implement. We found that both preferred items and parental attention effectively increased head elevation and decreased negative vocalizations during tummy time; however, parents tended to prefer the treatment that included the preferred item.

A Meta-Analysis of Treatment for Self-Injurious Behavior in Children and Adolescents With Intellectual and Developmental Disabilities

Self-injurious behavior (SIB) among children and youth with developmental disabilities has not diminished in prevalence despite the availability of effective interventions, and the impact on quality of life for people and their families is devastating. The current meta-analysis reviews SIB intervention research between 2011 and 2021 using single-case experimental designs with children and youth up to 21 years old and provides a quantitative synthesis of data from high-quality studies including moderator analyses to determine effects of participant and study characteristics on intervention outcomes. Encouraging findings include a high level of effectiveness across studies in the decrease of SIB (Tau-U = -0.90) and increase of positive behavior (Tau-U = 0.73), as well as an increase in studies (relative to prior reviews) reporting intervention fidelity, generalization, maintenance, and social validity. However, our findings shed limited light on potential moderating variables in the development of interventions for children and youth who exhibit SIB. Of the potential moderators of intervention effects, only implementer (researcher/therapist vs. parent/caregiver) and setting (clinic vs. home) were significantly associated with improved outcomes. We discuss the need for more robust involvement of natural communities of implementers in SIB intervention research to better equip them to effectively and sustainably meet the needs of people they care for. We also discuss the importance of creating systems enabling broad access for children with SIB to effective interventions in service of reducing burden for people, families, and society over time.

Pediatric Tube Weaning: A Meta-Analysis of Factors Contributing to Success

Approximately 3-10% of children have severe feeding issues, and some require enteral/tube nutrition to grow and thrive. For many children, tube feeding is temporary, making efficacious interventions for tube weaning essential. We conducted a systematic review and meta-analysis of tube weaning treatments. Outcomes included percentage of participants completely weaned from the tube, and mean percentage of kilocalories consumed orally following treatment. Data were extracted from 42 studies, including cohort studies and single-subject research design studies. We evaluated moderators of treatment success, including treatment setting, use of behavioral approaches, use of hunger provocation, and use of a multidisciplinary approach. Results indicated that, after treatment, children received significantly more calories orally, and 67-69% of children were fully weaned. These analyses suggest that current interventions are generally effective; however, variability within treatments exist. Prospective randomized clinical trials are needed to understand effective components of weaning interventions.

Does the choice of a linear trend-assessment technique matter in the context of single-case data?

Trend is one of the data aspects that is an object of assessment in the context of single-case experimental designs. This assessment can be performed both visually and quantitatively. Given that trend, just like other relevant data features such as level, immediacy, or overlap does not have a single operative definition, a comparison among the existing alternatives is necessary. Previous studies have included illustrations of differences between trend-line fitting techniques using real data. In the current study, I carry out a simulation to study the degree to which different trend-line fitting techniques lead to different degrees of bias, mean square error, and statistical power for a variety of quantifications that entail trend lines. The simulation involves generating both continuous and count data, for several phase lengths, degrees of autocorrelation, and effect sizes (change in level and change in slope). The results suggest that, in general, ordinary least squares estimation performs well in terms of relative bias and mean square error. Especially, a quantification of slope change is associated with better statistical results than quantifying an average difference between conditions on the basis of a projected baseline trend. In contrast, the performance of the split-middle (bisplit) technique is less than optimal.

Training programme for community service providers who support adults with intellectual disabilities: A systematic quantitative literature review of single-case research

BACKGROUND

Research on training direct support professionals to address challenging behaviour exhibited by adults with intellectual disabilities is essential in generating effective training approaches for this sector. This systematic review's objective was to evaluate the effects of training types and whether specific training delivery components influenced outcomes.

METHODS

Following PRISMA (2020) guidelines, 16 single-case design studies were included that directly evaluated behaviour change of service providers training for adults with intellectual disabilities in community settings. Study quality was assessed using Horner et al. (Exceptional Children, 2005, 71(2), 165-180) criteria. The database searched included Academic Search Complete, CINAHL, Embase, ERIC, Psych Info, and Web of Science.

RESULTS

Descriptive analysis of effect size outcomes suggested that all training types were associated with improved outcomes. Further, in situ training was associated with improved service provider performance. Interestingly, feedback was associated with poorer service provider performance.

CONCLUSIONS

We provide possible explanations for this surprising outcome and propose future research.

Systematic Review of Descriptions and Justifications Provided for Single-Case Quantification Techniques

There are currently a multitude of quantification techniques that have been developed for use with single-case designs. As a result, choosing an appropriate quantification technique can be overwhelming and it can be difficult for researchers to properly describe and justify their use of quantification techniques. However, providing clear descriptions and justifications is important for enhancing the credibility of single-case research, and allowing others to evaluate the appropriateness of the quantification technique used. The aim of this systematic literature review is to provide an overview of the quantification techniques that are used to analyze single-case designs, with a focus on the descriptions and justifications that are provided. A total of 290 quantifications occurred across 218 articles, and the descriptions and justifications that were provided for the quantification techniques that were used are systematically examined. Results show that certain quantification techniques, such as the non-overlap indices, are more commonly used. Descriptions and justifications provided for using the quantification techniques are sometimes vague or subjective. Single-case researchers are encouraged to complement visual analysis with the use of quantification techniques for which they can provide objective and appropriate descriptions and justifications, and are encouraged to use tools to guide their choice of quantification techniques.

Evaluating Technology-Based Self-Monitoring of Performance with Differential Reinforcement for Students with Disabilities

This study evaluated the use of a technology-based self-monitoring of performance (SMP) with differential reinforcement to increase task completion and reduce off-task behavior for three 5th-grade students with disabilities. A concurrent multiple baseline design across participants was used to examine the impact of the intervention on the targeted behaviors when implemented by a general education teacher and its maintenance effects with a delay of reinforcement. The implementation involved training students to use a mobile app for SMP and providing differential reinforcement contingent on task completion and accuracy of self-monitoring during academic periods. The secondary measure of off-task behavior was included to evaluate the relationship between task completion and engagement. The results demonstrated that the technology-based SMP with differential reinforcement increased task completion and reduced off-task behavior for all students. Furthermore, the gradual fading of the reinforcement, with a 45 min delay, was successful for all students. The efficiency and immediacy of the intervention suggest that technology-based SMP with differential reinforcement holds promise as a practical, efficient, and effective school-based intervention.

A Multilevel Meta-analysis of Single-Case Research on Interventions for Internalizing Disorders in Children and Adolescents

The effectiveness of interventions for internalizing disorders in children and adolescents was studied using a review and meta-analysis of published single-case research. Databases and other resources were searched for quantitative single-case studies in youth with anxiety, depressive, and posttraumatic stress disorders. Raw data from individual cases were aggregated and analyzed by means of multilevel meta-analytic models. Outcome variables were symptom severity assessed across baseline and treatment phases of the studies, and diagnostic status at post- and follow-up treatment. Single-case studies were rated for quality. We identified 71 studies including 321 cases (M^age = 10.66 years; 55% female). The mean quality of the studies was rated as below average, although there were considerable differences between the studies. Overall, positive within-person changes during the treatment phase in comparison to the baseline phase were found. In addition, positive changes in the diagnostic status were observed at post- and follow-up treatment. Yet high variability in treatment effects was found between cases and studies. This meta-analysis harvests the knowledge from published single-case research in youth-internalizing disorders and illustrates how within-person information from single-case studies can be summarized to explore the generalizability of the results from this type of research. The results emphasize the importance of keeping account of individual variability in providing and investigating youth interventions.

Using the high-probability instructional sequence to improve initiation and completion of low-probability instructions in young autistic children

This study examined the use of the high-probability (high-p) instructional sequence during pre-academic or academic activities for three young children diagnosed with autism spectrum disorder (ASD) served in public elementary schools. Specifically, we examined the effects of the high-p instructional sequence on the children's initiation and completion of low-probability (low-p) instructions, implemented by their classroom teachers. A nonconcurrent multiple-baseline design across participants was used to evaluate the intervention outcomes. The results indicated that the high-p instructional sequence may be an effective antecedent-based intervention for autistic children who typically initiate the low-p instructions but have difficulty completing the instructions. A strong magnitude of effect was shown for initiation across children. For one child, initiation and completion increased during high-p, and the improvement was maintained above criterion levels when high-p instructions in sequence were faded. For two children, we found high levels of initiation but variable performance in completion during high-p. The use of programmed reinforcement for one child suggests that for autistic children who do not often initiate the low-p instructions, the addition of programmed reinforcement may be needed to increase completion of low-probability instructions.

Rethinking the Place of Qualitative Methods in Behavior Analysis

Single-case design research is pervasive and dominant in the field of behavior analysis (BA). It allows for effective application of behavior change technologies in a wide variety of real-world settings. However, as the field has grown, behavioral scholars have suggested incorporating other methods into the investigator’s toolbox to supplement single-case design. To date, the call to expand beyond using only variations of single-case design as the standard for behavior analytic research has gone largely unheard. Given the need for behavior analytic work to be more closely aligned with consumer and stakeholder needs and priorities, along with a proliferation of practitioners and researchers in the field, now is the time to consider the benefits of qualitative research methods for behavior analysts. In particular, in areas of social validity and in exploring diverse applied topics, qualitative methods may help the field of behavior analysis to achieve greater success with documenting the outcomes from behavior change interventions. The present article explores areas where behavior analysis may benefit from utilizing qualitative methods, namely social validity and breadth of topics for study, and provides examples of the value of qualitative research from other fields. A brief outline of qualitative research is provided alongside consideration of the seven dimensions of applied behavior analysis. In situations where single-case design does not offer behavior analysts sufficient methodological opportunity, qualitative research methods could form a powerful addition to the field of behavior analysis.

Interpreting treatment effect size from single case experimental design data: a preliminary analysis of differential effects of treatments designed to increase or decrease behaviour

BACKGROUND

Estimates of treatment effect size from single case experimental design (SCED) data may be impacted by the direction for treatment effects (i.e. ascending or descending slope for the dependent variable). Estimating effect sizes for treatments designed to decrease behaviour are potentially more restricted because the intended direction for treatment is zero (i.e. an absolute basal). Conversely, effect sizes for interventions that increase behaviour are less restricted due to a relatively unconstrained ceiling from a pure measurement standpoint (i.e. no absolute ceiling). That is, treatments that increase behaviour have a broader range of possible effect size values as the ceiling is only limited by demand characteristics and the learners' skills and motivation to exhibit the behaviour.

METHOD

The current study represents a preliminary analysis of the mean and range of SCED effect sizes for treatments designed to either increase or decrease target behaviour. A within-case Cohen's d measure that was developed for SCED data was used to estimate treatment effect sizes.

RESULTS

Results indicated that the mean and range of effect size values for treatments that increased behaviour were significantly greater compared with treatments that decreased behaviour.

CONCLUSIONS

Results are discussed in terms of developing standards, or best practices, specific to interpreting effect size values and meeting quality control requirements for inclusion of the data set in future SCED meta-analytic studies estimating treatment effect size. Specifically, preliminary results suggest that benchmarks for low, medium and high SCED effect size values need to be developed separately for treatments that increase or decrease levels of the dependent variable.

Quantification of behavioral data with effect sizes and statistical significance tests

This article describes the use of statistical significance tests and distance-based effect sizes with behavioral data from single case experimental designs (SCEDs). Such data often are interpreted only with visual analysis. However, a growing movement in the field is to quantify results to improve decision-making and communication across studies and sciences. The goal of the present study was to assess the agreement between visual analysis and various statistical tests. We recruited visual analysts to judge 160 pairwise data sets from published articles and compared these analyses to significance tests and effect sizes. One-tailed significance testing of Tau z and the percentage of pairwise differences in the predicted direction (PWD) generally agreed with each other, and complemented the effect sizes of Ratio of Distances (RD) and g. Visual analysis was somewhat unreliable and should be combined with statistical complements to maximize decision accuracy.

Performance criteria-based effect size (PCES) measurement of single-case experimental designs: A real-world data study

Visual analysis and nonoverlap-based effect sizes are predominantly used in analyzing single case experimental designs (SCEDs). Although they are popular analytical methods for SCEDs, they have certain limitations. In this study, a new effect size calculation model for SCEDs, named performance criteria-based effect size (PCES), is proposed considering the limitations of 4 nonoverlap-based effect size measures, widely accepted in the literature and that blend well with visual analysis. In the field test of PCES, actual data from published studies were utilized, and the relations between PCES, visual analysis, and the 4 nonoverlap-based methods were examined. In determining the data to be used in the field test, 1,052 tiers (AB phases) were identified from 6 journals. The results revealed a weak or moderate relation between PCES and nonoverlap-based methods due to its focus on performance criteria. Although PCES has some weaknesses, it promises to eliminate the causes that may create issues in nonoverlap-based methods, using quantitative data to determine socially important changes in behavior and to complement visual analysis.

A proposal for the assessment of replication of effects in single-case experimental designs

In science in general and in the context of single‐case experimental designs, replication of the effects of the intervention within and/or across participants or experiments is crucial for establishing causality and for assessing the generality of the intervention effect. Specific developments and proposals for assessing whether an effect has been replicated or not (or to what extent) are scarce, in the general context of behavioral sciences, and practically null in the single‐case experimental designs context. We propose an extension of the modified Brinley plot for assessing how many of the effects replicate. To make this assessment possible, a definition of replication is suggested, on the basis of expert judgment, rather than on statistical criteria. The definition of replication and its graphical representation are justified, presenting their strengths and limitations, and illustrated with real data. A user‐friendly software is made available for obtaining automatically the graphical representation.

Cochran's Q Test of Stimulus Overselectivity within the Verbal Repertoire of Children with Autism

Stimulus overselectivity remains an ill-defined concept within behavior analysis, because it can be difficult to distinguish truly restrictive stimulus control from random variation. Quantitative models of bias are useful, though perhaps limited in application. Over the last 50 years, research on stimulus overselectivity has developed a pattern of assessment and intervention repeatedly marred by methodological flaws. Here we argue that a molecular view of overselectivity, under which restricted stimulus control has heretofore been examined, is fundamentally insufficient for analyzing this phenomenon. Instead, we propose the use of the term "overselectivity" to define temporally extended patterns of restrictive stimulus control that have resulted in disproportionate populations of responding that cannot be attributed to chance alone, and highlight examples of overselectivity within the verbal behavior of children with autism spectrum disorder. Viewed as such, stimulus overselectivity lends itself to direct observation and measurement through the statistical analysis of single-subject data. In particular, we demonstrate the use of the Cochran Q test as a means of precisely quantifying stimulus overselectivity. We provide a tutorial on calculation, a model for interpretation, and a discussion of the implications for the use of Cochran's Q by clinicians and researchers.

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

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.

Contingency-based delay to reinforcement following functional communication training for autistic individuals: A multilevel meta-analysis

LAY ABSTRACT

Functional communication training, an intervention for challenging behavior rooted in principles of applied behavior analysis, has copious empirical support dating back to the mid-1980s for autistic individuals. Recently, there has been a concerted effort to thin reinforcement delivery during functional communication training using contingency-based delays that, in turn, are designed to enhance practicality and feasibility while not compromising efficacy. In this synthesis, we meta-analyzed the literature base with the goal of investigating both combined and across type effectiveness of contingency-based delays. We also aimed to investigate moderating variables that might impact intervention outcomes. Findings showed that contingency-based delays were effective for individuals with an autism spectrum disorder diagnosis and most effective when the delay incorporated some form of positive reinforcement. In addition, differential reinforcement of alternative-based delays was overall more effective when compared to differential reinforcement of other behavior-based delays. Noteworthy moderating variables found to impact contingency-based delay efficacy included the intervention dosage and the topography of behavior. We discuss these findings and highlight directions where additional empirical research is warranted to improve our understanding about contingency-based delays for individuals diagnosed with autism spectrum disorder.