A Meta-Analysis of Peer-Mediated Social Interventions for Secondary Students With Intellectual and Developmental Disabilities

Abstract

Peer relationships and social interactions in the classroom can facilitate learning, and peer-mediated interventions (PMIs) are frequently used to support the development and quality of social interactions between students with intellectual and developmental disabilities (I/DDs) and their peers. This meta-analysis examined extant literature on PMI for secondary students with I/DD. We identified 37 studies and dissertations for inclusion in this review. Effect size (ES) estimates demonstrate significant positive effects in both group design (ES = 1.38) and single-case design (ES = 1.96). Across intervention types, peer networks (ES = 2.20) and peer support arrangements (ES = 2.25) produced larger effects than peer initiation/response interventions (ES = 1.53). Overall findings suggest that PMIs are efficacious in supporting social interactions between secondary students with I/DD and their peers and can be feasibly and successfully implemented by educators in school settings.

Keywords

intellectual disability exceptionalities autism social skills meta-analysis

One of the most common justifications to include students with autism, intellectual disability, and multiple disabilities (i.e., intellectual and developmental disabilities [I/DDs]) in general education settings is to foster peer relationships and strengthen their social communication skills. Yet, differences in the social development of individuals with I/DD often impacts their social awareness, peer interactions, and overall communication patterns (Carter et al., 2023). This may be compounded by their peers lacking the skills or support needed to be meaningful, equitable, and reciprocal partners in these friendships (Rossetti, 2024). For many individuals with I/DD, these factors lead to fewer friendships, higher rates of loneliness, less social integration in their classroom, and poor academic performance and participation (Carter et al., 2023; Cresswell et al., 2019; Welsh et al., 2001).

The quality and stability of peer relationships for students with I/DD often do not increase as these students age through adolescence (e.g., Cresswell et al., 2019). In observational studies, authors have reported infrequent or a lack of interactions between students with I/DD and their peers without I/DD (Carter et al., 2023). In addition to the social challenges that many students with I/DD experience, difficulty establishing and growing social connections at the secondary level may be exacerbated due to (a) shifting peer attitudes and expectations, (b) changing definitions of social success, and (c) the increasing importance and nuance of conversations (e.g., Carter et al., 2023; Rossetti, 2024). Without attention to their classroom social connections, students with I/DD may not fully access academic and social learning opportunities in secondary classrooms. As such, targeted social interventions to support the peer relationships and networks of students with I/DD have vast implications for increasing students’ social connectedness, access to their academic learning environment, and overall quality of life. Therefore, the purpose of this meta-analysis is to evaluate the effects of peer-mediated interventions (PMIs) on the social interactions of secondary students with I/DD. Specifically, we systematically synthesized both group design and single-case design (SCD) to estimate the overall impact of PMI in secondary settings.

Peer-Mediated Interventions

Peer-mediated interventions (Odom, 2019; Steinbrenner et al., 2020) are an empirically validated set of strategies that have demonstrated positive effects in supporting the development of social and communication behaviors for students with I/DD in service of fostering friendships and community membership, both inside and outside of the classroom (Steinbrenner et al., 2020). Peer-mediated interventions are broadly defined and include myriad instructional techniques but typically involve peers without I/DD who model or prompt interactions or act as intervention implementers (Odom, 2019). For this review, we will use Wong et al.’s (2015) definition that PMI involve, “teaching typically developing peers ways to interact with and help learners with ASD acquire new behavior, communication, and social skills by increasing social opportunities within natural environments” (p. 76).

Odom (2019) described three direct approaches to PMI as particularly effective in promoting increases in social relationships, communication, and peer interactions: (a) peer initiation and response interventions, (b) peer-mediated social networks, and (c) peer support arrangements. In direct approaches, compared with indirect approaches that address the ecology of the classroom or rely on peer proximity, adult facilitators teach peer implementers the strategies and skills needed to interact with and assist students with I/DD (Odom et al., 1985). These direct approaches differ from other PMIs (e.g., Best Buddies and cooperative learning structures; Odom, 2019), in that, they include adult facilitation and peer training. Adult facilitation and peer training are critical as extant literature has shown that proximity alone, without peer training, is not as efficacious and that adult prompting and reinforcement in natural settings during PMI support generalization and maintenance of social skills (Odom; 2019). Clearly defined implementation procedures and fidelity measures for practitioners and peer implementers are also typically included.

Types of PMI

Peer initiation and response interventions are among the oldest forms of PMI (Odom et al., 1985). In this approach, peer implementers are taught discrete techniques in social communication for initiating, responding to, reinforcing, and sustaining interactions with students with I/DD. Adult facilitators frequently teach peer implementers to provide social and verbal reinforcement to students with I/DD when they respond (Carter et al., 2013; Odom, 2019; Watkins et al., 2015).

Peer-mediated social network interventions are cohesive social groups designed to integrate students with I/DD into social environments within the school (Carter et al., 2013). Unlike other more traditional PMIs (i.e., peer initiation and peer proximity), peer network interventions focus on promoting friendships through positive interactions and shared activities, rather than targeting discrete social or communication skills (e.g., Asmus et al., 2017; Carter et al., 2019; Odom, 2019). During weekly formal meetings, peer network members engage in mutually enjoyable shared activities, practice social and communication skills in a naturalistic environment, and plan informal social opportunities to support skill generalization over time (Carter et al., 2013).

Peer support arrangements involve training peer implementers to increase the social interactions and participation of students with I/DD within general education academic contexts while students work alongside each other (Brock & Huber, 2017). Peer support arrangements combine the traditional social and communication focus of many PMI with the focus and intervention location of peer tutoring and often include additional components that address students’ individualized support goals. As such, peer support arrangements typically contain goals and strategies that address the academic, classroom engagement, social, and communication needs of students with I/DD (Brock & Huber, 2017).

Benefits for Peer Implementers

Peer-mediated intervention leverage the social nature of the classroom and build a natural community for students with I/DD while actively teaching the communication and social skills needed to sustain it (Watkins et al., 2015). Peer-mediated intervention can be conceptualized as “dual interventions,” providing training and skill development to both students with and without disabilities. This supports fostering community membership and social relationships, as all members of the community, regardless of disability status, are given the tools and skills needed to communicate and interact in a prosocial and inclusive manner. Emphasis on all students, with and without disabilities, improving social and communication skills is an important element of PMIs. Some researchers have noted that students with disabilities are often asked to accommodate or conform to the communication styles of their peers (e.g., masking), when the reverse should be true (Beechey, 2022). Because social interactions always occur between people, not within people, students with and without disabilities should receive social and communication training to become more accepting of differences and better communicative partners (Bambara, 2022). Furthermore, the training provided to peer implementers within PMI is beneficial, with many studies demonstrating positive social and academic effects for peer implementers (e.g., Carter et al., 2023; Schaefer et al., 2016; Travers & Carter, 2021). For example, many peer implementers report a deeper appreciation for diversity, greater commitment to inclusion, and improved attitudes toward their classmates with disabilities (Schaefer et al., 2016; Travers & Carter, 2021).

Study Purpose

The efficacy of PMI for students with I/DD has been examined in several focused reviews and meta-analyses in the last decade, establishing all variations of PMI as evidence-based practices for this population (e.g., Brock & Huber, 2017; Chang & Locke, 2016; Ezzamel & Bond, 2016; Hughes et al., 2012; Schaefer et al., 2016; Travers & Carter, 2021; Watkins et al., 2015). Within these reviews, authors have found that PMI are effective at increasing social and communication skills and are conducive for implementation across the school-age years and within school settings. With similar findings, researchers have also examined the effectiveness of PMI for students with I/DD in broader social skills intervention reviews (e.g., Steinbrenner et al., 2020; Wong et al., 2015).

This systematic and meta-analytic review aimed to expand upon these prior reviews in four ways. First, we focused this review on PMI, which can be more efficacious than other types of social interventions (Odom, 2019) that do not involve adult facilitation or peer training. Second, we focused on secondary settings where the changing social landscape of adolescence necessitates additional and unique intervention considerations. Third, we included group design and SCD studies and gray literature (i.e., dissertations) to present a more holistic view of how PMI have been examined. Finally, we used a meta-analysis to evaluate the effects of PMI on increasing the social and communication skills of secondary students with I/DD, a need noted in Travers and Carter’s (2021) recent review. Despite the frequency of PMIs being used in school settings (e.g., Brock & Huber, 2017; Travers and Carter, 2021), meta-analytic techniques to measure the effects of PMI at the secondary level have not been applied.

To this end, we posit the following research questions:

Research Question 1 (RQ1):What are the intervention and participant characteristics of studies examining PMI for secondary students with I/DD?

Research Question 2 (RQ2): What is the overall effect of PMI in supporting the frequency of interactions between students with I/DD and their peers?

Research Question 3 (RQ3): To what extent do effect sizes (ESs) differ across study variables, including the type of PMI, training provider, and presence of ongoing peer training and support?

The third research question is exploratory and descriptive, as we did not conduct a meta-regression.

Method

We conducted this meta-analytic and systematic review using best practices to support a comprehensive search of peer-reviewed literature and published dissertations (Cooper, 2016). We identified and screened records using the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA; Page et al., 2021; Figure 1).

Inclusion and Exclusion Criteria

First, we included only studies published in peer-reviewed, English-language, academic journals, or studies published as a dissertation between January 2000 and April 2025. Second, studies were required to have an experimental or quasi-experimental (e.g., single-group pre-post designs) design that allowed for direct analysis of intervention effects. This included both group design and SCD studies. We excluded qualitative research designs, case studies, and correlational studies as the independent variable was not actively manipulated. Single-case designs with an AB or ABA design were excluded due to limited experimental control. Third, studies needed to include participants at the secondary level (i.e., Grades 6–12 or ages 11–22) who were eligible for special education services under an I/DD (i.e., autism, intellectual disability, and multiple disabilities). When studies involved both students who met and did not meet these criteria (e.g., studies with elementary and secondary participants) and data had been disaggregated, only students who met full eligibility criteria were included in the analysis. Fourth, peer implementers within the study must have been both peers without I/DD and secondary students. We included group design studies that did not disaggregate but had a majority (50%) of students within the inclusion parameters.

Fifth, we only included studies where interventions were implemented within the school day in general education classrooms, special education classrooms, or pull-out settings. We excluded studies conducted outside school settings, such as in clinics, summer programs, theater programs, or virtual settings. Sixth, the study’s independent variable must have been a PMI (Odom, 2019) with the primary implementer being peers without I/DD who had received training. Studies that solely utilized peers in proximity, without peer training or peers actively implementing a PMI, were excluded. Students with I/DD and their peers must have been grouped together, and implementation training must have been given to at least the peer group by an adult facilitator. Studies, where PMI were part of a comprehensive treatment program, were excluded if they did not specifically discuss the peer training component and disaggregate the outcomes of the PMI. If the study did disaggregate the outcomes of the PMI, only the PMI outcomes were included within the analysis. Finally, authors must have included at least one dependent measure directly assessing instances or rates of social communication or social interactions (e.g., communication bids and responses). Studies solely measuring academic outcomes or academic-related behaviors, such as time on task or academic engagement, were excluded.

Systematic Search and Screening Procedures

To identify peer-reviewed literature, we conducted a systematic search using EBSCOhost to search the Education Resources Information Center (ERIC), Academic Search Complete, and PsycINFO databases, which provide comprehensive coverage of the disciplines most relevant to this review. Equivalent subjects and related words search features were not used and the search was limited to studies published in English. Boolean search terms (see Supplemental Material 1) were used within a full-text search to identify eligible articles. To identify published gray literature (i.e., dissertations), the first author utilized the same Boolean search terms in an abstract search in the ProQuest Dissertations and Theses Global database. The combined searches returned 2,019 articles and 1,732 articles remained after duplicates were removed.

We next reviewed the titles and abstracts of returned articles. The first author trained the second author in applying the inclusion and exclusion criteria to titles and abstracts on a subset of potential articles (n = 50) until 90% agreement was achieved. The second author then double coded an additional 20% of titles and abstracts. Intercoder reliability (ICR) was 95%, and consensus was reached through discussion on all disagreements. Intercoder reliability was calculated using a total agreement formula (i.e., number of agreements divided by the number of agreements plus disagreements multiplied by 100). Authors then independently reviewed all full-text articles and dissertations that qualified for consideration (n = 122). Intercoder reliability was 98%. Disagreements were resolved through discussion until consensus was reached. Of the 122 articles and dissertations that underwent full-text screening, 33 articles were included. We also conducted an ancestral search using the reference lists of included articles and related literature reviews and meta-analyses. An additional four articles were included, bringing the total to 37 articles that met inclusion criteria (see Supplemental Material 3).

Data Coding and Extraction

We first narratively summarized articles that met the full inclusion criteria with independent validation of the narrative table by the fourth author (see Table 1). Narrative data extraction included each study’s number of focal participants and peer implementers, the grade level(s) and demographics of the focal participants, the study design, the type of PMI, the intervention location and session duration, the type of dependent variable, and the inclusion of generalization, maintenance, fidelity, and social validity measures.

Table 1.

Descriptions of Studies.

Studies	Participants	Intervention location, session duration, session frequency	Intervention facilitator	Training provider	Ongoing peer support	G, M, F, SV	ES (SE)
Peer Initiation and Response
Hughes et al. (2000)	5 SWD, 71 peers, 1 peer/SWD	Classrooms and cafeteria, 5 minutes, daily	Research team	Research team	No	G, M, F, SV	4.14 (0.64)
Ogilvie (2008)^a	3 SWD, 3 peers, 1 peer/SWD	Academic and elective classrooms, class period, daily	School staff	Research team	Yes	G, M, F, SV	0.84 (0.35)
Hughes et al. (2011)	5 SWD, 48 peers, 11–16 peers/SWD	Elective classes and cafeteria, 5 minutes, daily	Research team	Research team	No	G, F, SV	44.86 (7.90)
Chung and Carter (2013)	2 SWD, 7 peers, 3–4 peers/SWD	Academic and elective classes, 20–50 minutes, 2–3 days/week	School staff	Research team	Yes	F, SV	1.26 (0.82)
Hughes, Bernstein, et al. (2013)	6 SWD, 38 peers, 10–14 peers/SWD	Academic classes, 5 minutes, daily	Research team	Student	No	G, M, F, SV	10.39 (3.23)
Hughes, Harvey, et al. (2013)	3 SWD, 3 peers, 1 peer/SWD	Elective classes, 90 minutes, and daily	Research team	Research team	No	F, SV	1.55 (0.37)
Reilly et al. (2014)	3 SWD, 41 peers, 3–8 peers/SWD	Cafeteria, not reported, not reported	Research team	Research team	No	G, M, F, SV	0.20 (0.44)
Potter (2014)^a	3 SWD, 3 peers, 1 peer/SWD	Cafeteria, lunch period, daily	Research team	Research team	Yes	M, F, SV	1.69 (.08)
Brain and Mirenda (2019)	3 SWD, 9 peers, 2–4 peers/SWD	Cafeteria, 30 minutes, daily	Research team	Research team	Yes	M, F, SV	3.04 (1.18)
MacFarland & Fisher (2019)	4 SWD, 7 peers, 1 peer/SWD	Classroom, school greenhouse, cafeteria, class period, daily	School staff	School staff	Yes	G	0.92 (1.33)
Barraza (2019)^a	3 SWD, 3 peers, 1–2 peers/SWD	Elective class; 50 minutes; daily	School staff	School staff with research team support	Yes	G, M, F, SV	0.01 (0.16)
Ackerman et al. (2020)	4 SWD, 2 peers, 1 peer/SWD	Academic classes, 10 minutes, not reported	Research team	Research team	Yes	M, F, SV	0.27 (0.29)
Chung and Douglas (2023)	3 SWD, 6 peers, 2 peers/SWD	Academic and elective classes, class period, daily	School staff	School staff	Yes	F, SV	1.73 (1.60)
Mahoney and Davis (2024)	3 SWD, 8 peers, 2–3 peers/SWD	Academic classes, 50 minutes, daily	Research team	Research team	Yes	F, SV	1.28 (0.39)
Peer Network
Leinert (2013)^a	3 SWD, 11 peers, 3–4 peers/SWD	Cafeteria, 30 minutes, daily	Research team	Research team	Yes	M, F, SV	1.93 (0.95)
Hochman et al. (2015)	4 SWD, 11 peers, 1–3 peers/SWD	Cafeteria, 30 minutes, 2–3 days/week	School staff	School staff with research team support	Yes	G, F, SV	3.62 (0.61)
Bambara et al. (2016)	3 SWD, 9 peers, 2–4 peers/SWD	Cafeteria, 30 minutes, 3–4 days/week	Research team	Research team	Yes	F, SV	2.08 (0.43)
Asmus et al. (2017)^b	47 SWD, 192 peers, 3–6 peers/SWD	Cafeteria, varied, varied	School staff	School staff	Yes	G, M, F, SV	1.38 (0.36)
Sreckovic et al. (2017)	3 SWD, 14 peers, 3–6 peers/SWD	Conference room or empty classroom, 25-30 minutes, 2 days/week	Research team	Research team	Yes	G, M, F, SV	1.20 (0.92)
Bambara et al. (2018)	4 SWD, 16 peers, 4 peers/SWD	Cafeteria, 30 minutes, 3–4 days/week	Research team	Research team	Yes	G, F, SV	2.61 (0.67)
Herbert et al. (2020)	3 SWD, 13 peers, 3–5 peers/SWD	Cafeteria 30 minutes, weekly	Research team	Research team	Yes	F, SV	8.79 (12.00)
Thomas (2020)^a	3 SWD, 12 peers, 2 peers/SWD	Cafeteria or study hall, 10 minutes, 3-4 days/week	Research team	Research team	Yes	G, F, SV	0.20 (0.62)
Thomas and Bambara (2020)	3 SWD, 7 peers, 2–3 peers/SWD	Cafeteria, 10 minutes, 3–4 days/week	Research team	Research team	No	G, F, SV	1.63 (0.66)
Bambara et al. (2021)	3 SWD, 10 peer, 3–4 peers/SWD	Cafeteria, 10 minutes, 3–4 days/week	Research team	Research team	Yes	G, M, F, SV	2.65 (0.85)
Cole et al. (2022)	3 SWD, 14 peers, 3–6 peers/SWD	Cafeteria, 30 minutes, 3–4 days/week	Research team	Research team	Yes	M, F, SV	1.69 (0.87)
Peer Support
Carter et al. (2007)	4 SWD, 4 peers, 1 peer/SWD	Academic classes (3) and elective class (1), class period, daily	Researcher team	Research team	Yes	F	1.99 (0.55)
Carter et al. (2011)	3 SWD, 6 peers, 1–3 peers/SWD	Elective classes, class period, daily	School staff	Research team	Yes	SV	1.80 (0.48)
Brock et al. (2016)	4 SWD, 10 peers, 2–3 peers/SWD	Elective classes, class period, daily	School staff	School staff with research team support	Yes	G, F, SV	3.85 (1.50)
Brock and Carter (2016)	4 SWD, 11 peers, 2–3 peers/SWD	Academic classes, class period, daily	School staff	School staff with research team support	Yes	F, SV	1.76 (0.57)
Carter et al. (2016)^b	51 SWD, 106 peers, not reported	Academic classes, class period, daily	School staff	School staff	Yes	G, M, F, SV	0.42 (7.07)
Biggs et al. (2017)	4 SWD, 8 peers, 2 peers/SWD	Academic classes, class period, multiple times a week	School staff	School staff with research team support	Yes	G, F, SV	3.41 (0.81)
Carter et al. (2017)	4 SWD, 13 peers, 1–6 peers/SWD	Academic classes (3) and elective class (1), class period, daily	School staff with research team support	Research team	Yes	F, SV	2.33 (0.98)
Huber et al. (2018)	3 SWD, 8 peers, 2–3 peers/SWD	Academic classes, class period, daily	School staff	School staff with research team support	Yes	F, SV	2.05 (0.69)
Schaefer et al. (2018)	3 SWD, 6 peers, 2 peers/SWD	Academic classes, class period, daily	School staff	Research team	Yes	G, F, SV	3.46 (0.65)
Athamanah and Cushing (2019)	3 SWD, 3 peers, 1 peer/SWD	Work-based learning settings, average 45 minutes, multiple times a week	School staff	Research team	No	F	3.11 (0.92)
Athamanah and Cushing (2023)	5 SWD, 5 peers, 1 peer/SWD	Work-based learning settings in high school, average 21 minutes, not reported	Research team	Research team	No	G; F; SV	1.72 (1.09)
Huber and Carter (2023)	3 SWD, 6 peers, 1–3 peers/SWD	Academic and elective classes, class period, multiple times a week	School staff	School staff	Yes	F, SV	1.54 (0.66)

Note. SCD = single-case design; SWD = students with disabilities; G = generalization; m = maintenance; F = fidelity; SV = social validity; ES = effect size; SE = standard error.

Indicates a dissertation study. ^bIndicates a group design study. All other studies use a single-case design.

Dummy Coding

We then dummy coded studies using an author-created coding manual (see Supplemental Material 2) to transform study characteristics into numeric variables and facilitate statistical analyses. We created dummy codes based on prior reviews of PMI as well as study variables hypothesized to affect study outcomes. Specifically, we coded three categories of variables: (a) study design and characteristics, (b) focal participant and peer characteristics, and (c) intervention and peer training characteristics. Intercoder reliability was calculated using the total agreement formula after studies were coded and resulted in 100% reliability.

ES Calculations

Effect sizes were calculated to estimate the effect of PMI on social interactions for secondary students with I/DD (Borenstein et al., 2010). We calculated ES indices that are specific to group and SCD studies but designed to be comparable. We analyzed group and SCD studies together and separately. Within the included studies, outcome data were presented in two ways. First, data were presented as separate instances of focal peer initiations and responses. Second, data were presented as a combined initiations and responses variable as total social interactions. If total interactions were presented, we calculated a single ES. If responses and bids were presented separately, we estimated two separate ES and then collapsed them into a single outcome variable of total social interactions. We made this decision because both initiations and responses represent social interactions from the student with I/DD and provided a consistent and comparable metric across studies.

Group Design Studies

For group design studies, we used the standardized mean difference ES provided by the authors as there are only two group design studies included. We then scaled the ES to Hedges’ g to account for small study sample sizes (Hedges, 1981). The ESs were calculated using the Comprehensive Meta-Analysis Software (CMA; Version 3).

In both studies, authors used hierarchical linear modeling to calculate the overall reported ES. Given the limited number of group design studies (n = 2), these results should be interpreted with caution, and we did not attempt to draw direct comparisons between group and SCD results.

SCD Studies

We used the between-case standardized mean difference (BC-SMD; Hedges et al., 2013; Shadish et al., 2014), which uses hierarchical linear modeling (HLM) and the estimated model predictors to estimate the magnitude of treatment effects for SCD studies. The BC-SMD is interpreted using Cohen’s (1988) guidelines, where a BC-SMD < 0.20 indicates a small effect and a BC-SMD > 0.80 indicates a large effect. Shadish et al. (2015) identified the BC-SMD as a robust ES consistent with the group standardized mean difference (Chen et al., 2023).

The BC-SMD differs from other methods used to estimate the ESs of SCD studies, such as visual analysis and non-overlap methods (Chen et al., 2023). Visual analysis is a core method of analysis in SCD studies to establish whether a functional relationship exists. While visual analysis is the most widely accepted means to determine whether experimental effects were demonstrated and replicated, this approach does not provide a standardized measure of magnitude of effects that can be compared across studies. Similarly, non-overlap methods are sensitive to the study’s design and do not account for sampling distributions nor nested data, limiting their utility in meta-analyses (Pustejovsky, 2019).

To calculate the BC-SMD, studies must have at least three data points in the baseline and intervention phases and three cases (e.g., across participants, behaviors, and settings). Maintenance and generalization points were excluded from analysis as most studies either did not measure these effects or there were not sufficient data. We extracted data from each SCD study using the WebPlotDigitizer (Version 4.4; Rohatgi, 2022), which has been used in previous reviews and has been found to have high rates of reliability (r = .99; Drevon et al., 2017). Next, the first author cleaned the data and assessed the extracted data for accuracy against reported results in each study. Data were only altered if the study’s dependent measure was reported as a whole number and the WebPlotDigitizer had extracted a non-whole number. We then input the cleaned data into scdhlm, an open-source, web-based program designed to calculate the BC-SMD estimate (Pustejovsky et al., 2021). For each study, we assigned session numbers to each case as the detrending variable, and ESs were estimated using the restricted maximum-likelihood estimation method with random effects for both the baseline and treatment conditions.

Meta-Analysis

Of the SCD studies, five had more than one ES suitable to address research questions two and three. In these studies, social interactions were either presented as separate initiations and responses, or the studies were multiple baseline within participants’ designs. Therefore, we assumed that the outcome measures were likely highly correlated within the studies (e.g., Huber et al., 2018) and we calculated estimates conservatively by averaging the ESs and standard deviations (SDs) to produce an overall mean and SDs. This approach avoided treating correlated outcomes as independent, which can inflate Type 1 error rates and lead to misleading conclusions. We also calculated liberal estimates (i.e., assuming no correlation between measures) but the difference was marginal and had no effect on ES interpretations. As such, we only used the conservative estimates in our analyses. We used the metafor package in R (Viechtbauer, 2010) to calculate weighted mean ESs and corresponding 95% confidence intervals within each design type (group and single-case).

Results

We included 37 studies in this systematic and meta-analytic review (see Supplemental Material 3). Descriptive information for each study can be found in Table 1. Of the 37 articles, five were published dissertations and 32 appeared in peer-reviewed journals. Notably, 30 of these were published within the last decade. Thirty-five articles utilized an SCD, and two articles utilized a group design. Of the 37 included studies, 14 were peer initiation or response interventions, 11 were peer network interventions, and 12 were peer support arrangements.

Research Question 1: Intervention and Participant Characteristics

Across studies, 220 students with developmental disabilities are represented in intervention conditions. Within peer initiation and response studies, 50 students with I/DD were included as participants as well as 249 of their peers. Peer network intervention studies included 79 students with I/DD and 309 peers; peer support arrangements studies included 91 students with I/DD and 186 peers. Across the 37 studies, 155 students with I/DD (71%) were male, 126 (57%) were White, 191 (87%) attended high school, and 176 (80%) had a primary diagnosis of autism or intellectual disability. A detailed summary of participant demographics by intervention type is provided in Table 2.

Table 2.

Intervention Participant Demographics.

Demographic	I/R	Peer network	Peer support
Total participants	N = 50	N = 79	N = 91
Sex
Male	37	59	59
Female	13	20	32
Race/ethnicity
White	21	47	58
African American or Black	11	10	14
Asian	5	1	5
Hispanic	6	18	0
Multiracial	1	3	3
Native American or Alaskan	0	0	2
Not reported	6	0	9
Grade level
Middle school	11	3	15
High school	39	76	76
Primary eligibility category
ASD	25	40	29
ID	10	23	49
ASD and ID	15	9	12
MD or DD	0	7	1

Note. I/R = initiation and response; ASD = autism spectrum disorder; ID = intellectual disability; MD = multiple disabilities other than ASD and ID; DD = developmental disability other than ASD or ID.

Across the 37 included studies, PMIs were implemented in a wide array of settings including academic content classes, elective classes, the cafeteria, study halls and home rooms, and work-based learning settings. Of the 37 studies, 20 were researcher-implemented interventions and 17 were implemented by school staff. Of the 17 school staff-implemented studies, 10 were peer support arrangements. Most peer initiation and response interventions and peer network interventions were implemented by researchers. Peer training was provided primarily by researchers in 25 studies, with 11 studies reporting peer training delivered by school staff. Of the 37 included studies, 29 included ongoing peer training and support, while eight did not include additional support beyond the initial training.

Research Question 2

To answer Research Question 2, we calculated individual omnibus ESs (i.e., overall ESs) for group and SCD studies to estimate the effect of PMI on increasing social interactions between students with I/DDs and their peers (Borenstein et al., 2010). We calculated ESs for the group design studies but we did not draw comparisons as they represent only two studies. Table 3 presents results for all ES calculations. Individual study ESs for SCD studies ranged from 0.01 (SE = 0.16) to 44.86 (SE = 7.90). Individual study ESs for group studies ranged from 0.42 (SE = 7.12) to 1.39 (SE = 0.36). Using a random effects model, we then estimated an omnibus ES for group and SCD studies. The SCD studies produced a large, combined ES of 1.96 (SE = 0.22, CI [1.52, 2.39]), and the group studies produced a large, combined ES of 1.39 (SE = 0.36, CI [0.68, 2.09]). These ESs are both considered large based on Cohen’s (1988) recommended interpretations. The ES for Hughes et al. (2011) was a notable outlier (ES = 44.86, SE = 7.90), therefore a second overall ES estimate was conducted omitting this study. This produced an ES of 1.92 (SE = 0.22, CI [1.49, 2.35]). Because including this study did not meaningfully change the overall interpretation of the magnitude of the ES, we included this study in our analysis. Overall, PMIs are effective in increasing social interactions between students with I/DDs and their peers across school settings. See Supplemental Materials for forest plots summarizing both group and SCD studies.

Table 3.

Descriptive Effect Size Estimates.

Category designation	Group designs		Single case designs
Category designation	Mean ES (SE)	95% CI	BC-SMD (SE)	95% CI
Overall ES	1.38 (0.36)^a	[0.68, 2.08]	1.96 (0.22)	[1.52, 2.39]
Type of PMI
Peer network	1.39 (0.36)^b	[0.68, 2.09]	2.20 (0.41)	[1.39, 3.02]
Peer support	0.42 (7.12)^c	[–13.54, 14.38]	2.25 (0.23)	[1.81, 2.70]
Peer initiation/response	—	—	1.53 (0.41)	[0.74, 2.32]
Grade
Middle	—	—	2.15 (0.39)	[1.39, 2.91]
High	1.38 (0.36)^a	[0.68, 2.09]	1.89 (0.26)	[1.38, 2.40]
Intervention grouping size
1 peer/SWD	—	—	1.75 (0.39)	[0.99, 2.50]
2–5 peers/SWD	0.42 (7.12)^c	[–13.54, 14.38]	2.02 (0.26)	[1.50, 2.53]
6+ peers/SWD	1.38 (0.36)^b	[0.68, 2.09]	13.30 (9.66)	[–5.64, 32.24]
Intervention location
Academic classes	0.42 (7.12)^c	[–13.54, 14.38]	1.70 (0.27)	[1.20, 2.23]
Non-academic	1.38 (0.36)^b	[0.68, 2.09]	2.20 (0.34)	[1.55, 2.86]
Frequency of intervention
Daily	0.42 (7.12)^c	[–13.54, 14.38]	2.02 (0.30)	[1.42, 2.61]
Multiple times/week	1.38 (0.36)^b	[0.68, 2.09]	2.23 (0.34)	[1.57, 2.89]
Not reported	—	—	0.71 (0.40)	[–0.08, 1.49]
Adult facilitator
Research staff	—	—	1.96 (0.32)	[1.34, 2.58]
School staff	1.39 (0.36)^a	[0.68, 2.09]	1.99 (0.32)	[1.34, 2.58]
Peer training provider
Research staff	—	—	1.88 (0.24)	[1.42, 2.34]
School staff	1.39 (0.36)^a	[0.68, 2.09]	1.98 (0.48)	[1.04, 2.93]
Ongoing peer support
Yes	1.39 (0.36)^a	[0.68, 2.09]	1.99 (0.25)	[1.49, 2.48]
No	—	—	1.88 (0.43)	[1.03, 2.73]

Note. ES = effect size; SE = standard error; CI = confidence interval; BC-SMD = between-case standardized mean difference; PMI = peer-mediated intervention; SWD = student with disability.

This represents two studies (Asmus et al., 2017 and Carter et al. 2016). ^bThis represents a single study (Asmus et al., 2017). ^cThis represents a single study (Carter et al., 2016).

Research Question 3

To answer Research Question 3, we grouped the studies by the type of PMI. In SCD studies, all types of PMI produced large effects; however, peer network (ES = 2.20, SE= 0.41, CI [1.39, 3.02]) and peer support arrangements (ES = 2.25, SE = 0.23, CI, [1.81, 2.70]) produced notably larger effects than peer initiation and response interventions (ES = 1.53, SE = 0.41, CI [0.74, 2.32]). We also analyzed the SCD studies for patterns related to the peer training provider and presence of ongoing peer training and support. Within SCD studies, the adult facilitator of the PMI produced similar effects for research staff (ES = 1.96, SE = 0.32, CI [1.34, 2.58]) and school staff (ES = 1.99, SE = 0.32, CI [1.34, 2.58]). When grouped by the peer training providers, SCD were similarly effective for both researcher-provided (ES = 1.88, SE = 0.24, CI [1.42, 2.34]) and school staff-provided (ES = 1.98, SE = 0.48, CI [1.04, 2.93]). We further analyzed study effects by whether peer implementers received ongoing coaching and support by PMI facilitators. SCD studies produced large effects regardless of whether peers received ongoing coaching (ES = 1.99, SE = 0.25, CI [1.49, 2.48]) or did not receive ongoing coaching (ES = 1.88, SE = 0.43, CI [1.03, 2.73]).

Discussion

The purpose of this review was to systematically analyze the effects of PMI as defined by Wong et al. (2015) and Odom (2019) on increasing social interactions for secondary students with I/DD and their peers. We identified 37 studies evaluating the efficacy of three types of PMI for secondary students with I/DD. Omnibus ES estimates were large for both group (ES = 1.38) and SCD (1.96) studies. The effects for peer networks (ES = 2.20) and peer support (ES = 2.25) were larger than the effect for peer initiation/response (ES = 1.53) among SCD studies. Following Hill et al. (2008), we interpret ESs using empirical benchmarks tied to the original measurement scale, expressing them in the original behavioral units (e.g., additional peer interactions, social contacts, or assertive acts). The average ES for peer initiation/response was ES = 1.53, which is equivalent to a 30% increase in the proportion of 30-second intervals in which students with I/DD interacted with peers. For peer networks, ES = 2.20 represents an average gain of about 1.8 additional peer interactions per minute for students with I/DD. For peer support arrangements, ES = 2.25 translates to a 9.5% increase in the percentage of 15-second intervals containing peer interactions. These findings make an important contribution to the literature examining the efficacy of PMI and align with previous narrative literature reviews (e.g., Brock & Huber, 2017; Chang & Locke, 2016; Ezzamel & Bond, 2016; Hughes et al., 2012; Schaefer et al., 2016; Steinbrenner et al., 2020; Travers & Carter, 2021; Watkins et al., 2015). Here, we note several important insights from this finding and provide implications for researchers and practitioners.

There were notable demographic discrepancies in the study participants, as critiqued in broader literature examining evidence-based practices for students with I/DD, and autism in particular (e.g., West et al., 2016). Study participants were mostly White (n = 126; 57%) and male (n = 155; 71%). An additional 15 participants did not have racial demographics reported. Considering about 41% of school-aged children diagnosed with I/DD are White (National Center for Education Statistics, 2023), there are additional opportunities to explore how PMI can be used to support culturally and linguistically diverse students with I/DD. Future research may consider how PMI can be adapted to incorporate students’ and families’ identities, values, and preferences. In addition, because autistic girls are often underdiagnosed (Lockwood Estrin et al., 2021) and their friendship experiences and related challenges may differ from those of boys (Sedgewick et al., 2019), future research should examine how PMIs can be adapted and evaluated specifically for girls.

Participants at the middle school level were noticeably absent with 87% of participants at the high school level. Furthermore, of the 220 total participants with I/DD across the included studies, 94 had a primary diagnosis of autism spectrum disorder and 82 had a primary diagnosis of an intellectual disability with only 36 participants having a primary diagnosis of co-occurring ASD and ID, and eight having a primary diagnosis of multiple disabilities or another developmental disability that was not ASD or ID. This implies that students with more complex support needs may not be fully represented in the literature examining the efficacy of PMI on social communication skills.

Findings also indicate a need for increased transparency when discussing intervention details, such as location, session frequency, and intervention session length. Most studies provided brief descriptions of intervention settings, and several studies did not report critical intervention components, such as the session length and the intervention frequency. This increased transparency is important for more robustly understanding the intervention and critical for replication efforts (Coyne et al., 2016). Similarly, this review highlights a need for increased rigor in reporting methods for control and baseline conditions. Limited reporting made it challenging to determine what students in these conditions were receiving compared with intervention groups as well as intervention fidelity across phases in the SCD studies. This is important as many students with I/DD receive some form of social skills or communication support. Increased reporting of baseline and control conditions would help contextualize who was included in the intervention and how much support participants in the comparison conditions were receiving (Lemons et al., 2014).

Peer network and peer support arrangements produced similar effects within SCD studies, but peer initiation and response interventions produced a noticeably smaller effect albeit still a large ES. This suggests that these three interventions are effective in increasing social interactions for students with I/DD and their peers, but there may be differential effects depending on the PMI that is implemented. Finally, SCD studies showed comparable effects whether facilitated by researchers or school staff, suggesting that these interventions are scalable and practical for school settings.

Implications for Practice

This meta-analytic and systematic review has several implications for practice in school settings. All three types of PMI that involve peer training and adult facilitation are effective practices for encouraging social interactions between students with I/DD and their peers. School professionals should consider incorporating these interventions into a broader plan for inclusion of students with I/DD. When implementing these practices, peer and focal student training should be explicit and systematic, as it appears this training is essential for successful implementation of PMI (e.g., Bambara et al., 2018). Educators may also consider how PMI may evolve and build off each other. For example, teachers may consider beginning with a peer initiation and response intervention when supporting initial development of social communication or conversational skills. But as both students with disabilities and their peers build skills, teachers may consider shifting toward peer networks or peer support arrangements to support the development of more authentic friendships.

When paraprofessionals or peers implement training components of these interventions, teachers should work closely with paraprofessionals and students implementing PMI to ensure fidelity of implementation and provide feedback. Furthermore, teachers should be mindful to train and teach peer implementers about equity and inclusion, embracing difference and diversity, and a wide range of communication styles and preferences. Supporting peer implementers’ growth and capacity for meaningful social interactions is just as essential as supporting the growth and capacity of students with disabilities (Fleming et al., 2025). Because students with disabilities often feel like they must mask or hide their disability, an emphasis on mutual learning and growth ensures that the goals of the intervention are not to eliminate non-harmful diagnostic traits (Ne’eman, 2021) or force social conformity (Camarata, 2022) but rather develop and improve foundational learning and social skills for all students to be successful (Bambara, 2022). This is important for equity, neurodiversity, and to help students feel comfortable and authentic within the intervention (e.g., Pak & Parsons, 2020; Scorgie & Forlin, 2019). It is additionally important to align intervention strategies with targeted intervention goals as increasing peer conversation to encourage interaction is not enough; to produce change in specific conversation skills, PMI must include explicit intervention strategies designed to elicit targeted outcomes (Bambara et al., 2016, 2018).

Finally, educators should be careful to support self-determination and agency when including students with disabilities in these interventions with an eye toward equity. Including student choice in goal setting, training, and implementation of the intervention can help ensure that these interventions do not inadvertently create a sense of otherness or become misaligned with the valued outcomes of the student.

Limitations and Future Research

There are several limitations within the current systematic and meta-analytic review that warrant consideration and offer clear directions for future research. First, we focused on a subset of PMIs, thus the effects of PMIs in the extant literature may be larger or smaller than reported in the current study. Future reviews should expand the scope of included interventions to better capture the range and variability of PMI outcomes. Second, we only included studies that were conducted with secondary students with I/DD; thus, important findings from PMI studies implemented for students with other disabilities, such as emotional or behavioral disorders, were excluded. Additional insights might be gained by expanding this focus in future reviews. A third limitation of our study was the inability to conduct a meta-regression. This was due to the nature of the study variables and the relatively small number of available studies. As a result, our examination of whether ESs differed across variables, such as PMI type, training provider, and ongoing peer support should be interpreted as exploratory and descriptive. Determining whether statistically significant differences exist would require a meta-regression. We recommend that future studies empirically examine these core variables so future meta-analytic reviews can aggregate their effects statistically. Fourth, wide CIs around some ESs indicated high variability. These results should be interpreted with caution.

Future research should also place greater emphasis on middle school populations, as only eight of the 37 studies in the current review included participants from this age group. In addition, few studies addressed generalization and maintenance outcomes, limiting our understanding of the sustained impact of PMIs over time. Greater attention to these aspects will help determine the long-term effectiveness and practical applicability of these interventions. Finally, more research is needed to explore whether PMIs facilitate the development of meaningful and reciprocal friendships. The extent to which these interventions promote authentic peer relationships remains unclear in the current literature.

Conclusion

This systematic and meta-analytic review provides additional evidence that PMIs can increase social interactions among secondary students I/DD. Across 37 studies, we found large ESs for each PMI, highlighting the importance of structured peer involvement that includes both training and adult facilitation. These findings reinforce the utility of PMI as a practical and scalable approach for developing meaningful peer interactions in inclusive educational settings

Supplemental Material

sj-docx-1-rse-10.1177_07419325251409318 – Supplemental material for A Meta-Analysis of Peer-Mediated Social Interventions for Secondary Students With Intellectual and Developmental Disabilities

Supplemental material, sj-docx-1-rse-10.1177_07419325251409318 for A Meta-Analysis of Peer-Mediated Social Interventions for Secondary Students With Intellectual and Developmental Disabilities by Sarah Emily Wilson, Jesse I. Fleming, Olivia S. Jamieson and William J. Therrien in Remedial and Special Education

Footnotes

Associate Editor: Matthew Brock

ORCID iDs

Sarah Emily Wilson

Jesse I. Fleming

William J. Therrien

Funding

The authors received no financial support for the research, authorship, and/or publication of this article.

Declaration of Conflicting Interests

The authors declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Supplemental Material

Supplemental material for this article is available at

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