Parent-Mediated Interventions for School-Age Children With ASD: A Meta-Analysis

Abstract

Parent-mediated interventions (PMIs) are commonly used with children with autism spectrum disorder (ASD), and their effectiveness for young children has been documented. However, no reviews have examined the use of PMIs with older children with ASD. Therefore, the purpose of this review is to investigate the state of the literature regarding PMIs for school-age children with ASD and to evaluate their effectiveness across domains. Eighteen studies of PMIs examining 170 child participants with ASD were included. Participants, interventions, and the effects of the interventions are described. Overall, studies demonstrated moderately positive effects for PMIs for school-age children with ASD. Group design studies demonstrated an overall effect size (ES) of 0.79, 95% confidence interval (CI) = [0.50, 1.09], while single-case design (SCD) studies yielded an overall ES of 1.84, 95% CI = [1.08, 2.60]. More research is needed to understand the differential effectiveness of parent training components, and future research should focus on including measures of parent treatment integrity, to aid in the understanding of program efficacy.

Keywords

evidence-based practices training parent autism spectrum disorders

Toddlers and young children with autism spectrum disorder (ASD) exhibit numerous language, social, and behavioral deficits, and these challenges often persist as children progress into adolescence (Ballaban-Gil et al., 1996). Furthermore, research suggests symptoms remain impactful as individuals mature, as adults with ASD tend to remain dependent on their families or other supports and experience impaired communication, leaving many without meaningful social relationships or employment (Howlin et al., 2004). Concern regarding their children’s future is a common source of stress for parents of children with ASD, and many turn to parent training (PT) programs as a potential opportunity to enhance their children’s outcomes.

The term “parent training” has been applied ambiguously within the field of treatment for ASD, with PT interventions being described using a variety of terms, including parent education and parent-implemented or parent-mediated intervention (PMI; Bearss et al., 2015). PT programs have targeted a variety of outcomes for children with ASD, including communication, socialization, adaptive skills, and challenging behavior. Training has been presented in a range of formats, from entirely self-guided to group or one-on-one instruction provided by a therapist, and have involved differing intensity and duration of intervention, ranging from brief bi-monthly consultation to several outpatient sessions per week. Bearss and colleagues (2015) provide a taxonomy to aid in the categorization of PT programs and understanding of the wide application of the term. They propose two broad categories of PT, parent support and PMI, suggesting the two are distinguished by the intent of the program and agent of change. In their taxonomy, PT programs categorized as parental support provide an indirect benefit to the child through care coordination and psychoeducation designed to promote knowledge gains in the parent. In contrast, PMIs are designed to actively engage the parent to aid in skill acquisition or behavior change in the child.

As Bearss and colleagues (2015) suggest, PMIs can be further defined as either primary or complementary interventions, based upon whether the parent is the primary change agent or a team member assisting in a therapist-led intervention. Primary PMIs involve the parent at the outset of treatment and provide coaching for the parent to directly facilitate improvement in their child’s outcomes. For example, the Joint Attention Symbolic Play Engagement and Regulation (JASPER; Kasari et al., 2014) intervention involves therapists coaching parents on facilitating joint attention, play skills, and language, to promote engagement during play and everyday activities. In contrast, complementary PMIs involve a therapist as the primary agent of change. While the therapist works directly with the child, the parent is given coaching to promote his or her application of the techniques.

Differences also exist in terms of the strategies used to instruct parents. Black and Therrien (2018) conducted a review examining the involvement of parents in interventions for school-age children with ASD following PT and found parent instruction included a variety of strategies, such as lecture/discussion, homework, written materials, data-collection instruction, role-play, videos, and coaching. In the field of PT, it has been assumed that the components used in PT are a primary source of behavior change, but little research has examined the extent to which particular instructional strategies are associated with outcomes for parents or their children (Kaminski et al., 2008).

Importance of PMI

Research suggests PMIs for children with ASD lead to improvement in a variety of children’s outcomes (McConachie & Diggle, 2007; Meadan et al., 2009; Patterson et al., 2012), but most of the literature surrounding such interventions has targeted children younger than 6 years old, with the majority of studies focusing on toddlers. Numerous studies indicate these interventions lead to improvements in a variety of outcomes for young children with ASD, including language skills (Harris et al., 1982; Smith et al., 2000), cognitive abilities and academic skills (Smith et al., 2000), ASD symptoms (Bradshaw et al., 2017), and problem behavior (Wacker et al., 2013). In addition, reviews of PMIs for young children with ASD (McConachie & Diggle, 2007; Meadan et al., 2009) have shown improvements in children’s social and communicative behavior, as well as enhanced parent–child interactions.

Having a child with ASD undoubtedly has a profound impact on a family. Parents of children with ASD experience significant levels of stress, isolation, and psychological difficulty. In fact, parents of children with ASD experience higher levels of stress than parents of typically developing children and parents of children with other disabilities (Hayes & Watson, 2013). Importantly, research indicates participation in PT leads to improvements in stress, self-efficacy, and mental health for parents of children with developmental disabilities (Hand et al., 2013; Singer et al., 2007). Participation in PT has also been shown to increase parents’ knowledge of ASD (Solish & Perry, 2008), as well as their ability to evaluate children’s interventions and make empirical decisions regarding their children’s treatment (Berquist & Charlop, 2014). Importantly, parents receiving training to implement interventions experience added benefits in comparison to parents whose children receive clinician-directed treatment (Bristol et al., 1993; Brookman-Frazee & Koegel, 2004). For example, in a study conducted by Brookman-Frazee and Koegel (2004), parents of children with ASD who collaborated with clinicians to deliver pivotal response training exhibited lower levels of stress and higher parenting confidence than parents whose children received the same clinician-directed intervention without parent involvement.

PMIs for School-Age Children

Although multiple reviews have found that parents are capable of implementing interventions (McConachie & Diggle, 2007; Meadan et al., 2009; Patterson et al., 2012), most of the literature reviews to date focusing on PMIs for ASD have examined effects for children younger than 6 years. No reviews have exclusively examined the effectiveness of PMIs delivered to school-age children (e.g., 6 years and older) with ASD, and the evidence to support PMI for this population is still rather inconclusive. Differences in methodological variables across studies, such as PMI dosage, instructional strategies used in PT, and outcomes targeted, further obscure the understanding of its effectiveness.

The same is true even with young children, for whom the use of PMI is well-supported. For example, in a recent meta-analysis of PMIs for children with ASD between the ages of 1 and 6 years, Nevill and colleagues (2018) found a small but positive treatment effect on ASD symptom severity, cognition, and socialization. However, the researchers stated differences in interventions complicated their ability to interpret and generalize findings related to PMI, and they were unable to examine the relationship between PMI dosage and child outcomes given the small number of studies reporting the dosage of intervention delivered by parents. In addition, concerns regarding study quality, such as risk of bias, imprecision, and inconsistency between findings, limited the researchers’ ability to draw strong conclusions, especially in terms of differential effectiveness across child domains.

Purpose

No syntheses to date have evaluated the effectiveness of PMI targeting school-age children with ASD by focusing exclusively on this age group. However, older children with ASD continue to experience communication, social, and behavioral challenges, suggesting PMI may maintain its importance as children progress into adolescence. Moreover, PMI may provide a source of much needed support for parents, whose psychological well-being tends to decrease as their children with ASD age (Fong et al., 1993).

It is currently unclear what techniques are being used within PMI to instruct parents and to what degree PMI results in gains for school-age children with ASD. Therefore, the purpose of this meta-analysis is to describe the studies evaluating primary PMIs for school-age children with ASD, in which parents are the primary change agents in their children’s treatment, and to determine their effectiveness in terms of child outcomes. Within this review, our sub-questions are (a) What PMIs have parents delivered to their school-age children with ASD, how were parents trained to implement these interventions, and what child outcomes were targeted; (b) What was the mean effect size (ES) of PMIs on child outcomes; and (c) Do the effects of interventions vary across child domains?

Method

Literature Search

We first developed requirements for articles that would be considered for inclusion in the review. Articles must have (a) been published in English in peer-reviewed journals; (b) been experimental or quasi-experimental in nature, which included both studies with a control group and all methods of single-case design (SCD); (c) described a study in which parents worked directly with their children with ASD as the sole interventionists (e.g., parent, not interventionist/therapist, directly delivered intervention to child); (d) included children with ASD (diagnosed with ASD, autism, autistic disorder, pervasive developmental disorder–not otherwise specified [PDD-NOS], high-functioning autism [HFA], or Asperger syndrome, as reported by the authors) aged 6 to 18 years as participants, with a mean age between 6 and 18 years or disaggregate their findings by age and/or disability category; and (e) presented quantitative child outcome data in that at least one dependent variable represented a quantifiable change in child participants; articles reporting exclusively descriptive results or that described only parent outcomes were excluded. In addition, outcome data must have resulted in sufficient within-study comparisons to be considered a valid study on its own. That is, a PMI condition must have been contrasted to a control condition; comparisons with other treatments were excluded. For example, one study (Cavkaytar & Pollard, 2009) was excluded because it compared treatments delivered by a parent, a therapist, and a parent–therapist team, but the PMI portion of the study did not provide outcome data alongside a counterfactual from which an ES could be calculated.

Searches were conducted in three ways. First, we conducted “all text” searches of two databases, Educational Resources Information Center (ERIC) ProQuest and PsycINFO, using Boolean operators and the terms autism or pervasive developmental disorder and parent-implemented, parent-mediated, parent-directed, caregiver-mediated, caregiver-directed, parent training, or parent education. Results were restricted to articles published in scholarly, peer-reviewed journals. The database searches yielded a total of 1,743 possible studies. After examining article abstracts using our inclusion criteria and eliminating duplicate results, 54 studies remained. Next, we reviewed the full-text articles to ensure they met the inclusion criteria. Through this process, 41 articles were excluded for the following reasons: 19 studies included a sample with a mean age less than 6 years and did not include a sufficient number of participants meeting our age criteria from which to calculate ESs (e.g., three comparisons were required for SCD studies). Ten studies lacked a control group, and three articles presented case studies, preventing the combination of ESs with those from the other studies in the corpus because these study designs do not establish functional control. Four studies were excluded because the described interventions were not implemented solely by parents, in that a therapist implemented part of the interventions with the children. Five studies were excluded because they did not include sufficient data from participants with ASD from which ESs could be calculated. For example, Elder (1995) included individuals displaying “autistic features” rather than with ASD diagnoses, and another study (Stuttard et al., 2014) included children with multiple disabilities and did not disaggregate their results. From the original corpus, 13 studies met the final inclusion criteria. Using the same procedures, all searches were repeated by two coders, who reviewed the potential articles to evaluate whether each study met the inclusionary criteria. Coders agreed on the inclusion and exclusion of 100% of the potential articles.

Subsequently, we examined entries within the reference lists of six previous literature reviews that evaluated PT programs and PMIs for children with ASD (Bearss et al., 2015; Lang et al., 2009; Patterson et al., 2012; Postorino et al., 2017; Schultz et al., 2011; Suppo & Floyd, 2012). These searches contributed one additional article. Last, we conducted an ancestral search by examining the reference lists of the studies to be included in the review. These searches yielded one additional study, resulting in a final corpus of 15 articles. Given that some articles reported on more than one study, the 15 articles represent the effects of 18 unique studies. References for articles included in the review are provided in the Supplemental Materials.

Coding Procedures

Codes were developed by briefly examining the studies to be included in the review, and detailed definitions of these codes are available from the primary author upon request. Articles were coded in terms of research design and child participants, including numerical descriptors such as the number of participants, age range, mean age, and diagnoses. Each study was coded using continuous variables in terms of duration (weeks), frequency (sessions per week), and intensity (minutes per session) of PT sessions, as well as format of PT (individual or group). Studies were coded in terms of the purpose of the intervention parents delivered to their children (social functioning, communication, behavior, including both increased compliance and reduction of challenging behavior, adaptive functioning, and ASD education) and whether researchers measured parents’ treatment integrity. Studies were also coded for PT setting (where parents attended training), intervention setting (where parents implemented interventions), outcome variables, and the source of outcome data (e.g., direct assessment or parent report). Codes for outcome variables were identical to those used to code the purpose of interventions, but the two were coded separately because studies occasionally assessed outcomes indirectly related to the primary purpose of an intervention. Two raters coded 60% of the group studies and 58% of the SCD studies, and initial interrater reliability was 95% for group studies and 99% for SCD studies. All discrepancies were resolved during coding sessions, with the reconciled codes used in subsequent analyses.

ES Calculation

ESs for the five-group design studies were calculated as the standardized mean difference between treatment and control groups. Therefore, only dependent measures reported using mean values and standardized deviations were included. We used the standard formula for Cohen’s d by subtracting the control mean from the treatment mean and dividing by the pooled standard deviation. All ESs were calculated using comprehensive meta-analysis (CMA) software (version 3; 2014). ESs were calculated by two raters, who agreed on 94% of values. All discrepancies were resolved, with the reconciled values used in subsequent analyses.

Two indices were calculated for the 13 SCD studies: the percentage of nonoverlapping data (PND) and the percentage of all nonoverlapping data (PAND). PND signifies the percent of the intervention data points that exceed the highest baseline data point (Scruggs et al., 1987). To calculate PND, one must determine the most extreme data point in the baseline phase and how many data points in the intervention phase surpass this point. Scruggs et al. (1987) recommend that the most effective interventions have a PND greater than 70, mildly effective interventions have a PND between 50 and 70, and interventions with no apparent differences have a PND less than 50.

The PAND represents the percent of all data remaining after removing the minimum number of data points that would eliminate all overlap between the baseline and intervention phase (Parker et al., 2007). Both PND and PAND reflect data nonoverlap between phases, but as Parker and colleagues indicate, PAND “uses all data from both phases, avoiding the criticism leveled at PND for wastefulness and for overemphasis on one unreliable data point” (p. 196). To calculate PAND, the number of overlapping data points is divided by the total number of data points across both phases. The criteria for PAND are similar to those for PND, with numbers greater than 50 suggesting moderate effects and numbers closer to 100 demonstrating the most effective interventions. To calculate the above study indices, we calculated PND and PAND for each subject within each study. Then, we summed the numerators and denominators of all subjects within each study, dividing to calculate the ESs for the study. We conducted interrater reliability for PND and PAND for 62% of the SCD studies, including 50% of the 52 panels across studies. Interrater reliability was 88% for PND and 100% for PND, and at the panel level, interrater reliability was 96% and 100%, respectively.

PND is a widely published measure of intervention effects as it is simply calculated, easily interpreted, and applicable to any SCD. However, it overemphasizes a single score in Phase A, reducing its usefulness in the presence of positive outliers. While PAND mitigates this limitation, it maintains several shortcomings similar to those of PND, including the inability to control for positive baseline trend and a lack of sensitivity and discrimination ability, especially at the top end (Parker et al., 2007). Furthermore, the application of nonparametric summary statistics such as PND and PAND to single-case data introduces numerous threats related to systematic bias and misrepresentation of data phenomena (Allison & Gorman, 1994). Therefore, we chose to augment the calculation of these statistics by computing Pustejovsky’s measurement-comparable log-ratio ES measure to quantify intervention effects (Pustejovsky, 2015). In contrast to PND and PAND, Pustejovsky’s ES is not subject to biases related to sample size or baseline levels of behavior, and aggregates are not impacted by differences in outcome metrics across studies. However, this measure of ES is not without its own set of limitations. Primarily, Pustejovsky’s ES is not able to distinguish between complete elimination of a behavior versus reduction to very low prevalence, and in comparison to nonparametric statistics such as PND and PAND, there have been far fewer evaluations of its utility in applied research (Pustejovsky, 2015).

To calculate Pustejovsky’s ESs, we first extracted dependent measure data from each study using Engauge Digitizer software (Version 10.4; Mitchell, 2014) to pinpoint coordinates of data points. Afterward, we confirmed the accuracy of the generated coordinate values by visually checking them against graphical displays and transferred the data into a spreadsheet. A second rater confirmed the extracted data for 30% of the studies by visually comparing the generated coordinates and original graphs. The second rater agreed on 100% of the extracted data points. Finally, ESs were estimated using the following equation:

ω = \log (\frac{M_{T}}{M_{B}}),

where M_B and M_T are mean values for the baseline and treatment phases, respectively. To simplify interpretation and increase the accessibility of our results, as recommended by Pustejovsky (2015), we transformed ESs to percent reduction values by converting log-ratios into exponentiation figures and multiplying by 100.

Analysis

For group studies, we first calculated Cohen’s d for each dependent measure. Then, ESs for each outcome category within each study were calculated. When studies included more than one dependent measure per outcome category, the ESs for all dependent measures were averaged. We then collapsed the ESs for outcomes within each study to calculate an overall study ES. Finally, using the CMA software, all standardized mean differences were scaled to Hedges g, which is the ES used in all subsequent analyses of group studies. In meta-analytic research, the next step would typically be to analyze mediating variables to explain the significant variability using Hedges (1982) equivalent to the analysis of variance (ANOVA) or modified weighted regression (Hedges & Olkin, 1985). However, these analyses are not appropriate in this review given the small number of studies. Therefore, we examined our research questions via a descriptive examination of weighted mean values and CIs, provided that each category consisted of at least two ESs.

For SCD studies, after calculating subject PNDs and PANDs, we averaged these metrics to obtain overall study PND and PAND indices. Then, study dependent variables were collapsed into categories-based outcome, and subject PNDs and PANDs in each category were averaged to calculate indices for each outcome category. To calculate the d-type ESs for the SCD studies, we first computed Pustejovsky’s measurement-comparable log-ratio ES measure for each outcome for each participant in all studies. Second, we used CMA software to combine all d-type ESs within each study to calculate an overall study ES. When studies included dependent measures from more than one outcome category, the d-type ESs for each similar dependent measure were averaged to obtain an ES for the outcome category. Furthermore, ESs for each outcome category were collapsed to estimate the effect of the interventions on particular outcomes. Last, to obtain unbiased estimates, all d-type ESs were scaled to Hedges g using the recommended correction factor J (Hedges & Olkin, 1985). Similar to the above, given the small sample of studies, we evaluated our research questions through a descriptive examination of weighted mean values and CIs. Furthermore, given the differences in how PT was conducted between SCD and group design studies, we chose not to combine the ESs for the two groups of studies.

Results

The purpose of this article was to examine PMIs for school-age children with ASD. A total of 15 articles, representing 18 studies, were reviewed. The results are presented in three sections. First, the participants and interventions used in the studies are described. Second, the effects of interventions used in group design studies are presented, including effects by child outcome. Last, similar effects are analyzed for the SCD studies. See Supplemental File Table 1 for detailed information regarding all studies included in the review. See Supplemental File Table 2 for mean ESs, standard errors (SEs), and CIs for group design studies and Supplemental File Table 3 for nonparametric indices, d-type ESs, SEs, and CIs related to SCD studies. Tables are provided in the Supplemental Materials.

Participants

Collectively, the 18 studies included a total of 170 child participants. The group design studies (n = 5) included a total of 133 participants (M = 44.3, SD = 19.6), diagnosed with either Asperger syndrome or ASD, while the SCD studies (n = 13) included a total of 37 participants (M = 3.1, SD = 0.8), diagnosed with either ASD or PDD-NOS. Overall, studies reported including participants diagnosed with ASD (84.1%), Asperger syndrome (38.8%), or PDD-NOS (2.4%). Given that studies must have included participants with a mean age between 6 and 18 years, participants across all studies ranged from 3.3 to 23.0 years old (M = 11.7). However, the majority of participants were school-aged. Of the 37 participants in the SCD studies, only one individual was older than school-age, and despite the fact that three-group design studies included participants younger than school-age, the mean ages of their participants were well within our desired range.

Interventions

Of the 18 interventions delivered to children, most focused on reducing challenging behavior and promoting desired behavior (n = 8), while others targeted the improvement of language and communication outcomes (n = 5), adaptive skills (n = 3), and social functioning (n = 2). PMIs within each domain involved teaching parents a range of instructional approaches to promote skill development in their children.

Challenging behavior

The five-group design studies (Kuravackel et al., 2018; Sofronoff et al., 2004; Stuttard et al., 2016) all targeted reducing child problem behaviors. Kuravackel and colleagues (2018) reported on two unique studies, comparing a parent group receiving the Collaborative Model for Promoting Competence and Success (COMPASS) for Hope (C-HOPE) intervention through face-to-face training to a control group and to those receiving the same intervention through telehealth. Both groups received the intervention over four 2-hr group sessions and four 1-hr one-on-one sessions offered over 8 weeks. Stuttard and colleagues (2016) examined the effects of training parents using the Cygnet intervention, which provided ASD education and aimed to reduce child problem behaviors through six weekly group training sessions. In both of these PT programs, parents were given information on ASD symptoms and their effect on behavior, and they were taught a variety of behavior management techniques, including antecedent strategies, steps for teaching replacement behaviors, and reinforcement practices. Sofronoff and colleagues (2004) also reported on two unique studies, targeting children’s social skills, as well as challenging behaviors. They compared parent groups who were taught through either one 1-hr group session or four weekly hour-long sessions in a one-on-one format to parents in a control group. Parents in both groups learned basic behavior management strategies and were taught to use visual supports and social stories to proactively decrease challenging behaviors, manage anxiety, and promote appropriate behavior and social skills.

Five SCD studies targeted children’s challenging behavior. Crone and Mehta (2016) instructed parents in the use of various strategies, including antecedent modification, redirection, and reinforcement, to decrease children’s problem behavior during meal-time. Marroquin and colleagues (2014) taught parents to use compliance training and least-to-most prompting to reduce children’s challenging behavior and promote appropriate behavior. Similarly, Robertson (2016) taught three parents of children with ASD to implement a differential reinforcement intervention incorporating visual supports to teach appropriate alternatives to child problem behaviors.

Language and communication

Five of the SCD studies targeted communication outcomes. Casey (1978) taught mothers to use manual signs with verbalizations to increase the development of communication skills and decrease problem behavior in their 6- and 7-year old children with ASD. Charlop and Trasowech (1991) taught the parents of three children with ASD to use a time delay procedure to increase appropriate spontaneous speech across multiple settings that were part of each child’s daily routine. Similarly, Charlop-Christy and Carpenter (2000) taught three parents of children with ASD to deliver incidental teaching and discrete trial training to improve their children’s speech. Following training in both studies, researchers collected data on children’s spontaneous speech, imitation, and incorrect speech, which included inappropriate verbalizations or verbalizations that were not spontaneous. Hsieh and colleagues (2011) also taught parents to implement incidental teaching to improve their children’s requesting behavior but collected data only on correct, independent responses.

Adaptive skills

Three articles reported on SCD studies aimed at improving children’s adaptive skills. Cosbey and Muldoon (2017) taught parents to implement a comprehensive feeding intervention utilizing communication supports and modifications to the physical and social environments to promote food acceptance. In the study by Harriage and colleagues (2016), parents learned to use least-to-most prompting procedures to teach pedestrian safety skills to their children, and Klett and Turan (2012) taught parents to use social stories and task analyses to teach menstrual care skills to their female children with ASD.

Social functioning

An additional two SCD studies described social skills interventions. Dogan and colleagues (2017) taught parents to be social skills trainers for their children with ASD, while Liu and colleagues (2015) taught a parent to implement a self-management intervention with her child, aimed at promoting social skills, such as not interrupting, asking for opinions, and greeting unfamiliar adults.

PT

PT delivered in the group design studies was conducted weekly, for 1 to 8 weeks, in 60- to 180-min individual or group sessions. Where reported (n = 4), parents attended PT during face-to-face sessions at a university or through teleconferencing at a university or clinic. None of the group design studies indicated where parents actually implemented the skills they were taught. In addition to didactic instruction, parents participating in the group design studies most often received written materials. In contrast, PT interventions delivered in the SCD studies were conducted weekly, for 4 to 20 weeks, in 10- to 120-min individual sessions. In addition to joining in lecture and discussion, parents in the SCD studies most often received feedback or modeling or participated in practice and role-play activities. In all but one of the SCD studies (Casey, 1978), parents received training and conducted PMIs in the home. Parents in the Casey (1978) study were instructed in a clinic and implemented the skills they learned in both the clinic and home setting. Two studies (Charlop & Trasowech, 1991; Crone & Mehta, 2016) reported training parents both in-home and in a clinic, while two additional studies (Harriage et al., 2016; Liu et al., 2015) described training and implementation both in-home and in the community. Overall, PT in the SCD studies took place over longer periods of time in shorter individualized sessions, while training in the group studies tended to take place over fewer weeks for longer sessions that were offered in a group format and generally included instructional strategies that were of low intensity and required little parent engagement. Furthermore, none of the group design studies reported levels of treatment integrity, compared with nine of the 13 SCD studies.

Effects for Group Design Studies

The group design studies obtained an overall ES of 0.79, 95% CI = [0.50, 1.09] in the comparison of parents participating in training and those in control groups. Two studies examined social outcomes, demonstrating an ES of 0.95, 95% CI = [0.45, 1.45], and all studies evaluated challenging behavior, demonstrating an ES of 0.80, 95% CI = [0.32, 1.28]. In an effort to be exhaustive in our literature search, we chose to consider for inclusion studies using quasi-experimental designs. One such study, Stuttard et al. (2016) was included in our final sample, and the lack of random assignment in this study introduces uncertainties regarding the internal validity of the researchers’ findings. Although the authors state there were no significant differences between treatment and control groups on key sociodemographic characteristics or outcome variables at baseline, the literature suggests the potential for an unknown covariate resulting in a difference between groups at postintervention. Therefore, we repeated our ES calculation removing outcomes from Stuttard and colleagues (2016). Excluding the quasi-experimental study, the remaining group design studies demonstrated an overall ES of 0.95, 95% CI = [0.60, 1.30], and an ES of 0.96, 95% CI = [0.56, 1.36] for challenging behavior.

Effects for SCD Studies

Overall, the 13 SCD studies demonstrated an ES of 1.84, 95% CI = [1.08, 2.60] for the effect of PMI on child outcomes. The studies focusing on communication (n = 5) demonstrated an ES of 2.40, 95% CI = [2.00, 3.88] on child communication outcomes. Outcome PNDs ranged from 51% to 100% (M = 60%), while study PANDs ranged from 65% to 100% (M = 75%). These indices suggest the interventions were moderately to highly effective, while the g ES indicates the interventions were highly effective in changing children’s communication skills. Studies targeting challenging behavior (n = 5) demonstrated an ES of 0.93, 95% CI = [0.35, 1.51] on child problem behaviors and compliance. Outcome PNDs ranged from 38% to 100% (M = 70%), while study PANDs ranged from 76% to 100% (M = 90%). These indices demonstrate wide variability, with 38% indicating no apparent difference following the intervention and 100% indicating the intervention was highly effective. The g ES, however, indicates the interventions were highly effective in decreasing challenging behavior.

Studies focusing on improving children’s social functioning (n = 2) demonstrated an ES of 0.66, 95% CI = [0.45, 0.86] on children’s conversational skills. Study PNDs ranged from 56% to 94% (M = 74%), while study PANDs ranged from 84% to 97% (M = 90%). Studies targeting adaptive behavior (n = 3) demonstrated an ES of 0.64, 95% CI = [0.46, 0.83] on children’s adaptive behaviors, including feeding, pedestrian safety, and menstrual care. Study PNDs ranged from 50% to 100% (M = 93%), while study PANDs ranged from 92% to 100% (M = 97%). The nonparametric statistics suggest the interventions were moderately to highly effective, while the g ESs indicate a moderately strong effect of the interventions on children’s social and adaptive functioning.

Discussion

The purpose of this meta-analysis was to examine PMIs for school-age children with ASD. We identified and reviewed a total of 15 articles published between in or before 2018. The majority of child participants were diagnosed with ASD, and the mean age of participants was 11.7 years. PT interventions took place for between 1 and 20 weeks, for between 10 and 180 min, in one-on-one or group sessions, delivered about once per week. Generally, SCD studies described PT that was provided in individualized sessions over a shorter duration at a greater intensity than those described in the group design studies. PT sessions used between one and seven strategies to instruct parents. The most widely used instructional strategy in PT was didactic instruction. However, parents in SCD studies tended to receive instruction that included higher intensity strategies, such as feedback, modeling, practice, and role-play than parents in the group design studies, who tended to receive didactic instruction paired with written materials.

There was considerable variability between the effects demonstrated by the SCD and group design studies, which may be due, in part, to differences inherent in the two experimental designs. For example, SCD studies typically use objective and direct data-collection methods, involve decision-making concurrent with data collection, and have thematic tendencies toward the behavior analytic. Differences in the intensity of the interventions and instructional strategies used may have also impacted the effectiveness of the interventions and contributed to the discrepancy in ESs between the two groups of studies. Research suggests behavioral interventions delivered at higher intensities over greater periods of time demonstrate greater effects (Reichow & Wolery, 2009), and research in parent and staff training indicates strategies used during training have varying effects on participants’ outcomes. For example, in a meta-analysis of PT for parents of children with behavior problems (Kaminski et al., 2008), studies of interventions using different instructional strategies to teach parents demonstrated varying ESs. In terms of improving parenting skills and behaviors, interventions including manuals (ES = 0.38), homework assignments (ES = 0.39), role-playing (ES = 0.45), and practicing with one’s own child (ES = 0.91) had differing effects.

Similarly, a review of training programs for staff working with individuals with intellectual disabilities (van Oorsouw et al., 2009), showed in-service training combined with coaching yields better outcomes than implementing either format alone. The researchers also found a package of instructional strategies was more effective than using a single technique. Importantly, van Oorsouw and colleagues (2009) indicated coaching was an essential instructional component within their corpus of studies, as programs including coaching demonstrated higher effects than those without this component. Interestingly, the majority of the SCD studies in our review included coaching as an instructional strategy during PT (n = 10), while none of the experimental studies reported coaching parents. In addition, PT in the SCD studies included more instructional components on average (M = 3.75) than the experimental studies (M = 2.40). Previous research suggests differences in the ESs between the two groups may be due, at least in part, to differences in the instruction parents received.

Parents’ treatment integrity may also play a part in the differences in results reported between SCD and group studies. Treatment integrity on the part of the parents was reported in most SCD studies, and was generally high, whereas treatment integrity was not reported in any of the group design studies. This is especially important to consider when interpreting the effects of the group design studies, as research indicates experimental results can be confounded when an intervention is not implemented as designed, making it challenging to discern a functional relationship between an intervention and behavior change (Cooper et al., 2007). The data-collection methods used in the studies is another difference between the group and SCD studies that could potentially explain the variability in outcomes between the two sets of studies. All of the outcomes in the group design studies were obtained through parent report, while all outcomes in the SCD studies were obtained through direct observation.

Interventions included in this review were primarily aimed at improving communication outcomes, social skills, problem behavior, or adaptive functioning. This finding is similar to those of other reviews of programs for younger children with ASD (Bearss et al., 2015; Patterson et al., 2012; Schultz et al., 2011), which found PT tended to focus on alleviating the core symptoms of ASD and to Black and Therrien (2018), which found PT interventions for school-age children with ASD tended to focus on communication, social/emotional functioning, and challenging behavior. Across group design studies (n = 5), a mean ES of 0.79 was obtained, indicating a moderately strong positive effect on children’s outcomes. Similarly, SCD studies demonstrated an overall ES of 1.84, suggesting a strong positive effect of PMI on outcomes for school-age children with ASD. While some SCD studies examined communication and adaptive outcomes, no group design studies evaluated those same variables from which overall conclusions can be drawn. However, SCD and group design studies examining social functioning demonstrated ESs of 0.66 and 0.95, respectively, indicating a moderately strong effect on children’s social skills. SCD and group design studies examining challenging behavior demonstrated ESs of 0.93 and 0.80, respectively, indicating a strong effect.

Meta-analyses of PMIs for younger children have reported comparable or smaller ESs. For example, Nevill et al. (2018) conducted a meta-analysis of PMIs for children with ASD between 1 and 6 years of age, calculating ESs of 0.16 for communication and language and 0.22 for socialization. Similarly, Oono et al. (2013) conducted a meta-analysis of parent-mediated early intervention programs for children with ASD, concluding that children in treatment groups exhibited language outcomes that were 0.14 to 0.45 standard deviations higher than those in comparison groups. An additional review of PT programs aimed at reducing disruptive behavior in children with ASD (Postorino et al., 2017) included studies with a mean participant age of 5.77 years and yielded an overall standardized difference in mean values of −0.59. The aforementioned ESs associated with PMIs for children with ASD less than 6 years old are significantly lower than those demonstrated by the studies in our review. Combined with our results, these findings indicate PMI maintains, and may even increase, in importance as children with ASD age.

Limitations

There are several limitations to this review and meta-analysis. First, only 18 studies met our criteria for review, making comparisons among and between study variables difficult. For example, comparisons of interventions including different populations and instructional strategies were not possible given the small sample size. Similarly, studies did not consistently report demographic information on their participants beyond gender, diagnosis, and age. Due to the small number of studies in our corpus and the limited number of studies reporting demographic information for their participants, we were unable to calculate ESs based on participant variables. Second, we did not use indicators of methodological quality as criteria for analysis. However, most studies did not include detailed descriptions of the characteristics of their PT or interventions implemented by parents. Therefore, the lack of information regarding the characteristics of the interventions and the small sample of studies would have made such an approach problematic. Many researchers have documented the tendency for only those studies with more rigorous methods and stronger results to be published, while unpublished studies tend to demonstrate smaller effects (Rosenthal, 1978) leading to potential publication bias. In addition, we did not contact authors or experts in the field to locate articles for inclusion in our review, nor did we include gray literature in our analysis. Similarly, we included one study using a quasi-experimental design (Stuttard et al., 2016), which introduces challenges related to the internal validity of findings given the lack of random assignment. However, excluding this study from our analysis resulted in a higher overall ES that still suggests a strong positive association between PMI and child outcomes. Finally, we required studies have a mean participant age indicating the majority of children were school-aged (6.0–18.0 years) to be considered for inclusion in the review, which inadvertently led to the inclusion of studies that involved a limited number of participants above or below school age. We were unable to remove the effects from those participants falling outside of our target age range due to study design, but overall, the studies overwhelmingly reported effects for school-age children.

Implications and Recommendations for Further Research

There are several practical implications of this analysis. First, results indicate that PMIs may be effective in improving outcomes for school-age children with ASD. PMIs targeting problem behavior and communication skills are most likely to have the greatest impact on child outcomes. Furthermore, the individualized instruction and intensity of SCD interventions is likely needed to make a significant difference in child outcomes. The studies examined in our analysis suggest the literature on PMI is moving toward establishing a well-developed standard of procedures. However, several areas still need to be addressed before establishing PMI as an evidence-based practice for school-age children with ASD. For example, the majority of the SCD studies examined in our review met Horner et al.’s (2005) criteria for SCD research to document a practice as evidence-based, such as replication of experimental effects across participants and the demonstration of a functional relationship between child outcomes and the delivery of PMI. However, we found operational definitions of PMIs, descriptions of implementation contexts, and measures of treatment fidelity lacking across studies. Given the small number of studies on the topic, additional research is needed to evaluate the effectiveness of these interventions. Future research should focus on the issues mentioned above, such as measuring parents’ adherence to interventions and analyzing the effectiveness of core components of PT used in PMIs. For example, the most intensive instructional components, such as individualized coaching, may have a greater impact on parent implementation and child outcomes than less intensive teaching methods, such as didactic instruction.

Previous reviews of staff training suggest there are similarities between programs used to train staff and parents and our findings are consistent with the findings of reviews in this area. For example, programs including coaching seem to demonstrate higher effects than programs that do not include this component. However, more research is needed to examine the differences between staff and PT and the variables within each context that contribute to the effectiveness of these programs. Through these additional understandings, the development of PT can be guided by our knowledge of the structure and instructional components that make training programs most effective for individuals with ASD and their families.

Supplemental Material

PI_Meta_Tables_Supplemental – Supplemental material for Parent-Mediated Interventions for School-Age Children With ASD: A Meta-Analysis

Supplemental material, PI_Meta_Tables_Supplemental for Parent-Mediated Interventions for School-Age Children With ASD: A Meta-Analysis by Marie Ratliff-Black and William Therrien in Focus on Autism and Other Developmental Disabilities

Supplemental Material

ReviewReferences_Supplemental_Final – Supplemental material for Parent-Mediated Interventions for School-Age Children With ASD: A Meta-Analysis

Supplemental material, ReviewReferences_Supplemental_Final for Parent-Mediated Interventions for School-Age Children With ASD: A Meta-Analysis by Marie Ratliff-Black and William Therrien in Focus on Autism and Other Developmental Disabilities

Footnotes

Declaration of Conflicting Interests

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

Funding

The author(s) received no financial support for the research, authorship, and/or publication of this article.

Supplemental Material

Supplemental material for this article is available online.

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