A Meta-Analysis of Interventions to Promote Self-Determination for Students With Disabilities

Abstract

Promoting self-determination is critical to enabling young people to achieve education-related goals and positive postschool employment, community participation, and quality of life outcomes. By developing skills associated with self-determination such as choice-making, decision-making, problem solving, goal setting and attainment, planning, self-management, self-advocacy, self-awareness, and self-knowledge, students with disabilities are better prepared to make purposeful decisions and choices. We conducted a meta-analysis of the literature on interventions to promote self-determination and associated skills with students with disabilities in the school context. We analyzed the types of interventions, populations of students with whom they were implemented, outcomes, and rigor of research. Results demonstrated that interventions to promote self-determination can be effective for students across grade levels, disability labels, and settings. There remains a need for increased focus on promoting self-determination within inclusive, general education settings with students with and without disabilities and of diverse backgrounds. Future researchers should also focus on the rigor of methodological design and associated reporting when conducting school-based research. Additional implications for research and practice are discussed.

Keywords

self-determination disabilities intervention meta-analysis

Researchers have established that students with disabilities who are more self-determined achieve education-related goals at a higher rate (S. Lee, Wehmeyer, Palmer, Soukup, & Little, 2008; Shogren, Palmer, Wehmeyer, Williams-Diehm, & Little, 2012) and have more positive employment, community participation, and quality of life outcomes when they leave school (Lachapelle et al., 2005; Nota, Ferrari, Soresi, & Wehmeyer, 2007; Shogren, Wehmeyer, Palmer, Rifenbark, & Little, 2015). Skills associated with self-determination, including choice-making, decision-making, problem solving, goal setting and attainment, planning, self-management, self-advocacy, self-awareness, and self-knowledge, enable students with disabilities to make purposeful major decisions and daily choices in their lives (Nota et al., 2007; Wehmeyer, 1997). Shogren, Wehmeyer, Palmer, Forber-Pratt, et al. (2015) described the process of conceptualizing a complex construct, like self-determination, as dynamic and impacted by research.

In the past 20 years since the construct of self-determination was first introduced to the disability field, research has emerged that necessitated the expansion of existing theoretical frameworks (Shogren, Wehmeyer, & Singh, 2017). In 2015, Shogren, Wehmeyer, Palmer, Forber-Pratt, et al. introduced Causal Agency Theory, which defines self-determination as a general psychological construct within the organizing structure of theories of human agentic behavior. Causal Agency Theory builds on previous theoretical frameworks, such as the functional model of self-determination (Wehmeyer, 1992), but also capitalizes on the emergence of positive psychology and a strengths-based focus in the disability field.

Within the context of Causal Agency Theory, self-determination is defined as a “. . . dispositional characteristic manifested as acting as the causal agent in one’s life” (Shogren, Wehmeyer, Palmer, Forber-Pratt, 2015, p. 258). Within this understanding, self-determined people act in service to freely chosen goals, and self-determined actions function to enable a person to be the causal agent in their life. Through repeated opportunities to engage in self-determined actions, people develop enhanced self-determination throughout the life course (Shogren, Little, & Wehmeyer, 2017). For the purposes of this review, skills associated with self-determination include the skills outlined in Causal Agency Theory: choice-making, decision-making, problem solving, goal setting and attainment, planning, self-management, self-advocacy, self-awareness, and self-knowledge. Given these new and emerging definitional frameworks for understanding self-determination and its development, and the implications for assessment and instruction in inclusive contexts, there is a need to update existing reviews of the research on interventions designed to promote self-determination.

In 2001, Algozzine, Browder, Karvonen, Test, and Wood conducted a comprehensive review of the literature on interventions to promote “components” of self-determination. The authors targeted studies that focused on enhancing these “components,” which were (a) choice-making, (b) decision-making, (c) problem solving, (d) goal setting and attainment, (e) self-advocacy, (f) self-efficacy, (g) self-awareness and understanding, and (h) self-observation, evaluation, and reinforcement. Algozzine, Browder, Karvonen, Test, and Wood (2001) found that the majority of self-determination intervention research has been conducted with transition-age students with intellectual disability and learning disabilities, although other participant personal factors (e.g., gender, race/ethnicity, socioeconomic status) were not reported. Thus, there is a need to explore the degree to which personal factors that were not in Algozzine et al. (2001) impact self-determination. In addition, subsequent reviews with more specific scopes have been conducted. For example, Wood, Fowler, Uphold, and Test (2005) examined the research on interventions to promote skills associated with self-determination for students with severe intellectual disability, including some of the skills targeted in Algozzine et al. (2001). They included interventions focused on person-centered planning, student-directed Individualized Education Program (IEP), self-regulation, self-monitoring, and self-instruction. Fowler, Konrad, Walker, Test, and Wood (2007) and Konrad, Fowler, Walker, Test, and Wood (2007) reviewed the literature to identify interventions to promote self-determination that targeted academic skills as the dependent measures for students with intellectual and developmental disabilities and any disabilities, respectively. Cobb, Lehmann, Newman-Gonchar, and Alwell (2009) conducted a narrative meta-synthesis of all of the existing systematic reviews, concluding that multicomponent interventions yielded greater positive effects than single-component interventions on self-determination and academic productivity. Still other reviews have looked at specific curricula or interventions.

Raley, Mumbardó-Adam, Shogren, Simó-Pinatella, and Giné (in press) reviewed curricula specifically designed to increase overall student self-determination. S. Lee, Wehmeyer, and Shogren (2015) and Hagiwara, Shogren, and Leko (2017) reviewed the research on a specific model of teaching, the Self-Determined Learning Model of Instruction (SDLMI; Wehmeyer, Palmer, Agran, Mithaug, & Martin, 2000). However, there has not been a comprehensive review of the literature since Algozzine et al. (2001) that has attempted to synthesize the impact of interventions to promote overall self-determination and skills associated with self-determined actions aligned with Causal Agency Theory. However, such a review would provide important directions for the field, providing guidance for future research integrating emerging theoretical perspectives and the degree to which recommendations made in the literature (e.g., use of multicomponent interventions) have been actualized.

The purpose of this review, therefore, was to conduct an up-to-date review of the literature on interventions to promote overall self-determination and skills associated with self-determined action (i.e., choice-making, decision-making, problem solving, goal setting and attainment, planning, self-management, self-advocacy, self-awareness, and self-knowledge). Given the emergence of Causal Agency Theory, a robust framework exists to identify skills associated with self-determination to target in the search for literature. Therefore, the search terms used in the present review are reflective of those in Algozzine et al. (2001), but we omitted self-observation, self-evaluation, and self-reinforcement to align with the recent reconceptualization of self-determined action that is driven by research conducted over the intervening years (Shogren, Wehmeyer, Palmer, Forber-Pratt, et al., 2015). The research questions that guided this review were as follows:

Research Question 1: What interventions to promote self-determination of students with disabilities have been studied in the school context?

Research Question 2: How have interventions intended to promote self-determination of students with disabilities been implemented?

Research Question 3: What populations of students with disabilities have been targeted in interventions designed to promote self-determination?

Research Question 4: What was the rigor of the body of research on interventions designed to promote self-determination of students with disabilities?

Research Question 5: What were the outcomes of interventions designed to promote self-determination of students with disabilities?

Method

Inclusion Criteria

There were five criteria for inclusion in this literature review. First, studies had to be published in an English-language, peer-reviewed journal between 2000 and 2017. The publication date range began with 2000 as Algozzine et al. (2001) included articles from 1972 to 2000. Second, study participants had to include students with disabilities. However, in addition, studies could include students without disabilities. Third, participants had to be aged 3 to 21 because implementation was required to have occurred in the school context (i.e., K-12 or 18-21 school-affiliated program). Fourth, studies must have reported outcomes of an intervention intended to promote overall self-determination or one or more skills associated with self-determined action (i.e., choice-making, decision-making, problem solving, goal setting and attainment, planning, self-management, self-advocacy, self-awareness, and self-knowledge).

Search Procedures

To identify intervention studies, a systematic search process for peer-reviewed articles was conducted. First, electronic databases, including ERIC and PsycINFO, were searched to collect articles published between 2000 and 2017. Search terms included one of the skills associated with self-determined action (i.e., choice-making, decision-making, problem solving, goal setting and attainment, planning, self-management, self-advocacy, self-awareness, and self-knowledge) or “multicomponent” and “self-determination” combined with “disabilit*.” The search terms were used both with and without hyphens to ensure inclusion of all potentially relevant articles.

Article Selection

The titles and abstracts of the search results were screened for inclusion based on their alignment with the inclusion criteria, and 62 were selected for independent examination of the full-text records. Approximately 30% of the 404 articles (n = 122 articles) were randomly selected to demonstrate reliability in decisions about inclusion, and findings indicated 86.3% agreement across reviewers. Reviewers discussed all disagreements until they reached consensus on inclusion. After reviewing full-texts of the 62 identified articles, 30 articles were removed for the following reasons: not in the K-12 or 18-21 school context (n = 12 articles; e.g., Mazzotti, Kelley, & Coco, 2015), not a report of findings from an intervention (n = 8 articles; e.g., Mithaug, 2002), not meeting requirements of an empirical intervention study (n = 7 articles; e.g., Kleinert, Harrison, Mills, Dueppen, & Trailor, 2014), or not measuring overall self-determination or a skill associated with self-determined action (n = 3 articles; e.g., Seong, Wehmeyer, Palmer, & Little, 2015). Similar to the process described above, approximately 30% of the 62 articles (n = 19 articles) were randomly selected for screening for reliability in decisions about inclusion, and findings indicated 89.5% agreement among randomly selected articles. Reviewers discussed all disagreements and reached consensus on inclusion. As a result, 32 articles were identified that met inclusion criteria. Upon review of the included articles by a content expert, two additional articles (Kelly & Shogren, 2014; S. Lee et al., 2008) were identified that did not appear in any of the previous search phases. These articles met all inclusion criteria and were subsequently included for a total of 34 articles (marked with * in the References; see Figure 1).

Figure 1.

Search and article selection flow diagram.

Data Extraction

We coded the 34 articles that met inclusion criteria in two domains: relevant study characteristics and features of the interventions. The study characteristics domain included (a) sample size; (b) participant ages or grade levels, gender, and race/ethnicity; (c) disability label; (d) setting; (e) implementer; (f) intervention length and session duration; and (g) research design. The features of interventions domain included (a) the targeted skill associated with self-determined action or overall self-determination; (b) measures used; (c) dependent variables related to enhanced skills associated with self-determination, overall self-determination, transition and postschool, or other generalized and maintenance outcomes; and (d) outcomes, including effect sizes and social validity. In analyzing the features of interventions, articles were also coded for quality indicators (QIs), as described in the following section.

Coding procedures for QIs

We coded all articles for their incorporation of the QIs established by the Council for Exceptional Children (CEC; 2014) and evaluated by Cook et al. (2015) for group and single-case design studies. QI categories include (a) context and setting, (b) participants, (c) intervention agents, (d) description of practice, (e) implementation fidelity, (f) internal validity, (g) outcome measure/dependent variables, and (h) data analysis. Each QI category included multiple criteria, with 18 criteria applying to both group and single-case designs, six only to group designs, and four only to single-case designs. This resulted in a total of 24 criteria that were coded for group designs and 22 for single-case designs.

Each article was evaluated to determine whether each criterion was 0 = not reported or 1 = sufficient information reported, following standards established in previous reviews using the CEC (2014) QIs (Royer, Lane, Cantwell, & Messenger, 2017). To be considered a methodologically sound study based on the CEC’s (2014) QIs, 100% of the criteria for each QI category must be met; however, other literature reviews have acknowledged the difficulty in meeting all QI criteria when conducting school-based inquiry (Lane, Kalberg, & Shepcaro, 2009). As such, we have adopted modified evaluation criteria used in previous studies that considers a study methodologically sound if it meets 80% of QI criteria (Lane et al., 2009; Royer et al., 2017).

Interrater reliability of data extraction

We independently identified and recorded study characteristics, features, and QIs, and interrater agreement was assessed for 32.4% of the 34 included articles (n = 11). Interrater agreement was calculated by dividing the number of agreements by the number of agreements plus disagreements multiplied by 100. Overall interrater agreement was 88.8%. Disagreements in coding were discussed until a consensus was reached for each disagreement.

Metric for effect sizes

To estimate the common effect of interventions on student self-determination or skills associated with self-determined action, we calculated effect size across included studies (Borenstein, Hedges, Higgins, & Rothstein, 2009). Procedures for computing effect sizes differed by research design (i.e., group or single-case).

Group design

We explored multiple indices, including the d-index (Cohen, 1988) utilized by Algozzine et al. (2001), and based on current best practices in meta-analysis decided on the r effect size statistic to incorporate the maximum possible number of studies in the meta-analysis. Effect size r represents the magnitude of the relationship between two linearly related variables (Borenstein et al., 2009) and is more widely applicable than other effect sizes as it can be calculated in a variety of ways from study-reported findings (from significance levels, raw means and standard deviations, t statistics, F statistics; Card, 2015). According to Cohen (1988) and Rosenthal (1996), the r effect size is interpreted as follows: small (>0.10), medium (>0.30), large (>0.50), and very large (>0.70). The inclusion of a control group varied across included studies, and consequently the data were either reported as pre-/post-intervention for all participants or post-intervention by intervention and control groups. If only one measure for overall self-determination or a skill associated with self-determination was reported, the r effect size was computed and reported. If more than one measure for overall self-determination or a skill associated with self-determined action was reported, the r effect size was computed based on each measure as a separate intervention. The mean effect size was then determined across interventions within a study for an average effect size. After an average effect size was calculated for each study, the mean effect size across studies was calculated.

Single-case design

A variety of methods have been employed to conduct meta-analyses of single-case research, and there is considerable debate as to the most appropriate metric to use as each effect size index has associated limitations (Maggin, Lane, & Pustejovsky, 2017). We considered many effect size indices that have been used in previous meta-analyses, including Percentage of Nonoverlapping Data (PND; Scruggs, Mastropieri, & Casto, 1987), Hedge’s g (Hedges, Pustejovsky, & Shadish, 2012), and Tau-U (Parker, Vannest, Davis, & Sauber, 2011). We ultimately selected Tau-U because it has more statistical power than any other nonoverlap index, and it is also the most discriminating (Parker et al., 2011).

To compute Tau-U for the single-case design studies included in this review, we utilized an online Tau-U calculator (www.singlecaseresearch.org) to analyze data for multiple phases rather than from a single phase independently. Thus, we derived the data points of both the baseline and intervention phases from the single-case design graphs of each article. After entering those data, the output included the Tau-U, p value, and confidence interval for each study that contained sufficient information to derive baseline and intervention data points. The Tau-U effect size reflects the percentage of intervention phase data which shows improvement, and the associated p value denotes the significance of the improvement trend (Parker et al., 2011).

Results

What Interventions to Promote Self-Determination Have Been Studied?

A total of 34 articles published between 2000 and 2015 were identified that met the search criteria. The most articles were published in 2012 (n = 6 articles; 17.6%), and half of the studies in this year were conducted by a single research team (e.g., Palmer, Wehmeyer, Shogren, Williams-Diehm, & Soukup, 2012). No intervention studies targeting change in overall self-determination or skills associated with self-determined action were identified in 2005, 2007, 2016, and 2017.

There was a total of seven single-component interventions that targeted one skill associated with self-determined action (20.6%; e.g., Campbell-Whatley, 2008) and 27 multicomponent interventions that taught multiple skills associated with self-determined action (79.4%; e.g., Sheppard & Unsworth, 2011). Among single-component interventions, two targeted problem-solving skills (Cote et al., 2010; Glago, Mastropieri, & Scruggs, 2009) and two focused on self-advocacy skills (Cuenca-Sanchez, Mastropieri, Scruggs, & Kidd, 2012; Lancaster, Schumaker, & Deshler, 2002). A single article targeted goal setting and attainment (Taylor-Ritzler et al., 2001), planning (Powers et al., 2001), and self-awareness (Campbell-Whatley, 2008).

Regarding outcome variables, 12 studies (35.3%) measured change in overall self-determination using a validated measure (e.g., The Arc’s Self-Determination Scale; Test & Neale, 2004), while 18 studies (52.9%) measured change in one or more skills associated with self-determination using either a validated measure (e.g., Problem-Solving Inventory; Lusk & Cook, 2009) or a researcher-created measure of the skill (e.g., Cote et al., 2010). Four studies (11.8%) measured both overall self-determination and one or more skills associated with self-determination. In addition, 24 studies (70.6%) also measured outcomes in addition to self-determination (e.g., transition or postschool outcomes). The measures used to assess outcome variables for each study are listed in the online supplemental table (available at https://journals-sagepub-com.web.bisu.edu.cn/doi/full/10.1177/0741932518802274).

How Have Interventions to Promote Self-Determination Been Implemented?

Many of the studies (n = 12 articles; 35.3%) were implemented in segregated settings (e.g., special education classrooms; Hagner et al., 2012), although six studies (17.6%) were conducted in inclusive settings (e.g., general education classrooms; Lusk & Cook, 2009) and seven in both settings (20.6%; e.g., Shogren et al., 2012). The other nine studies (26.5%) did not describe the setting of the intervention. In 26 studies (76.5%), interventions were implemented by people natural to the setting, including teachers (e.g., Test & Neale, 2004) and parents (e.g., Hagner et al., 2012). In these studies, researchers or project staff provided training on intervention strategies to natural implementation agents. In one instance, project staff and school personnel delivered an intervention together (Wehmeyer, Garner, Yeager, & Lawrence, 2006). Alternatively, researchers or project staff delivered the intervention in seven studies (20.6%; e.g., Lusk & Cook, 2009).

Research-based curricula or existing models were used to promote student self-determination in 31 studies (91.2%). The most frequently used were the SDLMI (n = 12 articles), Whose Future Is It Anyway? (WFA; n = 4 articles), the Self-Advocacy Strategy (n = 3 articles), and NEXT S.T.E.P Curriculum (n = 3 articles). Two studies used more than one curriculum or model (Wehmeyer, Palmer, Shogren, Williams-Diehm, & Soukup, 2013; Wehmeyer, Palmer, Williams-Diehm, et al., 2011). There were five studies (14.7%) that used technology as part of the intervention. For example, Y. Lee et al., (2011) used Rocket Reader, a computer-based program supporting students to self-direct reading.

Only five studies (14.7%) described the length of each intervention session. Of those that did, the mean duration ranged from 30 to 190 min. Three of the five studies reported a mean session length of 30 min. Twelve studies (35.3%) described the duration of the entire intervention, ranging from 2 to 104 weeks. The most frequently reported intervention duration was 8 weeks (n = 3 articles), followed by 7 weeks (n = 3 articles) and 2 weeks (n = 2 articles). Nine studies (26.5%) reported the frequency of intervention sessions, and most studies included four (n = 3 articles) or five (n = 4 articles) sessions per week.

What Populations Have Been Targeted to Participate in Interventions to Promote Self-Determination?

Sample sizes ranged from 4 (e.g., McGlashling-Johnson, Agran, Sitlington, & Cavin, 2003) to 22 (Lancaster et al., 2002) for single-case designs and from 13 (Campbell-Whatley, 2008) to 493 (Wehmeyer, Palmer, Lee, Williams-Diehm, & Shogren, 2011) for group designs. The aggregate sample size across studies was 3,091 students, comprised of 3,009 participants (M = 125) included in group designs and 82 participants (M = 8.7) included in single-case designs. The aggregate sample was comprised of 1,730 males (56.0%) and 1,280 females (41.4%), although two studies did not report information on participant gender (e.g., Taylor-Ritzler et al., 2001) resulting in the absence of reported gender for 81 participants (2.6%). Participants across studies included children and adolescents ranging from 5 (Palmer & Wehmeyer, 2003) to 21 years (Agran & Wehmeyer, 2000). While most studies reported age ranges, means, and standard deviations, only seven studies (20.6%) reported individual grade levels (e.g., Cuenca-Carlino & Mustian, 2013). Most studies were conducted with students exclusively in high school (n = 8 articles; 23.5%; e.g., Shogren et al., 2012) or a combination of students in high school and 18-21 school-affiliated programs (n = 10 articles; 29.4%; e.g., Taylor-Ritzler et al., 2001).

In terms of race/ethnicity, the majority of participants identified as White/Caucasian (n = 1,633; 52.8%) while others identified as Hispanic/Latino(a) (n = 488; 15.8%), African American/Black (n = 568; 18.4%), American Indian or Alaska native (n = 20; 0.6%), Asian (n = 54; 1.7%), or other (n = 111; 3.6%), and some participants identified as two or more races (n = 6; 0.2%). For 211 participants (6.8%), no race/ethnicity information was provided. The most common disability label was learning disabilities (n = 1,202; 38.9%), followed by intellectual disability (n = 726; 23.5%). Other disability categories included autism spectrum disorder (n = 104; 3.4%), speech and language disability (n = 20; 0.6%), emotional and behavioral disorders (n = 134; 4.3%), other health impairments (n = 81; 2.6%), physical disabilities (n = 14; 0.5%), multiple disabilities (n = 12; 0.4%), or other (e.g., two or more disabilities; n = 197; 6.4%). For 535 participants with disabilities (17.3%), no information on specific disability was provided. Finally, two studies also included students without disabilities (n = 66; 2.1%).

What Was the Rigor of the Body of Research on Interventions Designed to Promote Self-Determination?

Table 1 provides details on the degree to which identified studies addressed QIs for group or single-case research based on information reported in the article. Because the number of criteria assessed per study varied based on research design (10 single-case and 24 group design), we reported the number and percentage of articles that met at least one, more than one, and all elements within each QI category. Across included studies, the QI category with the highest adherence was the description of practice (85.3%), which assesses the degree to which the critical features of the intervention are described so that it is clearly understood and can be reasonably replicated. Another area of strong adherence to QIs across studies was the context and setting category (73.5%), which assesses with one criterion the extent to which sufficient information is provided on the context or setting (e.g., type of school, geographic location, community setting).

Table 1.

Quality Indicators of Interventions Targeting Overall Self-Determination or Skills Associated With Self-Determination.

Quality indicator (number of criteria)	At least one criterion met	More than one criterion met	All criteria met
Context and setting (1)	25 (73.5%)	—	25 (73.5%)
Participants (2)	27 (79.4%)	19 (55.9%)	19 (55.9%)
Intervention agent (2)	29 (85.3%)	21 (61.8%)	21 (61.8%)
Description of practice (2)	32 (94.1%)	29 (85.3%)	29 (85.3%)
Implementation fidelity (3)	20 (58.8%)	11 (32.4%)	3 (8.8%)
Internal validity (9)	33 (97.1%)	17 (50.0%)	15 (44.1%)
Outcome measures/dependent variables (6)	34 (100.0%)	18 (52.9%)	17 (50.0%)
Data analysis (3)	34 (100.0%)	18 (52.9%)^a	18 (52.9%)^a

Reflective of only studies that used a group design.

The QI category with the lowest adherence to the included criteria was by far implementation fidelity (8.8%). This category assesses the degree to which documentation is provided that the practice is implemented with fidelity through the report of intervention procedure adherence, dosage, and exposure. Beyond implementation fidelity, three other QI categories were relatively similar in their lower rates of adherence across all articles: internal validity (44.1%), outcomes measures/dependent variables (50.0%), and data analysis (52.9%). For example, one criterion for the outcome measures/dependent variables category was adequacy of evidence of social validity. While social validity was assessed in nine of 10 single-case design studies (90.0%), only five of 24 studies (20.8%) using group design reported social validity, for a total of 14 studies (41.2%). Overall, when evaluating the 34 studies based on the criteria for methodological soundness (i.e., meeting 80% of QI criteria; Lane et al., 2009), only four studies (11.8%; Cote et al., 2010; Cuenca-Carlino & Mustian, 2013; Kelly & Shogren, 2014; Y. Lee et al., 2011) demonstrated met this criterion.

What Were the Outcomes of Interventions to Promote Self-Determination?

Group design effect sizes

Twelve group design studies included sufficient information for effect size calculations. For nine of the 12 studies, more than one measure of self-determination or a skill associated with self-determination was used and consequently, multiple effect sizes were computed and then aggregated for a single effect size for the study. The average effect size across all studies with sufficient information to compute the r effect size was 0.41, indicating a medium effect. Effect sizes ranged from 0.07 to 0.79. Table 2 presents group design effect sizes and associated interpretations.

Table 2.

Group Design Studies Effect Sizes.

Article	Number of effect sizes	M	Effect size interpretation
Campbell-Whatley (2008)	1	0.70	Very large effect
Glago, Mastropieri, and Scruggs (2009)	4	0.67	Large effect
Hagner et al. (2012)	2	0.61	Large effect
Y. Lee et al. (2011)	2	0.07	Not significant
Palmer, Wehmeyer, Gipson, and Agran (2004)	2	0.40	Medium effect
Palmer et al. (2012)	1	0.26	Small effect
Powers et al. (2001)	1	0.79	Very large effect
Seong, Wehmeyer, Palmer, and Little (2015)	2	0.67	Large effect
Sheppard and Unsworth (2011)	2	0.43	Medium effect
Wehmeyer, Palmer, Lee, Williams-Diehm, and Shogren (2011)	2	0.10	Small effect
Wehmeyer, Palmer, Williams-Diehm et al. (2011)	2	0.17	Small effect
Wehmeyer, Palmer, Shogren, Williams-Diehm, and Soukup (2013)	2	0.10	Small effect

Note. Reflective of only group-design studies with sufficient information to calculate effect size.

Single-case design effect sizes

Sufficient data were available for six single-case studies (see Table 3), and Tau-U was calculated. The other four single-case designs included more than five AB phase pairs, which exceeded the allowable limit of the Tau-U online calculator. Tau-U effect sizes ranged from 0.43 (p < .001) to 1.00 (p = 0) with an average effect size of 0.88, which is a medium effect. To provide an example of the interpretation of these data, a Tau-U effect size of 0.88 indicates 88% of the intervention phase data show improvement, and the associated p value of < 0.001 indicates that the improvement trend is significant. Two articles (Agran, Blanchard, Wehmeyer, & Hughes, 2002; Test & Neale, 2004) had a Tau-U effect size of 1.00 (p = 0) indicating 100% of the intervention phase data improved, and the improvement trend was significant.

Table 3.

Single-Case Design Studies Effect Sizes.

Article	Tau-U	p value	95% CI
Agran, Blanchard, Wehmeyer, and Hughes (2001)	0.43	<.001	[0.02, 0.65]
Agran, Blanchard, Wehmeyer, and Hughes (2002)	1.00	0	[0.73, 1.00]
Agran & Wehmeyer (2000)	0.68	0	[0.43, 0.94]
Kelly and Shogren (2014)	0.85	0	[0.58, 0.98]
McGlashling-Johnson, Agran, Sitlington, and Cavin (2003)	0.91	0	[0.54, 1.00]
Test & Neale (2004)	1.00	0	[0.63, 1.00]

Note. Reflective of only single-case design studies with sufficient information to calculate Tau-U. CI = confidence interval.

Social validity

Of the studies that reported social validity, all 14 (100%) reported positive outcomes. Data were collected via formal or informal interviews (n = 4 articles; 28.6%), survey (n = 5 articles; 35.7%), or both (n = 5 articles; 35.7%). Students (n = 2 articles; 14.3%), teachers (n = 1 article; 7.1%), and both teachers and students (n = 11 articles; 78.6%) contributed social validity data. One of the studies (7.1%) that collected data from teachers and students also obtained social validity from families (Kim & Park, 2012).

Discussion

The importance of self-determination for students with disabilities to achieve both academic goals and associated postschool outcomes such as employment, community integration, and quality of life is well documented in the literature (Lachapelle et al., 2005; Nota et al., 2007; Shogrenet et al., 2012; Shogren, Wehmeyer, Palmer, Rifenbark, & Little, 2015). Given the value of self-determination in the lives of students with disabilities, it is essential that skills associated with self-determination are integrated into instruction in the school context. As Algozzine et al.’s (2001) comprehensive review of intervention studies to promote self-determination was conducted over a decade and a half ago, there is a need for an updated review to document more recent innovation in self-determination research and practice, consistent with emerging theory. The novelty of this review is the utilization of current meta-analysis procedures that were unavailable in 2001 to identify the effectiveness of interventions designed to promote self-determination, with a specific focus on students.

Major findings include (a) an increase in the number of participants in self-determination intervention studies, (b) positive outcomes for students with diverse personal characteristics (e.g., disability status, gender), and (c) a need for improved rigor in reporting quality of research. It is clear that research on interventions to promote self-determination has expanded since 2001, as evidenced by over 3 times as many participants despite 17 less studies included in this review as compared with Algozzine et al. (2001). All studies suggested positive outcomes of intervention for overall self-determination or one or more skills associated with self-determined action. The studies were implemented across grade levels (primarily middle and high school), disability groups, and settings using a variety of instructional methods; however, there are issues that impact the quality of self-determination research, including methodological soundness and reporting, and challenges when conducting school-based research, that are discussed below.

Limitations

With regard to the findings, there are several limitations that must be considered when interpreting the results. One limitation is the lack of information available within articles to allow for meta-analysis. As described previously, only 18 studies (52.9%) included enough information for the calculation of effect sizes, limiting the degree to which effects can be analyzed across studies. The review by Algozzine et al. also noted this limitation as only 43.1% of studies included were amenable to meta-analysis. This finding demonstrates that an area of need across research remains the inclusion of sufficient information to calculate effect sizes. Another limitation was the use of researcher-created measures across a number of studies, an issue also stated by Algozzine et al. (2001) as such measures have not been validated across a diverse sample, and thus may not be as useful across populations and purposes. Interpreting the findings of studies with nonvalidated measures remains problematic and should be considered in the context of ongoing research.

Finally, in the context of identifying and coding the articles for inclusion in this meta-analysis, interrater reliability above 90% is desirable. In this review, interrater reliability for article inclusion and variable coding ranged between 86.3% and 89.5%. These reliability figures may be attributed to differences in interpretation of the degree to which methodological clarity was provided. However, 100% agreement was reached on inclusion and coding disagreements following discussion. This suggests a need to further consider the best way to operationally define inclusion criteria and analysis of articles for meeting QIs.

Implications for Research

As researchers continue to study interventions to promote student self-determination and associated skills, a number of factors, including access to and progress in the general education curriculum and rigor of methodological design, merit increased attention.

Inclusion and access to the general education curriculum

As described in the results, only six studies (17.6%) took place in general education settings, and only two studies (5.9%) included students without disabilities. Given the potential for self-determination interventions to increase access to and progress in the general education curriculum of students with disabilities (S. Lee et al., 2008), future studies should explore the impact of interventions designed to promote self-determination on student goal attainment of both academic and transition-related goals in general education contexts. Shogren, Wehmeyer, and Lane (2016) described how intervention and supports to enhance self-determination could be implemented within a tiered system as a Tier 1 universal support for all students. The authors explain how skills associated with self-determination are critical for all students, which is a finding supported by special and general education literature. This way, teachers can support students with and without disabilities to meet state or local education agency standards to learn core content that is closely related to skills associated with self-determined action (Wehmeyer, Field, Doren, Jones, & Mason, 2004). Both general and special education research suggest skills associated with self-determination are critical for all students, particularly in core content areas like mathematics (Miller, 2013; Raley, Shogren, & McDonald, 2018). It is often assumed that students learn skills associated with self-determined action, such as goal setting, problem solving, and decision-making incidentally; however, more explicit instruction needs to be dedicated to these skills (Shogren et al., 2016), which are included in almost all state or local education agency content objectives (Council of Chief State School Officers, & National Governors Association, 2011).

Rigor of research

The results from the QI analysis and meta-analysis suggest the need for enhanced focus on rigor in research design as only four studies met the weighted evaluation standard of meeting 80% of the QI criteria. As mentioned, according to CEC (2014), 100% of QIs must be met to be considered a methodologically rigorous study. However, if these criteria were applied to the current meta-analysis, all but one study (Cote et al., 2010) would be considered not methodologically sound. Thus, there is a need to find the balance between rigorous QIs for research design and the challenges that arise from implementation in applied settings, like K-12 contexts (Fixsen, Blase, Metz, & Van Dyke, 2013).

An area of need across all studies that was identified by QI analysis was implementation fidelity. Only three studies (8.8%) met all three QI criteria of this category, which assessed information reported on implementation fidelity related to adherence, dosage or exposure, and regular data collection using a direct and reliable measure (CEC, 2014). This mirrors the finding of Algozzine et al. (2001) that less than 20% of included studies reported any information on implementation fidelity. Therefore, a continuing recommendation for future research is to incorporate tenets of implementation science during the design phase of conducting research to plan how programs will be put into action to produce outcomes (Fixsen, Naoom, Blase, Friedman, & Wallace, 2005), with a specific focus on methods to ensure and document implementation fidelity. Such information is critical to understand whether the intervention was implemented as intended and it can be reliably concluded that the intervention led to positive outcomes, rather than an extraneous variable.

Another finding that is consistent with Algozzine et al. (2001) is the lack of social validity across included studies as only 45.1% of studies in their review assessed student, teacher, or other stakeholder (e.g., family) perceptions of usefulness of the intervention. This was a greater issue for group designs, instead of single-case designs, and specific attention should be directed to the most effective ways to include social validity data in group evaluations. Although the findings from this review suggest that perceptions were positive when social validity was assessed in 41.2% of included studies, a necessary component of future research should include reliable measurement and clear reporting of social validity. Finally, although the majority of studies met the criteria for the participants QI category, it is important to note that information on participant race/ethnicity was frequently omitted. Therefore, it is critical for future research to examine and report the effects of personal factors, namely, race/ethnicity, to identify differential effects of personal factors on outcomes related to self-determination intervention.

Implications for Practice

This review suggests that the implementation of practices to promote self-determination impacts outcomes for students with disabilities and provides guidance for practitioners working to support the development of self-determination. The most commonly utilized intervention was the SDLMI (Wehmeyer et al., 2000) as it was used in 12 studies (35.3%) in this review. Given the plethora of research supporting its effectiveness (Hagiwara et al., 2017; S. Lee et al., 2015) and the availability of materials to support its implementation (Shogren, Wehmeyer, Burke, & Palmer, 2017), it is an effective intervention for teachers working to integrate skills associated with self-determination, particularly self-regulated problem solving in service to goals with a high level of flexibility. As a multicomponent intervention, the SDLMI involves instruction on multiple skills associated with self-determination (e.g., choice-making, problem solving). In 2001, Algozzine et al. noted that most studies were designed to promote choice-making skills of people with moderate to severe intellectual disability or self-advocacy skills of people with learning disabilities or mild intellectual disability, and Cobb et al. (2009) found that multicomponent interventions showed greater positive effects on self-determination and academic producitivity outcomes. The more prevalant use of the SDLMI documented in this review provides evidence of a more comprehensive approach to teaching skills associated with self-determination, recognizing the value and impact of multicomponent interventions.

There are also a compelling number of studies that suggest that self-determination interventions can be useful in the context of transition planning and that this remains a central area of focus in the research. This likely emerges from the early emphasis on the role of self-determination in transition planning; 26 studies (76.5%) in the review included transition-age students. Given that all of these studies resulted in either enhanced overall self-determination or a skill associated with self-determination, it is evident that viable means of promoting self-determination for transition-age youth with disabilities have been established. Practitioners can help students set and achieve education- and transition-related goals, benefiting students in school and in the real world.

Conclusion

Since Algozzine and colleagues (2001) first systematically analyzed the literature on interventions to promote self-determination, there has been ongoing development. Over the last two decades, self-determination has expanded in numerous ways both in the literature and in practice including theory, research, and practice. Researchers have further defined self-determination through Causal Agency Theory (Shogren, Wehmeyer, Palmer, Forber-Pratt, et al., 2015) to more fully describe how people become self-determined and guide intervention and assessment. In addition to a better understanding of self-determination, researchers have contributed to the literature regarding interventions to support students with disabilities. However, there is an ongoing need to attend to issues that impact the quality of self-determination research, including methodological soundness and reporting, and challenges associated with conducting school-based research. Overall, however, practitioners can support students by incorporating evidence-based self-determination instruction for students with disabilities in general education settings as a means to enhance transition planning and access to and participation in the general education curriculum. By continuing to focus on and improve instruction to promote self-determination, it is possible to further enhance the focus on enabling young people with disabilities to set and achieve goals as causal agents in their own lives.

Supplemental Material

802274_supplement – Supplemental material for A Meta-Analysis of Interventions to Promote Self-Determination for Students With Disabilities

Supplemental material, 802274_supplement for A Meta-Analysis of Interventions to Promote Self-Determination for Students With Disabilities by Kathryn M. Burke, Sheida K. Raley, Karrie A. Shogren, Mayumi Hagiwara, Cristina Mumbardó-Adam, Hatice Uyanik and Sarah Behrens in Remedial and Special Education

Footnotes

Acknowledgements

The authors acknowledge their mentors and colleagues in Special Education 998: Self-Determination, Support Needs, and the Application of Positive Psychology to the Education of Students With Extensive and Pervasive Support Needs for their support in this work. In addition, the authors acknowledge Dr. Jason Travers from the University of Kansas for his support in planning for the single-case meta-analysis.

Associate Editor: Daniel Maggin

Authors’ Note

Both Kathryn Burke and Sheida Raley provided equal contributions to the article and are co-first authors.

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 at .

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