Abstract

This article reports the results of an examination of the endorsement, reliability, and factorial validity of the VIA–Youth and assessment of character strengths and virtues developed for the general population in youth with and without intellectual disability. Findings suggest that, generally, youth with intellectual disability endorsed character strengths as being like them at lower levels, although few differences were significant. Issues related to measurement, particularly the establishment of measurement invariance, emerged for some virtues. Reliability of the scale was similar across the two groups. Implications for future research and practice are discussed.

Assessment in the disability field, particularly the intellectual disability field, has been dominated by a focus on the identification of deficits and limitations. Historically and currently, the diagnostic criteria for intellectual disability require documentation of significant limitations in intellectual functioning and adaptive behavior (Schalock et al., 2010; Schalock et al., 2007). However, increasingly, policy and best practice recommendations in special education and transition services and supports recognizes that information on limitations in functioning alone is not sufficient to guide the development of a comprehensive plan for education and transition supports and services. For example, the Individuals With Disabilities Education Act requires that the individualized education program (IEP) team must consider the strengths of the child and that transition services must take into account the “child's strengths, preferences, and interests” (20 U.S.C. Sec. 1401 [34]). However, in order to systematically consider the strengths of children with disabilities, valid and reliable assessments of strengths are needed to enable this consideration. In practice, general statements about strengths are often made and included in a child's IEP and transition documents, but these statements are typically not based on assessment data as there have not been valid and reliable tools to identify strengths rather than deficits, particularly from the perspective of adolescents with intellectual disability (Epstein, Synhorst, Cress, & Allen, 2009; Woodard, 2009).

Just as in the intellectual disability field, the field of psychology has also been dominated by a focus on identifying and addressing deficits. In the early 2000s, however, the field of positive psychology emerged, placing increased attention on the importance of identifying and building on positive traits and emotions (Seligman & Csikszentmihalyi, 2000). One area that has received significant attention in the field of positive psychology is assessing and intervening to promote character strengths and virtues (Peterson & Seligman, 2004). Specifically, a classification system, the VIA Classification of Strengths, was developed by a group of 55 scientists to provide an alternative to the Diagnostic and Statistical Manual of Mental Disorders-Fifth Edition (American Psychiatric Association, 2013) classification system.

VIA Classification of Strengths

The VIA Classification of Strengths defines character as “a family of positive characteristics shown in feelings, thoughts, and actions, each of which exists in degrees” (Park & Peterson, 2009, p. 3). The classification system includes 24 character strengths, which are listed in Table 1 with a brief description of each. The 24 character strengths are organized into six overarching virtues (i.e., wisdom, courage, humanity, justice, temperance, and transcendence), which are defined as “core characteristics valued by moral philosophers and religious thinkers” (Park & Peterson, 2009, p. 3). Two assessments have been developed based on the VIA Classification—the VIA Inventory of Strengths (VIA-IS; Peterson & Seligman, 2004) and the VIA Inventory of Strengths for Youth (VIA-Youth; Park & Peterson, 2006b). Both are self-report measures of the 24 character strengths and 6 virtues, however, the VIA-IS is for adults 18 years and over and the VIA-Youth is for youth ages 10-17 years. The main purpose of the tools are to identify the strengths that people endorse (i.e., rate as being like them) at the highest levels, which are called signature strengths, and use this information to develop interventions that capitalize on these strengths. For example, researchers have found in randomized control trials that, when individuals are asked to use their highest rated strengths in new ways each day for a week, they show increases in happiness and well-being and decreases in depression for up to 6 months (Gander, Proyer, Ruch, & Wyss, 2012; Seligman, Steen, Park, & Peterson, 2005). In youth populations, interventions around signature strengths use have led to elevations in engagement and hope (Madden, Green, & Grant, 2011).

Table 1

The VIA Classification of Character Strengths and Virtues

The VIA Classification of Character Strengths and Virtues
The VIA Classification of Character Strengths and Virtues

Character Strengths and Disability

As mentioned previously, the VIA-IS and VIA-Youth were developed to enable self-report on the degree to which people believe items describing character strengths are like them or not like them. The tools were developed with the general population, and initial research did not explicitly include people with disabilities. There have been efforts, however, to demonstrate the reliability and validity of the VIA-Youth in adolescents with disabilities. Shogren, Wehmeyer, Lang, and Niemiec (2016) collected data from approximately 300 adolescents with and without disabilities, finding similarities in the reliability and factorial validity of the scale across the two groups, although adolescents with disabilities tended to rate themselves lower on the degree to which the character strengths were like them. The sample was comprised of youth with a wide range of disabilities (i.e., learning disabilities, intellectual disability, autism, other health impairments, emotional disturbances, speech and language impairments, and physical and sensory disabilities) and analyses of subgroup differences were not possible because of the small sample size. Another tool, the Assessment Scale for Positive Character Traits–Developmental Disabilities (ASPeCT-DD; Woodard, 2009), was developed to allow for proxy report for people with severe disabilities, including intellectual disability, on 10 strengths identified in the field of positive psychology. The ASPeCT-DD predated the VIA Classification system, and does not have a self-report version.

There is a need for ongoing work to determine the reliability and validity of self-report tools in adolescents with intellectual disability, particularly related to the VIA Classification as it is a widely utilized classification system for strengths and virtues in the field of positive psychology (Peterson & Seligman, 2004) that is aligned with interventions and positive outcomes in the general population that have been demonstrated to impact quality-of-life-related outcomes (Seligman et al., 2005). Having self-report measures, in addition to proxy report measures, is important to enable people with intellectual disability to voice their perceptions (Stancliffe, Tichá, Larson, Hewitt, & Nord, 2015), particularly when assessing character strengths. Work is needed to determine the degree to which the VIA-Youth provides a valid and reliable tool for this population to guide future assessment and intervention work. Having valid and reliable tools enables the assessment of strengths and the development and implementation of a variety of character strengths interventions that build on the character strengths of people with disabilities, shifting the focus from identifying and remediating deficits (Dykens, 2005, 2006; Niemiec, Shogren, & Wehmeyer, in press). This does not mean that the enhancement of skills will not be a focus, but instead, as Diener (2009) wrote about positive psychology, “positive psychologists do not ignore the negative in life. However, they maintain that often one form of solution to problems, and in some cases the most effective one, is to build on the positive rather than directly work on the problem” (p. 10).

Purpose of the Study

The purpose of this study was to build on previous research on the VIA-Youth with adolescents with disabilities (Shogren et al., 2016) and specifically examine the endorsement, reliability, and factorial validity of the tool with youth with intellectual disability compared to youth without disability. Such work is important because of the unique needs of adolescents with intellectual disability related to assessment (Stancliffe et al., 2015) and the lack of attention to self-report of character strengths in the intellectual disability field. Specifically, we examined differences based in endorsement and measurement of the 24 character strengths and six virtues (Park & Peterson, 2006b) defined in the VIA Classification. The overarching goal was to initiate research on the reliability and validity of the measure in youth with intellectual disability, and examine comparability to its use in youth without intellectual disability. This study, although preliminary, was developed to inform future research on support needs assessment in the population of adolescents with intellectual disability. We examined three research questions:

  1. Are there differences in the endorsement of the 24 character strengths and six virtues across adolescents with and without intellectual disability?

  2. Are there differences in the measurement and factorial validity of the 24 character strengths and six virtues across adolescents with and without intellectual disability?

  3. Are there differences in the reliability of the 24 character strengths and six virtues across youth with and without intellectual disability?

Method

Sample and Procedures

Participants with and without disabilities were recruited through school districts across the United States and through community organizations that supported youth with and without intellectual disability (i.e., The Arc of the United States, Special Olympics, YMCA, Boy Scouts of America). When working with school districts, the research team planned recruitment efforts in collaboration with an administrator (i.e., dean, principal) or a specific teacher interested in the project. Recruitment efforts targeted teachers and related support providers that worked with students with and/or without an intellectual disability. The presence of intellectual disability was confirmed by teachers using students' educational records, and to ensure the sample of students without disabilities did not have other disabilities, teachers confirmed that the students did not receive special education services. In working with community organizations, the research team disseminated recruitment information to a variety of local, state, and national organizations that had distribution lists targeting adolescents with intellectual disability and their parents, and asked them to share the information.

The sample included 125 adolescents with intellectual disability and 133 adolescents without disability, aged 10–17 (M = 13.64; SD = 2.0). The average age for participants with intellectual disability was slightly higher at 14.0 (SD = 1.92) years versus 13.3 (SD = 2.01) for participants without disability. There were more females (n = 81) than males (n = 52) in the no disability group, but more males (n = 67) than females (n = 58) in the intellectual disability group. Approximately 55% of the sample was Caucasian, with 30% (n = 75) reporting their ethnicity as Hispanic/Latino. Further demographic information is provided in Table 2.

Table 2

Descriptive Statistics for Participants With Intellectual Disability, No Disability, and in Total

Descriptive Statistics for Participants With Intellectual Disability, No Disability, and in Total
Descriptive Statistics for Participants With Intellectual Disability, No Disability, and in Total

Measure

As described previously, the VIA Inventory of Strengths for Youth (VIA-Youth; Park & Peterson, 2006a) was the primary focus of this study. It was developed to be a self-report measure of character strengths and virtues for youth ages 10–17. It was created by modifying the VIA-IS, which was created for adults over the age of 18. The original VIA-Youth contained 198 items, but subsequent work by the researchers that developed the assessment led to a shorter version that used the four highest correlated questions for each character strength. This shorter version consists of 96 items rated on a 5-point Likert scale (1 = very much like me; 2 = mostly like me; 3 = somewhat like me; 4 = a little like me; and 5 = very much unlike me) that can be conceptually grouped into the 24 character strengths and six overarching virtues listed in Table 1 (VIA-Youth; Park & Peterson, 2006b). The short version was used in this study. Researchers have found that the VIA-Youth has strong reliability (coefficient alpha ranging from .75 to .95 for the 24 character strengths) and construct validity showing small to moderate correlations with related constructs, such as life satisfaction (VIA Institute on Character, n.d.).

Missing Data

For the 258 participants with and without disabilities, there was a small amount of missing data on single questions on the VIA-Youth, ranging from 1 to 7 (0.4%–2.7%) missing responses across items. Approximately 70% of the sample (n = 182) answered all questions; 15 students without disabilities left at least one question blank and 32 students with intellectual disability left one or more questions blank. The first part of the analysis plan (described subsequently) required complete data for an observation to be retained, so the data was imputed. To impute the missing data, covariates were identified that were statistically significant predictors of missingness and were used with group membership for an imputation process. Due to the small amount of missingness, only a single imputation was required (Little, Jorgensen, Lang, & Moore, 2013); predictive mean matching with 25 iterations was used in the multiple imputation with chained equations process via the mice package (van Buuren & Groothuis-Oudshoorn, 2011) in R 3.2.0 (R Core Team, 2015).

Analysis Plan

Research question 1: Endorsement

After imputing the data, responses were averaged to generate scores for each of the 24 character strengths and six virtues for each student, consistent with the scoring procedures for the VIA-Youth. These averaged scores were first used to look at differences in endorsement of character strengths and virtues across the two groups. Mean differences were compared for the averaged responses for the 24 character strengths and six virtues with a t-test. In order to control for Type I error, alpha levels were adjusted for all mean difference testing; adjustment for the 24 strengths resulted in a critical value of t(256) = ±3.122 (p < .002). The adjusted critical value for t-tests of the six virtues was t(256) = ±2.660 (p < .0083).

Research question 2: Measurement and factorial validity

Next, the averaged responses were used as parcels to examine measurement invariance and latent differences using multigroup confirmatory factor analysis (MG-CFA; Kline, 2011), as the sample size was too small to analyze 96 individual questions. The averaged character strength responses, consistent with theoretical framework for the VIA-Youth (see Table 1) and previous research with youth with disabilities (Shogren et al., 2016), was used to create a separate model for each of the six virtue constructs (i.e., wisdom, courage, humanity, justice, temperance, and transcendence) to test measurement invariance and latent differences, referred to as the virtue models. Figure 1 provides an example of a single factor model for one of the virtues, wisdom. This same structure was replicated for each of the remaining virtues. A seventh, overall model was then created with all six virtue parcels loading on a higher order VIA-Youth strengths construct as this was the best fitting model in the Shogren et al. (2016) analyses. The overall VIA-Youth model with six indicators, one for each virtue, is shown in Figure 2. Although the decision to use parcels was informed by sample size, the use of parcels also enables more reliable estimates of latent means, variances, and covariances at the construct level and is appropriate for the present analysis (Little, 2013). We considered acceptable model fit at each level to be a root mean square error of approximation (RMSEA) of less than .08 and a relative non-normed fit index (NNFI) and comparative fit index (CFI) of .90 or greater (Little, 2013).

Figure 1

Wisdom virtue factor model with five strength indicators. Scale was set with fixed factor as indicated by fixing variance to 1 on the Wisdom factor.

Figure 1

Wisdom virtue factor model with five strength indicators. Scale was set with fixed factor as indicated by fixing variance to 1 on the Wisdom factor.

Figure 2

VIA-Youth factor model with six virtue indicators. Scale was set with fixed factor as indicated by fixing variance to 1 on the VIA factor.

Figure 2

VIA-Youth factor model with six virtue indicators. Scale was set with fixed factor as indicated by fixing variance to 1 on the VIA factor.

The first step was to test for measurement invariance across the six virtues to determine if the same measurement framework could be used across groups. Measurement invariance is tested in three steps consisting of tests of configural, weak, and strong invariance—configural tests for equality of structural form, weak tests for equality of factor loadings, and strong tests for equality of intercepts (item means). If measurement invariance is established because change in comparative fit index (CFI) is < .01 between invariance steps (Cheung & Rensvold, 2002), then latent difference (latent invariance testing) can be conducted for the models across the two groups, after accounting for measurement error. Such comparisons provide meaningful information above and beyond comparing average raw scores. Mplus 7.3 (Muthén & Muthén, 1998–2012) was used for invariance testing, and fixed factor scaling was used to set the scale of the latent variables; fixed factor sets latent variance to 1 and latent mean to 0 for the reference group, in this case, participants without disabilities. As such, estimates for the intellectual disability group reflect differences relative to those without disability.

In addition to the tests for invariance conducted for each of the virtue models, invariance testing was also used to examine the overall VIA-Youth model shown in Figure 2. Following the same steps to evaluate measurement invariance as used for research question 1, the overall VIA-Youth model was evaluated for configural, weak, and strong invariance between adolescents with and without intellectual disability. Based on those model results, the latent variance and/or mean were evaluated for equivalence between groups.

Research question 3: Reliability

Cronbach's coefficient alpha (α) and McDonald's omega (ω) for uncorrelated residuals were used to assess internal consistency separately for participants with and without intellectual disability. The alpha function in the psych package (Revelle, 2015) in R (R Core Team, 2015) was used to compute α and generate a 95% confidence interval with bootstrapped results for both the 24 strengths and six virtues; the number of bootstrap iterations was set to 5000. Because Cronbach's coefficient α contains error variance that cannot be removed, ω was calculated for the virtue models to provide a second measure of internal consistency. The statistic ω is based in the factor analytic framework, enabling error variance to be separated from true variance to get a more accurate measure of internal consistency (McDonald, 2013). Configural model results from research question 1 were used to compute ω.

Results

Research Question 1: Endorsement

Means, standard deviations, and results from the t test with unequal variances for both the 24 strengths and six virtues are presented in Table 3. The means (higher means indicate lower endorsement) on the 24 strengths ranged from 1.9 to 2.9 for the intellectual disability group and from 1.7 to 2.7 for the no disability group, suggesting a general pattern of lower endorsement of strengths in the intellectual disability group for the raw averages scores, although there were limited numbers of statistically significant differences. In terms of statistically significant differences, only two means were significantly different from each other: humility (t[256] = 3.42, p < .001) and teamwork (t[256] = 3.43, p = .001), with youth with intellectual disability endorsing these character strengths at significantly lower levels. At the virtue level, the general pattern of lower endorsement but with limited numbers of significant differences held. Significant differences were only found for the justice virtue (t[256] = 2.81, p = .005).

Table 3

Means, Standard Deviations, and Group Mean Differences of the VIA-Youth Strengths and Virtues

Means, Standard Deviations, and Group Mean Differences of the VIA-Youth Strengths and Virtues
Means, Standard Deviations, and Group Mean Differences of the VIA-Youth Strengths and Virtues

Research Question 2: Measurement and Factorial Validity

Measurement invariance

Next, moving beyond raw scores, we explored measurement invariance and latent differences of the virtues using MG-CFA. The results were mixed for measurement invariance, suggesting potential differences in the measurement of several of the virtues across the two groups. Non-normed fit indices (NNFI) and CFI fit statistics were > .90 for all models, but root mean square error of approximations (RMSEA) varied, sometimes improving with each stage of model testing and other times getting worse. Fit statistics for the final models at each stage of measurement invariance testing can be found in Table 4. Only the courage and justice virtues passed strong invariance testing, suggesting that the same parcels reflecting the associated character strengths could be used equivalently across students with and without disability. Humility passed weak invariance testing. However, wisdom, temperance, and transcendence did not pass invariance testing, suggesting the need to consider the use of the parcels that specified the constructs. The parcels that had to be freed (i.e., the character strengths that differed across groups at the measurement level) are noted in Table 4.

Table 4

Measurement Invariance Testing Results for the Virtue Factors and the VIA Factor

Measurement Invariance Testing Results for the Virtue Factors and the VIA Factor
Measurement Invariance Testing Results for the Virtue Factors and the VIA Factor

If a model failed weak invariance, this indicated that not all factor loadings could be equated across groups. This generally occurred because one or more factor loadings in the intellectual disability group were larger than those found in the no disability group. The one exception was on the character strength of forgiveness in the temperance virtue model where the factor loading was smaller. Failure at strong invariance stage was due to intercepts that could not all be equated, and, in all but one instance, one or more intercepts in the intellectual disability group were found to be smaller than in the no disability group. Only the humility intercept in the temperance model was larger in the intellectual disability group than in the no disability group.

We also explored measurement invariance of the six virtues loading on an overall strengths factor, consistent with findings across disability groups from Shogren et al. (2016). Fit statistics for configural, weak, and strong models indicated good fit based on NNFI but RMSEA was .096 in the configural model, .106 in the weak model, and .104 in the partially strong model. For those same three models, NNFI was 0.969, 0.963, and 0.964; CFI values were 0.981, 0.972, and 0.968. On balance, model fit was considered acceptable because the lower bound of the RMSEA confidence interval was in an acceptable range and RMSEA has been shown to perform poorly with small samples (Kline, 2011). Measurement invariance testing of the VIA-Youth model showed that factor loadings could be equated between groups but intercepts could not. Unstandardized factor loadings from the weak invariance model ranged from 0.359–0.548 (.565–.842 standardized). Temperance had the smallest standardized factor loading at 0.565 (S.E. = .048); the other virtue indicators had estimates that exceeded >.70, meaning that more than half of their variance was explained by the VIA-Youth construct. Moving to the strong invariance model, ΔCFI = .014, intercepts in the configural model were examined and, based on the relatively large difference on the estimated intercept for justice, this parameter was freed. Change in CFI was .04, less than the threshold for change so no further changes to the model were made. Model fit for the partially strong VIA model was χ2 = 64.55, df = 27, p < .001, CFI = .968, Tucker-Lewis Index (TLI) = .964, RMSEA = .104, 90% CI for RMSEA = (.071, .137), on average acceptable. Model fit statistics for each invariance testing step can be found at the bottom of Table 5.

Table 5

Model Fit for Nested Model Testing Results

Model Fit for Nested Model Testing Results
Model Fit for Nested Model Testing Results

Latent mean and variance differences

Latent means were compared in the courage and the justice model, the two models that passed strong measurement invariance (i.e., factor loadings and intercepts could be equated). Similar to the results from the t tests of the six virtues that are listed in Table 3, the latent mean for justice was significantly different between the two groups χ2 (1) = 9.777, p = .002 with Cohen's d = 0.320. Latent means for courage also significantly differed between groups, χ2 (1) = 5.251, p = .022 with Cohen's d = 0.323. Both latent means were higher in the intellectual disability group, indicating lower endorsement of strengths, as compared to the no disability group.

Differences in latent variances were also examined in the constructs that passed weak invariance, courage and humanity. Based on a corrected alpha level of .025 (.05 divided by the number of tests), variances were found to differ between groups. The nested model result comparing the courage model with equated variances to the model with freed variances for courage returned χ2 (1) = 5.929, p = .015. The result for the humanity variance test also showed a comparable result with χ2 (1) = 5.737, p = .017. Generally, the variances were larger in the intellectual disability group when compared to the no disability group where variance was fixed to 1 in the model. The intellectual disability variances were ψ = 1.8 (SE = 0.42) for courage and ψ = 1.8 (SE = 0.44) for humanity, compared to the no disability variances, which were both fixed to 1 when the scale was set with fixed factor scaling. Nested model testing results for both latent means and latent variances are listed in Table 5.

The partially strong measurement model from the overall strength model (see Figure 2) was also used to explore differences in latent variances. Change in model fit was statistically significant based on Δχ2(1) = 11.71, p < .001. The latent variance for the intellectual disability group was wider than the variance in the no disability group (ψ = 1.917 [SE = 0.364] v. ψ = 1.000 [SE = 0.000]). Because the model intercepts could not all be equated in the strong invariance model, latent means could not be compared.

Research Question 3: Reliability

Cronbach α values for the 24 strengths are listed in Table 6. The 95% confidence intervals (CI) for each group overlapped for 50% of the strengths, indicating that the alphas did not differ in those cases. In the cases where the confidence intervals did not overlap, αs were higher in the no disability group, except for judgment where the α = .80, 95% CI[.72, .86] in the intellectual disability group and α = .71, 95% CI[.60–.79] in the no disability group.

Table 6

Character Strength-Level Internal Consistency Grouped by Virtues

Character Strength-Level Internal Consistency Grouped by Virtues
Character Strength-Level Internal Consistency Grouped by Virtues

The 95% confidence intervals for α levels of the virtues overlapped on four of the six virtues, wisdom, courage, humanity, and transcendence. When results for the intellectual disability group are compared to those for the no disability group, α was higher for justice (αj = .86, 95% CI[.82–.89] v. αt = .81, 95% CI[.75–.85]) but lower for temperance (αj = .73, 95% CI[.65–.79] v. αt = .87, 95% CI[.82–.90]). An examination of ω, which is based on the factor models where measurement error is accounted for, showed overall higher internal consistency for virtues in the intellectual disability group on every virtue but temperance. The intellectual disability group ω's ranged from .69–.87 and from .66–.81 in the no disability group. Internal consistency results for the virtues, separated by group, are provided in Table 7.

Table 7

Virtue Internal Consistency Based on Coefficient Alpha (α) and Omega (ω)

Virtue Internal Consistency Based on Coefficient Alpha (α) and Omega (ω)
Virtue Internal Consistency Based on Coefficient Alpha (α) and Omega (ω)

Discussion

The purpose of this study was to explore the endorsement, measurement, and reliability of the VIA-Youth by examining differences across youth with and without intellectual disability. There is a need for tools that assess character strengths to allow for the data from such assessments to be utilized to understand and build on strengths in special education and disability supports and services, consistent with emerging directions in the field and the mandates in the Individuals With Disabilities Education Act. In the following sections, we discuss limitations of this study, followed by implications for future research and practice.

Limitations

The major limitation in this study was the sample size. The sample size limited our ability to explore item-level interactions and to build more complex models to examine the relationships between the character strengths and virtues. As such, these findings must be considered preliminary, and primarily indicate the need for future work. Given the number of constructs assessed on the VIA-Youth, the nature of the scale introduces the need for larger samples. With models run in isolation, we lack the understanding of how the strengths and virtues relate as a whole. Running multiple single factor models also led to increased chance for Type I error and model fit statistics that did not truly reflect model fit, given RMSEA performs poorly with small samples and models with too few degrees of freedom. Given that research investigating strengths among people with intellectual disability is in its infancy and the limitations associated with the study, the results must be interpreted cautiously and future work is needed with a larger sample size to more systematically examine measurement invariance and latent differences. Additionally, the impact of various personal factors, such as gender, race/ethnicity, and socioeconomic status should be examined in future research.

Implications for Research and Practice

Generally, youth with intellectual disability tended to endorse the presence of character strengths and virtues in themselves at lower levels than their peers without disabilities, although there were only a few significant mean-level differences. At the character strengths level, humility and teamwork showed significant differences. Given the role of collaborative and comparative interactions with peers in both of these strengths, it may be that the more restricted social experiences and networks that characterize the lives of adolescents with intellectual disability (Fisher & Shogren, 2016) lead to less experience with these strengths, and therefore significantly lower endorsement. At the virtue level, justice was the only virtue that showed a significant difference. Justice encompasses teamwork, fairness, and leadership character strengths, and the differences in the teamwork character strength may be driving this finding; however, the virtue-level difference suggests again the possible influences of limited access to community and social interactions and leadership experiences, which research repeatedly has shown characterizes the lives of adolescents with intellectual disability (Balcazar et al., 2012; Caldwell, 2010; Powers et al., 2002).

Findings related to measurement invariance provide information about factorial validity and the degree to which the proposed structure of the scale holds across youth with and without intellectual disability. At the level of the virtue models and in the overall model, the findings suggest that issues related to measuring strengths in youth with intellectual disability need to be carefully attended to, and ongoing research is needed. Only the courage and justice virtue models fully passed invariance testing, suggesting that the same items and parcels could be used to measure these constructs across the two groups. The remaining constructs required that some factor loadings or intercepts be freed at the measurement level, generally because of lower loadings or intercepts in the intellectual disability group. Although freeing certain parcels did allow testing to move forward, it is critical that future research more specifically examine, in larger samples, if there are items that function differently across the two groups or items for which further supports are needed for youth with intellectual disability to reliably respond.

Additionally, work is needed to examine the role of experiences in shaping these differences. Several of the parameters that had to be freed in invariance testing (see Table 4) could be influenced by a lack of opportunities to engage in activities that support the development of these character strengths and the ability to identify them in oneself and others. This hypothesis is further supported by the wider variability found across the constructs in the intellectual disability group, suggesting greater variability in endorsement, perhaps shaped by wider variability in experiences. Future work is needed to determine how to best use assessment data from the VIA-Youth to understand experiences and lack of experiences of youth with and without disabilities, and the degree to which this knowledge can be used to build on character strengths and to create these environmental opportunities for success. Additionally, ongoing research is needed to explore the factorial validity of the scale across youth with and without disabilities and the need to reconceptualize the aggregation of items into character strengths and virtues to inform the use of information at the level of character strengths or virtues to derive implications for supports.

Additionally, building on character strengths may involve identifying the highest endorsed strengths and supporting youth in using these character strengths in relationships, work, and community (Niemiec et al., in press), but may also necessitate the use of other interventions to promote meaningful assessment of character strengths, such as strengths-spotting, where youth learn how to identify strengths in others and then in themselves, particularly if they have a difficult time identifying strengths in themselves (Niemiec, 2014). Research on the use and impact of interventions derived from character strengths assessment in youth with intellectual disability is needed.

The variability in endorsement also influenced the reliability of the scale. For example, the forgiveness character strength had a lower mean and factor loading in the intellectual disability group, which lowered the reliability of the virtue forgiveness was associated with (temperance). Given that this virtue and its associated character strengths of forgiveness, humility, prudence, and self-regulation are highly valued constructs but rarely explicitly taught in the disability field, the findings suggest that considering ways to enable youth to identify, use, and experience these strengths may be powerful. They also suggest that, given the low reliabilities of the character strengths level, interpretations at the virtues level may be more impactful.

Conclusions

To enable the use of meaningful information about strengths to guide intervention in the disability field, valid and reliable assessments are needed. The VIA-Youth was developed in the general population to identify and build on signature strengths, and research has suggested the power of these interventions to influence well-being. This study began to explore measurement-related issues in youth with intellectual disability and to highlight important directions for future research on measurement of character strengths in this population and the need to examine ways to raise awareness and experiences with character strengths in youth with intellectual disability. However, further research is needed to determine the role of the VIA-Youth in advancing strengths-based assessment in youth with intellectual disability, as well as to determine effective strategies for integrating strengths-based assessment into systems of support for adolescents with intellectual disability.

References

References
American Psychiatric Association
. (
2013
).
Diagnostic and statistical manual of mental disorders (5th ed.)
.
Washington, DC
:
Author
.
Balcazar,
F. E.,
Taylor-Ritzler,
T.,
Dimpfl,
S.,
Portillo-Peña,
N.,
Guzman,
A.,
Schiff,
R.,
&
Murvay,
M.
(
2012
).
Improving the transition outcomes of low-income minority youth with disabilities
.
Exceptionality
,
20
(
2
),
114
132
.
Caldwell,
J.
(
2010
).
Leadership development of individuals with developmental disabilities in the self-advocacy movement
.
Journal of Intellectual Disability Research
,
54
(
11
),
1004
1014
.
Cheung,
G. W.,
&
Rensvold,
R. B.
(
2002
).
Evaluating goodness-of-fit indexes for testing measurement invariance
.
Structural Equation Modeling
,
9
(
2
),
233
255
.
Diener,
E.
(
2009
).
Positive psychology: Past, present, and future
.
In
S. J.
Lopez
&
C. R.
Synder
(
Eds.
),
The Oxford handbook of positive psychology (2nd ed
.,
pp
.
7
11
).
Oxford, England
:
Oxford University Press
.
Dykens,
E. M.
(
2005
).
Happiness, well-being, and character strengths: Outcomes for families and siblings of persons with mental retardation
.
Mental Retardation
,
43
,
360
364
.
Dykens,
E. M.
(
2006
).
Toward a positive psychology of mental retardation
.
American Journal of Orthopsychiatry
,
76
(
2
),
185
193
.
Epstein,
M. H.,
Synhorst,
L. L.,
Cress,
C. J.,
&
Allen,
E. A.
(
2009
).
Development and standardization of a test to measure the emotional and behavioral strengths of preschool children
.
Journal of Emotional and Behavioral Disorders
,
17
(
1
),
29
37
.
Fisher,
K. W.,
&
Shogren,
K. A.
(
2016
).
Does academic tracking impact adolescents' access to social capital?
Remedial and Special Education
,
37
,
89
100
.
Gander,
F.,
Proyer,
R. T.,
Ruch,
W.,
&
Wyss,
T.
(
2012
).
Strength-based positive interventions: Further evidence for their potential in enhancing well-being
.
Journal of Happiness Studies
,
14
(
4
),
1241
1259
.
Individuals With Disabilities Education Act
,
20 U.S.C. §§ 1400 et seq
. (
2006 & Supp. V. 2011
)
Kline,
R. B.
(
2011
).
Principles and practice of structural equation modeling (3rd ed.)
.
New York, NY
:
Guilford
.
Little,
T. D.
(
2013
).
Longitudinal structural equation modeling
.
New York, NY
:
Guilford Press
.
Little,
T. D.,
Jorgensen,
T. D.,
Lang,
K. M.,
&
Moore,
E. W. G.
(
2013
).
On the joys of missing data
.
Journal of Pediatric Psychology
,
39
(
2
),
1
12
.
Madden,
W.,
Green,
S.,
&
Grant,
A. M.
(
2011
).
A pilot study evaluating strengths-based coaching for primary school students: Enhancing engagement and hope
.
International Coaching Psychology Review
,
6
,
71
83
.
McDonald,
R. P.
(
2013
).
Test theory: A unified treatment
.
New York, NY
:
Psychology Press
.
Muthén,
L. K.,
&
Muthén,
B. O.
(
1998-2012
).
Mplus user's guide (6th ed.)
.
Los Angeles, CA
:
Muthén & Muthén
.
Niemiec,
R. M.
(
2014
).
Mindfulness and character strengths: A practical guide to flourishing
.
Cambridge, MA
:
Hogrefe
.
Niemiec,
R. M.,
Shogren,
K. A.,
&
Wehmeyer,
M. L.
(
in press
).
Character strengths and intellectual and developmental disability: A strengths-based approach from positive psychology
.
Education and Training in Autism and Developmental Disabilities
.
Park,
N.,
&
Peterson,
C.
(
2006a
).
Moral competence and character strengths among adolescents: The development and validation of the Values in Action Inventory of Strengths for Youth
.
Journal of Adolescence
,
29
(
6
),
891
905
.
Park,
N.,
&
Peterson,
C.
(
2006b
).
Values in Action (VIA) Inventory of Character Strengths for Youth
.
Adolescent & Family Health
,
4
,
35
40
.
Park,
N.,
&
Peterson,
C.
(
2009
).
Character strengths: Research and practice
.
Journal of College and Character
,
10
(
4
),
1
10
.
Peterson,
C.,
&
Seligman,
M. E. P.
(
2004
).
Character strengths and virtues: A classification and handbook
.
New York, NY, and Washington, DC
:
Oxford University Press and American Psychological Association
.
Powers,
L. E.,
Ward,
N.,
Ferris,
L.,
Nelis,
T.,
Ward,
M.,
Wieck,
C.,
&
Heller,
T.
(
2002
).
Leadership by people with disabilities in self-determination systems change
.
Journal of Disability Policy Studies
,
13
(
2
),
126
134
.
R Core Team
. (
2015
).
R: A language and environment for statistical computing
.
Vienna, Austria
:
R Foundation for Statistical Computing
.
Revelle,
W.
(
2015
).
psych: Procedures for personality and psychological research (version 1.5.8)
.
Evanston, IL
:
Northwestern University
.
Schalock,
R. L.,
Borthwick-Duffy,
S.,
Bradley,
V.,
Buntix,
W. H. E.,
Coulter,
D. L.,
Craig,
E. P. M.,
Yeager,
M. H.
(
2010
).
Intellectual disability: Definition, classification, and systems of support (11th ed.)
.
Washington, DC
:
American Association on Intellectual and Developmental Disabilities
.
Schalock,
R. L.,
Luckasson,
R. A.,
Shogren,
K. A.,
Borthwick-Duffy,
S.,
Bradley,
V.,
Buntix,
W. H.,
Yeager,
M. H.
(
2007
).
The renaming of mental retardation: Understanding the change to the term intellectual disability
.
Intellectual and Developmental Disabilities
,
45
(
2
),
116
124
.
Seligman,
M. E. P.,
&
Csikszentmihalyi,
M.
(
2000
).
Positive psychology: An introduction
.
American Psychologist
,
55
(
1
),
5
14
.
Seligman,
M. E. P.,
Steen,
T. A.,
Park,
N.,
&
Peterson,
C.
(
2005
).
Positive psychology progress: Empirical validation of interventions
.
American Psychologist
,
60
(
5
),
410
421
.
Shogren,
K. A.,
Wehmeyer,
M. L.,
Lang,
K.,
&
Niemiec,
R. M.
(
2016
).
The application of the VIA Classification of Strengths to youth with and without disabilities
.
Manuscript submitted for publication
.
Stancliffe,
R. J.,
Tichá,
R.,
Larson,
S. A.,
Hewitt,
A. S.,
&
Nord,
D.
(
2015
).
Responsiveness to self-report interview questions by adults with intellectual and developmental disability
.
Intellectual and Developmental Disabilities
,
53
(
3
),
163
181
.
van Buuren,
S.,
&
Groothuis-Oudshoorn,
K.
(
2011
).
Mice: Multivariate imputation by chained equations in R
.
Journal of Statistical Software
,
45
,
1
67
.
VIA Institute on Character
. (
n.d.
).
Psychometric data—Youth survey
.
Woodard,
C. R.
(
2009
).
Psychometric properties of the ASPeCT-DD: Measuring positive traits in persons with developmental disabilities
.
Journal of Applied Research in Intellectual Disabilities
,
22
(
5
),
433
444
.

Author notes

The research reported here was supported by the VIA Institute on Character through a grant awarded to the University of Kansas. The opinions expressed are those of the authors and do not represent views of the institute.