The impact of customized employment on the competitive integrated employment outcomes of transition age youth with intellectual and developmental disabilities: A randomized controlled trial study.

BACKGROUND: Customized employment (CE) is recognized in the Workforce Innovation and Opportunity Act (2014) as a strategy for promoting competitive integrated employment. However, the existing body of evidence supporting CE is mainly descriptive rather than experimental research. OBJECTIVE: This study examined the impact of CE on the employment outcomes, hours worked per week, and wages of transition-age youth with intellectual and developmental disabilities. METHOD: The outcomes of transition-age youth participating in a CE intervention were compared to those receiving treatment-as-usual using a randomized controlled trial design. RESULTS: Participants receiving CE were significantly more likely to secure competitive integrated employment than controls who received treatment-as-usual. Participants in the intervention and control conditions earned similar wages. Participants in the control condition worked more hours per week than those in CE. CONCLUSION: The findings from this study demonstrate the effectiveness of CE to assist transition-age youth with intellectual and developmental disabilities in obtaining competitive integrated employment, but future research is needed to examine factors impacting weekly hours and wages of participants in CE.

Understanding COVID-19 infection among people with intellectual and developmental disabilities using machine learning.

BACKGROUND: People with intellectual and developmental disabilities (IDD) were disproportionately affected by the COVID-19 pandemic. Predicting COVID-19 infection has been difficult. OBJECTIVE: We sought to address two research questions in this study: 1) to assess the overall utility of a machine learning model to predict COVID-19 diagnosis for people with IDD, and 2) to determine the primary predictors of COVID-19 diagnosis in a random sample of Home and Community Based Services users in one state. METHODS: We merged three major IDD-specific datasets (National Core Indicators, Supports Intensity Scale, Medicaid HCBS expenditures) from one state to create one combined dataset for analyses that included more than 700 variables. We then built a random forest machine learning algorithm to predict COVID-19 diagnosis and to explore the top predictors of such a diagnosis, when present. RESULTS: Our algorithm predicted COVID-19 diagnosis in a random sample of HCBS users with IDD with 62.5% accuracy. The top predictors of having a documented case of COVID-19 among our sample were higher age, having high overall, medical, or behavioral support needs, living in a lower-income neighborhood, total Medicaid expenditure, and higher body mass index. CONCLUSIONS: Results largely followed trends in the general population, and were largely suggestive that increased contact with other people may have exposed a person with IDD to greater COVID-19 risk.

A case study of pragmatic measure development of the Treatment Integrity for Elementary Settings self-report measure for teachers.

Introduction: Due to usability, feasibility, and acceptability concerns, observational treatment fidelity measures are often challenging to deploy in schools. Teacher self-report fidelity measures with specific design features might address some of these barriers. This case study outlines a community-engaged, iterative process to adapt the observational Treatment Integrity for Elementary Settings (TIES-O) to a teacher self-report version designed to assess the use of practices to support children's social-emotional competencies in elementary classrooms. Method: Cognitive walkthrough interviews were conducted with teachers to improve the usability of the teacher self-report measure, called the Treatment Integrity for Elementary Schools-Teacher Report (TIES-T). Qualitative content analysis was used to extract themes from the interviews and inform changes to the measure. Results: Increasing clarity and interactive elements in the measure training were the dominant themes, but suggestions for the measure format and jargon were also suggested. Conclusion: The suggested changes resulted in a brief measure, training, and feedback system designed to support the teacher's use of practices to support children's social-emotional competencies in elementary classrooms. Future research with the TIES-T will examine the score reliability and validity of the measure.

Collecting observational data in schools is challenging, so developing teacher self-report measures and involving teachers in the design process is important to help make them easier to use. This paper reports on the development of a teacher self-report measure designed to collect information about the instructional practices teachers deliver to promote positive student behavior.

Effects of Customized Employment on the Independence of Youth With Intellectual and Developmental Disabilities.

Participation in work during school is a known predictor of postsecondary employment for transition-age youth with intellectual and developmental disabilities (IDD). Recent research has demonstrated the benefits of work on skill development in major life domains. The purpose of this study was to examine the impact of customized employment on the support needs of youth with IDD with a significant disability compared to those receiving treatment as usual. Findings indicated significant increases in independence in three specific domains for the treatment group versus control on the Supports Intensity Scale-Adult Version, including Home Living, Employment, and Protection and Advocacy. Findings suggest a therapeutic effect of work activities on growth and development in important life domains. Implications for future research, policy, and practice are discussed.

Examining the Role of Student Responsiveness in Treatment Effects of a Tier 2 Program Targeting Reductions in Problem Behavior.

Student responsiveness's role in promoting intervention outcomes for students who exhibit problem behavior is understudied. Due to the relational nature of many interventions delivered by teachers that target social, emotional, or behavioral outcomes of students in classrooms, it is essential to assess how responsive students are to teachers' attempts to engage them in the intervention, particularly for students with problem behaviors that may impede teachers' attempts to engage these students in intervention effectively. In the current study, we combine samples from four randomized controlled trials to examine the relationship between student outcomes and teacher attempts to deliver BEST in CLASS, a Tier 2 intervention, via student responsiveness. Delivery of BEST in CLASS and student responsiveness were assessed through direct observations and teachers' reported measures. Results suggest that teacher adherence and competence in delivering BEST in CLASS practices was associated with reductions in problem behavior from pretest to post-test via student responsiveness. Limitations of the current study and implications for future research are discussed.

Exploring control-value motivational profiles of mathematics anxiety, self-concept, and interest in adolescents.

In this study, we identified multidimensional profiles in students' math anxiety, math self-concept, and math interest using data from a large generalizable sample of 16,547 9th grade students in the United States who participated in the National Study of Learning Mindsets. We also analyzed the extent that students' profile memberships are associated with related measures such as prior mathematics achievement, academic stress, and challenge-seeking behavior. Five multidimensional profiles were identified: two profiles which demonstrated relatively high levels of interest and self-concept, along with low math anxiety, in line with the tenets of the control-value theory of academic emotions (C-VTAE); two profiles which demonstrated relatively low levels of interest and self-concept, and high levels of math anxiety (again in accordance with C-VTAE); and one profile, comprising more than 37% of the total sample, which demonstrated medium levels of interest, high levels of self-concept, and medium levels of anxiety. All five profiles varied significantly from one another in their association with the distal variables of challenge seeking behavior, prior mathematics achievement, and academic stress. This study contributes to the literature on math anxiety, self-concept, and interest by identifying and validating student profiles that mainly align with the control-value theory of academic emotions in a large, generalizable sample.

Variable- and person-centered approaches to examining construct-relevant multidimensionality in writing self-efficacy.

Self-efficacy is an essential component of students' motivation and success in writing. There have been great advancements in our theoretical understanding of writing self-efficacy over the past 40 years; however, there is a gap in how we empirically model the multidimensionality of writing self-efficacy. The purpose of the present study was to examine the multidimensionality of writing self-efficacy, and present validity evidence for the adapted Self-Efficacy for Writing Scale (SEWS) through a series of measurement model comparisons and person-centered approaches. Using a sample of 1,466 8th-10th graders, results showed that a bifactor exploratory structural equation model best represented the data, demonstrating that the SEWS exhibits both construct-relevant multidimensionality and the presence of a global theme. Using factor scores derived from this model, we conducted latent profile analysis to further establish validity of the measurement model and examine how students disaggregate into groups based on their response trends of the SEWS. Three profiles emerged, differentiated by global writing self-efficacy, with substantively varying factor differences among the profiles. Concurrent, divergent, and discriminant validity evidence was established through a series of analyses that assessed predictors and outcomes of the profiles (e.g., demographics, standardized writing assessments, and grades). Theoretical and practical implications and avenues for future research are discussed.

Co-Occurring Mental Illness and Behavioral Support Needs in Adults with Intellectual and Developmental Disabilities.

People with intellectual and developmental disabilities (IDD) have higher incidences of mental health conditions and behavioral support needs than people without IDD but may not receive needed care from community providers. We examined rates of co-occurring conditions in a representative sample of adults with IDD who use state funded services in Virginia. Using data from two datasets, we identified four categories of mental health and behavioral conditions. We used these categories to examine differences in individual- and system-level factors in people with and without co-occurring conditions. We found high rates of co-occurring conditions in our sample. We found important disability factors and system-level characteristics that were associated with having a diagnosed mental health condition or behavioral support needs. Differing patterns of diagnosis and treatment for co-occurring conditions suggests more work needs to be done to support people with IDD and co-occurring mental health conditions living in the community.

An Examination of Support Needs, Supports, and Outcomes for People With Intellectual and Developmental Disabilities.

Researchers used a merged dataset to examine if more resources were expended on those with greater support needs and if support needs impacted personal outcomes when controlling for relevant personal and contextual factors. Results indicated that the amount of support a person receives had a direct relationship to their needs. However, we also found that people with the greatest needs had weaker personal outcomes suggesting that distribution of resources based on need may not result in equivalent outcomes. The authors suggest strategies at an individual and systems level to address the outcomes gap for people with the greatest support needs.

Using social network analysis in applied psychological research: A tutorial.

Social network analysis (SNA) is a highly flexible research method that allows for novel exploration of a wide variety of research phenomena. Evidence from fields as disparate as public health, education, informatics, sociology, and medicine has demonstrated the importance of recognizing the complexity inherent in individuals' connections with others. In this article, we provide a brief conceptual overview of social network theory and methodology, and then demonstrate how to apply SNA to an applied psychological research context studying students embedded in classrooms. We also provide numerous supporting materials on our OSF page, including R code for all analyses, a dataset containing social network data, and a glossary of key terms in social network analysis. We conclude with a set of recommendations for researchers interested in applying SNA to their own contexts and content areas. (PsycInfo Database Record (c) 2023 APA, all rights reserved).

Effects of a 9-Month Military-Base Internship on the Competitive Integrated Employment of Military Dependent and Connected Youth with ASD.

This waitlist-controlled cluster randomized clinical trial presents the results of PS + ASD for military dependent and connected youth with ASD. Following earlier findings regarding PS + ASD, this study expands upon that previous work by including a new population, military dependent and connected transition aged youth with ASD. Findings indicate that military dependent and connected youth who participated in PS + ASD gained competitive integrated employment at 60% despite the impact of the COVID-19 pandemic and economic downturn. In addition, these youth worked a mean of 24.42 h weekly and earned an average hourly wage of $9.38 at one year post baseline while the waitlist control group participants did not gain CIE. In addition, by 18 months, 58.3% of participants gained positions in federal employment. Implications of the study are discussed.

Comparing employment, employment services, and employment goals in propensity-matched samples of people with intellectual and developmental disabilities with and without autism.

Background: People with intellectual and developmental disabilities (IDD) tend to have poor employment outcomes relative to the general population, as do people with autism. Research is unclear, however, about how people with IDD with and without autism compare on a variety of employment-related indicators, including desire to work, having work as a goal in their service plans, and being employed. Objectives: To understand how people with IDD with and without autism compare on important employment related outcomes, based on a matched random sample. Methods: Using merged administrative datasets, we used propensity score matching to construct statistically proximate samples of Medicaid waiver users in a single state with IDD both with and without autism, and then tested differences between the two groups on important employment-related indicators. Results: People with IDD and autism were less likely than people with IDD alone to have a goal for employment in their individualized service plans and to hold employment in group community settings. There was no statistical difference between the two groups in terms of desire to have a job or employment in individual community settings. Conclusions: Results reinforce the importance of planning for employment if holding employment is a person's aim, regardless of the presence of autism.

The Effects of Prime Supporters within a College Student's Support Network.

College students face academic and emotional challenges within and outside of the classroom. There is not a unique way to deal with all of these challenges, however obtaining support from other individuals in their network can be an important factor in their success in dealing with these challenges. Exploratory social support network data from 38 undergraduate students were collected and analyzed to find common network structures and examine the relationship between these structures and student characteristics, GPA, perceived social support, and use of other help resources. We found half of the students had what we defined to be a novel network characteristic, prime supporters, which are individuals who provided academic and emotional support to students for both routine and intense academic and emotional problems. We found students with a prime supporter in their social network tended to have higher GPAs and perceived social support than those without a prime supporter. Students with prime supporters also had differences in academic help-seeking behavior. These findings suggest the need for further research on the social networks of college students, particularly the presence of individuals who are providers of multiple sources of support.

Measuring Four Personal Opportunities for Adults With Intellectual and Developmental Disabilities.

This study tests an empirically derived model for measuring personal opportunities for people with intellectual and developmental disabilities (IDD) using National Core Indicators In-Person Survey (NCI-IPS) state and national datasets. The four personal opportunities measured, (a) privacy rights, (b) everyday choice, (c) community participation, and (d) expanded friendships, were informed by existing conceptualizations of service as well as NCI-IPS measures. Analyses confirmed the fit of a four-factor model and demonstrated that factors were significantly and positively correlated. To demonstrate the relationships between personal opportunities and personal and environmental characteristics, we estimated a structural equation model that regressed personal opportunities on age, gender, place of residence, and level of intellectual disability. Implications for using personal opportunities for evaluating service quality of IDD systems are discussed.

Promising Practices in the Frontiers of Quality Outcome Measurement for Intellectual and Developmental Disability Services.

Medicaid Home and Community-Based Services (HCBS) for people with intellectual and developmental disabilities (IDD) are vital for supporting people with IDD to live well in their communities, but there are not set standards for monitoring quality outcomes related to HCBS. In this paper, we propose promising practices for improving the quality of HCBS outcome measurement, based both in the literature and our own experience conducting an extensive U.S. state-level study. Specifically, we discuss: (1) using merged administrative datasets, (2) developing high-quality psychometrics that attend to ecological issues in measurement, (3) using advanced statistical analyses, and (4) creating immersive, user-friendly translational dissemination products. We conclude by suggesting what we see as important new frontiers for researchers to consider in order to enhance the quality of HCBS outcome measurement for people with IDD in the future.

Children With Intellectual Disability and Victimization: A Logistic Regression Analysis.

It is a common assumption that children with disabilities are more likely to experience victimization than their peers without disabilities. However, there is a paucity of robust research supporting this assumption in the current literature. In response to this need, we conducted a logistic regression analysis using a national dataset of responses from 26,572 parents/caregivers to children with and without disabilities across all 50 states, plus the District of Columbia. The purpose of our study was to acquire a greater understanding of the odds of victimization among children with and without intellectual disability (ID), while controlling for several child and parent/adult demographic correlates. Most notably, our study revealed that children with ID have 2.84 times greater odds of experiencing victimization than children without disabilities, after adjusting for the other predictors in the model. Implications for future research and practice are discussed.

Language skills and friendships in kindergarten classrooms: A social network analysis.

The purpose of this study was to determine the extent that language skills contribute to kindergarten children's classroom-based friendship networks. We assessed language skills and collected friendship data via individual interviews of 419 children from 21 kindergarten classrooms. Using social network analysis, we found that language skills were significantly associated with friendship centrality and reciprocity after controlling for classroom and child-level factors. Children classified as at risk for specific language impairment (SLI) were significantly less central to friendship networks, and the odds of a reciprocal friendship tie were more than 50% lower compared to children who were not classified as at risk. Of children at risk, girls were significantly more central than boys. We couch our results within limitations of our study and provide recommendations for future research. (PsycInfo Database Record (c) 2023 APA, all rights reserved).

Understanding afterschool engagement: Investigating developmental outcomes for adolescents.

Though student engagement is hypothesized to be a factor in explaining student level differences in afterschool programs, the measurement of student engagement in this context is inconsistent, and findings from the small number of studies about how engagement impacts developmental and academic outcomes are mixed. In this study, we tested the factor structure of Wang and colleagues' school engagement scale with a sample of middle school students (N = 197) who attended an afterschool program in an urban setting. Results suggest that a bifactor model of engagement best fits the data, meaning that engagement consists of four specific factors (affective, behavioral, cognitive, social) and a global factor. We then used structural equation modeling to examine the relationship between engagement, academic outcomes, and positive youth development (PYD). Results also showed positive associations with student mathematics achievement and PYD, but no significant associations were found between engagement and English achievement. This study provides a theoretically aligned way to measure engagement and evidence to support engagement as a key factor in predicting youth outcomes in an out-of-school context.