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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

Development and Initial Psychometrics of a Generic Treatment Integrity Measure Designed to Assess Practice Elements Targeting Social, Emotional, and Behavioral Outcomes in Early Childhood Settings.

Though treatment integrity measurement is important for research intended to promote social and behavioral outcomes of children at risk for emotional and behavioral disorders (EBDs) in early childhood settings, measurement gaps exist in the field. This paper reports on the development and preliminary psychometric assessment of the treatment integrity measure for early childhood settings (TIMECS), an observational measure designed to address existing measurement gaps related to treatment integrity with tier 2 interventions in the early childhood field. To assess the preliminary score reliability (interrater) and validity (construct, discriminant) of the TIMECS, live observations (N = 650) in early childhood classrooms from 54 teachers (92.

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.

Using Machine Learning to Predict Patterns of Employment and Day Program Participation.

In this article, we demonstrate the potential of machine learning approaches as inductive analytic tools for expanding our current evidence base for policy making and practice that affects people with intellectual and developmental disabilities (IDD). Using data from the National Core Indicators In-Person Survey (NCI-IPS), a nationally validated annual survey of more than 20,000 nationally representative people with IDD, we fit a series of classification tree and random forest models to predict individuals' employment status and day activity participation as a function of their responses to all other items on the 2017-2018 NCI-IPS. The most accurate model, a random forest classifier, predicted employment outcomes of adults with IDD with an accuracy of 89 percent on the testing sample, and 80 percent on the holdout sample.

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 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.

Testing a Wellness Indicators Measure for People with Intellectual and Developmental Disabilities.

Background And Purpose: People with intellectual and developmental disabilities (IDD) often have health and wellness issues that are not as good as people without disabilities. States are required to monitor health and wellness for people with IDD who use many disability services. However, there are few ways to monitor wellness between states or at different points in time.

Identifying Predictors for Enhanced Outcomes for People With Intellectual and Developmental Disabilities.

People with intellectual and developmental disabilities (IDD) often rely on Medicaid-funded services and supports to facilitate their daily living. The financial investment for these services is significant, yet little work has been conducted to understand how these investments affect life outcomes. This pilot study used a novel data integration approach to offer initial insights about how Medicaid expenditures relate to outcomes using Medicaid claims data, results of the National Core Indicators consumer survey, and data from the Supports Intensity Scale (SIS).