Evaluating Measurement Invariance Over Time for a Personal Opportunities Scale for People With IDD: Implications for Policy and Practice.

Personal opportunities refer to chances for people with intellectual and developmental disabilities (IDD) to take self-directed action based on their interests, strengths, and preferences. This study tested for measurement invariance across five years of cross-sectional data, including data collected during the COVID-19 pandemic, to determine whether the scale performed consistently over time. Analysis revealed significant differences in both the National Core Indicators In-Person Survey (NCI-IPS) outcomes and in the Personal Opportunities scale.

Examining the Dimensionality, Internal Consistency, and Invariance of the Depression, Anxiety, and Stress Scale-21 (DASS-21) Across Age, Race, Ethnicity, and Caretaking Status.

This study investigates the performance of the Depression, Anxiety, and Stress Scale-21 (DASS-21) across diverse demographic groups during the COVID-19 pandemic. Utilizing a large, generalizable U.S.

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.

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.

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.

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.

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.

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.

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.

Measuring and Tracking Personal Opportunity Outcome Measures Over 3 Years to Guide Policy and Services That Promote Inclusive Community Living.

National policy and litigation have been a catalyst in many states for expanding personal outcomes for people with intellectual and developmental disabilities (IDD) and have served as an impetus for change in state IDD systems. Although several metrics are used to examine personal outcomes, the National Core Indicators (NCI) In-Person Survey (IPS) is one tool that provides an annual depiction of the lives of people who receive Medicaid Home and Community Based IDD waiver services (HCBS). This article examines whether a validated, three-factor (Privacy Rights, Everyday Choice, and Community Participation) measure of Personal Opportunity, derived from NCI items, functions as predicted across non-equivalent, NCI cohorts (=2400) from Virginia in 2017, 2018, and 2019.