ERIC Number: EJ1322256
Record Type: Journal
Publication Date: 2021-Nov
Pages: 15
Abstractor: As Provided
ISBN: N/A
ISSN: ISSN-1944-7515
EISSN: N/A
Using Machine Learning to Predict Patterns of Employment and Day Program Participation
Broda, Michael D.; Bogenschutz, Matthew; Dinora, Parthenia; Prohn, Seb M.; Lineberry, Sarah; Ross, Erica
American Journal on Intellectual and Developmental Disabilities, v126 n6 p477-491 Nov 2021
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. The most important variable in this prediction was whether or not community employment was a goal in this person's service plan. These results suggest the potential machine learning tools to examine other valued outcomes used in evidence-based policy making to support people with IDD.
Descriptors: Artificial Intelligence, Prediction, Employment Patterns, Day Programs, Intellectual Disability, Developmental Disabilities, Participation, Adults, Classification
American Association on Intellectual and Developmental Disabilities. P.O. Box 1897, Lawrence, KS 66044-1897. Tel: 785-843-1235; Fax: 785-843-1274; e-mail: AJMR@allenpress.com; Web site: https://meridian.allenpress.com/aaidd
Publication Type: Journal Articles; Reports - Research
Education Level: N/A
Audience: N/A
Language: English
Sponsor: N/A
Authoring Institution: N/A
Grant or Contract Numbers: N/A