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Statistical Models to Predict Mental Illness Among State and Federal Prisoners

NCJ Number
252633
Author(s)
Jeremy Aldworth; Phillip Kott; Sarra Hedden; Joseph Gfroerer; Lauren Glaze
Date Published
June 2021
Length
120 pages
Annotation

This paper examines the feasibility of adapting and applying a proposed model-based methodology to the data of the 2016 Survey of Prison Inmates (SPI) to obtain nationally representative estimates of serious mental illness (SMI) and any mental illness (AMI) among state and federal prisoners.

Abstract

The model-based methodology used in this study was developed by the federal Substance Abuse and Mental Health Services Administration (SAMHSA) to obtain nationally representative estimates of SMI and AMI among the adult U.S. civilian, non-institutionalized population in the 2008-12 Mental Health Surveillance Study (MHSS) as part of the National Survey on Drug Use and Health (NSDUH); however, caution is advised in the current study’s use of this model with the 2016 SPI, particularly at the domain level (for example, sex or age group). Also, the methodology has potential limitations when applied to the SPI, due to the small sample size of the MHSS subsample used to develop the SPI prediction model. There is limited information in the 2016 SPI available for inclusion in prediction models; and different populations represented in the model development process (parolees, probationers, and arrestees surveyed in NSDUH) and estimation phase (federal and state prisoners surveyed in the SPI). Despite the noted limitations, however, this approach for estimating mental illness among prisoners may provide useful indicators that are consistent with estimates produced by other federal agencies and researchers. Estimates of SMI and AMI are higher among the prisoner population than among the general adult population, and there are large differences between federal and state prisoners, as well as between male and female prisoners. There are minimal differences by age group. 25 tables and 4 figures