Citation

Ciarlo JA, Tweed DL. Eval. Program Plann. 1992; 15(2): 195-210.

Copyright

(Copyright © 1992, Elsevier Publishing)

DOI

10.1016/0149-7189(92)90008-I

PMID

unavailable

Abstract

This article addresses several services-planning issues necessary for successful implementation of an indirect needs-assessment model to estimate geographic differences in the prevalence of needs for alcohol, drug abuse, and mental health (ADM) services. These include: (1) definition and selection of appropriate ADM services need categories as "target groups", (2) selection of a model that can validly estimate the prevalence of those need categories, and (3) understanding the data requirements, calculation procedures, and limitations on the generalizability of selected models. A strategy for making the best possible use of indirect needs-assessment models, additional research findings to buttress the validity of selected models, and procedures for model implementation in a state are also presented. A key to effective use of such procedures is clear identification of the target groups to be estimated, ranging from the broadest and most prevalent to highly specialized, low-prevalence need groups. Because predictive models are weaker with narrowly defined, low-prevalence need categories than with larger ones, and because of the importance of presenting a full picture of the ADM needs of a state, it is recommended that states employ a series of "nested" target groups that represent the full range of population needs. While the originally proposed models studied here would be useful with higher-prevalence need categories, only two newly developed models that involve the poverty social indicator could successfully predict to low-prevalence surveyed "chronic mental illness" in this study. Enough is now known about indirect needs-assessment models to warrant implementation by states of one of the better-performing models. The results presented strongly support the validity and potential utility of specific models for estimating varieties of need for ADM services at both state and subarea levels.