Predicting four types of service needs in older adults

Logistic regression analysis was used to predict four service need variable s. A sample of nearly 5000 older Missourians were assessed on a comprehensi ve set of variables, representing all of the categories of the behavioral m odel. Variables in the behavioral model predicted perceived need for frail elderly services better than they predicted unmet need for frail elderly se rvices, perceived need for community services, and unmet need for community services. Health need variables were better predictors of all of the servi ce need variables than predisposing or enabling variables. Although the inc lusion of interaction terms in the prediction models did nor increase model fit, some of the interaction terms were significant and helped to clarify the relationship between certain predictor variables and the four service n eed variables. (C) 2001 Elsevier Science Ltd. All rights reserved.