Using decision tree analysis to identify population groups at risk of subjective unmet need for assistance with activities of daily living.

ABSTRACT:

Background

Identifying predictors of subjective unmet need for assistance with activities of daily living (ADL) is necessary to allocate resources in social care effectively to the most vulnerable populations. In this study, we aimed at identifying population groups at risk of subjective unmet need for assistance with ADL and instrumental ADL (IADL) taking complex interaction patterns between multiple predictors into account.

Methods

We included participants aged 55 or older from the cross-sectional German Health Update Study (GEDA 2019/2020-EHIS). Subjective unmet need for assistance was defined as needing any help or more help with ADL (analysis 1) and IADL (analysis 2). Analysis 1 was restricted to participants indicating at least one limitation in ADL (N = 1,957). Simila

SUBMITTER: Jaehn P 

PROVIDER: S-EPMC10483760 | biostudies-literature | 2023 Sep

REPOSITORIES: biostudies-literature