An Active Inference Approach to Dissecting Reasons for Nonadherence to Antidepressants.

ABSTRACT:

Background

Antidepressant medication adherence is among the most important problems in health care worldwide. Interventions designed to increase adherence have largely failed, pointing toward a critical need to better understand the underlying decision-making processes that contribute to adherence. A computational decision-making model that integrates empirical data with a fundamental action selection principle could be pragmatically useful in 1) making individual-level predictions about adherence and 2) providing an explanatory framework that improves our understanding of nonadherence.

Methods

Here we formulated a partially observable Markov decision process model based on the active inference framework that can simulate several processes that plausibly influence adherence

SUBMITTER: Smith R 

PROVIDER: S-EPMC7272309 | biostudies-literature | 2021 Sep

REPOSITORIES: biostudies-literature