Predicting anxiety treatment outcome in community mental health services using linked health administrative data.

ABSTRACT: Anxiety disorders is ranked as the most common class of mental illness disorders globally, affecting hundreds of millions of people and significantly impacting daily life. Developing reliable predictive models for anxiety treatment outcomes holds immense potential to help guide the development of personalised care, optimise resource allocation and improve patient outcomes. This research investigates whether community mental health treatment for anxiety disorder is associated with reliable changes in Kessler psychological distress scale (K10) scores and whether pre-treatment K10 scores and past health service interactions can accurately predict reliable change (improvement). The K10 assessment was administered to 46,938 public patients in a community setting within the Western Australia dat

SUBMITTER: Chai KEK 

PROVIDER: S-EPMC11375212 | biostudies-literature | 2024 Sep

REPOSITORIES: biostudies-literature