Predicting prognosis for adults with depression using individual symptom data: a comparison of modelling approaches.

ABSTRACT:

Background

This study aimed to develop, validate and compare the performance of models predicting post-treatment outcomes for depressed adults based on pre-treatment data.

Methods

Individual patient data from all six eligible randomised controlled trials were used to develop (k = 3, n = 1722) and test (k = 3, n = 918) nine models. Predictors included depressive and anxiety symptoms, social support, life events and alcohol use. Weighted sum scores were developed using coefficient weights derived from network centrality statistics (models 1-3) and factor loadings from a confirmatory factor analysis (model 4). Unweighted sum score models were tested using elastic net regularised (ENR) and ordinary least squares (OLS) regression (models 5 and 6). Indi

SUBMITTER: Buckman JEJ 

PROVIDER: S-EPMC9899563 | biostudies-literature | 2023 Jan

REPOSITORIES: biostudies-literature