Uncovering heterogeneous associations of disaster-related traumatic experiences with subsequent mental health problems: A machine learning approach.

ABSTRACT:

Aim

Understanding the differential mental health effects of traumatic experiences is important to identify particularly vulnerable subpopulations. We examined the heterogeneous associations between disaster-related traumatic experiences and postdisaster mental health, using a novel machine learning-based causal inference approach.

Methods

Data were from a prospective cohort study of Japanese older adults in an area severely affected by the 2011 Great East Japan Earthquake. The baseline survey was conducted 7 months before the disaster and the 2 follow-up surveys were conducted 2.5 and 5.5 years after (n = 1150 to n = 1644 depending on the exposure-outcome combinations). As disaster-related traumatic experiences, we assessed complete home loss and loss of loved ones. Using th

SUBMITTER: Shiba K 

PROVIDER: S-EPMC9102396 | biostudies-literature | 2022 Apr

REPOSITORIES: biostudies-literature