Machine learning-based ability to classify psychosis and early stages of disease through parenting and attachment-related variables is associated with social cognition.

ABSTRACT:

Background

Recent views posited that negative parenting and attachment insecurity can be considered as general environmental factors of vulnerability for psychosis, specifically for individuals diagnosed with psychosis (PSY). Furthermore, evidence highlighted a tight relationship between attachment style and social cognition abilities, a key PSY behavioral phenotype. The aim of this study is to generate a machine learning algorithm based on the perceived quality of parenting and attachment style-related features to discriminate between PSY and healthy controls (HC) and to investigate its ability to track PSY early stages and risk conditions, as well as its association with social cognition performance.

Methods

Perceived maternal and paternal parenting, as well as attachment

SUBMITTER: Antonucci LA 

PROVIDER: S-EPMC7989088 | biostudies-literature | 2021 Mar

REPOSITORIES: biostudies-literature