Shaping Tomorrow's Support: Baseline Clinical Characteristics Predict Later Social Functioning and Quality of Life in Schizophrenia Spectrum Disorder

Overview

Journal Soc Psychiatry Psychiatr Epidemiol

Specialties Psychiatry
Public Health
Social Sciences

Date 2024 Mar 8

PMID 38456932

Authors

Jiasi Hao

Natalia Tiles-Sar

Tesfa Dejenie Habtewold

Edith J Liemburg

Richard Bruggeman

Lisette van der Meer

Behrooz Z Alizadeh

Affiliations

Soon will be listed here.

Abstract

Purpose: We aimed to explore the multidimensional nature of social inclusion (mSI) among patients diagnosed with schizophrenia spectrum disorder (SSD), and to identify the predictors of 3-year mSI and the mSI prediction using traditional and data-driven approaches.

Methods: We used the baseline and 3-year follow-up data of 1119 patients from the Genetic Risk and Outcome in Psychosis (GROUP) cohort in the Netherlands. The outcome mSI was defined as clusters derived from combined analyses of thirteen subscales from the Social Functioning Scale and the brief version of World Health Organization Quality of Life questionnaires through K-means clustering. Prediction models were built through multinomial logistic regression (Model) and random forest (Model), internally validated via bootstrapping and compared by accuracy and the discriminability of mSI subgroups.

Results: We identified five mSI subgroups: "very low (social functioning)/very low (quality of life)" (8.58%), "low/low" (12.87%), "high/low" (49.24%), "medium/high" (18.05%), and "high/high" (11.26%). The mSI was robustly predicted by a genetic predisposition for SSD, premorbid adjustment, positive, negative, and depressive symptoms, number of met needs, and baseline satisfaction with the environment and social life. The Model (61.61% [54.90%, 68.01%]; P =0.013) was cautiously considered outperform the Model (59.16% [55.75%, 62.58%]; P =0.994).

Conclusion: We introduced and distinguished meaningful subgroups of mSI, which were modestly predictable from baseline clinical characteristics. A possibility for early prediction of mSI at the clinical stage may unlock the potential for faster and more impactful social support that is specifically tailored to the unique characteristics of the mSI subgroup to which a given patient belongs.

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