Abstract

Social factors, such as social cognition skills (SCS) and social determinants of health (SDH), may be vital for mental health, even when compared with classical psycho-physical predictors (demographic, physical, psychiatric, and cognitive factors). Although major risk factors for psychiatric disorders have been previously assessed, the relative weight of SCS and SDH in relation to classical psycho-physical predictors in predicting symptoms of mental disorders remains largely unknown. In this study, we implemented multiple structural equation models (SEM) from a randomized sample assessed in the Colombian National Mental Health Survey of 2015 (CNMHS, n = 2947, females: 1348) to evaluate the role of SCS, SDH, and psycho-physical factors (totaling 17 variables) as predictors of mental illness symptoms (anxiety, depression, and other psychiatric symptoms). Specifically, we assessed the structural equation modeling of (a) SCS (emotion recognition and empathy skills); (b) SDH (including the experience of social adversities and social protective factors); (c) and classical psycho-physical factors, including psychiatric antecedents, physical–somatic factors (chronic diseases), and cognitive factors (executive functioning). Results revealed that the emotion recognition skills, social adverse factors, antecedents of psychiatric disorders and chronic diseases, and cognitive functioning were the best predictors of symptoms of mental illness. Moreover, SCS, particularly emotion recognition skills, and SDH (experiences of social adversities, familial, and social support networks) reached higher predictive values of symptoms than classical psycho-physical factors. Our study provides unprecedented evidence on the impact of social factors in predicting symptoms of mental illness and highlights the relevance of these factors to track early states of disease.

Highlights

  • Social processes are vital to achieving mental wellbeing[1,2]

  • We found the social determinants of health (SDH) and social cognition skills (SCS) structural equation models (SEM), in particular, the SDH-SEM reached higher fit indexes than SCS-SEM (Table 2). In this randomized probabilistic design, we evaluated to what extent a combined set of social factors (SCS and SDH) is able to predict symptoms of mental illness

  • This is the first study to highlight the importance of a broad range of social factors in combination with classical factors in predicting the presence of a broad spectrum of symptoms of mental illness, which can be considered as subclinical states of mental disorders

Read more

Summary

Introduction

Social processes are vital to achieving mental wellbeing[1,2]. Social and familial support, as well as social group membership, can positively impact resiliency and mental health[1]. Regression coefficients showed that symptoms of mental illness were positively predicted by the presence of social adverse factors (F:M = 0.49:0.48, P < 0.0001), physical–somatic problems (F:M = 0.25:0.22, P < 0.0001), and psychiatric antecedents (F:M = 0.22:0.14, P < 0.001).

Results
Conclusion
Full Text
Published version (Free)

Talk to us

Join us for a 30 min session where you can share your feedback and ask us any queries you have

Schedule a call