# Organization of Psychosocial Processes in Metropolitan and Non-Metropolitan Regions

## TL;DR

This study explores how social, emotional, and behavioral factors in adolescents differ between urban and rural areas, revealing how these factors are organized and influence well-being.

## Contribution

The study introduces a novel comparison of psychosocial network structures in metropolitan versus non-metropolitan adolescent populations.

## Key findings

- Emotional distress, sensation seeking, and problem behaviors act as key bridges in non-metropolitan adolescent networks.
- Metropolitan networks show stronger central roles for positive well-being, social connectedness, and parental/peer disapproval.
- Network structures differ significantly between urban and rural environments, suggesting context-specific influences on adolescent behavior.

## Abstract

Adolescents’ social, emotional, and behavioral characteristics do not operate in isolation but form interconnected systems that shape well-being. These processes may differ across geographic settings, particularly between metropolitan (MSA) and non-metropolitan (non-MSA) environments, which vary in social norms, community resources, and daily experiences. However, little research has examined how these psychosocial factors are organized as part of a broader system in different environments.

This study compared the structure of psychosocial networks among adolescents living in MSA and non-MSA settings. We aimed to identify whether social, emotional, and behavioral constructs cluster differently across environments and whether specific constructs show stronger influence or bridging roles within each network.

Data were drawn from the 2023 Monitoring the Future survey of U.S. adolescents. Twelve psychosocial and behavioral constructs were examined, including emotional distress, self-esteem, positive well-being, social connectedness, sensation seeking, boredom, problem behaviors, and perceived parental and peer disapproval of substance use, and substance use. Separate correlation-based networks were generated for MSA and non-MSA youth. System-level measures (average degree, betweenness, eigenvector centrality) were used to assess overall structure, and node-level metrics identified constructs serving as central or bridging elements within each network.

Emotional distress, sensation seeking, and problem behaviors played stronger bridging roles in non-MSA than MSA environments. In contrast, MSA networks were more evenly distributed, with positive well-being, social connectedness, and parental or peer disapproval showing stronger central influence.

Different organization of psychosocial processes across environments can inform context-sensitive strategies to support adolescent well-being.