Staying in Place, Staying Connected: Exploring Tie-Retention to Inform Network-Based Health Interventions in Public...

Area of Science:

• Sociology
• Public Health
• Network Science

Background:

• The COVID-19 pandemic significantly altered social dynamics through distancing measures and population shifts.
• Public housing communities, serving low-income and mobile populations, were particularly vulnerable to these disruptions.
• Understanding relationship persistence in these settings is crucial for community well-being and intervention design.

Purpose of the Study:

• To investigate the factors influencing the maintenance of social relationships (tie-retention) within public housing communities during the COVID-19 pandemic.
• To develop a predictive model for relationship maintenance using longitudinal survey data.
• To identify key attributes of social ties and individuals that predict relationship longevity.

Main Methods:

• An egocentric longitudinal survey was conducted with 187 adults in two Boston public housing developments.
• Data collection occurred between March 2019 and approximately 1 year post-baseline.
• Multilevel hierarchical logistic regression was employed to model tie-retention, considering predictors like multiplexity, tie strength, individual attributes, and homophily.

Main Results:

• The best-fitting model identified multiplexity, longer relationship duration, shared educational background (homophily), and individual smoking as significant predictors of relationship maintenance.
• These factors collectively explained a substantial portion of the variance in tie-retention.
• The model's fit was assessed using the Akaike information criterion (AIC).

Conclusions:

• Durable and homophilous social ties play a critical role in relationship maintenance within disadvantaged urban communities.
• Findings suggest that social network-based interventions in public housing should leverage these strong, shared connections for greater effectiveness and longevity.
• The study provides valuable insights for designing targeted interventions in similar low-income urban settings facing social disruption.