Addressing Health Disparities Through Theoretically Informed Digital Behavioral Interventions: Integrating Social Cognitive Theory and Ecological Models in Underserved Populations

Authors

  • Olivia M. Henderson

    School of Psychological Sciences, The University of Melbourne, Melbourne, Victoria, Australia​

Keywords:

Health Disparities; Digital Behavioral Interventions; Social Cognitive Theory; Ecological Models; Underserved Populations; Chronic Disease Management

Abstract

This study explores how digital behavioral interventions (DBIs), grounded in Social Cognitive Theory (SCT) and Ecological Models (EM), can reduce health disparities in underserved populations (rural, low-socioeconomic status, racial/ethnic minorities). A mixed-methods design was used: 520 adults with type 2 diabetes (rural Kentucky: n=310; low-income urban Los Angeles: n=210) participated in a 6-month trial of “HealthBridge,” a culturally tailored DBI. Quantitative data (HbA1c levels, medication adherence, app engagement) and qualitative data (50 participant interviews, 22 stakeholder surveys) were analyzed. Results showed: (1) Intervention group had 1.3% lower HbA1c (p<0.001) and 28% higher adherence (p<0.01) than controls; (2) Rural participants had 37% lower app engagement (p<0.05) due to internet insecurity; (3) Cultural tailoring (bilingual content, local resource links) improved retention by 42%. Findings highlight that DBIs must integrate individual-level SCT constructs (self-efficacy) with EM’s community/policy supports to address disparities.

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Issue

Vol. 1 No. 1 (September 2025)

Section

Articles