Mobile App Use and Pregnancy Health Literacy: Cross-Sectional Study Using Bayesian Network Analysis

Area of Science:

• Digital Health Interventions
• Maternal Health Technology
• Health Communication

Background:

• Low health literacy affects 15%-44% of pregnant women, negatively impacting maternal and fetal health.
• Pregnancy apps are increasingly used, but their psychological mechanisms for improving health literacy are unclear.
• Cognitive Load Theory (CLT) and ICALM provide frameworks for understanding digital interventions in pregnancy.

Purpose of the Study:

• To investigate the psychological and social-cognitive pathways through which pregnancy app engagement influences health literacy and behaviors.
• To understand how digital engagement impacts health literacy and health behaviors in pregnant women.

Main Methods:

• Cross-sectional survey of 998 pregnant/postpartum women (18-45 years) in the US.
• Bayesian Network (BN) modeling informed by CLT and ICALM, analyzing data from Pregnancy+ users, other app users, and non-users.
• Measurement of digital engagement, emotions, health literacy, support, and health behaviors (physical activity, nutrition, stress management).

Main Results:

• Pregnancy apps enhance health literacy and behaviors indirectly through positive emotions and strengthened support networks.
• No direct pathways were found between digital engagement and health literacy or behaviors.
• Pregnancy+ users showed stronger adherence to these pathways, reporting more joyfulness, higher support levels, and better critical health literacy.

Conclusions:

• Pregnancy apps enhance health literacy by fostering positive emotions and social support, acting as psychological support systems.
• Findings validate CLT and ICALM in pregnancy contexts, emphasizing emotionally supportive app design.
• App developers should prioritize emotional support and social connection; healthcare providers should recommend apps promoting emotional well-being.