Designing Health Recommender Systems to Promote Health Equity: A Socioecological Perspective.

Area of Science:

• Digital Health
• Health Equity Research
• Socio-ecological Models in Health

Background:

• Health recommender systems (HRS) personalize health information and interventions.
• HRS can leverage individual preferences and broader social influences (peers, community, society).
• The socio-ecological model highlights multi-level factors influencing health outcomes.

Purpose of the Study:

• To explore the potential of HRS in decreasing health inequities.
• To analyze how HRS can address individual and structural health determinants.
• To identify challenges and future research priorities for equitable HRS.

Main Methods:

• Literature review and analysis of current HRS capabilities.
• Application of the socio-ecological model to understand health determinants.
• Discussion of design paradigms and equity-focused approaches for HRS.

Main Results:

• Current HRS primarily focus on individual behaviors and lack integration of user experiences.
• Existing HRS show limited reach and effectiveness for marginalized populations.
• There is a need to incorporate structural barriers and systemic factors into HRS design.

Conclusions:

• A new design paradigm is essential for HRS to address structural barriers and promote health equity.
• HRS should integrate decolonial perspectives and focus on health systems.
• Evaluating health equity impacts and using data for policy influence are crucial future directions for HRS.