Read this first: What is double-loop learning in global health?
Example 1: Addressing low uptake of a vaccine program
Single–Loop Learning: Improve logistics and supply chain management to ensure consistent vaccine availability at clinics.
Double–Loop Learning: Engage with community leaders to understand cultural beliefs and concerns around vaccination, and co-design a more localized and trustworthy immunization strategy.
What is the difference? Double-loop learning questions the assumption that the primary goal should be to increase uptake at all costs. It considers whether the program design respects community autonomy and addresses their real concerns. It may surface competing values of public health impact vs. community self-determination.
Example 2: Responding to an infectious disease outbreak
Single–Loop Learning: Rapidly mobilize health workers and supplies to affected areas to contain the outbreak following established emergency protocols.
Double–Loop Learning: Critically examine why the health system was vulnerable to this outbreak, and work with communities to redesign surveillance, preparedness and response systems to be more resilient.
What is the difference? Double-loop learning interrogates whether the existing outbreak response system is built on the value of health equity. It asks if the system privileges the needs of some populations over others and perpetuates historical power imbalances. It strives to create a more inclusive, participatory approach to defining outbreak preparedness and response priorities.
Example 3: Implementing a maternal health intervention that shows low adherence
Single–Loop Learning: Retrain health providers to improve their counseling skills and provide better patient education on the intervention.
Double–Loop Learning: Conduct participatory research with women and families to understand their needs, preferences and barriers to care-seeking, and collaborate with them to iteratively adapt the intervention design.
What is the difference? Double-loop learning challenges the implicit assumption that the intervention design is inherently correct and that non-adherence is a ‘user error’. It examines whether the intervention embodies values of respect, humility and co-creation with communities. It seeks to align the intervention with women’s self-articulated reproductive health values and preferences.
Example 4: Evaluating an underperforming community health worker (CHW) program
Single–Loop Learning: Strengthen CHW supervision, increase performance incentives, and optimize the ratio of CHWs to households.
Double–Loop Learning: Facilitate a joint reflection process with CHWs and community representatives to examine program strengths, challenges and equity gaps, and co-create a revised strategy that better aligns with community priorities and integrates CHWs’ insights.
What is the difference? Double-loop learning questions whether the CHW program is driven by the value of empowering communities as agents of their own health vs. treating CHWs as an instrument of technocratic public health aims. It re-centers the program on the value of CHW leadership and community-driven problem definition.
Example 5: Reforming a health financing policy to improve population coverage
Single–Loop Learning: Adjust the premium amounts, enrollment processes and benefit package based on initial uptake data.
Double–Loop Learning: Convene citizen panels and key stakeholders to deliberate on the fundamental goals and values underlying the financing reforms, and recommend redesigning the policy to better advance equity and financial protection.
What is the difference? Double-loop learning interrogates whether the true intent of the policy is to advance equity and financial protection for marginalized groups or simply to expand coverage as an end unto itself. It opens up debate on the core values and theory of change underlying the reforms. It aims to re-anchor the policy in a wholistic vision of equitable universal health coverage.