Taking the pulse why and how we change everything in response to learner signals

Taking the pulse: why and how we change everything in response to learner signals

Reda SadkiLearning design, Theory

The ability to analyze and respond to learner behavior as it happens is crucial for educators.

In complex learning that takes place in digital spaces, task separation between the design of instruction and its delivery does not make sense.

Here is the practical approach we use in The Geneva Learning Foundation’s learning-to-action model to implement responsive learning environments by listening to learner signals and adapting design, activities, and feedback accordingly.

Listening for and interpreting learner signals

Educators must pay close attention to various signals that learners emit throughout their learning journey. These signals appear in several key ways:

  1. Engagement levels: This includes participation rates, the quality of contributions in discussions, how learners interact with each other, and knowledge artefacts they produce.
  2. Emotional responses: The tone and content of learner feedback can indicate enthusiasm, frustration, or confusion.
  3. Performance patterns: Trends in speed and volume of responses tend to strongly correlate with more significant learning outcome indicators.
  4. Interaction dynamics: Learners can feel a facilitator’s conviction (or lack thereof) in the learning process. Observing the interaction should focus first on the facilitator’s own behavior: what are they modeling for learners?
  5. Technical interactions: The way learners navigate the learning platform, which resources they access most, and any technical challenges they face are important indicators.

Making sense of learner signals

Once these signals are identified, a nuanced approach to analysis is necessary:

  1. Contextual consideration: Understanding the broader context of learners’ experiences is vital. For example, differences between language cohorts might reflect varying levels of real-world experience and cultural contexts.
  2. Holistic view: Look beyond immediate learning objectives to understand all aspects of learners’ experiences, including factors outside the course that may affect their engagement.
  3. Temporal analysis: Track changes in learner behavior over time to reveal important trends and patterns as the course progresses.
  4. Comparative assessment: Compare behavior across different cohorts, language groups, or demographic segments to identify unique needs and preferences.
  5. Feedback loop analysis: Examine how learners respond to different types of feedback and instructional interventions to provide valuable insights.

Adapting learning design in situ

What can we change in response to learner behavior, signals, and patterns?

  1. Customized content: Tailor case studies, examples, and scenarios to match the real-world experiences and cultural contexts of different learner groups.
  2. Flexible pacing: Adjust the rhythm of content delivery and activities based on observed engagement patterns and feedback.
  3. Varied support mechanisms: Implement a range of support options, from technical assistance to emotional support, based on identified learner needs.
  4. Dynamic group formations: Adapt group activities and peer learning opportunities based on observed interaction dynamics and skill levels.
  5. Multimodal delivery: Offer content and activities in various formats to cater to different learning preferences and technical capabilities.

Responding to learner signals

Feedback plays a crucial role in the learning process:

  1. Comprehensive acknowledgment: Feedback mechanisms should demonstrate to learners that their input is valued and considered. This might involve creating, at least once, detailed summaries of learner feedback to show that every voice has been heard.
  2. Timely interventions: Using real-time feedback to address emerging issues or confusion quickly can prevent small challenges from becoming major obstacles.
  3. Personalized guidance: Tailor feedback to individual learners based on their unique progress, challenges, and goals.
  4. Peer feedback facilitation: Create opportunities for learners to provide feedback to each other to foster a collaborative learning environment.
  5. Metacognitive prompts: Incorporate feedback that encourages learners to reflect on their learning process to promote self-awareness and self-directed learning.

Balancing act

When combined, these analyses provide clues to inform decisions.

Nothing should be set in stone.

Decisions need to be pragmatic and rapid.

In order to respond to the pattern formed by signals, what are the trade-offs?

The digital economy of effort makes rapid changes possible.

Nevertheless, we consider the cost of each change versus its benefit.

This adaptive approach involves careful balancing of various factors:

  1. Depth versus speed: Navigate the tension between providing comprehensive feedback and maintaining a timely pace of instruction.
  2. Structure versus flexibility: Maintain a coherent course structure while allowing for adaptations based on learner needs.
  3. Individual versus group needs: Balance addressing individual learner challenges with maintaining the momentum of the entire cohort.
  4. Emotional support versus learning structure: Provide necessary emotional support, especially in challenging contexts, while maintaining focus on learning objectives.

Learning is research

Each learning experience should be treated as a research opportunity:

  1. Data collection: Systematically collect data on learner behavior, feedback, and outcomes.
  2. Team reflection: Conduct regular debriefs with the instructional team to share insights and adjust strategies.
  3. Iterative design: Use insights gained from each cohort to refine the learning design for future iterations.
  4. Cross-cohort learning: Apply lessons learned from one language or cultural group to enhance the experience of others, while respecting unique contextual differences.

Image: The Geneva Learning Foundation Collection © 2024

Community-based monitoring for immunization

Integrating community-based monitoring (CBM) into a comprehensive learning-to-action model

Reda SadkiGlobal health

According to Gavi, “community-based monitoring” or “CBM” is a process where service users collect data on various aspects of health service provision to monitor program implementation, identify gaps, and collaboratively develop solutions with providers.

  • Community-based monitoring (CBM) has emerged as a promising strategy for enhancing immunization program performance and equity.
  • CBM interventions have been implemented across different settings and populations, including remote rural areas, urban poor, fragile/conflict-affected regions, and marginalized groups such as indigenous populations and people living with HIV.

By engaging service users, CBM aims to foster greater accountability and responsiveness to local needs.

  • However, realizing CBM’s potential in practice has proven challenging.
  • Without a coherent approach, CBM risks becoming just another disconnected tool.

The Geneva Learning Foundation’s innovative learning-to-action model offers a compelling framework within which CBM could be applied to immunization challenges.

The model’s comprehensive design creates an enabling environment for effectively integrating diverse monitoring data sources – and this could include community perspectives.

Health workers as trusted community advisers… and members of the community

A distinctive feature of TGLF’s model is its emphasis on health workers’ role as trusted advisors to the communities they serve.

The model recognizes that local health staff are not merely service providers, but often deeply embedded community members with intimate knowledge of local realities.

For example, in TGLF’s immunization learning initiatives, participating health workers frequently share insights into the social, cultural, and economic factors shaping vaccine hesitancy and uptake in their communities.

  • They discuss the everyday barriers families face, from misinformation to transportation challenges, and strategize context-specific outreach approaches.
  • This grounding in community realities positions health workers as vital bridges for facilitating community engagement in monitoring.

When local staff are empowered as active agents of learning and change, they can more effectively champion community participation, translating insights into tangible improvements.

Could CBM fit into a more comprehensive system from local monitoring to action?

TGLF’s model supports health workers in this bridging role by providing a comprehensive framework for local monitoring and action.

Through peer learning networks and problem-solving cycles, the model equips health staff to collect, interpret, and act on unconventional monitoring data from their communities.

For instance, in TGLF’s 2022 “Full Learning Cycle” initiative, 6,185 local health workers from 99 countries examined key immunization indicators to inform their analyses of root causes and then map out corrective actions.

  • Participants began monitoring their own local health indicators, such as vaccination coverage rates.
  • For many, this was the first time they had been prompted to use this data for problem-solving a real-world challenge they face, rather than just reporting up the next level of the health system.

They discussed many factors critical for tailoring immunization strategies.

This transition – from being passive data collectors to active data users – has proven transformative.

It positions health workers not as cogs in a reporting machine, but as empowered analysts and strategists.

By discussing real metrics with peers, participants make data actionable and contextually meaningful.

Guided by expert-designed rubrics and facilitated discussions, health workers translated this localized monitoring data into practical improvement plans.

For an epidemiologist, this represents a significant shift from traditional top-down monitoring paradigms.

By valuing and actioning local knowledge, TGLF’s model demonstrates how community insights can be systematically integrated into immunization decision-making.

However, until now, its actors have been health workers, many of them members of the communities they serve, not service users themselves.

CBM’s focus on monitoring is important – but leaves out key issues around community participation, decision-making autonomy, and strategy.

How could we integrate CBM into a transformative approach?

TGLF’s experiences suggest that CBM could be embedded within comprehensive learning-to-action systems focused on locally-led change.

TGLF’s model is more than a monitoring intervention.

  • It combines structured learning, rapid solution sharing, root cause analysis, action planning, and peer accountability to drive measurable improvements.
  • These mutually reinforcing components create an enabling environment for health workers to translate insights into impact.

In this framing, community monitoring becomes one critical input within a continuous, collaborative process of problem-solving and adaptation.

Several features of TGLF’s model illustrate how this integration could work in practice:

  1. Peer accountability structures, where health workers regularly convene to review progress, share challenges, and iterate solutions, create natural entry points for discussing and actioning community feedback.
  2. Rapid dissemination channels, like TGLF’s “Ideas Engine” for spreading promising practices across contexts, enable local innovations in response to community-identified gaps to be efficiently scaled.
  3. Emphasis on root cause analysis and systemic thinking equips health workers to interpret community insights within a broader ecosystem lens, connecting localized issues to upstream determinants.
  4. Cultivation of connected leadership empowers local actors to champion community priorities and navigate complex change processes.

TGLF’s extensive digital network connects health workers across system levels and contexts, enabling them to learn from each other’s experiences with no upper limit to the number of participants.

By contrast, CBM seems to assume that a community is limited to a physical area, which fails to recognize that problem-solving complex challenges requires expanding the range of inputs used.

Within a networked approach that connects both community members and health workers across boundaries of geography, health system level, and roles, CBM could become an integral component of a transformative approach to health system improvement – one that recognizes communities and local health workers as capable architects of context-responsive solutions.

Fundamentally, the TGLF model invites a shift in mindset about whose expertise counts in monitoring and driving system change.

CBM could provide the ‘connective tissue’ for health workers to revise how they listen and learn with the communities they serve.

For immunization programs grappling with persistent inequities, this shift from passive compliance to proactive local problem-solving is critical.

As the COVID-19 crisis has underscored, rapidly evolving public health challenges demand localized action that harnesses the full range of community expertise.

TGLF’s model offers a tested framework for actualizing this vision at scale.

By investing in local health workers’ capacity to learn, adapt, and lead change in partnership with the communities they serve, the model illuminates a promising pathway for integrating CBM into immunization monitoring and beyond.

For epidemiologists and global health practitioners, TGLF’s approach invites a reframing of how we conceptualize and operationalize community engagement in health system monitoring.

It challenges us to move beyond tokenistic participation towards genuine co-design and co-ownership of monitoring processes with local actors.

Realizing this vision will require significant shifts in mindsets, power dynamics, and resource flows.

But as TGLF’s initiatives demonstrate, when we invest in the leadership of those closest to the challenges we seek to solve, transformative possibilities emerge.

Further rigorous research comparing the impacts of different CBM integration models could help accelerate this paradigm shift, surfacing critical lessons for the immunization field and global health more broadly.

TGLF’s model not only offers compelling lessons for reimagining monitoring and improvement in immunization programs, it also provides a pathway for integrating CBM into a system that supports actual change.

CBM practitioners are likely to struggle with how to incorporate it into existing practices.

By investing in frontline health workers as change agents, and surrounding them with an empowering learning ecosystem, the model offers a path to then bring in community monitoring.

Without such leadership from health workers, it is unlikely that communities are able to participate.

The journey to authentic community engagement in health system monitoring is undoubtedly complex.

But if we are to deliver on the promise of equitable immunization for all, it is a journey we must undertake.

TGLF’s model lights one promising path forward – one that positions communities and local health workers as the beating heart of a learning health system.

While Gavi’s evidence brief affirms the promise of CBM for immunization, TGLF’s experience with its own model suggests the full potential of CBM may be realized by embedding it within more comprehensive, digitally-enabled learning systems that activate health workers as agents of change – and do so with both physical and digital communities implementing new forms of peer and community accountability that complement conventional kinds (supervision, administration, donor, etc.).

Heini Utenen OpenWHO confusion about methods and learner preferences

Why asking learners what they want is a recipe for confusion

Reda SadkiGlobal health, Theory

A survey of learners on a large, authoritative global health learning platform has me pondering once again the perils of relying too heavily on learner preferences when designing educational experiences.

One survey question intended to ask learners for their preferred learning method.

The list of options provided includes a range of items.

(Some would make the point that the list conflates learning resources and learning methods, but let us leave that aside for now.)

Respondents’ top choices (source) were videos, slides, and downloadable documents.

At first glance, this seems perfectly reasonable.

After all, should we not give learners what they want?

As it happens, the main resources offered by this platform are videos, slides, and other downloadable documents.

(If we asked learners who participate in our peer learning programmes for their preference, they would likely say that they prefer… peer learning.)

Beyond this availability bias, there is a more significant problem with this approach: learner preferences often have little correlation with actual learning outcomes.

And learners are especially bad at self-evaluating what learning methods and resources are most conducive to effective learning.

The scientific literature is quite clear on this point.

Bjork’s 2013 article on self-regulated learning emphatically states that: “learners are often prone to illusions of competence during learning, and these illusions can be remarkably compelling.”

The study by Deslauriers et al. (2019) provides a compelling demonstration that while students express a strong preference for traditional lectures over active learning methods, they actually learn significantly more from the active approaches they claim to dislike.

This disconnect between preference and efficacy is not surprising when we consider how learning actually works.

Effective learning requires effort, struggle, and sometimes discomfort as we grapple with new ideas and challenge our existing mental models.

It is not always an enjoyable process in the moment, even if the long-term results are deeply rewarding.

Furthermore, learners (like all of us) are subject to various cognitive biases that can lead them astray when evaluating their own learning.

The illusion of explanatory depth, for example, can cause us to overestimate how well we understand a topic after passively consuming information about it.

None of this is to say we should ignore learner perspectives entirely.

Motivation and engagement do matter for learning.

But we need to be thoughtful about how we solicit and interpret learner feedback.

Asking about preferences for specific content formats (videos, slides, etc.) tells us very little about the actual learning activities and cognitive processes involved.

A more productive approach might be to focus on understanding learners’ goals, challenges, and contexts.

What are they trying to achieve?

What obstacles do they face?

What constraints shape their learning environment?

With this information, we can design evidence-based learning experiences that truly meet their needs – even if they don’t always match their stated preferences.

As learning professionals, our job is not to give learners what they think they want.

It is to create the conditions for transformative learning experiences that expand their capabilities and perspectives.

This often means pushing learners out of their comfort zones and challenging their assumptions about how learning should look and feel.

Bjork, R. A., Dunlosky, J., & Kornell, N. (2013). Self-regulated learning: Beliefs, techniques, and illusions. Annual Review of Psychology, 64, 417-444. https://doi.org/10.1146/annurev-psych-113011-143823

Deslauriers, L., McCarty, L.S., Miller, K., Callaghan, K., Kestin, G., 2019. Measuring actual learning versus feeling of learning in response to being actively engaged in the classroom. Proceedings of the National Academy of Sciences 201821936. https://doi.org/10.1073/pnas.1821936116

Learn health, but beware of the behaviorist trap

Reda SadkiGlobal health, Theory

The global health community has long grappled with the challenge of providing effective, scalable training to health workers, particularly in resource-constrained settings.

In recent years, digital learning platforms have emerged as a potential solution, promising to deliver accessible, engaging, and impactful training at scale.

Imagine a digital platform intended to train health workers at scale.

Their theory of change rests on a few key assumptions:

  1. Offering simplified, mobile-friendly courses will make training more accessible to health workers.
  2. Incorporating videos and case studies will keep learners engaged.
  3. Quizzes and knowledge checks will ensure learning happens.
  4. Certificates, continuing education credits, and small incentives will motivate course completion.
  5. Growing the user base through marketing and partnerships is the path to impact.

On the surface, this seems sensible.

Mobile optimization recognizes health workers’ technological realities.

Multimedia content seems more engaging than pure text.

Assessments appear to verify learning.

Incentives promise to drive uptake.

Scale feels synonymous with success.

While well-intentioned, such a platform risks falling into the trap of a behaviorist learning agenda.

This is an approach that, despite its prevalence, is a pedagogical dead-end with limited potential for driving meaningful, sustained improvements in health worker performance and health outcomes.

It is a paradigm that views learners as passive recipients of information, where exposure equals knowledge acquisition.

It is a model that privileges standardization over personalization, content consumption over knowledge creation, and extrinsic rewards over intrinsic motivation.

It fails to account for the rich diversity of prior experiences, contexts, and challenges that health workers bring to their learning.

Most critically, it neglects the higher-order skills – the critical thinking, the adaptive expertise, the self-directed learning capacity – that are most predictive of real-world performance.

Clicking through screens of information about neonatal care, for example, is not the same as developing the situational judgment to adapt guidelines to a complex clinical scenario, nor the reflective practice to continuously improve.

Moreover, the metrics typically prioritized by behaviorist platforms – user registrations, course completions, assessment scores – are often vanity metrics.

They create an illusion of progress while obscuring the metrics that truly matter: behavior change, performance improvement, and health outcomes.

A health worker may complete a generic course on neonatal care, for example, but this does not necessarily translate into the situational judgment to adapt guidelines to complex clinical scenarios, nor the reflective practice to continuously improve.

The behaviorist paradigm’s emphasis on information transmission and standardized content may stem from an implicit assumption that health workers at the community level do not require higher-order critical thinking skills – that they simply need a predetermined set of knowledge and procedures.

This view is not only paternalistic and insulting, but it is also fundamentally misguided.

A robust body of scientific evidence on learning culture and performance demonstrates that the most effective organizations are those that foster continuous learning, critical reflection, and adaptive problem-solving at all levels.

Health workers at the frontlines face complex, unpredictable challenges that demand situational judgment, creative thinking, and the ability to learn from experience.

Failing to cultivate these capacities not only underestimates the potential of these health workers, but it also constrains the performance and resilience of health systems as a whole.

Even if such a platform achieves its growth targets, it is unlikely to realize its impact goals.

Health workers may dutifully click through courses, but genuine transformative learning remains elusive.

The alternative lies in a learning agenda grounded in advances of the last three decades learning science.

These advances remain largely unknown or ignored in global health.

This approach positions health workers as active, knowledgeable agents, rich in experience and expertise.

It designs learning experiences not merely to transmit information, but to foster critical reflection, dialogue, and problem-solving.

It replaces generic content with authentic, context-specific challenges, and isolated study with collaborative sense-making in peer networks.

It recognizes intrinsic motivation – the desire to grow, to serve, to make a difference – as the most potent driver of learning.

Here, success is measured not in superficial metrics, but in meaningful outcomes: capacity to lead change in facilities and communities that leads to tangible improvements in the quality of care.

Global health leaders faces a choice: to settle for the illusion of progress, or to invest in the deep, difficult work of authentic learning and systemic change, commensurate with the complexity and urgency of the task at hand.

Image: The Geneva Learning Foundation Collection © 2024

Why health leaders who are critical thinkers choose rote learning for others-small

Why health leaders who are critical thinkers choose rote learning for others

Reda SadkiGlobal health

Many health leaders are highly analytical, adaptive learners who thrive on solving complex problems in dynamic, real-world contexts.

Their expertise is grounded in years of field experience, where they have honed their ability to rapidly generate insights, test ideas, and innovate solutions in collaboration with diverse stakeholders.

In January 2021, as countries were beginning to introduce new COVID-19 vaccines, Kate O’Brien, who leads WHO’s immunization efforts, connected global learning to local action:

“For COVID-19 vaccines […] there are just too many lessons that are being learned, especially according to different vaccine platforms, different communities of prioritization that need to be vaccinated. So [everyone]  has got to be able to scale, has got to be able to deal with complexity, has got to be able to do personal, local innovation to actually overcome the challenges.”

In an Insights Live session with the Geneva Learning Foundation in 2022, she made a compelling case that “the people who are working in the program at that most local level have to be able to adapt, to be agile, to innovate things that will work in that particular setting, with those leaders in the community, with those families.”

However, unlike Kate O’Brien, some senior leaders in global health disconnect their own learning practices and their assumptions about how others learn best.

When it comes to designing learning initiatives for their teams or organizations, these leaders may default to a more simplistic, behaviorist approach.

They may equate learning with the acquisition and application of specific skills or knowledge, and thus focus on creating structured, content-driven training programs.

The appeal of behaviorist platforms – with their promise of efficient, scalable delivery and easily measured outcomes – can be seductive in the resource-constrained, results-driven world of global health.

Furthermore, leaders may hold assumptions that health workers – especially those at the community level – do not require higher-order critical thinking skills, that they simply need a predetermined set of knowledge and procedures.

This view is fundamentally misguided.

A robust body of scientific evidence on learning culture and performance demonstrates that the most effective organizations are those that foster continuous learning, critical reflection, and adaptive problem-solving at all levels.

Health workers at the frontlines face complex, unpredictable challenges that demand situational judgment, creative thinking, and the ability to learn from experience.

Failing to cultivate these capacities not only underestimates the potential of these health workers, but it also constrains the performance and resilience of health systems as a whole.

The problem is that this approach fails to cultivate the very qualities that make these leaders effective learners and problem-solvers.

Behaviorist techniques, with their emphasis on passive information absorption and narrow, pre-defined outcomes, do not foster the critical thinking, creativity, and collaborative capacity needed to tackle complex health challenges.

They may produce short-term gains in narrow domains, but they cannot develop the adaptive expertise required for long-term impact in ever-shifting contexts.

To help health leaders recognize this disconnect, it is useful to engage them in reflective dialogue about their own learning processes.

By unpacking real-world examples of how they have solved thorny problems or generated novel insights, we can highlight the sophisticated cognitive strategies and collaborative dynamics at play.

We can show how they constantly question assumptions, synthesize diverse perspectives, and iterate solutions – all skills that are essential for navigating complexity, but are poorly served by rigid, content-focused training.

The goal is not to dismiss the need for foundational knowledge or skills, but rather to emphasize that in the face of evolving challenges, adaptive learning capacity is the real differentiator.

It is the ability to think critically, to imagine new possibilities, to learn from failure, and to co-create with others that drives meaningful change.

By tying this insight directly to leaders’ own experiences and values, we can inspire them to champion learning approaches that mirror the richness and dynamism of their personal growth journeys.

Ultimately, the most impactful health organizations will be those that not only equip people with essential skills, but that also nurture the underlying cognitive and collaborative capacities needed to continually learn, adapt, and innovate.

By recognizing and leveraging the powerful learning practices they themselves embody, health leaders can shape organizational cultures and strategies that truly empower people to navigate complexity and drive transformative change.

This shift requires letting go of the illusion of control and predictability that behaviorism offers, and instead embracing the messiness and uncertainty of real learning.

It means creating space for experimentation, reflection, and dialogue, and trusting in people’s inherent capacity to grow and create.

It is a challenging transition, but one that health leaders are uniquely positioned to lead – if they can bridge the gap between how they learn and how they seek to enable others’ learning.

Image: The Geneva Learning Foundation Collection © 2024

Self-Regulated Learning: Beliefs, Techniques, and Illusions

8 things we know about learning across the lifespan in a complex world

Reda SadkiTheory

The work by Robert A. Bjork and his colleagues is very helpful to make sense of the limitations of learners’ perceptions. Here are 8 summary points from their paper about self-regulated learning.

  1. Our complex and rapidly changing world increasingly requires self-initiated and self-managed learning, not simply during the years associated with formal schooling, but across the lifespan.
  2. Learning how to learn is, therefore, a critical survival tool, but research on learning, memory, and metacognitive processes has demonstrated that learners are prone to intuitions and beliefs about learning that can impair, rather than enhance, their effectiveness as learners.
  3. Becoming sophisticated as a learner requires not only acquiring a basic understanding of the encoding and retrieval processes that characterize the storage and subsequent access to the to-be-learned knowledge and procedures, but also knowing what learning activities and techniques support long-term retention and transfer.
  4. Managing one’s ongoing learning effectively requires accurate monitoring of the degree to which learning has been achieved, coupled with appropriate selection and control of one’s learning activities in response to that monitoring.
  5. Assessing whether learning has been achieved is difficult because conditions that enhance performance during learning can fail to support long-term retention and transfer, whereas other conditions that appear to create difficulties and slow the acquisition process can enhance long-term retention and transfer.
  6. Learners’ judgments of their own degree of learning are also influenced by subjective indices, such as the sense of fluency in perceiving or recalling to-be-learned information, but such fluency can be a product of low-level priming and other factors that are unrelated to whether learning has been achieved.
  7. Becoming maximally effective as a learner requires interpreting errors and mistakes as an essential component of effective learning rather than as a reflection of one’s inadequacies as a learner.
  8. To be maximally effective also requires an appreciation of the incredible capacity humans have to learn and avoiding the mindset that one’s learning abilities are fixed.

Source: Bjork, R.A., Dunlosky, J., Kornell, N., 2013. Self-Regulated Learning: Beliefs, Techniques, and Illusions. Annu. Rev. Psychol. 64, 417–444. https://doi.org/10.1146/annurev-psych-113011-143823

Petra Klepac Climate change, malaria and neglected tropical diseases-a scoping review

Klepac and colleagues‘ scoping review of climate change, malaria and neglected tropical diseases: what about the epistemic significance of health worker knowledge?

Reda SadkiGlobal health

By Luchuo E. Bain and Reda Sadki

The scoping review by Klepac et al. provides a comprehensive overview of codified academic knowledge about the complex interplay between climate change and a wide range of infectious diseases, including malaria and 20 neglected tropical diseases (NTDs).

The review synthesized findings from 511 papers published between 2010 and 2023, revealing that the vast majority of studies focused on malaria, dengue, chikungunya, and leishmaniasis, while other NTDs were relatively understudied.

The geographical distribution of studies also varied, with malaria studies concentrated in Africa, Brazil, China, and India, and dengue and chikungunya studies more prevalent in Australia, China, India, Europe, and the USA.

One of the most striking findings of the review is the potential for climate change to have profound and varied effects on the distribution and transmission of malaria and NTDs, with impacts likely to vary by disease, location, and time.

However, the authors also highlight the uncertainty surrounding the overall global impact due to the complexity of the interactions and the limitations of current predictive models.

This underscores the need for more comprehensive, collaborative, and standardized modeling efforts to better understand the direct and indirect effects of climate change on these diseases.

Another significant insight from the review is the relative lack of attention given to climate change mitigation and adaptation strategies in the existing literature.

Only 34% of the included papers considered mitigation strategies, and a mere 5% addressed adaptation strategies.

Could we imagine future mapping to recognize the value of new mechanisms for and actors of knowledge production that do not meet the conventional criteria for what currently counts as valid knowledge?

What might be the return on going at least one step further beyond questioning our own underlying assumptions about ‘how science is done’ to actually supporting and investing in innovative indigenous- and community-led, co-created initiatives?

This gap highlights the urgent need for more research on how to effectively reduce the impact of climate change on malaria and NTDs, particularly in areas with the highest disease burdens and the populations most vulnerable to the impacts of climate change.

While the review emphasizes the need for more research to fill these evidence gaps, this begs the question of the resources and time required to fill them.

This is where there is likely to be value in the experiential data from health workers on the frontlines to provide insights into the mechanisms of climate change impacts on health and effective response strategies.

The upcoming Teach to Reach 10 event (background | registration) , a massive open peer learning platform that brings together health professionals from around the world to network and learn from each other’s experiences, offers a unique opportunity to engage thousands of health workers in a dialogue that can deepen our understanding of how climate change is affecting the health of local communities.

Experiential data has been, historically, dismissed as ‘anecdotal’ evidence at best.

The value and significance of what you know because you are there every day, serving the health of your community, has been ignored.

The expertise and knowledge of frontline health workers are often overlooked or undervalued in global health decision-making processes, despite their critical role in delivering health services and their deep understanding of local contexts and challenges.

Yes, the importance of incorporating the insights and experiences of health workers in the global health discourse cannot be overstated.

As Abimbola and Pai (2020) argue, the decolonization of global health requires a shift towards valuing and amplifying the voices of those who have been historically marginalized and excluded from the dominant narratives.

This concept, known as epistemic justice, recognizes that knowledge is not solely the domain of academic experts but is also held by those with lived experiences and practical expertise (Fricker, 2007).

Epistemic injustice, as defined by Fricker (2007), occurs when an individual is wronged in their capacity as a knower, either through testimonial injustice (when a speaker’s credibility is undervalued due to prejudice) or hermeneutical injustice (when there is a gap in collective understanding that disadvantages certain groups).

In the context of global health, epistemic injustice often manifests in the marginalization of knowledge held by communities and health workers in low- and middle-income countries, as well as the dominance of Western biomedical paradigms over local ways of knowing (Bhakuni & Abimbola, 2021).

By engaging health workers from around the world in peer learning and knowledge sharing, Teach to Reach can help to challenge the epistemic injustice that has long plagued global health research and practice.

By providing a platform for health workers to share their experiences and insights, Teach to Reach – alongside many other initiatives focused on listening to and learning from communities – can contribute to ensuring that the fight against malaria and NTDs in the face of climate change is informed not only by rigorous scientific evidence but also by the practical wisdom of those on the ground.

That is only if global partners are willing to challenge their own assumptions, and take the time to listen and learn.

Moreover, the decolonization of global health requires a shift towards more equitable and inclusive forms of knowledge production and dissemination.

This involves challenging the historical legacies of colonialism and racism that have shaped the global health field, as well as the power imbalances that continue to privilege certain forms of knowledge over others (Büyüm et al., 2020).

By fostering a dialogue between health workers and global partners, Teach to Reach can help to bridge the gap between research and practice, ensuring that the latest scientific findings are effectively translated into actionable strategies that are grounded in local realities and responsive to the needs of those most affected by climate change and infectious diseases.

The value of experiential data from health workers in filling evidence gaps and informing effective response strategies cannot be understated.

As the Klepac review highlights, there is a paucity of research on the impacts of climate change on many NTDs and the effectiveness of mitigation and adaptation strategies.

While more rigorous scientific studies are undoubtedly needed, waiting years or decades for this evidence to accumulate before taking action is not a viable option given the urgency of the climate crisis and its devastating impacts on health.

Health workers’ firsthand observations and experiences can provide valuable insights into the complex mechanisms through which climate change is affecting the distribution and transmission of malaria and NTDs, as well as the effectiveness of different intervention strategies in real-world settings.

This type of contextual knowledge is essential for developing locally tailored solutions that account for the unique social, cultural, and environmental factors that shape disease dynamics in different communities.

Furthermore, engaging health workers as active partners in research and decision-making processes can help to ensure that the solutions developed are not only scientifically sound but also feasible, acceptable, and sustainable in practice.

The involvement of frontline health workers in the co-creation of knowledge and interventions can lead to more effective, equitable, and context-specific solutions that are responsive to the needs and priorities of local communities.

References

Abimbola, S., & Pai, M. (2020). Will global health survive its decolonisation? The Lancet, 396(10263), 1627-1628.

Bhakuni, H., & Abimbola, S. (2021). Epistemic injustice in academic global health. The Lancet Global Health, 9(10), e1465-e1470.

Büyüm, A. M., Kenney, C., Koris, A., Mkumba, L., & Raveendran, Y. (2020). Decolonising global health: If not now, when? BMJ Global Health, 5(8), e003394.

Fricker, M. (2007). Epistemic injustice: Power and the ethics of knowing. Oxford University Press.

Klepac, P., et al., 2024. Climate change, malaria and neglected tropical diseases: a scoping review. Transactions of The Royal Society of Tropical Medicine and Hygiene. https://doi.org/10.1093/trstmh/trae026

77th World Health Assembly Climate and Health Resolution

How will we turn a climate change and health resolution at the World Health Assembly into local action?

Reda SadkiGlobal health

The Geneva Learning Foundation (TGLF) has developed a new model that could help address the urgent challenge of climate change impacts on health by empowering and connecting health workers who serve communities on the receiving end of those impacts.

This model leverages TGLF’s track record of facilitating large-scale peer learning networks to generate locally-grounded evidence, elevate community voices, and drive policy change.

A key strength of TGLF’s approach is its ability to rapidly connect diverse networks of health workers across geographic and health system boundaries.

For example, in March 2020, with support from the Bill and Melinda Gates Foundation, TGLF worked with a group of 600 of its alumni – primarily government staff working in local communities of Africa, Asia, and Latin America – to develop the Ideas Engine.

Within two weeks, the Ideas Engine had connected over 6,000 immunization staff from 90 countries to share strategies for maintaining essential services during the COVID-19 pandemic.

Within just 10 days, participants contributed 1,235 ideas and practices.

They then developed and implemented recovery plans, learning from and supporting each other. 

Within three months, over a third of participants reported successfully implementing their plans, informed by these crowdsourced insights.

This illustrates how peer learning – a tenet of TGLF’s model – can facilitate and accelerate problem-solving.

The Ideas Engine became a core component of TGLF’s model for turning knowledge into action, results, and impact.

TGLF has also demonstrated the model’s effectiveness in informing global health policy initiatives.

Working with the Wellcome Trust, TGLF mobilized – in the first year – over 8,000 health professionals from 99 low- and middle-income countries to take ownership of the goals of the Immunization Agenda 2030 (IA2030) strategy.

This participatory approach generated over 500,000 data points in just four months, providing IA2030 stakeholders with valuable, contextually-grounded evidence to inform decision-making.

Fostering a culture of continuous learning and adaptation among health workers lays the groundwork for a more resilient, equitable, and sustainable approach to global health in the face of accelerating climate change.

Applying this model to the climate and health nexus, TGLF supported 4,700 health workers from 68 countries in 2023 to share observations of changes in climate and health in the communities they serve.

Over 1,200 observations highlighted the diverse and severe consequences already being experienced.

See what we learned: Investing in the health workforce is vital to tackle climate change: A new report shares insights from over 1,200 on the frontline

This demonstrates the feasibility of rapidly generating a new kind of evidence base on local climate-health realities.

Furthermore, if we assume that each health worker could reduce the climate-related health burden for those they serve by a modest five percent, a million health workers connected to and learning from each other could make a significant dent in climate-attributable disease and death. 

This illustrates the model’s potential to achieve population-level impact, beyond sharing knowledge and strengthening capacity.

At Teach to Reach 10 on 20-21 June 2024, over 20,000 health workers will be sharing experience of their responses to the impacts of climate change on health. Learn more…

It is important to note that TGLF’s approach differs from models that work through health professional associations in several key ways.

First, it directly engages health workers across all levels of the health system, not just those in leadership positions.

Second, it focuses on peer learning and locally-led action, rather than top-down dissemination of information.

Third, it leverages digital technologies to connect health workers across geographies and hierarchies, enabling rapid exchange of insights and innovations at the point of need.

Finally, it embeds participatory and citizen science methods to ensure solutions are grounded in community needs and that everyone can contribute to climate and health science.

TGLF’s model offers a complementary pathway to address current global priorities of generating novel evidence on climate-health impacts in ways that are directly relevant and useful to communities facing them.

This model can help fill critical evidence gaps, identify locally-adapted solutions, and build momentum for transformative change.

TGLF’s track record in mobilizing collective intelligence to drive impact in global health crises suggest transferability to the climate and health agenda.

As the world grapples with the accelerating health threats posed by climate change, investing in health workers as agents of resilience has never been more urgent or important.

50 years of the Expanded Programme on Immunization

50 years of the Expanded Programme on Immunization

Reda SadkiGlobal health

In two articles published during the fiftieth year of the World Health Organization’s Expanded Programme on Immunization (EPI), Samarasekera and Shattock provide valuable insights into EPI’s remarkable impact on reducing childhood mortality and morbidity since its launch in 1974.

Shattock et al. present a detailed quantitative analysis of the lives saved and health gains attributed to vaccination.

They estimate that “since 1974, vaccination has averted 154 million deaths, including 146 million among children younger than 5 years of whom 101 million were infants younger than 1 year.” 

The authors further emphasize the long-term benefits of vaccination, noting that “for every death averted, 66 years of full health were gained on average, translating to 10.2 billion years of full health gained.”

These findings underscore the transformative impact of EPI on global health outcomes.

Bill Moss of the International Vaccines Access Center (IVAC) calls this “one of humankind’s greatest achievements”.

Inherent uncertainties based on the modeling approaches, data limitations and gaps, and challenges in attributing causality over a 50-year time horizon do not diminish their significance.

Fresh challenges

Samarasekera highlights several fresh challenges as EPI moves into its next 50 years:

  1. COVID-19 pandemic disruptions: The pandemic has led to 67 million children globally missing out on one or more vaccines. This has resulted in outbreaks of vaccine-preventable diseases, with measles outbreaks being reported in twice as many countries in 2023 compared to 2022. Due to pandemic disruption, many unimmunized children are now older than 2 years, requiring new approaches to reach them and prevent further outbreaks.
  2. Sustainable funding: Countries are facing challenges in sustaining funding for immunization programs due to debt crises, conflicts, and climate change.
  3. Improving collaboration during emergencies: There is a need for quicker access to vaccines and better coordination among stakeholders during humanitarian crises and outbreaks.
  4. Reaching the “last child”: Challenges persist in reaching children in conflict areas, active war zones, and those facing humanitarian crises, with immunization coverage in these settings being as low as 50-60%.

While both articles recognize the urgent need to address these setbacks and reach underserved populations, they tend to emphasize the role of global agencies and donors in driving progress.

For example, Samarasekera highlights the importance of initiatives like Gavi, the Vaccine Alliance, which was established in 2000 “to close the equity gap in access to vaccines,” and the Accelerated Development and Introduction Plans, which “expedited vaccine introduction in Gavi-supported countries.”

While global plans and funding have been – and remain – undoubtedly crucial, this begs three questions:

How to carry out such coordinated action and advocacy?

Who will do it?

What, if anything, should be different, compared to what was done in the past?

Can we assume deployment?

Both articles acknowledge that today’s challenges are different, and that immunization strategies should be grounded in local realities.

Samarasekera’s report suggests exploring ideas such as involving community health workers more effectively, introducing newly approved vaccines (e.g., for malaria), and innovating vaccine delivery methods (e.g., microarray patches, single-dose vaccines).

Ephrem T. Lemango, for example, emphasizes the role of health workers : “They are the most trusted source of information” for communities. “If we can skill these community health workers to vaccinate, provide them the required vaccines, then the likelihood of reaching the last child could be much more imminent”.

Samarasekera also quotes O’Brien, who stresses that “every government that has had backsliding needs a plan, and most governments have made a plan and are starting to deploy. We have a very narrow window to get this completed.” 

Neither article delves deeply into the specific strategies or mechanisms that connect global policy and funding to local action.

Can “deployment” be assumed?

There is wide recognition that local adaptation is a key challenge.

This is most obvious in zones of armed conflict or when faced with the breakdown of trust in vaccines or government

At the end of the day, it is health workers at the local levels that get the job of vaccination done.

They are also the first to see epidemic outbreaks and to recognize changes in community trust.

Does the future of vaccination require new ways of thinking and doing to adapt or invent strategies to lead to improved, sustained health outcomes?

Global advocacy for community health workers to be paid is undeniably important.

But paid to do what, how, and with what degree of recognition and support of their capacities, leadership, and expertise?

This is where learning from the Movement for Immunization Agenda 2030 (IA2030) may offer useful insights that complement the top-down, global-level efforts emphasized in the articles.

What is the Movement for Immunization Agenda 2030 (IA2030)?

Launched by the Geneva Learning Foundation in March 2022, the Movement is a global network of over 10,000 health workers from 99 countries who have pledged to work together to achieve the goals of the Immunization Agenda 2030, the global strategy adopted by the World Health Assembly in 2020.

Through peer learning and locally-led action, IA2030 members are sharing experiences, identifying root causes of immunization challenges, and implementing corrective actions tailored to their specific contexts.

What does that actually mean?

Wasnam Faye, a Senegalese midwife, moved the needle of vaccination coverage in a poor-performing remote health outpost from 8% to over 80%.

How did she do it?

At Teach to Reach, she met a doctor from the Democratic Republic of Congo who shared his EPI know-how with her, over WhatsApp.

She then invited and trained caregivers to become peer educators, also building on what she heard at Teach to Reach.

She then realized that she could speak about HPV vaccination for their daughters to mothers who came for cervical cancer screening.

In global health, individual case studies and lived experience are often dismissed as anecdotal evidence.

Each edition of Teach to Reach connects over 15,000 health workers, who share experience around their local challenges.

At that scale, the cumulative insights gained take us beyond anecdotes and enable us to document how change happens at the local levels.

Watch: Teach to Reach Insights Live with Orin Levine

Rethinking immunization’s learning culture: Capacity for change, innovation, and risk

To catch up and achieve the goals set for 2030, these articles suggest that a combination of increased funding, political commitment, and innovative strategies will be needed.

It is important to recognize that top-down control and directive management appear to have been key to how immunization programmes achieved impressive results in previous decades.

This explains why some EPI stakeholders may have an innovation challenge: why risk making changes or consider new models? 

Addressing these underlying issues may require strengthening learning culture.

“Learning culture” is a new concept in global health that provides the missing link between learning and performance.

It measures the capacity for change and the leadership to recognize and support that capacity over time.

That requires sustained financing, including specific funding required to test and scale new models and approaches. 

But who will risk funding new ways to tackle the challenges facing immunization programs, such as weak health systems, inadequate infrastructure, and community trust?

References

Faye, W., Jones, I., Mbuh, C., & Sadki, R. (2023). Wasnam Faye. Vaccine angels – Give us the opportunity and we can perform miracles. (IA2030 Case study 18) (1.0). The Geneva Learning Foundation. https://doi.org/10.5281/zenodo.7785244

Jones, I., Eller, K., Mbuh, C., Steed, I., & Sadki, R. (2024). Making connections at Teach to Reach 8 (IA2030 Listening and Learning Report 6) (1.0). Teach to Reach: Connect 8, Geneva, Switzerland. The Geneva Learning Foundation. https://doi.org/10.5281/zenodo.8398550

Jones, I., Sadki, R., Brooks, A., Gasse, F., Mbuh, C., Zha, M., Steed, I., Sequeira, J., Churchill, S., & Kovanovic, V. (2022). IA2030 Movement Year 1 report. Consultative engagement through a digitally enabled peer learning platform (1.0). The Geneva Learning Foundation. https://doi.org/10.5281/zenodo.7119648

Samarasekera, U., 2024. 50 years of the Expanded Programme on Immunization. The Lancet 403, 1971–1972. https://doi.org/10.1016/S0140-6736(24)01016-X

Shattock, A.J., et al. Contribution of vaccination to improved survival and health: modelling 50 years of the Expanded Programme on Immunization. The Lancet S014067362400850X. https://doi.org/10.1016/S0140-6736(24)00850-X

Climate change and health-Health workers on climate, community, and the urgent need for action

Climate change and health: Health workers on climate, community, and the urgent need for action

Reda SadkiGlobal health

As world leaders gathered for the COP28 climate conference, the Geneva Learning Foundation called for the insights of health workers on the frontlines of climate and health to be heard amidst the global dialogue.

Ahead of Teach to Reach 10, a new eyewitness report analyses 219 new insights shared by 122 health professionals – primarily those working in local communities across Africa, Asia and Latin America – to two critical questions: How is climate change affecting the health of the communities you serve right now? And what actions must world leaders take to help you protect the people in your care?

(Teach to Reach is a regular peer learning event. The tenth edition on 20-21 June 2024 is expected to gather over 20,000 community-based health workers to share experience of climate change impacts on health. Request your invitation here.)

Their answers paint a picture of the accelerating health crisis unfolding in the world’s most climate-vulnerable regions. Community nurses, doctors, midwives and public health officers detail how volatile weather patterns are driving up malnutrition, infectious disease, mental illness, and more – while simultaneously battering health systems and blocking patient access to care.

Yet woven throughout are also threads of resilience, ingenuity and hope. Health advocates are not just passively observing the impacts of climate change, but actively responding – often with scarce resources. From spearheading tree-planting initiatives to strengthening infectious disease surveillance to promoting climate literacy, they are innovating locally-tailored solutions.

Importantly, respondents emphasize that climate impacts cannot be viewed in isolation, but rather as one facet of the interlocking crises of environmental destruction, poverty, and health inequity. Their insights make clear that climate action and community health are two sides of the same coin – and that neither will be achieved without deep investment in local health workforces and systems.

Rooted in direct lived experience and charged with moral urgency, these frontline voices offer a stirring reminder that climate change is not some distant specter, but a life-and-death challenge already at the doorsteps of the global poor. As this new collection of insights implores, it’s high time their perspectives moved from the margins to the center of the climate debate.

As Charlotte Mbuh of The Geneva Learning Foundation explains: “We hope that the chorus of voices will grow to strengthen the case for  why and how investment in human resources for health is likely to be a ‘best buy’ for community-focused efforts to build the climate resilience of public health systems.”

Jones, I., Mbuh, C., Sadki, R., & Steed, I. (2024). Climate change and health: Health workers on climate, community, and the urgent need for action (1.0). The Geneva Learning Foundation. https://doi.org/10.5281/zenodo.11194918