Reframing how we think about impact of information on individuals

Reframing how we think about impact of information on individuals

I've been recently researching and studying models of information environment and how it impacts the delivery of health information, programmes and services to different populations. What we know is that we lack metrics and measures that would inform public health action in relation to health information and the information environment.

In past several years, we convened several WHO infodemic management conferences that specifically were advancing the groundwork towards actionable metrics and measures. We discussed models that helped us think through the interlinkages between the information environment, individual-level effects, health system and societal effects of information and infodemics. But there's a lot of work that still needs to be done, especially in developing metrics at the community, health system and societal levels.

The exposome: environment - exposure - risk factors pulled together

So one way to think about the information ecosystems, exposure and risk factors is the exposome approach that has been developed in environmental health.

Here's an example of exposome research that got me thinking: Air pollution, smoking and built environment are associated with an increase risk of childhood obesity. The?exposome approach has changed the way we investigate?how environmental exposure to a hazard affects health. Instead of analysing the possible health consequences of, exposome studies consider?many different exposures a person faces altogether. This approach takes into account many elements we are exposed to through our diet, lifestyle and the environment where we live.

Exposome research is a field in environmental health that aims to understand the totality of environmental exposures an individual experiences throughout their lifetime and how those exposures interact with their genetics to influence health outcomes. The exposome concept was introduced as a counterpart to the genome, recognizing that environmental factors play a significant role in human health.

The exposome encompasses all external factors to which an individual is exposed, including chemical pollutants, biological agents, lifestyle factors, psychosocial stressors, and socioeconomic conditions. It takes into account both acute and chronic exposures, as well as the timing, duration, intensity, and frequency of those exposures. By studying the exposome, researchers seek to unravel the complex interactions between environmental factors and human health, moving beyond traditional approaches that focus primarily on single exposures or individual genes.

How does the exposome approach map onto the information environment and exposure to the information?

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So if we do a quick mapping of the interplay between the built information environment, the exposure/overload to information, and the risk factors/information-seeking behaviors, we can explain and understand this interplay a lot better:

  1. Information Environment: The information environment refers to the characteristics of the digital platforms, online spaces, and communication channels through which information is accessed and disseminated. This includes factors such as platform use, moderation policies, user experience, and digital inequities. The information environment shapes the availability and accessibility of information and influences individuals' exposure to different sources of information. For example, the algorithms used by social media platforms can impact the content that users are exposed to, potentially creating filter bubbles or echo chambers where individuals are primarily exposed to information that aligns with their existing beliefs or interests. Digital inequities, such as disparities in internet access or cost or platform, can further influence the availability and reach of information, potentially leading to unequal exposures across different populations.
  2. Information Overload and Exposure to Information: In the digital age, individuals can be exposed to a vast amount of information, which can lead to information overload. Exposure to information overload can have implications for individuals' health and well-being. Within the context of exposure, it is important to consider the types of information individuals are exposed to. This includes questions and concerns that go unaddressed, low-quality information, narratives, misinformation, and disinformation. Exposure to unaddressed concerns or misinformation can impact individuals' perceptions, decision-making, and behavior. It can also contribute to the spread of false or misleading information, potentially leading to negative health outcomes. Therefore, understanding the mix, quality, accuracy, and trustworthiness of the information individuals are exposed to is crucial in evaluating their overall exposure.
  3. Risk Factors and Information-seeking Behaviors: The third level involves considering the risk factors and information-seeking behaviors of individuals. Risk factors can include previous experiences, social determinants of health, language and medium preferences, health, information, science and digital literacy levels, mental health status, and trust in health information, services, and workers. These factors shape how individuals seek and engage with health information. For example, individuals with low health, science, information or digital literacy may have limited access to accurate and reliable information, which can impact their exposure to health-related information. Mental health status and trust in health information or services can also influence individuals' information-seeking behaviors and their susceptibility to misinformation or disinformation. Understanding these factors is important in assessing the differential exposures individuals may have based on their unique circumstances and needs.

Overall, these three levels interact and influence each other. The information environment sets the stage for individuals' exposure to information, while information overload and the quality of information they encounter impact their overall exposure. Simultaneously, individual risk factors and information-seeking behaviors shape the types of information individuals are exposed to and how they interpret and use that information. Considering these interactions can provide a more comprehensive understanding of how individuals are exposed to information and the potential implications for their health and well-being.

I'd be curious to hear your thoughts - let me know if you have anything to add or modify in this approach.

Why should we care about this reframing?

  • Long exposure to seemingly benign narratives can cause more harm to individuals and communities than a single outrageous piece of circulating misinformation. Most of our metrics take into account volume of "bad" information, but don't look at information exposure or information-seeking behaviors of individuals, or the built information environment they live in. For example, we may notice high engagement and circulation of a misinformation narrative online that claims that the new booster vaccine causes infertility in men. But we might miss narratives that have continued to appear at lower volume that point out questions men have about the safety of vaccines for them, since there are not many vaccines that target adult men.
  • We are misunderstanding what causes most harm from infodemics - it's the questions, concerns and information voids that go unaddressed. We have been experiencing an overemphasis on fact-checking and debunking every rumor in relation to health. We know that only 5-20% of information that was circulating about COVID-19 during the pandemic was mis/disinformation. The rest were questions, concerns, and information voids when people were actively searching for information but not finding it. Instead of trying to correct health misinformation when it is already circulating widely, health authorities can have a much bigger impact in understanding and addressing people's concerns and questions they have on health matters, and ensuring that they can find health information when they are looking for it.
  • The built environment matters in information seeking. In digital context, if we ask a mobile phone voice assistant a health-related question, we will get a different answer and suggested links to resources than if we asked a search engine, a bulletin board, or a chatbot. We can not pretend that the built environment, AI-driven assistance to users, and content moderation do not affect exposure and access to information.
  • Health information inequalities are a barrier to health information use. We cannot assume that everyone has equal access to all of the health information available or produced for their community, the disease they are experiencing, or identity. There are structural, societal and individual factors that impact how a person will search for, access, use and act on health information.

Elisabeth Wilhelm

Integrating Information, Behavior and Public Health Insights for Action

1 年
Alejandro Posada

Systems Change Research Fellow @ALNAP | Locally Led Response & Accountability | Political Economy | Development & Humanitarian | Mis & Disinformation | Inequality | University of Oxford & Chevening Alumni

1 年

Fascinating take, Tina. Thank you for sharing. I think it aligns nicely with the way we are approaching information ecosystems at Rooted in Trust in Internews. Some thoughts came to mind. Through our work with at-risk and minority communities, we have identified that the real complexity lies in encountering more and more communities facing a combination of information overload and a lack of information tailored to their specific, contextual needs. Together, these factors can exacerbate the impacts of mistrust in health-related information. The second point is that we need more research on risk factors, particularly how social determinants impact the way people relate to health information. We have an upcoming piece that focuses on inequity-driven mistrust, where we explore how trust in health information for at-risk populations in the Global South is influenced by multidimensional inequalities often entrenched in postcolonial structures of knowledge production, unequal health systems, decontextualized health responses, and/or disproportionate distribution of medical supplies. I'd be happy to share it with you once it is out.

Jelena Kalinic

President at CSO "Science and the world", founder of Vakcine.ba& Nauka govori, Biologist, award winning Science/Health journalist&communicator, MA in literature and film

1 年

Would you be so kind to allow me to translate this in Bosnian/Serbian/Croatian/Montenegrin and publish it on my other website (Quantum of Science/Science speaks)?

Jennifer Bueno

Especialista en Alfabetización en Salud Digital | Fortaleciendo la Salud a través de la Comunicación Humana Ms. Com-Ed | Ph.D. (C) & Becaria de investigación #eHealthLiteracy #InfodemicManager #DigitalHealthLiteracy

1 年

This post made me want to be more active on social media again! As a researcher in women's digital health literacy, I've found Social-cognitive Theory, Cognitive Load Theory (particularly interesting), and IBM-HAPA to be my holy trinity of models. Understanding the information landscape requires a flexible and creative mindset, just like how we, as speech-language pathologists, approach our cases of communication disorders. That's why I returned to my human communication-language-cognition roots. It has been essential in navigating this complex field. The exposome approach analogy you mentioned sheds light on the interplay between the built environment, information overload, and individual factors. I agree that addressing unaddressed concerns and information voids is crucial beyond debunking misinformation. However, if misunderstood, the premise can lead to producing more and more content. I'm committed to empowering individuals with tailored interventions and promoting media literacy skills in this digital age to rebalance the scales between information and literacy. We need to adjust the focus and put more emphasis on people and less on the machines. As always, thank you for sharing your valuable insights!

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