• The digital divide worsens health inequalities as users who struggle to access, understand, and use digital health tools are excluded from these essential resources.
• Community-led digital literacy programs have the potential to drive confidence among people with limited technological skills and build new social norms around digital health adoption.
• Behavioral design strategies can align digital health platforms with how people think and behave, making these tools more approachable and less cognitively demanding.
• Trust-focused messaging is key to reducing the ambiguity and perceived risk associated with digital health tools to encourage adoption and skills development.

As modern healthcare becomes increasingly technology-driven, digital health literacy has the potential to significantly improve global health outcomes. From empowering individuals to self-manage their medical care to serving as a “social vaccine” against the spread of disease, digital health literacy allows people to find and apply information effectively for the good of themselves and society at large.^2,3 Public health experts have even deemed digital literacy to be a “super social determinant of health,” signifying the critical role it plays in all the other social conditions that affect health outcomes—including educational attainment, economic stability, and access to safety net programs like housing support and food banks.⁴

Unfortunately, there is a persistent gap between those who have access to digital technologies—such as internet connectivity, computers, and smartphones—and those who do not. This gap, known as the digital divide, amplifies health inequalities among low-income groups and populations living in remote areas that lack reliable access to the internet or digital devices.⁵ In the United States, more than one in six people in poverty have no internet at home.⁷ What’s more, a quarter of adults from low-income households don’t own a smartphone, and 41% lack a laptop or desktop computer.²⁹ The digital divide is an even bigger issue in regions of the world with historically limited internet access, like in Africa, where only 36% of the population has broadband internet.⁸

Importantly, simply improving physical access to technology is not enough to bridge this gap. Language barriers, educational limitations, and lack of confidence can reduce adoption, even when tools are made readily available. In Africa, issues rooted in limited internet access are further exacerbated by widespread inadequacies in digital literacy.⁸ Even in Canada, where the vast majority have access to the internet, 46% feel that they don’t have the digital literacy skills to fully utilize digital health tools.⁹ 

Around the world, those with limited tech experience often resist adopting digital health tools, struggle to use them effectively, and may even distrust them altogether. To ensure full, equitable use of new technologies, people need to see them as accessible, inclusive, valuable, and trustworthy.⁶ In the following sections, we’ll be diving into some of the promising behavioral science interventions that can help us change perceptions about digital health technology and promote the development of technological skills.

A common priority among organizations looking to increase digital health literacy is improving access to digital tools. But this is only part of the challenge. Equally important is ensuring potential users know what digital tools are available and feel confident operating them. This means looking closely at the psychological and behavioral factors that influence digital health adoption, especially among groups that are used to engaging with the healthcare system via traditional means like simple phone calls and in-person visits.

A useful framework for understanding these barriers is the theory of mind (ToM), which refers to the functions of the human mind that allow us to attribute mental states to others.³⁰ In the context of digital health, ToM refers to the ability for digital health systems to understand the thoughts, beliefs, and emotions of users, acknowledging that their needs and abilities may diverge from those of policy developers or platform designers. According to the United Nations, digital spaces tend to reflect the biases and motivations of those with the most opportunities and access to the internet, so they’re often designed and developed to prioritize certain populations, such as urban over rural and rich over poor.⁶ As a result, these spaces often fail to accommodate the unique mental states of individuals who are less familiar with technology.

Let’s look at some of the cognitive biases that can shape how users interact with new technology to better understand why many are hesitant about digital health adoption, even as access improves.

Cognitive Biases and Behavioral Factors Reduce Digital Health Adoption

The barriers to digital health adoption aren’t just physical or financial—they’re deeply rooted in behavioral factors that shape how people interact with technology.¹⁰ For example, many people with limited digital experience feel a sense of information overload when confronted with unfamiliar online tools. As a result, these individuals might avoid using technology altogether rather than risk making mistakes, like accidentally deleting an important health record or canceling an upcoming appointment.

Social norms also play a role in digital health adoption. One study exploring technology uptake among older adults in the U.S. and China found that perceptions about the widespread use of digital health technologies influenced user adoption of such tools.³¹ This research also revealed that social norms around the use of health technology made older adults feel more confident in their own technical abilities. Conversely, in communities where digital health tools are not widely adopted—such as rural areas with limited internet access—individuals might feel that these platforms are not designed for them, even as internet connectivity becomes increasingly available. 

Users can also resist technology simply because it’s different from what they’re used to. This resistance to change often stems from the status quo bias, which might cause individuals to stick with traditional healthcare interactions and reject new tools, even if these tools could make their lives easier. For instance, if a patient needs to request a medication refill, they might opt to visit the doctor face-to-face instead of using telemedicine services, which could save them time and travel costs.

Previous struggles with technology can further exacerbate feelings of hesitation about digital health tools. Say someone had a frustrating experience the first time they tried to download their medical records. These negative feelings can become an anchor through which they evaluate all digital health tools and services. Even if they encounter user-friendly patient platforms in the future, their initial belief that “this is too complicated” can remain a barrier to adoption, prompting them to stick with traditional methods like requesting a fax or visiting the clinic in person for paper print-outs.

These cognitive barriers highlight a need to facilitate positive, confidence-building experiences to encourage the adoption of digital health. How can we do this? One comprehensive study on digital literacy in Kentucky revealed a key need for community-level digital skills training programs to increase people’s comfort with online tools.¹¹ Let’s explore how digital literacy programs like these might work to improve health technology adoption alongside efforts to expand internet connectivity to underserved communities. 

Community-based digital health literacy programs can empower individuals to make use of available digital resources by providing training, support, and resources to those who may be unfamiliar with these tools. By using locals and peers as facilitators, these programs aim to meet people where they are with peers who understand them, reducing the intimidation factor that comes with embracing new and potentially confusing technology. 

Digital Health Literacy Programs Around the World

What exactly might these programs look like? One excellent example is the Digital Outreach for Obtaining Resources and Skills (DOORs) program, a nationwide psychosocial program aimed at improving digital literacy through interactive, hands-on learning.¹² The program primarily teaches people how to use their smartphones to achieve their wellness goals and connect with formal health services. It has been successfully adopted by several community-led and peer-support initiatives across the United States.

Digital skills programs have also been effective at improving digital health literacy among community health workers (CHWs) in Sub-Saharan Africa, an area where over 50% of healthcare workers lack adequate digital health training.¹³ As more CHWs embrace these digital tools, patients too are likely to feel more comfortable using digital health services, as many locals currently worry about the reliability of these tools and the quality of care that can be delivered via digital interventions.¹³ Addressing these concerns through public awareness is crucial, and modeling their use by getting technology into the hands of CHWs is an excellent way to build trust and encourage widespread adoption.

Social Cognitive Theory and the Adoption of Technology

The success of these programs lies partly in their ability to build self-efficacy, or the belief that one is capable of performing the necessary behavior to accomplish their goals. Self-efficacy is a core component of Social Cognitive Theory (SCT), which explains how personal, behavioral, and environmental factors play a role in learning. In the context of digital health adoption, SCT suggests that one’s confidence in their ability to use digital tools is crucial for successful behavior change. Not only that, but environmental factors—like social norms and cultural influences—can go a long way toward changing how people think about technology, which is exactly what makes peer-led programs so effective. As a result, community-led initiatives have the potential to improve digital health literacy and encourage technology adoption among systemically underserved groups, particularly in low-income communities, rural areas, and senior care centers.

Part of making health platforms accessible means ensuring they are easy to navigate and understand, especially if we expect people to effectively apply digital health information to make impactful decisions about their healthcare needs. While many digital health tools are user-friendly, most are designed by experts with a technical mindset, which can make them complex and difficult to navigate.¹⁴ Recently, there has been a push for designers to seek input from pharmaceutical companies and clinicians in the development of digital health technologies, which has helped introduce more functional technologies in healthcare settings.¹⁴ However, these tools are still largely designed for patients’ perceived needs and rarely involve actual patients in the design process. This often results in an unintuitive digital experience for the end user. Even if you consider yourself tech-savvy, you’ve likely encountered a few maddening telehealth platforms and patient portals that make you want to toss your laptop out the window. 

This familiar frustration with complex user interfaces can be explored through cognitive load theory, which suggests that the human brain has a limited capacity to process information. Encountering too much information all at once can create mental strain, which can impact our decision-making, disrupt our focus, and hurt our overall performance. It’s easy, then, to see how overly complex apps can overwhelm users and interfere with the development of digital skills. Not only that, but people with lower overall health literacy tend to require more cognitive capacity when processing health information.16 This suggests that users who lack both digital literacy and health literacy could be even more likely to experience mental fatigue, especially when facing confusing interfaces loaded with complicated charts, health data, and technical jargon. 

Jargon, common in healthcare communication, often finds its way onto health platforms, adding another layer of confusion for users. For instance, words like “hypertension” instead of “high blood pressure” or “benign” instead of “not harmful” can cause users to misinterpret information in their online health records, leading to unnecessary anxiety and leaving users unsure of their next steps. Research suggests that the use of jargon in sharing complex information can compound feelings of overwhelm, make people feel incapable of understanding information, and reduce the likelihood that people will adopt digital tools.¹⁷ Complex user interfaces and jargon-heavy reports are even more likely to cause frustration among individuals with visual or cognitive impairments—after all, imagine trying to book an optometry appointment when you can’t read the screen! The same goes for people who don’t speak the language in which the app is written. Overall, including medical jargon in an online health portal is a sure way to exclude the very patients intended to benefit from improved healthcare accessibility offered by digital solutions.

Since many healthcare providers are well aware of these usability problems, they’re sometimes hesitant to recommend digital health tools—like wearable devices or telemedicine platforms—to users with limited digital literacy or different accessibility requirements, even though these have the potential to enhance patient involvement and improve their overall quality of care.³² Turns out, this reluctance is justified: a 2020 survey found that 28% of consumers have switched healthcare providers because of a poor digital experience.¹⁵ Without addressing issues with usability, digital health platforms risk alienating a large portion of patients, particularly those with limited digital skills or health literacy. Patients who feel excluded or overwhelmed often avoid these tools altogether, losing access to convenient and timely care while missing out on opportunities to build their digital confidence and take a more active role in their health decisions.

People with low digital literacy are more likely to adopt interfaces that are easy to use.¹⁴ So, how do we go about building usable tools? Jakob Nielsen's 10 usability heuristics are an excellent place to start. These are broad rules of thumb for designing user interfaces that align with how humans actually think and behave. For example, Nielsen stresses that systems should communicate with users in familiar, real-world language, provide “emergency exits” to allow users to back out of unintended actions, and minimize cognitive load by making options visible and easily accessible. Today, Nielsen’s original usability heuristics have evolved to incorporate newer concepts like nudging and personalization to address users’ evolving expectations, which can be even more valuable for encouraging digital health adoption by those with limited tech experience. Let’s look at these behavior-based design strategies and their potential applications in digital healthcare.

Designing Digital Tools that Resonate with Patients

Research on digital health literacy and treatment adherence has revealed that patients are more likely to engage in recommended health behaviors—like activities that lower their blood pressure or dietary changes that can help with certain health conditions—when they receive text messages with an element of personalization.¹⁴ Conversely, patients’ motivation to engage in digital health communication declines when they feel that the messaging is overly generic and unrelatable. But there’s more to creating user-relevant tools than personalizing the messaging they receive.

Patient-driven solutions—as opposed to digital tools designed exclusively by researchers or clinicians—have the power to personalize the entire user experience. For example, the Nightscout Project is a patient-led DIY mobile technology system developed to help patients manage diabetes. After its launch in 2014, the platform rapidly scaled to serve a global population, suggesting that a bottom-up approach driven by patient needs is vital to creating effective and widely adopted digital health tools.¹⁸

Driving Engagement and Action with Precision Nudging

Nudging is a behavioral science concept that involves subtly influencing people’s decisions without restricting their freedom of choice. In the context of digital health tools, nudges might take the form of notifications, text message reminders, or even pre-selected default options on patient portals that encourage users to take a specific action, like viewing their blood test results or booking an appointment. Nudging has the potential to significantly boost the adoption of digital health tools while at the same time helping people apply digital information to improve their own health outcomes. Reducing friction by directing people toward certain actions can be particularly beneficial when people are facing uncertainty, cognitive overload, low confidence, or low motivation. 

Nudging can become even more powerful when combined with AI algorithms. Precision nudging, for example, is a targeted personalization intervention that leverages AI to optimize nudge messages so they address patient-specific barriers to digital health engagement.¹⁹ What’s more, these precision nudge messages are strategically designed by behavioral science experts to address the specific psychological and social factors that influence behavior, especially among traditionally underserved groups. For instance, one study explored the use of precision nudging to encourage women to attend a mammogram screening.¹⁹ Amazingly, about the same number of women from varying ages, races, educational backgrounds, and household income levels ended up completing their overdue mammograms, suggesting that this strategy could be highly valuable for reducing health disparities and fostering equitable outcomes.

Patients with low digital health literacy often lack trust in digital health tools, which presents yet another significant barrier to engaging with and benefiting from these technologies.²⁰ This skepticism is often rooted in fears about security issues and privacy concerns.¹⁴ After all, digital health platforms store and use highly sensitive personal data, so users who don’t fully understand how these systems work are understandably hesitant to engage with them. In contrast, users who are more familiar with online security measures and feel confident navigating online platforms safely tend to feel more in control of their data, making them less likely to perceive digital health platforms as unnecessarily risky. Let’s explore some of the behavioral biases that influence how people perceive the risks associated with digital health tools.

When Privacy Fears Outweigh Perceived Benefits

Incidents of high-profile data breaches, like large health system hacks, can cause people to overestimate the risk of using digital health tools. Why? The availability heuristic is a cognitive shortcut that causes us to judge the likelihood of events based on how easily we can recall similar examples. Thanks to the availability bias, hearing about a data breach in one digital health system can make people jump to the conclusion that all digital health apps are insecure. One respondent from the aforementioned Kentucky survey sums it up nicely: “Scams, you gotta watch out for scams. Hackers. Oh, Lord, you’re getting hacked.”¹¹

To compound the effect of the availability bias, the perceived risk associated with potential data breaches is often greater than the perceived gains associated with using digital health tools. This bias, known as loss aversion, might explain why some people fear losing their privacy more than they value the benefits of digital tools. In fact, research shows that 81% of Americans believe the potential risks of data collection outweigh the benefits.²¹  When users perceive high risks with sharing their data—while feeling that they personally benefit very little from company data collection—they’re more likely to prioritize data security concerns over the potential benefits of digital health platforms or services.

How Uncertainty Drives Digital Reluctance

Another bias driving skepticism around digital health platforms is the ambiguity effect, which details our distaste for uncertainty and why we often choose options that feel more predictable and familiar. In the context of digital health literacy, people who don’t fully understand how digital tools handle data might gravitate toward traditional, offline healthcare methods, such as calling the doctor instead of using the patient portal. 

Unfortunately, current solutions to satisfy people’s cybersecurity concerns often fall short. Privacy policies and terms of service are typically generic, long-winded, and rarely read in full—only about one in five adults report that they often read a company’s privacy policy before agreeing to it.²¹ What’s more, just 6% of adults say they understand a great deal about what companies do with the data they collect. It’s clear that the vast majority of users don’t understand how data is handled, and this makes them wary about using digital health platforms that require their personal information. While it’s best practice to be vigilant when using online tools, an elevated perception of risk and uncertainty can deter those with low digital literacy from engaging with health technologies, presenting a significant barrier to learning and skill development. 

How can we build trust in digital health tools? First, platforms need to provide clear communication about how data is used and stored. The World Economic Forum stresses the importance of designing digital tools with transparency in mind, using plain, non-technical language so users clearly understand why their data is being collected and how it is used.²² Diagrams and images can be valuable for helping people visualize how their data is protected, especially when using cutting-edge privacy-enhancing technologies that can be difficult to explain to a lay audience. Beyond this, it’s important to give users control over how their data is used. This means offering clear opt-in and opt-out choices for data sharing and using default settings that prioritize privacy. 

Using Authority and Social Proof to Address Cybersecurity Concerns

Endorsements from professionals and health organizations can go a step further to build trust in online tools, as research suggests that consumers are more likely to trust services that are recommended by experts.²³ This is known as the authority bias, which explains how we are more likely to accept the opinions and judgments of authority figures. Since people are also influenced by the opinions of their peers, social proof alongside expert endorsements could positively impact people’s willingness to engage with digital health tools. Some ways to do this might include partnering with trusted medical professionals to recommend digital platforms, displaying user testimonials within apps, and featuring logos from regulatory bodies. Incorporating peer-sharing features and community forums can also give the impression that other people trust and use the platform.

Why Users Trust Apple Health with Their Data

Apple Health is an excellent case study of a trustworthy health tool. In fact, informal polls suggest that users tend to trust Apple with their health data more than many other digital health tools.²⁴ Part of the reason for this is that Apple frequently assures users that it will never sell their health data to advertisers. This is the mere exposure effect at work, which suggests that repeatedly encountering the same information builds a sense of comfort and familiarity, reinforcing trust over time.

Apple is also transparent about storing personal data directly on users’ phones, ensuring data is encrypted when not in use, and requiring that users grant access to third-party apps that wish to use this data. The Apple Health app itself provides a clear breakdown of the steps the company takes to protect your privacy, including reassurances like “your information is encrypted and you can stop sharing at any time.” It also helps that Apple presents users with beautiful visualizations of their own data, increasing the perceived value to users and countering the potential risks of giving up their personal information.

Increasing digital health literacy is an incredibly complex undertaking. While efforts to expand access, offer training, improve usability, and address security concerns can go a long way to help people extract value from these tools, these are not quick-fix solutions. Persistent systemic issues like income inequality and lack of infrastructure can severely undermine efforts to boost digital literacy, especially in areas of the world where these problems are the norm rather than the exception. 

As such, efforts to increase digital health literacy among individuals must go hand in hand with broader policies to tackle disparities in access. For example, many American states have implemented strategic broadband plans to improve access to the internet while incentivizing internet service providers to make plans more affordable.²⁸ Moves like this are crucial for deploying digital health literacy solutions at scale. 

At the same time, it’s important that these technologies foster trust in healthcare, especially among groups that are already resistant to medical information or health interventions. Efforts to increase digital health literacy should encourage the participation of these groups rather than give them new reasons to distrust or resist modern healthcare.

So far, small-scale solutions like community-led training have been effective at increasing people’s comfort with health technology, and may also be the best way to combat skepticism toward contemporary medicine. The success of these pioneering programs suggests that incremental improvements are a step in the right direction for reducing the digital divide and ensuring equal access to valuable digital health information.

As virtual tools become increasingly integrated into healthcare systems, improving digital health literacy is now more essential than ever. Addressing challenges with usability, trust, and disparities in access requires a multifaceted approach. Not only should people be able to seek out and find health information online, but they also need the skills to understand, evaluate, and apply this information to make better decisions about their well-being. By establishing community-led digital literacy programs, using behavioral design to align digital tools with how people naturally think and behave, and building trust in online health tools with transparent messaging, we can empower individuals to take full advantage of the incredible tools at their disposal and play an active role in their own healthcare.

The benefits of digital health literacy extend beyond individual empowerment. It has the potential to expand access to specialized care, reduce healthcare wait times, provide better chronic illness management, and enhance disease surveillance.²⁵ Fortunately, many governments have acknowledged the pressing need to address the digital divide and encourage widespread adoption of these technologies. For instance, the Canadian government is investing $17.6 million to support non-profit organizations in teaching digital literacy skills in communities across the country.²⁶ Similarly, the Ukrainian government has launched the Diia.Digital national digital education platform, the EU has set a target to ensure that 80% of adults have basic digital literacy skills by 2030, and Ghana has launched a $212 million “eTransform” program to increase training, mentoring, and access to technologies in partnership with World Bank’s Digital Economy for Africa initiative.²⁷

As organizations of all shapes and sizes work to improve global digital health literacy, insights from behavioral science can be incredibly valuable for ensuring initiatives resonate with the individuals they aim to help. At The Decision Lab, we have extensive experience applying behavioral science at the intersection of technology and healthcare, leveraging decision-making insights to encourage digital adoption and foster health and well-being through scalable, people-first programs. Let’s work together to translate insights into impact.

Bridging the digital divide: How can we keep healthcare accessible in the digital age? 

Digital health literacy has become a crucial factor in determining health outcomes. However, individuals with limited access to technology or digital skills struggle to fully participate in modern healthcare systems. This article explores how the growing digital divide is creating new challenges for ensuring equitable access to medical care, including who is most at risk and the barriers they face.

Your Phone is the Future of Healthcare: Interview with a Behavioral Scientist

Mobile technology has the potential to improve access to health information and counter some of the most significant biases that prevent people from playing an active role in their own care. In an interview with behavioral science expert Dr. Sarah Watters, we explore how mobile health technology can bridge gaps in healthcare by providing context-relevant solutions for the management of chronic conditions. 

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