Digital cybersecurity programs overlook older adults, leaving critical vulnerability gap

The study found that nearly all digital learning formats become less appealing as age increases. Older adults show a consistent decline in interest across almost every type of online cybersecurity tool examined, including interactive modules, gamified learning platforms, VR and AR simulations and mobile-based experiences. The sharpest decline occurs in areas that require rapid navigation, complex interaction or immersive engagement, features that dominate many of the modern cybersecurity training tools currently promoted by industry and government.

Older adults, who face some of the highest financial risks from cybercrime, show the lowest interest in many of the digital learning tools currently used to teach cybersecurity, according to a new U.S.-based study. The findings raise urgent questions about whether existing digital education strategies are adequately serving the populations most vulnerable to scams, identity theft and online fraud.

The study, Designing for Life: A Socioeconomic View of Digital Learning Preferences in Cybersecurity, with Emphasis on Older Adults, examines how age, connectivity, subjective well-being and socioeconomic conditions shape online learning preferences.

The research, based on a nationally representative survey of 1,113 U.S. adults, challenges the belief that designing digital courses for cybersecurity resilience simply requires more sophisticated technology, more interactive design or more narrative-based content. Instead, the study demonstrates that adults’ learning preferences are tightly tied to structural and psychosocial realities that influence their confidence, willingness and ability to engage with digital tools. 

The steepest drop in preference for most cybersecurity learning tools

The study found that nearly all digital learning formats become less appealing as age increases. Older adults show a consistent decline in interest across almost every type of online cybersecurity tool examined, including interactive modules, gamified learning platforms, VR and AR simulations and mobile-based experiences. The sharpest decline occurs in areas that require rapid navigation, complex interaction or immersive engagement, features that dominate many of the modern cybersecurity training tools currently promoted by industry and government.

This does not mean that older adults reject digital cybersecurity learning altogether. Instead, the data show that learning tools must align with usability expectations and cognitive preferences shaped by aging. The commonly used assumption that older adults prefer actor-based scam videos did not hold. While these videos did not show an age-based decline in preference, they also did not stand out as uniquely appealing to older learners. They were simply accessible across age groups, suggesting they fill a neutral space rather than a targeted advantage.

The findings carry major implications for cybersecurity policy, especially for programs aimed at protecting seniors from fraud. Older adults lose more money per scam incident than any other age group, yet their preferred learning methods diverge sharply from the technological direction of many cybersecurity education providers. Tools that assume comfort with high interactivity, rapid navigation, or gamified feedback risk alienating the very learners who most need protection. The study calls for greater attention to cognitive load, clarity of purpose and ease of use, core principles of aging-friendly instructional design.

Well-being, education and internet reliability strongly shape learning engagement

The study brings to light several socioeconomic and psychosocial variables that profoundly influence digital learning preferences. One of the strongest predictors is subjective well-being. Adults with higher levels of well-being express greater interest in nearly all forms of online learning, including immersive formats such as VR and AR. The effect is nonlinear, suggesting that improvements in well-being enhance engagement but the rate of increase slows as well-being rises. This pattern signals the interdependence between emotional health and digital learning readiness.

Education is another major factor. Adults with higher levels of educational attainment show more openness to technologically demanding formats, likely because they possess stronger digital literacy and greater comfort navigating online platforms. However, this relationship is not entirely linear: the benefit of additional education appears to flatten or even reverse when technological complexity becomes overwhelming. This reinforces the study’s argument that design, not demographics, determines learning engagement.

Income, surprisingly, plays only a subtle role. The authors note that while income has a small positive effect on preferences for VR and AR learning tools, it does not strongly predict engagement with most other formats. This finding challenges stereotypes that financial resources alone determine digital learning capability. Instead, it suggests that psychological comfort and digital familiarity matter more than purchasing power.

The strongest structural predictor of all is high-speed internet quality. Individuals with reliable, stable connectivity express higher interest in nearly every digital tool examined. This demonstrates that the digital divide is not merely about device ownership but about the quality of the online experience. Unstable connections, long loading times and streaming interruptions undermine learners’ willingness to engage, disproportionately affecting rural communities, low-income households and older adults who may rely on outdated devices.

Together, these findings show that cybersecurity learning engagement depends on a blend of emotional readiness, educational background and infrastructural access. Without addressing these factors, even the most sophisticated online tools will struggle to reach the audiences most at risk.

Cybersecurity education must shift toward accessibility, purpose and adaptive design

The study calls for a major redesign of cybersecurity education frameworks to better reflect the learning needs of diverse age groups, especially older adults. The authors argue that digital learning tools must be structured around clarity, low cognitive load and well-signaled purpose. Older adults benefit from learning environments that reduce multitasking demands, limit rapid visual changes and provide predictable navigation paths. Tools must also offer layered instruction rather than overwhelming users with advanced features or multiple parallel tasks.

The research warns against assuming that narrative content alone will bridge generational gaps. Actor-based scam videos, often considered an easy default for senior learning, did not earn special preference among older respondents. This suggests that senior audiences require more intentional instructional design, including stronger cues about personal relevance, opportunities for repetition, and step-by-step guidance that reinforces learning retention.

The authors also urge policymakers and cybersecurity educators to rethink gamification strategies. While gamified tools are widely used to capture attention and improve retention, the study shows that these methods disproportionately appeal to younger adults and those with higher digital literacy. For older adults, gamification can increase cognitive strain and reduce confidence.

A key recommendation is the integration of adaptive design features that tailor pacing, complexity and feedback to the learner. AI-enabled personalization could play a role here, provided tools remain transparent, manageable and accessible. Another recommendation is the use of hybrid learning models that incorporate both digital and offline components, allowing learners with lower digital confidence to build foundational skills in controlled, supportive environments.

The findings highlight the urgent need for public institutions, community programs and private-sector cybersecurity initiatives to rethink their outreach strategies. Older adults are not resistant to cybersecurity learning, they are resistant to poorly designed tools that fail to account for age-related needs, limited internet access or low digital confidence.