Digital health skills drive adoption of AI wearables for self-medication

The authors note that over-the-counter drugs represent a large share of worldwide medicine use, and many users treat common conditions without consulting physicians. While this autonomy offers convenience and reduces healthcare burdens, it carries risks: incorrect dosing, drug interactions, and repeated misuse can lead to complications, hospitalizations or long-term consequences.

A new study has found that people with stronger digital health skills are significantly more likely to use artificial intelligence–assisted wearable systems to help manage self-medication. The findings suggest that the rapid expansion of consumer healthcare technology will increasingly depend on users’ ability to understand and navigate digital health information, setting the stage for a wider transformation in personal health management.

The peer-reviewed study, “eHealth Literacy, Attitudes, and Willingness to Use an Artificial Intelligence-Assisted Wearable OTC-EHR System for Self-Medication: An Empirical Study Exploring AI Interventions,” published in Systems, examines how digital health competency shapes trust, attitudes and adoption behavior toward a proposed wearable system that integrates Over-the-Counter Electronic Health Records (OTC-EHR) with smartwatch-based monitoring. The research offers new evidence on how consumers interact with AI tools designed to support medication choices at home.

The authors identify AI wearables as a key opportunity to support safer medication use, reduce avoidable clinical visits and give individuals more control over their health decisions. However, they also warn that adoption is uneven, largely determined by users’ eHealth literacy.

AI wearables expected to transform self-medication, but skills gap persists

The authors note that over-the-counter drugs represent a large share of worldwide medicine use, and many users treat common conditions without consulting physicians. While this autonomy offers convenience and reduces healthcare burdens, it carries risks: incorrect dosing, drug interactions, and repeated misuse can lead to complications, hospitalizations or long-term consequences.

To address these challenges, the researchers propose an AI-assisted wearable system that integrates OTC-EHR with smartwatch sensors. The envisioned system collects physiological and behavioral data, such as heart rate, activity levels, sleep patterns and medication histories—then uses AI algorithms to detect patterns, identify potential risks and provide personalized self-medication guidance. Users receive continuous recommendations about dosage, timing and drug interactions based on their own health metrics.

According to the study, such a system could significantly improve self-medication safety by giving users real-time, context-aware insights into their conditions. But whether users will adopt this technology depends heavily on their ability to understand, evaluate and apply health information sourced from digital tools, a competency the authors identify as eHealth literacy.

The research shows a clear trend: individuals with high eHealth literacy are far more prepared to interact with AI-driven health systems, actively use wearable devices and feel confident integrating digital tools into their medication routines. They are more likely to track health metrics, interpret AI-generated advice and make decisions aligned with evidence-based recommendations.

However, the study finds that users with lower digital health literacy struggle to evaluate digital inputs, often relying entirely on AI recommendations or deferring to medical professionals. This discrepancy reveals a skills gap that could limit the reach of AI wearables if not addressed through user-centered design, education and support.

eHealth literacy predicts trust, usage and data-sharing behavior

Using survey responses from 372 internet users in China, the researchers map the relationship between eHealth literacy and attitudes toward the AI-assisted OTC-EHR smartwatch system. The analysis shows that eHealth literacy strongly predicts willingness to adopt wearable devices for health management. Participants with higher literacy levels expressed greater readiness to monitor personal health through wearables, store medication histories, and use personalized drug-management tools integrated into consumer devices.

These users also demonstrated a greater willingness to share anonymous medication-use data to support AI analysis. The study attributes this openness to their stronger understanding of data privacy, risk assessment and the value of evidence-based digital decision-making. The authors note that data-sharing willingness is a critical component of AI health systems, as larger datasets allow algorithms to learn, identify risk patterns and improve the accuracy of recommendations.

However, while eHealth literacy significantly increased willingness to adopt the device, it did not directly predict perceived helpfulness of the system. Users’ perception of utility depended more on personal attitudes, expectations and perceived relevance to their routines. This distinction underscores the importance of user perception in digital health innovation, even when technical literacy is high.

Another key finding is the relationship between eHealth literacy and trust in AI. Individuals with stronger health literacy demonstrated higher levels of trust in AI-assisted medication advice but continued to prefer a balanced approach, using AI support while maintaining personal oversight. Rather than adopting AI suggestions blindly, these users approached the system as a tool that enhanced their own decision-making.

On the other hand, participants with lower eHealth literacy tended to rely more heavily on AI or healthcare professionals for medication decisions. Their dependence on external support reflected lower confidence in evaluating health information independently. The authors warn that this reliance may increase vulnerability if AI systems are adopted without adequate user education, as misunderstandings or overconfidence in AI-generated guidance could pose risks.

Overall, eHealth literacy plays a crucial role not only in adoption but in shaping how users interact with AI recommendations, balancing autonomy with guidance and interpreting health insights accurately.

Wearable OTC-EHR systems seen as viable support tools, but user education critical

The authors argue that an AI-assisted OTC-EHR wearable system has substantial potential to improve self-medication habits and reduce preventable errors. The system’s design integrates digitally stored medication histories with continuous biometric monitoring, providing a personalized profile that supports informed choices. By alerting users to potential drug interactions, excessive usage or risk signals, the system could reduce misuse and enhance patient safety.

Participants across the study generally agreed that such a system could help them manage day-to-day health needs more effectively. Even users with limited eHealth literacy recognized the value of automated reminders, pattern detection and personalized feedback. The authors note that this widespread willingness is particularly important, as it suggests public openness to integrating consumer wearables with health decision-making tools.

However, the research also highlights significant barriers that must be addressed to ensure safe and effective adoption. Users expressed concerns about data security, privacy and the accuracy of AI-generated guidance. The authors emphasize that these concerns require transparent system design, clear communication of data practices and regulatory compliance to build and maintain public trust.

The study suggests that developers must adopt a “user-centered” approach to design, ensuring interfaces are intuitive, explanations are clear and risks are communicated effectively. Additional resources, such as educational programs and accessible instructions, could help users with lower eHealth literacy navigate the system safely.

The authors also recognize the potential societal value of OTC-EHR wearables in reducing burdens on healthcare systems. As populations age and chronic conditions rise, preventive self-care supported by reliable digital tools could reduce the frequency of unnecessary medical visits and support better long-term health outcomes. AI-assisted monitoring could help individuals identify early warning signs and intervene sooner, preventing complications and reducing healthcare costs.

Yet the study warns that without targeted interventions to improve eHealth literacy, the benefits of these systems may not be evenly distributed. Populations with lower digital health skills risk being left behind, relying too much on automated advice or misinterpreting digital information. The authors urge policymakers, public health agencies and educators to integrate digital health training into health promotion strategies to close this gap.