The vast amount of data available to patients and consumers—from web sources, social media, wearables, and AI chatbots—has democratized health information on an unprecedented scale. This shift presents unique opportunities and challenges for the healthcare industry.
This evolution affects not only patients but also healthcare providers, as the traditional relationship between patients and healthcare professionals is being disrupted. This makes it a critical area for discussion among medical professionals worldwide. However, much of the current discourse either ridicules the pitfalls or labels the changes as transformative without critically assessing the paradigm shift they cause in patients’ relationships with their health. The lack of guidelines on managing this shift means we are failing to understand and adapt to patient needs.
Biohacking, a trend where consumers and patients use technology to make small changes to their health without medical intervention, is growing. Patients are increasingly using devices, AI, and online peer support to assess their health and interpret biomarkers. This trend is unlikely to diminish anytime soon.
To unpack the impact, we must first assess the information patients have access to and explore the impact of each source individually and as a whole based on recent developments.
From Website Information to AI Interactive Information Provision
The information landscape has become more complex, driven by the surge in AI interactive bots and AI-generated content. Amidst the overflow of online information and the varied formats it comes in, reputable websites and brands have an increasing responsibility to be guiding lights for consumers and patients looking for healthcare-related information.
Recent enhancements in Google Search algorithms aim to direct users towards more relevant, high-quality health data, including detailed information about healthcare providers and insurance networks, representing significant improvements. Academic research highlights the growing reliance on online resources.
A 2020 study published in the International Journal of Environmental Research and Public Health by Maria Magdalena Bujnowska-Fedak highlights how accessible online health information significantly influences patient behavior and engagement in health practices. The widespread dissemination of information about chronic diseases, for instance, has shown to improve patient management skills but has also led to increased health-related fears among some populations (Bujnowska-Fedak, 2020). The findings advocate for enhanced digital literacy initiatives and a comprehensive regulatory framework to bolster the reliability of online health content.
AI’s Role as an Information Purveyor
Recently, Google began using AI to answer healthcare questions through search previews called AI overviews. These generate conversational answers based on internet data. Before these developments, users could often distinguish between reputable medical websites and less trustworthy sources from standard search results. However, a single block of text combining information from multiple sources might cause confusion, as more sources do not necessarily mean better accuracy.
Increasingly, patients are also turning to AI-powered chatbots for health advice. Chatbots like ChatGPT, trained on internet data, pose similar problems. However, there are also apps trained only on medical journal information or FDA-approved chatbots like Woebot, which uses Cognitive Behavioral Therapy (CBT) techniques. Woebot provides immediate, 24/7 support and is FDA-designated for treating conditions like postpartum depression.
This growing reliance on chatbots and their design to interact with various formats highlights the importance of accurate and reliable health information. While these tools can enhance comprehension and empower patients by making complex information accessible, they also have the potential to mislead, leading to misdiagnoses and increased anxiety among patients.
Wearables and the Rise of Biohacking
There is an increasing interest in the amount of data available from devices and the availability of digital biomarkers. A striking example of digital biomarkers in action is the Apple Watch’s ability to detect atrial fibrillation (AFib), an irregular heart rhythm that can lead to serious complications like stroke. Traditionally, detecting AFib required periodic ECGs in a clinical setting. However, the Apple Watch continuously monitors the heart rate and rhythm, using its built-in sensors to identify irregularities indicative of AFib.
Multiple consumers go online to make sense of device data, which can include the increasing availability of biomarkers from consumer wearables or medical devices. Technology like that used in continuous glucose monitors (CGM), originally intended for diabetic patients, can now be used more broadly by consumers to understand and moderate their glucose levels and other health metrics.
The biohacking community is rapidly growing, reflecting this surge in interest. For example, r/biohackers, a subreddit dedicated to biohacking, registered a 20% increase in subscribers between April and July 2024. This indicates a significant rise in public engagement and interest in self-monitoring and health optimization through technology.
Wearables now monitor a range of mental health metrics, from heart rate and sleep patterns to mood tracking and electrodermal activity. These advancements offer deeper insights into emotional well-being, stress levels, and overall mental health, helping users manage their conditions more effectively.
The table below outlines key metrics tracked by various wearables, providing a snapshot of how these devices contribute to understanding and managing health:
| Metric | Description | Applicable Wearables |
| Heart Rate | Continuous monitoring to detect elevated heart rates indicative of stress or anxiety. | Apple Watch, Garmin, Fitbit |
| Heart Rate Variability | Measurement of variations in time between heartbeats, providing insights into stress and overall well-being. | Apple Watch, Garmin, Whoop |
| Sleep Tracking | Monitoring sleep patterns, duration, and quality to identify issues linked to mental health conditions. | Apple Watch, Fitbit, Oura Ring |
| Electrocardiogram (ECG) | Monitoring heart rhythms to detect conditions exacerbated by stress or anxiety. | Apple Watch |
| Blood Oxygen Saturation | Measuring blood oxygen levels, which can affect mental clarity and energy levels. | Apple Watch, Garmin, Fitbit |
| Stress Monitoring | Using various metrics to provide stress scores and help manage stress levels. | Apple Watch, Garmin, Fitbit |
| Mood Tracking | Tracking mood changes over time to identify patterns and triggers related to mental health. | Various health apps |
| Electrodermal Activity (EDA) | Measuring skin conductance to assess stress and emotional responses. | Fitbit Sense, Garmin |
These metrics, captured through advanced technology, are transforming how individuals interact with their health data, promoting proactive management and a better understanding of their overall well-being.
Understanding Next Steps
The collaboration among regulators, digital platforms, and healthcare professionals currently falls short, risking the integrity of healthcare guidance. As digital health information becomes more entrenched in patient care, the necessity for a unified approach to manage this digital ecosystem becomes more apparent. Such an approach should enhance the quality of online health information to safeguard and improve patient decision-making.
To date, it is difficult to find comprehensive studies examining the evolving information landscape. However, it is clear that the stakes are high. Ensuring the reliability of digital health data, promoting digital literacy, and fostering responsible biohacking practices are essential steps in this journey. By working together, stakeholders can create a more robust framework that empowers patients with accurate, reliable, and actionable health information. This collaborative effort will not only bridge the current gaps but also pave the way for a future where digital health resources are a trusted and integral part of healthcare decision-making.
References
Bujnowska-Fedak, M. M. (2020). Trends in the use of the Internet for health purposes in Poland. BMC Public Health, 20, 1230.
Bujnowska-Fedak, M. M., & Węgierek, P. (2024). The complex impact of digital health information on patient behavior and decision-making. International Journal of Environmental Research and Public Health.
Google. (2023). “Search updates and insights.” Google Blog. Retrieved from Google Blog
Reddit statistic on biohacking retrieved via querying the subreddit using social listening tool Brandwatch.
Table data retrieved via desk research. Key references for the table data include sources such as DIY Genius, Wareable, Online Tech Tips, and Mindbodygreen, which discuss the features and capabilities of various wearable health devices (DIY Genius, 2024; Wareable, 2024; Online Tech Tips, 2024; Mindbodygreen, 2024) (DIY Genius) (Online Tech Tips) (Wareable) (Fitbit) (wearablestouse.com) (MindBodyGreen).
About Vicky Britton
Vicky Britton is a social media research consultant specializing in advanced online research within the pharmaceutical sector. She leverages digital insights to enhance patient engagement and support informed decision-making in healthcare. Vicky has worked for companies such as Storyful, Cognizant, and Accenture. She is also a writer and a speaker at digital health conferences, dedicated to promoting transparent communication and amplifying patient voices in the industry.