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These findings can be used to enhance usability of the digital health app and improve outcomes and quality of life among patients with long COVID.
A combination of surveys and usability testing was used to incorporate patient feedback during the development of a digital health app designed to aid in the self-management of long COVID.
Results uncovered the preferences of patients, including an intuitive onboarding process, the addition of a symptom list, and the ability to report on a range of symptoms and activities, according to a study published in JMIR Formative Research.1
Long COVID, or post-COVID-19 syndrome, is characterized by persistent, general, unspecific symptoms such as sleep disturbances, myalgia, fatigue, and concentration difficulties which can last for months post-infection. These fibromyalgia-like symptoms have been increasingly reported and approximately 30% of people with long COVID fulfill the classification criteria for fibromyalgia.2
“Digital health solutions have recently proven efficacy in chronic pain and fibromyalgia management,” wrote a team of investigators led by Marc Blanchard, PhD, associated with the Department of Rheumatology, Lausanne University Hospital (CHUV), University of Lausanne, Switzerland. “Self-management plays a big role in the empowerment of these patients, and encouraging studies showed the efficacy of such programs. Moreover, cognitive behavioral therapy or mindfulness and education training have shown substantial positive effects in a self-management setting, thus empowering the patients by involving them in the therapeutic process.”
Investigators sought the insight of patients with post-viral fibromyalgia-like symptoms when designing the digital health self-management app (POCOS) by using patient preference surveys and usability testing. Expectations regarding features, content, and usability were used to steer development. Patients were recruited from the Swiss patient post–COVID-19 association, Long COVID Schweiz.
In the first survey, patients were asked if they would prefer a symptoms list with intensity scales or an automated chatbot, the number of symptoms- and activity-reporting questions they would regularly like to answer, and the most relevant symptoms and activities they would like to report.
Most (n = 48/53; 91%) patients reported a preference for a symptom list rather than an automated chatbot. Participants were also in alignment on the number of symptom- and activity-reporting questions they would like to answer, with most preferring 5-10 questions (70% and 58%, respectively). The most relevant symptoms included sleep quality, pain, fatigue, concentration level, memory level, and pain location. Activities included nonmedical therapies, doctor visits, painkiller use, and physical activities.
One of the key challenges was the usability of the app, in which most patients had some difficulty with navigating the onboarding process. Only 2 of the 6 participants demonstrated a sufficient understanding of the functionalities and were able to use the app without help from investigators. Two other participants were completely unable to register or use the app because of a lack of information and guidance. Only 1 patient reported the app as intuitive and easy to use. While these results seem underwhelming, they also validated the importance of aligning the app with the needs of its users to improve satisfaction and engagement.
Exclusively recruiting a small sample of participants from a Swiss patient post-COVID-19 association may have reduced the generalizability of the findings, according to investigators. Studies involving a larger, more diverse sample could help to confirm and expand on these results. Future research should also focus on the onboarding procedures to assess its impact on patient engagement, usability, retention rates, and their ability to optimally manage digital health resources.
“The advancement of patient-centered digital health solutions, as evidenced by the app developed in this study, underscores a paradigm shift toward more responsive and adaptive health technology design,” investigators concluded. “This approach is anticipated to enhance patient adherence and the efficacy of digital health interventions.”
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