Zhang et al. (2025)
- Authors: Tianmai M. Zhang, Sydney P. Sharp, John D. Scott, Douglas Taren, Jane C. Samaniego, Elizabeth R. Unger, Jeanne Bertolli, Jin-Mann S. Lin, Christian B. Ramers, Job G. Godino
- Institutes: Laura Rodriguez Research Institute, Family Health Centers of San Diego, San Diego, CA, USA, University of Washington, Seattle, WA, USA, University of Colorado, Aurora, CO, USA, Centers for Disease Control and Prevention, Atlanta, GA, USA, University of California, San Diego, La Jolla, CA, USA, San Diego State University, San Diego, CA, USA, Clinton Health Access Initiative, Boston, MA, USA
- Publisher: JMIR Formative Research
- Link: DOI
Summary
This research demonstrates that wearable devices like Fitbits can provide valuable objective insights into the daily lives of Long COVID patients, particularly within low-income communities. By showing that some patients remain physically active despite severe symptoms, the study challenges simplistic assumptions about the relationship between activity and disease recovery. These findings encourage clinicians to move toward personalized management strategies that incorporate objective behavioral data rather than relying solely on patient self-reports.
What was researched?
This study examined the relationship between physical activity, physiological data, and self-reported symptoms in patients with Long COVID. Researchers aimed to identify distinct patterns of behavior and health outcomes over a six-month period using wearable technology.
Why was it researched?
While Long COVID research often relies on self-reported measures, objective data from wearable devices is less common. Understanding how daily physical activity interacts with symptom severity is crucial for developing better treatment and rehabilitation plans, especially for underserved populations.
How was it researched?
The study followed a prospective cohort of 172 low-income patients who used Fitbit devices to track activity and completed patient-reported outcome surveys at baseline, three, and six months. Participants were categorized into active and inactive groups based on World Health Organization physical activity guidelines. Data was analyzed using linear mixed-effects regression to identify longitudinal associations between activity levels and symptoms.
What has been found?
Inactive patients reported significantly more severe fatigue, shortness of breath, and physical limitations compared to those who were more active. Over time, inactive participants experienced a decline in their ability to participate in social roles and an increase in sleep-related symptoms. However, the study also found that a segment of Long COVID patients could remain physically active despite experiencing persistent and debilitating symptoms.
Discussion
The study highlights the feasibility and importance of using wearable technology in low-income clinical settings to monitor post-viral illnesses. It suggests that physical activity levels alone do not fully reflect the complexity of a patient’s symptom burden. Limitations identified include high attrition rates and missing data common in longitudinal studies using consumer-grade wearables.
Conclusion & Future Work
Long COVID patients display diverse activity profiles that correlate with their functional outcomes and ability to engage in social activities. These results support the implementation of personalized rehabilitation plans that consider an individual’s unique activity profile.