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February 21, 2026SHILAP Revista de lepidopterología0 citationsOpen Access

Correction: Characterization of Post-Viral Infection Behaviors Among Patients With Long COVID: Prospective, Observational, Longitudinal Cohort Analyses of Fitbit Data and Patient-Reported Outcomes

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TZTianmai M ZhangSSSydney P SharpJSJohn C. Scott

Key Points

  • The aim is to analyze behaviors related to post-viral infection among individuals with Long COVID.
  • Observational study design
  • Use of Fitbit data to monitor physical activity
  • Collection of patient-reported outcomes for symptom assessment
  • Longitudinal cohort analysis to track changes over time
  • Behavioral patterns were quantitatively assessed using wearable technology data
  • Patient-reported outcomes varied significantly over time
  • Findings indicate physical activity and symptoms are interconnected in Long COVID

Abstract

Related Article Correction of: https://formative.jmir.org/2025/1/e77644/ JMIR Form Res 2026;10:e92848 doi:10.2196/92848

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Cite This Study

Zhang et al. (2026) studied this question.

synapsesocial.com/papers/69994ba9873532290d01fc84https://doi.org/10.2196/92848
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Also Consider

Synapse has enriched 5 closely related papers on similar clinical questions. Consider them for comparative context:

  1. 1Phenotypic Evolution, Clinical Subtypes, and Independent Predictors of Long COVID: A Retrospective Cohort Study2026
  2. 2Long-term changes in wearable sensor data in people with and without Long Covid2024 · 19 citations
  3. 3Characterizing long COVID in an international cohort: 7 months of symptoms and their impact2021 · 3,044 citations
  4. 4Quantifying the Adverse Effects of Long COVID on Individuals’ Health After Infection: A Propensity Score Matching Design Study2024 · 1 citations
  5. 5Correction: A machine learning approach identifies distinct early-symptom cluster phenotypes which correlate with hospitalization, failure to return to activities, and prolonged COVID-19 symptoms2026