The symptoms evolution of long COVID‑19 (SE-LC19): a new patient-reported content valid instrument

Author:

Rofail Diana,Somersan-Karakaya Selin,Mylonakis Eleftherios,Choi Julia Y.,Przydzial Krystian,Marquis Sarah,Zhao Yuming,Hussein Mohamed,Norton Thomas D.,Podolanczuk Anna J.,Geba Gregory P.

Abstract

Abstract Background The field of long COVID research is rapidly evolving, however, tools to assess and monitor symptoms and recovery of the disease are limited. The objective of the present study was to develop a new patient-reported outcomes instrument, the Symptoms Evolution of Long COVID‑19 (SE-LC19), and establish its content validity. Methods The 40-item SE-LC19 instrument was developed based on patient-relevant empirical evidence from scientific literature and clinical guidelines that reported symptoms specific to long COVID. A 2-part mixed-method approach was employed. Part 1: Qualitative interviews with a purposive sample of 41 patients with confirmed long COVID were conducted for the content validation of SE-LC19. During cognitive debriefing interviews, patients were asked to describe their understanding of the instrument’s instructions, specific symptoms, response options, and recall period to ensure its relevance and comprehensiveness. Five clinicians of different medical specialties who regularly treated patients with long COVID were also interviewed to obtain their clinical expert opinions on SE-LC19. Part 2: Exploratory Rasch Measurement Theory (RMT) analysis was conducted to evaluate the psychometric properties of the SE-LC19 data collected during the interviews. Results Overall, patients reported that the instructions, questions, recall period, and response options for SE-LC19 were comprehensive and relevant. Minor conceptual gaps reported by patients captured nuances in the experience of some symptoms that could be considered in future studies. Some patients suggested a revision of the recall period from 24 h to 7 days to be able to capture more symptoms given the waxing and waning nature of some symptoms. Clinicians found the instrument comprehensive with minimal suggestions regarding its content. Exploratory RMT analyses provided evidence that the SE-LC19 questionnaire performed as intended. Conclusion The present mixed-methods study in patients with confirmed long COVID supports the content validity and applicability of the SE-LC19 instrument to evaluate the symptoms of patients with long COVID. Further research is warranted to explore the psychometric properties of the instrument and refine a meaningful and robust patient-relevant endpoint for use in different settings such as clinical trials and clinical practice to track the onset, severity, and recovery of long COVID.

Funder

Regeneron Pharmaceuticals

Department of Health and Human Services, Office of the Administration for Strategic Preparedness and Response, and Biomedical Advanced Research and Development Authority

Publisher

Springer Science and Business Media LLC

Reference31 articles.

1. Vanichkachorn G, Newcomb R, Cowl CT et al (2021) Post-COVID-19 syndrome (long haul syndrome): description of a multidisciplinary clinic at Mayo Clinic and characteristics of the initial patient cohort. Mayo Clin Proc 96:1782–1791

2. Crook H, Raza S, Nowell J, Young M, Edison P (2021) Long covid-mechanisms, risk factors, and management. BMJ 374:n1648

3. National Institute for Health and Care Excellence (NICE). COVID-19 rapid guideline: managing the long-term effects of COVID-19. https://www.nice.org.uk/guidance/ng188

4. Centers for Disease Control and Prevention. Long COVID or post-COVID conditions. https://www.cdc.gov/coronavirus/2019-ncov/long-term-effects/index.html

5. Callard F, Perego E (2021) How and why patients made Long Covid. Soc Sci Med 268:113426

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3