Review 1: "Conceptualizing the Episodic Nature of Disability Among Adults Living with Long COVID: A Qualitative Study"

David Russell

Conceptualising the Episodic Nature of Disability among Adults Living with Long COVID: A Qualitative Study

by Kelly K. O’Brien, Darren A. Brown, Kiera McDuff, Natalie St. Clair-Sullivan, Patricia Solomon, Soo Chan Carusone, Lisa McCorkell, Hannah Wei, Susie Goulding, Margaret O’Hara, Catherine Thomson, Niamh Roche, Ruth Stokes, Jaime H. Vera, Kristine M. Erlandson, Colm Bergin, Larry Robinson, Angela M. Cheung, Brittany Torres, Lisa Avery, Ciaran Bannan, and Richard Harding

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dx.doi.org

Description

ABSTRACTObjectivesTo describe episodic nature of disability among adults living with Long COVID.MethodsWe conducted a community-engaged qualitative descriptive study involving online semi-structured interviews and participant visual illustrations. We recruited participants via collaborator community organizations in Canada, Ireland, United Kingdom, and United States.ParticipantsAdults who self-identified as living with Long COVID. We purposively recruited for diversity in age, gender, race/ethnicity, sexual orientation, and duration since initial COVID-19 infection.Main Outcome Measure(s)We used a semi-structured interview guide to explore experiences of disability living with Long COVID, specifically health-related challenges and how they were experienced over time. We asked participants to draw their health trajectory and conducted a group-based content analysis.ResultsAmong the 40 participants, the median age was 39 years (interquartile range: 32, 49); majority were women (63%), white (73%), heterosexual (75%), and living with Long COVID for ≥1 year (83%). Participants described their disability experiences as episodic in nature, characterized by fluctuations in presence and severity of health-related challenges (disability) that may occur both within a day and over the long-term living with Long COVID. They described living with ‘ups and downs’, ‘flare-ups’, and ‘peaks’ followed by ‘crashes’, ‘troughs’, and ‘valleys’, likened to a ‘yo-yo’ ‘rolling hills’, and ‘rollercoaster ride’ with ‘relapsing/remitting’, ‘waxing/waning’, ‘fluctuations’ in health. Drawn illustrations demonstrated variety of trajectories across health dimensions, some more episodic than others. Uncertainty intersected with the episodic nature of disability, characterized as unpredictability of episodes, their length, severity and triggers, and process of long-term trajectory, which had implications on broader health.ConclusionsAmong this sample of adults living with Long COVID, experiences of disability were described as episodic, characterized by fluctuating health challenges, which may be unpredictable in nature. Results help to better understand experiences of disability among adults living with Long COVID to inform healthcare and rehabilitation.KEY MESSAGESWhat is already known on this topic:Globally, a growing number of individuals are living with persistent and prolonged signs and symptoms following infection consistent with COVID-19, referred to as Long COVID, Post COVID-19 Condition (PCC) or Post-acute sequelae of SARS-CoV2 (PASC). Individuals living with Long COVID are experiencing a range of symptoms and impairments that impact their ability to carry out day to day activities or engage in social and community life roles.What this study adds:Disability living with Long COVID was described as episodic, characterized by fluctuations in presence and severity of health related challenges, which may be unpredictable in nature, occurring both within the day, and over the long-term of months and years living with Long COVID.How this study might affect research, practice or policy:Results will help researchers, healthcare providers, policymakers, employers, and community members to better understand experiences of disability among adults living with Long COVID, to inform future disability measurement, health and rehabilitation care and service delivery, programs and policies for insurance, return to work, and workplace accommodations.

RR:C19 Evidence Scale rating by reviewer:

Strong. The main study claims are very well-justified by the data and analytic methods used. There is little room for doubt that the study produced has very similar results and conclusions as compared with the hypothetical ideal study. The study’s main claims should be considered conclusive and actionable without reservation.

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Review:

This manuscript, titled “Conceptualizing the Episodic Nature of Disability among Adult Living with Long COVID: A Qualitative Study,” addresses a central aspect of the Long COVID illness experience: episodic disability stemming from the ups and downs of Long COVID symptoms. The authors conducted 40 interviews among persons with Long COVID as well as participant visual illustrations of their illness and symptom fluctuations. I believe this manuscript has the potential to make a significant contribution to the literature, specifically by providing one of the most detailed accounts of symptom fluctuations and episodic disability in the context of Long COVID. To further improve and clarify the paper, I would recommend the following:

First, in the Abstract, they should indicate the time frame for data collection in the Methods section. They should then, in their Introduction, identify existing research/literature on Long COVID regarding the episodic nature of symptoms and disability. Previous research on Long COVID has touched on these topics (even if only tangentially) — I think it would be beneficial to the paper and to the readers to briefly highlight and summarize such work.

Uncertainty represents a core concept in the authors research and findings, but I believe more could have been done to clarify the type of uncertainty that the authors find evidence for in their data. From my reading, I believe that participants expressed “illness uncertainty” (wishing to know more about the causes and trajectory of their illness), and “medical uncertainty” (having interactions with healthcare professionals who are not able to diagnose and/or treat their underlying illness). Previous research on Long COVID has highlighted aspects of uncertainty in persons illness experiences; it might be useful to briefly summarize this literature in the introduction and clarify the gap that their work helps to fill in relation to this specific concept/topic (which might be a focus on the links between episodic disability, healthcare interactions, and illness/medical uncertainty), as well as wrap up by discussing how their findings help clarify/expand on this work.

In the Data Collection and Analysis portion, authors could and should expand on how exactly the visual illustrations of participants’ illness were recorded, if some participants turned down or refused the opportunity to provide an illustration, and what methods of analysis were used to draw insights from these illustrations of their symptoms and health trajectories. They should also specify what type of content analysis method was used — was it a conventional (inductive) or deductive approach (where coding was informed by theory/concepts), or a mix of the two?

Furthermore, in Table 1 (Characteristics of Participants), it would be nice to know how long participants were experiencing symptoms on average (number of days/months with Long COVID), as well as how the self-reported concurrent health conditions were recorded during data collection. Was a list of these conditions obtained by a checklist approach through the demographic questionnaire, or through open-ended responses? I am curious as only three conditions are listed in the frequency table.

The authors should have also specified how many participants were contacted in order to recruit the 40 interview participants. The ID numbers reported in the Results section do not match the number of interviews (N=40), perhaps because the IDs include both participants and non-participants who were not able to be reached/scheduled for an interview. I would recommend clarifying this in the Participants section and restructuring the IDs so that they range from 1 to 40 in line with the data. Likewise, from how many different participants were quotes drawn and presented in the Results (to show breadth of the analysis)?

Table 1 also shows that 34 / 40 participants experienced a relapse in symptoms, which is 85% — the authors have noted this as 93%, which is notably higher than 85%. Lastly, Table 1 suggests that some interview participants had prior symptoms of health conditions (C.1. “Persistent or Stable Disability”), such as headache and sleep difficulties. I wondered as I read this section on changes in disability over time how participants’ conceptions of episodic disability were shaped by, or related to, their prior health? This is something the authors could explore further.

Finally, in the Discussion section, I appreciate where the authors discuss how one of the challenging aspects of Long COVID is how the burden of disease decreases as (acute illness) symptoms disappear, only to increase again with the emergence of symptoms corresponding to chronic illness. It seems that this under-recognition by healthcare providers (medical uncertainty) related to the treatment of Long COVID during this period between transition from acute to chronic illness deserves more attention. Later in the discussion, the authors mention related chronic and episodic conditions such as ME, CFS, Lyme, and dysautonomia. It would be nice to know if previous research on these conditions also highlights episodic disability as a feature of these conditions — how are they similar to Long COVID? Are partnerships with persons who have these conditions important because of the similarities between experiences of episodic disability alongside illness?

Ultimately, the authors highlight their use of both 40 interviews as well as graphical illustrations. However, I believe the researchers could do more to integrate findings from the analysis of visual illustrations into the findings from the interviews. Aside from one illustration that is discussed in the Results, the reader does not really get a sense of the variation in these illustrations or the ways that they complement the study findings.