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Record W4309168489 · doi:10.1101/2022.11.12.22282116

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

2022· preprint· en· W4309168489 on OpenAlexafffundabout
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, Angela M. Cheung, Brittany Torres, Lisa Avery, Ciarán Bannan, Richard Harding

Bibliographic record

VenuemedRxiv · 2022
Typepreprint
Languageen
FieldMedicine
TopicLong-Term Effects of COVID-19
Canadian institutionsPrincess Margaret Cancer CentreHealth Sciences CentreToronto Rehabilitation InstituteSunnybrook Health Science CentreMcMaster UniversityUniversity Health NetworkUniversity of Toronto
FundersCanadian Institutes of Health ResearchPittsburgh Liver Research Center, University of PittsburghCanada Research Chairs
KeywordsInterquartile rangePsychologyQualitative researchGerontologyEthnic groupMedicineDemographySociology

Abstract

fetched live from OpenAlex

ABSTRACT Objectives To describe episodic nature of disability among adults living with Long COVID. Methods We 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. Participants Adults 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. Results Among 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. Conclusions Among 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 MESSAGES What 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.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.005
metaresearch head score (Gemma)0.009
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Meta-epidemiology (narrow), Research integrity
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.075
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0050.009
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.002
Scholarly communication0.0000.000
Open science0.0010.002
Research integrity0.0000.004
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.020
GPT teacher head0.358
Teacher spread0.338 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations8
Published2022
Admission routes3
Has abstractyes

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