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Long Covid stigma: estimating burden and validating scale in a UK-based sample
Preprint
en En
| PREPRINT-MEDRXIV
| ID: ppmedrxiv-22275585
ABSTRACT
BackgroundStigma can be experienced as perceived or actual disqualification from social and institutional acceptance on the basis of one or more physical, behavioural or other attributes deemed to be undesirable. Long Covid is a predominantly multisystem condition that occurs in people with a history of SARSCoV2 infection, often resulting in functional disability. AimTo develop and validate a Long Covid Stigma Scale (LCSS); and to quantify the burden of Long Covid stigma. Design and SettingFollow-up of a co-produced community-based Long Covid online survey using convenience non-probability sampling. MethodThirteen questions on stigma were designed to develop the LCSS capturing three domains - enacted (overt experiences of discrimination), internalised (internalising negative associations with Long Covid and accepting them as self-applicable) and anticipated (expectation of bias/poor treatment by others) stigma. Confirmatory factor analysis tested whether LCSS consisted of the three hypothesised domains. Model fit was assessed and prevalence was calculated. Results966 UK-based participants responded (888 for stigma questions), with mean age 48 years (SD 10.7) and 85% female. Factor loadings for enacted stigma were 0.70-0.86, internalised 0.75-0.84, anticipated 0.58-0.87, and model fit was good. The prevalence of experiencing stigma at least sometimes and often/always was 95% and 76% respectively. Anticipated and internalised stigma were more frequently experienced than enacted stigma. Those who reported having a clinical diagnosis of Long Covid had higher stigma prevalence than those without. ConclusionThis study establishes a scale to measure Long Covid stigma and highlights common experiences of stigma in people living with Long Covid.
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Texto completo:
1
Colección:
09-preprints
Base de datos:
PREPRINT-MEDRXIV
Tipo de estudio:
Observational_studies
/
Prognostic_studies
/
Qualitative_research
Idioma:
En
Año:
2022
Tipo del documento:
Preprint