Cross-Cultural Adaptation and Psychometric Properties of the Thai Version of the Modified COVID-19 Yorkshire Rehabilitation Scale in Individuals with Long COVID
Abstract
Objective: To translate and cross-culturally adapt the modified coronavirus disease 2019 (COVID-19) Yorkshire Rehabilitation Scale (C19-YRSm) into a Thai version, and assess its psychometric properties in individuals with long COVID.
Material and Methods: The C19-YRSm underwent translation and cross-cultural adaptation to produce a Thai version. Its 2 subscales, symptom severity and functional ability, were examined using confirmatory factor analysis (CFA). In instances where the results were deemed unfit, alternative factor structures were explored through exploratory factor analysis (EFA). After that, internal consistency and test-retest reliability were calculated at 2-day intervals. Construct validity was assessed by examining correlations between the Thai version of the 36-item Short Form Health Survey questionnaire (Thai SF-36) and the Thai Fall Efficacy Scale-International (Thai FES-I).
Results: The study sample comprised 338 individuals with long COVID. The results of the CFA indicated a poor fit. Subsequent evaluation using EFA revealed that the symptom severity and functional ability subscales were rearranged into 3 new subscales: major symptoms, minor symptoms, and functional ability. Internal consistency was found to be good to excellent (Cronbach’s alpha: 0.77-0.90). Test-retest reliability for all subscales of the Thai C19-YRSm demonstrated high consistency (intraclass correlation coefficients (ICC(2,1)): 0.88-0.95). Convergent validity showed moderate to strong correlations with the Thai SF-36, while discriminant validity, compared to the FES-I, showed fair to poor correlations.
Conclusion: The vigorous psychometric properties of the questionnaire make it highly suitable for cross-cultural research, enabling the assessment of long COVID severity among Thai individuals in clinical and research settings.
Keywords
Full Text:
PDFReferences
Wiersinga WJ, Rhodes A, Cheng AC, Peacock SJ, Prescott HC. Pathophysiology, transmission, diagnosis, and treatment of coronavirus disease 2019 (COVID-19): a review. JAMA 2020;324:782-93.
World Health Organization. Coronavirus (COVID-19) dashboard [homepage on the Internet]. Geneva: World Health Organization; 2020 [cited 2023 Aug 27]. Available from: http://covid19.who.int
Barker-Davies RM, O'Sullivan O, Senaratne KPP, Baker P, Cranley M, Dharm-Datta S, et al. The stanford hall consensus statement for post-COVID-19 rehabilitation. Br J Sports Med 2020;54:949-59.
Ayoubkhani D, Munro M. Prevalence of ongoing symptoms following coronavirus (COVID-19) infection in the UK [homepage on the Internet]. Newport: Office for National Statistics; 2023 [cited 2022 Mar 24]. Available from: https://www.ons.gov.uk/peoplepopulationandcommunity/healthandsocialcare/conditionsanddiseases/datalist?filter=datasets
Taquet M, Dercon Q, Luciano S, Geddes JR, Husain M, Harrison PJ. Incidence, co-occurrence, and evolution of long-COVID features: a 6-month retrospective cohort study of 273,618 survivors of COVID-19. PLoS Med 2021;18:e1003773.
Lopez-Leon S, Wegman-Ostrosky T, Perelman C, Sepulveda R, Rebolledo PA, Cuapio A, et al. More than 50 long-term effects of COVID-19: a systematic review and meta-analysis. Sci Rep 2021;11:16144.
Krongthaeo S, Partiprajak S, Piaseu N, Ckumdee S, Taaon C, Kongsuwan A. Prevalence and exploratory factor analysis of long COVID-19 symptoms among experienced infected population in Bangkok, Thailand. BMC Public Health 2024;24:2863.
National institute for health and care excellence. COVID-19 rapid guideline: managing the long-term effects of COVID-19 [homepage on the Internet]. London: National institute for health and care excellence; 2020 [cited 2022 Jun 5]. Available from: https://www.nice.org.uk/guidance/ng188
PHOSP-COVID Collaborative Group. Clinical characteristics with inflammation profiling of long COVID and association with 1-year recovery following hospitalisation in the UK: a prospective observational study. Lancet Respir Med 2022;10:761-75.
Cutler DM. The costs of long COVID. JAMA Health Forum 2022;3:e221809.
O'Connor RJ, Preston N, Parkin A, Makower S, Ross D, Gee J, et al. The COVID-19 Yorkshire rehabilitation scale (C19-YRS): application and psychometric analysis in a post-COVID-19 syndrome cohort. J Med Virol 2021;94:1027-34.
Sivan M, Preston N, Parkin A, Makower S, Gee J, Ross D, et al. The modified COVID-19 Yorkshire rehabilitation scale (C19-YRSm) patient-reported outcome measure for long Covid or post-COVID-19 syndrome. J Med Virol 2022;94:4253-64.
Smith A, Greenwood D, Horton M, Osborne T, Goodwin M, Lawrence RR, et al. Psychometric analysis of the modified COVID-19 Yorkshire rehabilitation scale (C19-YRSm) in a prospective multicentre study. BMJ Open Respir Res 2024;11: e002271.
Beaton DE, Bombardier C, Guillemin F, Ferraz MB. Guildines for the process of cross-cultural adaptation of self-report measures. SPINE 2000;25:3186-91.
Anthoine E, Moret L, Regnault A, Sebille V, Hardouin JB. Sample size used to validate a scale: a review of publications on newly-developed patient reported outcomes measures. Health Qual Life Outcomes 2014;12:176.
MacCallum RC, Widaman KF, Zhang S, Hong S. Sample size in factor analysis. Psychological Methods 1999;4:84-99.
Witt S, Krauss E, Barbero MAN, Muller V, Bonniaud P, Vancheri C, et al. Psychometric properties and minimal important differences of SF-36 in idiopathic pulmonary fibrosis. Respir Res 2019;20:47.
Lim LL, Seubsman SA, Sleigh A. Thai SF-36 health survey: tests of data quality, scaling assumptions, reliability and validity in healthy men and women. Health Qual Life Outcomes 2008;6:52.
Yardley L, Beyer N, Hauer K, Kempen G, Piot-Ziegler C, Todd C. Development and initial validation of the falls efficacy scale-international (FES-I). Age Ageing 2005;34:614-9.
Kempen GI, Yardley L, van Haastregt JC, Zijlstra GA, Beyer N, Hauer K, et al. The short FES-I: a shortened version of the falls efficacy scale-international to assess fear of falling. Age Ageing 2008;37:45-50.
Thiamwong L. Psychometric testing of the falls efficacy scale-international (FES-I) in Thai older adults. Songkla Med J 2011;22:277-87.
Kamper SJ, Ostelo RW, Knol DL, Maher CG, de Vet HC, Hancock MJ. Global perceived effect scales provided reliable assessments of health transition in people with musculoskeletal disorders, but ratings are strongly influenced by current status. J Clin Epidemiol 2010;63:760-6.
Brown TA, Little TD, editor. Confirmatory factor analysis for applied research. 2nd ed. New York: The Guilford Press; 2015.
Portney L. Foundations of clinical research: applications to evidence-based practice. 4th ed. Philadelphia: F.A. Davis Company; 2020.
Tavakol M, Wetzel A. Factor analysis: a means for theory and instrument development in support of construct validity. Int J Med Educ 2020;11:245-7.
Subramanian A, Nirantharakumar K, Hughes S, Myles P, Williams T, Gokhale KM, et al. Symptoms and risk factors for long COVID in non-hospitalized adults. Nat Med 2022;28:1706-14.
Chen KY, Li T, Gong FH, Zhang JS, Li XK. Predictors of health-related quality of life and influencing factors for COVID-19 patients, a follow-up at one month. Front Psychiatry 2020;11:668.
Fernandez-de-Las-Penas C, Notarte KI, Peligro PJ, Velasco JV, Ocampo MJ, Henry BM, et al. Long-COVID symptoms in individuals infected with different SARS-CoV-2 variants of concern: a systematic review of the literature. Viruses 2022;14:2629.
Refbacks
- There are currently no refbacks.
This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.