Hostname: page-component-586b7cd67f-r5fsc Total loading time: 0 Render date: 2024-11-22T19:46:21.797Z Has data issue: false hasContentIssue false

Translation, cultural adaptation, and validation of the Brazilian Portuguese version of the End-of-Life Professional Caregiver Survey

Published online by Cambridge University Press:  27 November 2019

Ana Cláudia Mesquita Garcia*
Affiliation:
School of Nursing, Federal University of Alfenas, Alfenas, Brazil
Vivian Marina Calixto Damasceno Spineli
Affiliation:
School of Nursing, University of São Paulo, São Paulo, Brazil
Aline Helena Appoloni Eduardo
Affiliation:
Nursing Department, Federal University of São Carlos, São Carlos, Brazil
Everson Meireles
Affiliation:
Health Sciences Center, Federal University of Recôncavo da Bahia, Cruz das Almas, Brazil
Guilherme Antonio Moreira de Barros
Affiliation:
Medical School, São Paulo State University – UNESP, Botucatu, Brazil
Mark Lazenby
Affiliation:
School of Nursing, University of Connecticut, Storrs
*
Author for correspondence: Ana Cláudia Mesquita Garcia, School of Nursing, Federal University of Alfenas (UNIFAL-MG), Rua Gabriel Monteiro da Silva, 700 - Centro, Alfenas/MG, CEP 37130-001, Brazil. E-mail: [email protected]

Abstract

Objectives

The aim of this study was to translate, culturally adapt, and psychometrically evaluate the Brazilian version of the “End-of-Life Professional Caregiver Survey” (BR-EPCS).

Method

This is an observational cross-sectional study. The sample was composed of 285 Brazilian healthcare professionals who work or worked in the palliative care area. A minimum number of 280 participants were established, following the recommendation of 10 subjects for each instrument item. The European Organisation for Research and Treatment of Cancer — Quality of Life Group Translation Procedure protocol was used for the translation and the cultural adaptation. For the precise/reliable evaluation of factors measured by the BR-EPCS, Cronbach's alpha (α) and composite reliability coefficients were used. The factorial analyses were made by means of the exploratory structural equation modeling methods and confirmatory factor analysis. We have conducted a multiple linear regression analysis to evaluate the sociodemographic variables' capabilities in the result prediction measured by BR-EPCS factors.

Results

The factorial analysis showed the relevance of two factors: Factor 1 — “Given care effectiveness” (18 items; Cronbach's α = 0.94; Composite Reliability = 0.95) and Factor 2 — “Mourning and ethical and cultural values” (10 items; Cronbach's α = 0.89; Composite Reliability = 0.88). Multiple linear regression analyses revealed that the working time, sex, palliative care training, and its own advance directives are predictors of the constructs assessed by the BR-EPCS.

Significance of results

The BR-EPCS is a reliable, valid, and culturally appropriate tool to identify the educational needs of healthcare professionals who work with palliative care. This instrument can be used for educational and research reasons.

Type
Original Article
Copyright
Copyright © Cambridge University Press 2019

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

Footnotes

Deceased.

References

Aparuhov, T, Muthén, LK and Muthén, BO (2009) Exploratory structural equation modeling. Structural Equation Modeling: A Multidisciplinary Journal 16(3), 397438.CrossRefGoogle Scholar
Case, AA, Orrange, SM and Weissman, DE (2013) Palliative medicine physician education in the United States: A historical review. Journal of Palliative Medicine 16(3), 230236.CrossRefGoogle ScholarPubMed
Connor, S and Sepulveda, C (2014) Global Atlas of Palliative Care at the End-of-Life. Available online: http://www.thewpca.org/resources/global-atlas-of-palliative-care/.Google Scholar
Damásio, BF (2012) Uses of exploratory factorial analysis in psychology. Avaliação Psicológica 11(2), 213228.Google Scholar
Dancey, CP and Reidy, J (2006) Statistics without Maths for psychology: using SPSS for windows, 3rd ed. Porto Alegre: Artmed.Google Scholar
Fan, SY, Lin, WC and Lin, IM (2015) Psychosocial care and the role of clinical psychologists in palliative care. The American Journal of Hospice and Palliative Care 32(8), 861868.CrossRefGoogle ScholarPubMed
Hair, JF, Black, WC, Anderson, RE, et al. (2010) Multivariate data analysis, 6th ed. Porto Alegre: Bookman.Google Scholar
Horn, JL (1965) A rationale and technique for estimating the number of factors in factor analysis. Psychometrika 30, 179185.CrossRefGoogle Scholar
Kline, RB (2011) Principles and practice of structural equation modeling, 3rd ed. New York: The Guilford Press.Google Scholar
Kulis, D, Bottomley, A, Velikova, G, et al. (2017) EORTC Quality of Life Group — Translation Procedure. (4th ed.) Brussels, Belgium: EORTC Quality of Life Group. Available online: https://www.eortc.org/app/uploads/sites/2/2018/02/translation_manual_2017.pdf.Google Scholar
Lazenby, M, Ercolano, E, Schulman-Green, D, et al. (2012) Validity of the End-of-Life Professional Caregiver Survey to assess for multidisciplinary educational needs. Journal of Palliative Medicine 15(4), 427431.CrossRefGoogle ScholarPubMed
Muthén, LK and Muthén, BO (1998-2012) Mplus user's guide, 7th ed. Los Angeles: Muthén & Muthén.Google Scholar
Terwee, CB, Bot, SD, de Boer, MR, et al. (2007) Quality criteria were proposed for measurement properties of health status questionnaires. Journal of Clinical Epidemiology 60(1), 3442.CrossRefGoogle ScholarPubMed
World Health Organization (WHO) (2018) Palliative care — key facts. Available at: http://www.who.int/news-room/fact-sheets/detail/palliative-care.Google Scholar
Supplementary material: File

Garcia et al. supplementary material

Appendix

Download Garcia et al. supplementary material(File)
File 69.6 KB