Measuring the symptom experience of Chinese cancer patients: A validation of the Chinese version of the memorial symptom assessment scale

Cheng, Karis K. F., Wong, Eric M. C., Ling, W. M., Chan, Carmen W. H. and Thompson, David R. (2009) Measuring the symptom experience of Chinese cancer patients: A validation of the Chinese version of the memorial symptom assessment scale. Journal of Pain And Symptom Management, 37 1: 44-57. doi:10.1016/j.jpainsymman.2007.12.019

Author Cheng, Karis K. F.
Wong, Eric M. C.
Ling, W. M.
Chan, Carmen W. H.
Thompson, David R.
Title Measuring the symptom experience of Chinese cancer patients: A validation of the Chinese version of the memorial symptom assessment scale
Journal name Journal of Pain And Symptom Management   Check publisher's open access policy
ISSN 0885-3924
Publication date 2009-01
Year available 2009
Sub-type Article (original research)
DOI 10.1016/j.jpainsymman.2007.12.019
Volume 37
Issue 1
Start page 44
End page 57
Total pages 13
Editor Russell K. Portenoy
Place of publication New York, N.Y., U.S.A.
Publisher Elsevier Science
Collection year 2010
Language eng
Subject 320206 Tumor Immunology
920102 Cancer and Related Disorders
119999 Medical and Health Sciences not elsewhere classified
Abstract The purpose of this study was to translate the Memorial Symptom Assessment Scale (MSAS) into Chinese and evaluate the psychometric properties of this version. The original MSAS is a 32-item, patient-rated measure that was developed to assess common cancer-related physical and psychological symptoms with respect to frequency, intensity, and distress. In this study, a two-phase design was used. Phase I involved iterative forward–backward translation, testing of content validity (CVI) and a pretest. Phase II established the psychometric properties of the Chinese version MSAS (MSAS-Ch). Results showed that the MSAS-Ch achieved content relevancy CVI of 0.94 and semantic equivalence CVI of 0.94. Pretesting was performed in 10 cancer patients, and the results revealed adequate content coverage and comprehensibility of the MSAS-Ch. A convenience sample of 370 patients undergoing cancer therapy or at the early post-treatment stage was recruited for psychometric evaluation. Confirmatory factor analysis confirmed the construct validity of the MSAS-Ch, with a good fit between the factor structure of the original version and our present sample data (goodness-of-fit indices all above 0.95). The internal consistency reliability of subscales and total MSAS-Ch was moderately high, with Cronbach alpha coefficients ranging from 0.79 to 0.87. The test–retest intraclass correlation results for the subscale and total MSAS-Ch ranged from 0.68 to 0.79. The subscale scores of MSAS-Ch were moderately correlated with the scores on various validation measurements that assessed psychological distress, pain, and health-related quality of life (r = 0.46–0.65, P < 0.01), confirming that they were measurements of similar constructs. The validity of the construct validity was also supported by comparing the MSAS-Ch scores for subpopulations that varied clinically. Inpatients and patients with poorer performance status scored higher on the MSAS-Ch subscale and total scores than outpatients and patients with higher performance status (P < 0.05). Our study shows that the MSAS-Ch has adequate psychometric properties of validity and reliability, and can be used to assess symptoms during cancer therapy and at the early post-treatment stage in Chinese-speaking patients.
Keyword symptoms
References 1. Naughton M, Homsi J. Symptom assessment in cancer patients. Curr Oncol Rep 2002;4:256e263. 2. Portenoy RK, Thaler HT, Kornblith AB, et al. The Memorial Symptom Assessment Scale: an instrument for the evaluation of symptom prevalence, characteristics and distress. Eur J Cancer 1994; 30A(9):1326e1336. 3. Chang VT, Hwang SS, Feuerman M, et al. Symptom and quality of life survey of medical oncology patients at a Veterans Affairs Medical Center: a role for symptom assessment. Cancer 2000;88: 1175e1183. 4. Donnelly S, Walsh D, Rybicki L. The symptoms of advanced cancer: identification of clinical and research priorities by assessment of prevalence and severity. J Palliat Care 1995;11(1):27e32. 5. Ruthledge DM, McGuire C. Evidence-based symptom management. In: Yarbro CH, Frogge MH, Goodman M, eds. Cancer symptom management, 3rd ed. Sudbury, MA: Jones & Bartlett, 2003. 6. Paice JA. Assessment of symptom clusters in people with cancer. J Nat Cancer Instit Mono 2004;32:98e102. 7. Chang VT, Hwang SS, Feuerman M. Validation of the Edmonton Symptom Assessment Scale. Cancer 2000;88:2164e2171. 8. Portenoy RK, Thaler HT, Kornblith AB, et al. Symptom prevalence, characteristics and distress in a cancer population. Qual Life Res 1994;3: 183e189. 9. Tranmer JE, Heyland D, Dudgeon D, et al. Measuring the symptom experience of seriously ill cancer and noncancer hospitalized patients near the end of life with the Memorial Symptom Assessment Scale. J Pain Symptom Manage 2003;25:420e429. 10. Armstrong TS. Symptoms experience: a concept analysis. Oncol Nurs Forum 2003;30(4):601e606. 11. Alexander J. Symptom management. In: Gukkatte MM, ed. Clinical guide to antineoplastic therapy: a chemotherapy handbook. Pittsburgh, PA: Oncology Nursing Society, 2001: 297e313. 12. Brescia FJ, Adler D, Gray G, et al. Hospitalized advanced cancer patients: a profile. J Pain Symptom Manage 1990;5:221e227. 13. Coyle N, Adelhardt J, Foley KM, Portenoy RK. Character of terminal illness in the advanced cancer patient: pain and other symptoms during the last four weeks of life. J Pain Symptom Manage 1990;5:85e93. 14. Kutner JS, Bryant LL, Beaty BL, et al. Time course and characteristics of symptom distress and quality of life at the end of life. J Pain Symptom Manage 2007;5:85e93. 15. Vainio A, Auvinen A. Prevalence of symptoms among patients with advanced cancer: an international collaborative study. J Pain Symptom Manage 1996;12(1):3e10. 16. Collins JJ, Devine TD, Dick GS, et al. The measurement of symptoms in young children with cancer: the validation of the Memorial Symptom Assessment Scale in children aged 7e12. J Pain Symptom Manage 2002;23(1):10e16. 17. Yu CLM, Fielding R, Chan CLW, et al. Measuring quality of life of Chinese cancer patients: a validation of the Chinese version of the functional assessment of cancer therapy-general (FACT-G) scale. Cancer 2000; 88:1715e1727. 18. Chan WH. The Chinese translation of the revised Piper Fatigue Scale and Symptom Distress Scale. Research Report, . The Chinese University of Hong Kong. Hong Kong: The Nethersole School of Nursing, 2000. 19. Wang XS, Mendoza TR, Gai S, Cleeland CS. The Chinese version of the Brief Pain Inventory (BPI-C): its development and use in a study of cancer pain. Pain 1996;67:407e416. 20. Yates JW, Chalmer B, McKegney FP. Evaluation of patients with advanced cancer using the Karnofsky Performance Status. Cancer 1980;40: 2222e2224. 21. Davis LL. Instrument review: getting the most from a panel of experts. Applied Nurs Res 1992;5: 194e197. 22. Haynes SN, Richard DCS, Kubany ES. Content validity in psychological assessment: a functional approach to concepts and methods. Psychol Assessment 1995;7:238e247. 23. Lynn MR. Determination and quantification of content validity. Nurs Res 1986;35(6):382e385. 24. Alexander M, Berger W, Buchholz P, et al. The reliability, validity, and preliminary responsiveness of the eye allergy patient impact questionnaire. Health Qual Life Outcomes 2005;3(1):67. 25. Gaul W, Schader M. The robustness of LISREL unweighted squares estimation against small sample size in confirmatory factor analysis models. In: Gaul W, Schader M, eds. Classification as a tool of research. Amsterdam: Elsevier Science Publishers, 1986: 3e10. 26. Steiger JH. Changing causal relationships without changing the fit: some rules for generating equivalent LISREL models. Multivariate Behav Res 1990;21:309e331. 27. Tucker L, Lewis C. A reliability coefficient for maximum likelihood factor analysis. Psychometrika 1973;38:1e10. 28. Bentler PM, Bonett DG. Significance tests and goodness of fit in the analysis of covariance structures. Psychol Bull 1980;88:588e606. 29. MacCallum RC, Hong S. Power analysis in covariance structure modeling using GFI and AGFI. Multivariate Behav Res 1997;32:193e210. 30. Marsh HW, Balla JR, Hau KT. An evaluation of incremental fit indices: a clarification of mathematical and empirical properties. In: Marcoulides GA, Schumacker RE, eds. Advanced structural equation modelling: Issues and techniques. Hillsdale, NJ: Erlbaum Publishers, 1996: 315e535. 31. Hu L, Bentler PM. Cutoff criteria for fit indexes in covariance structure analysis: conventional criteria versus new alternatives. Struct Equation Model 1999;6(1):1e55. 32. Pett MA, Lackey NR, Sullivan JJ. Making sense of factor analysis: The use of factor analysis in health care research. Thousand Oaks, CA: Sage Publications, 2003. 33. Nunnally JC, Bernstein IH. Psychometric theory, 3rd ed. New York: McGraw-Hill, 1994. 34. Bland JM, Altman DG. Statistical methods for assessing agreement between two methods of clinical measurement. Lancet 1986;1:307e310. 35. Sitzia J, Dikken C, Hughes J. Psychometric evaluation of a questionnaire to document side-effects of chemotherapy. J Advanced Nurs 1997;25: 999e1007. 36. Denegar CR, Ball DW. Assessing reliability and precision of measurement: an introduction to intraclass correlation and standard error of measurement. J Sport Rehab 1993;2:35e42. 37. Homsi J, Walsh D, Rivera N, et al. Symptom evaluation in palliative medicine: patients report vs systematic assessment. Support Care Cancer 2006; 14(5):444e453.
Q-Index Code C1
Q-Index Status Confirmed Code

Document type: Journal Article
Sub-type: Article (original research)
Collections: 2010 Higher Education Research Data Collection
School of Nursing, Midwifery and Social Work Publications
Version Filter Type
Citation counts: TR Web of Science Citation Count  Cited 22 times in Thomson Reuters Web of Science Article | Citations
Scopus Citation Count Cited 19 times in Scopus Article | Citations
Google Scholar Search Google Scholar
Created: Tue, 05 May 2009, 09:54:27 EST by Vicki Percival on behalf of School of Nursing, Midwifery and Social Work