German translation, cultural adaptation and validation of the unidimensional self-efficacy scale for multiple sclerosis

Barbara Seebacher, Roger J Mills, Markus Reindl, Laura Zamarian, Simone Kircher, Christian Brenneis, Rainer Ehling, Florian Deisenhammer, Barbara Seebacher, Roger J Mills, Markus Reindl, Laura Zamarian, Simone Kircher, Christian Brenneis, Rainer Ehling, Florian Deisenhammer

Abstract

Background: Self-efficacy concerns individuals' beliefs in their capability to exercise control in specific situations and complete tasks successfully. In people with multiple sclerosis (PwMS), self-efficacy has been associated with physical activity levels and quality of life. As a validated German language self-efficacy scale for PwMS is missing the aims of this study were to translate the Unidimensional Self-Efficacy Scale for Multiple Sclerosis (USE-MS) into German, establish face and content validity and cultural adaptation of the German version for PwMS in Austria. A further aim was to validate the German USE-MS (USE-MS-G) in PwMS.

Methods: Permission to translate and validate the USE-MS was received from the scale developers. Following guidelines for translation and validation of questionnaires and applying Bandura's concept of self-efficacy, the USE-MS was forward-backward translated with content and face validity established. Cultural adaptation for Austria was performed using cognitive patient interviews. Reliability was assessed using Cronbach's alpha, Person separation index and Lin's concordance correlation coefficient. Rasch analysis was employed to assess construct validity. Comparison was made to scales for resilience, general self-efficacy, anxiety and depression, multiple sclerosis fatigue and health-related quality of life. Data were also pooled with an historic English dataset to compare the English and German language versions.

Results: The translation and cultural adaptation were successfully performed in the adaptation process of the USE-MS-G. Pretesting was conducted in 30 PwMS, the validation of the final USE-MS-G involved 309 PwMS with minimal to severe disability. The USE-MS-G was found to be valid against the Rasch model when fitting scale data using a bifactor solution of two super-items. It was shown to be unidimensional, free from differential item functioning and well targeted to the study population. Excellent convergent and known-groups validity, internal consistency, person separation reliability and test-retest reliability were shown for the USE-MS-G. Pooling of the English and German datasets confirmed invariance of item difficulties between languages.

Conclusion: The USE-MS-G is a robust, valid and reliable scale to assess self-efficacy in PwMS and can generate interval level data on an equivalent metric to the UK version.

Trial registration: ISRCTN Registry; ISRCTN14843579 ; prospectively registered on 02. 01. 2019.

Keywords: Austria; Cross-cultural comparison; Multiple sclerosis; Patient reported outcome measures; Self-efficacy; Validation studies.

Conflict of interest statement

The authors declare that they have no competing interests.

References

    1. Compston A, Confavreux C, Lassmann H, McDonald I, Miller D, Noseworthy J, et al. McAlpine’s multiple sclerosis. 4th ed edn. London: Elsevier; 2006.
    1. Bandura A. Social foundations of thought and action: a social cognitive theory. Englewood Cliffs: Prentice-Hall; 1986.
    1. Finn A. The relationship between self-efficacy and health promoting behaviors, illness severity, mental health, and perceived quality of life in multiple sclerosis patients. Modern Psychol Stud. 2006;11(2):Article 3.
    1. Rigby SA, Domenech C, Thornton EW, Tedman S, Young CA. Development and validation of a self-efficacy measure for people with multiple sclerosis: the multiple sclerosis self-efficacy scale. Mult Scler. 2003;9(1):73–81. doi: 10.1191/1352458503ms870oa.
    1. Young CA, Mills RJ, Woolmore J, Hawkins CP, Tennant A. The unidimensional self-efficacy scale for MS (USE-MS): developing a patient based and patient reported outcome. Mult Scler. 2012;18(9):1326–1333. doi: 10.1177/1352458512436592.
    1. Airlie J, Baker GA, Smith SJ, Young CA. Measuring the impact of multiple sclerosis on psychosocial functioning: the development of a new self-efficacy scale. Clin Rehabil. 2001;15(3):259–265. doi: 10.1191/026921501668362643.
    1. Rasch G. Probabilistic models for some intelligence and attainment tests. Chicago: University of Chicago Press; 1980.
    1. Kurtzke JF. Rating neurologic impairment in multiple sclerosis: an expanded disability status scale (EDSS) Neurology. 1983;33(11):1444–1452. doi: 10.1212/WNL.33.11.1444.
    1. McDonald WI, Compston A, Edan G, Goodkin D, Hartung HP, Lublin FD, et al. Recommended diagnostic criteria for multiple sclerosis: guidelines from the international panel on the diagnosis of multiple sclerosis. Ann Neurol. 2001;50(1):121–127. doi: 10.1002/ana.1032.
    1. Seebacher B, Mills RJ, Reindl M, Zamarian L, Kuisma R, Kircher S, et al. German translation, cultural adaption and validation of the unidimensional self-efficacy scale for multiple sclerosis: a study protocol. BMJ Open. 2019;9(8):e029565. doi: 10.1136/bmjopen-2019-029565.
    1. Linacre JM. Sample size and item calibration stability. Rasch Measure Transact. 1994;7(4):328.
    1. Linacre J. Understanding Rasch measurement: optimizing rating scale category effectiveness. J Appl Measure. 2002;3(1):85–106.
    1. Potter K, Cohen ET, Allen DD, Bennett SE, Brandfass KG, Widener GL, et al. Outcome measures for individuals with multiple sclerosis: recommendations from the American Physical Therapy Association neurology section task force. Phys Ther. 2014;94(5):593–608. 10.2522/ptj.20130149.
    1. Surveillance of Multiple sclerosis in adults: management (NICE guideline CG186). (2018). Accessed 29 Dec 2018.
    1. Schwarzer R, Jerusalem M. Generalized self-efficacy scale. In: Weinman J, Wright S, Johnston M, editors. Measures in health psychology: a user’s portfolio causal and control beliefs. Windsor, UK: NFER-NELSON; 1995. pp. 35–37.
    1. Leppert K, Koch B, Brähler E, Strauß B. Die Resilienzskala (RS) – Überprüfung der Langform RS-25 und einer Kurzform RS-13. Klinische Diagnostik und Evaluation. 2008;2:226–243.
    1. Simeoni M, Auquier P, Fernandez O, Flachenecker P, Stecchi S, Constantinescu C, et al. Validation of the multiple sclerosis international quality of life questionnaire. Mult Scler. 2008;14(2):219–30. 10.1177/1352458507080733.
    1. Zigmond AS, Snaith RP. The hospital anxiety and depression scale. Acta Psychiatr Scand. 1983;67(6):361–370. doi: 10.1111/j.1600-0447.1983.tb09716.x.
    1. Petermann F. Hospital anxiety and depression scale, deutsche version (HADS-D) Z Psychiatr Psychol Psychother. 2011;59(3):251–253. doi: 10.1024/1661-4747/a000077.
    1. Mills RJ, Young CA, Pallant JF, Tennant A. Rasch analysis of the modified fatigue impact scale (MFIS) in multiple sclerosis. J Neurol Neurosurg Psychiatry. 2010;81(9):1049–1051. doi: 10.1136/jnnp.2008.151340.
    1. Schwarzer R, Jerusalem ME. Skalen zur Erfassung von Lehrer- und Schülermerkmalen: Dokumentation der psychometrischen Verfahren im Rahmen der Wissenschaftlichen Begleitung des Modellversuchs Selbstwirksame Schulen. Berlin: Freie Universität Berlin; 1999.
    1. Schumacher J, Leppert K, Gunzelmann T, Strauß B, Brähler E. Die Resilienzskala – Ein Fragebogen zur Erfassung der psychischen Widerstandsfähigkeit als Personmerkmal. Z Klin Psychol Psychiatr Psychother. 2004;53:16–39.
    1. Wagnild GM, Young HM. Development and psychometric evaluation of the resilience scale. J Nurs Meas. 1993;1(2):165–178.
    1. Flachenecker P, Vogel U, Simeoni MC, Auquier P, Rieckmann P. MusiQol: international questionnaire investigating quality of life in multiple sclerosis: validation results for the German subpopulation in an international comparison. Der Nervenarzt. 2011;82(10):1281–1289. doi: 10.1007/s00115-011-3276-9.
    1. NFI-MS Neurologischer Fragebogen zur Müdigkeit. NFI-MS Austria/German - Version of 30 Sep 13 - Mapi ID7555 / NFI-MS_AU10_deu-ATdoc. 2010.
    1. Mills RJ, Young CA, Pallant JF, Tennant A. Development of a patient reported outcome scale for fatigue in multiple sclerosis: the neurological fatigue index (NFI-MS) Health Qual Life Outcomes. 2010;8(1):22. doi: 10.1186/1477-7525-8-22.
    1. Mills RJ, Calabresi M, Tennant A, Young CA. Perceived changes and minimum clinically important difference of the neurological fatigue index for multiple sclerosis (NFI-MS) Mult Scler. 2013;19(4):502–505. doi: 10.1177/1352458512457840.
    1. Beaton D, Bombardier C, Guillemin F, Ferraz M. Recommendations for the cross-cultural adaptation of the DASH & QuickDASH outcome measures. Toronto, Canada: Institute for Work and Health; 2007.
    1. Guillemin F, Bombardier C, Beaton D. Cross-cultural adaptation of health-related quality of life measures: literature review and proposed guidelines. J Clin Epidemiol. 1993;46(12):1417–1432. doi: 10.1016/0895-4356(93)90142-N.
    1. Gorecki C, Brown JM, Cano S, Lamping DL, Briggs M, Coleman S, Dealey C, McGinnis E, Nelson AE, Stubbs N et al: Development and validation of a new patient-reported outcome measure for patients with pressure ulcers: the PU-QOL instrument. Health and quality of life outcomes. 2013;11:95. 10.1186/1477-7525-11-95.
    1. Gustafsson J-E. Testing and obtaining fit of data to the Rasch model. Br J Math Stat Psychol. 1980;33(2):205–233. doi: 10.1111/j.2044-8317.1980.tb00609.x.
    1. Teresi JA, Kleinman M, Ocepek-Welikson K. Modern psychometric methods for detection of differential item functioning: application to cognitive assessment measures. Stat Med. 2000;19(11-12):1651–83. 10.1002/(SICI)1097-0258(20000615/30)19:11/12<1651::AID-SIM453>;2-H.
    1. Wainer H, Kiely G. Item clusters and computer adaptive testing: a case for testlets. J Educ Meas. 1987;24(3):185–202. doi: 10.1111/j.1745-3984.1987.tb00274.x.
    1. Andrich D. Components of variance of scales with a bifactor subscale structure from two calculations of α. Educ Meas Issues Pract. 2016;35(4):25–30. doi: 10.1111/emip.12132.
    1. Rodriguez A, Reise SP, Haviland MG. Evaluating bifactor models: calculating and interpreting statistical indices. Psychol Methods. 2016;21(2):137–150. doi: 10.1037/met0000045.
    1. Mokkink LB, Terwee CB, Patrick DL, Alonso J, Stratford PW, Knol DL, et al. The COSMIN study reached international consensus on taxonomy, terminology, and definitions of measurement properties for health-related patient-reported outcomes. J Clin Epidemiol. 2010;63(7):737–45. 10.1016/j.jclinepi.2010.02.006.
    1. Lin LI-K. A concordance correlation coefficient to evaluate reproducibility. Biometrics. 1989;45(1):255–268. doi: 10.2307/2532051.
    1. van Kampen DA, Willems WJ, van Beers LWAH, Castelein RM, Scholtes VAB, Terwee CB. Determination and comparison of the smallest detectable change (SDC) and the minimal important change (MIC) of four-shoulder patient-reported outcome measures (PROMs) J Orthop Surg Res. 2013;8(1):40. doi: 10.1186/1749-799X-8-40.
    1. Fisher WPJ. Rating Scale Instrument Quality Criteria. Rasch Measure Transact. 2007;21(1):1095.
    1. Nunnally JC, Bernstein IH. Psychometric theory. 3rd ed edn. New York: McGraw-Hill; 1994.
    1. de Vet HC, Terwee CB, Ostelo RW, Beckerman H, Knol DL, Bouter LM. Minimal changes in health status questionnaires: distinction between minimally detectable change and minimally important change. Health Qual Life Outcomes. 2006;4(1):54. doi: 10.1186/1477-7525-4-54.
    1. Beckerman H, Roebroeck ME, Lankhorst GJ, Becher JG, Bezemer PD, Verbeek AL. Smallest real difference, a link between reproducibility and responsiveness. Qual Life Res. 2001;10(7):571–578. doi: 10.1023/a:1013138911638.
    1. Hinkle DE, Wiersma W, Jurs SG. Applied statistics for the behavioral sciences. 5th ed edn. Boston: Houghton Mifflin; 2003.
    1. Hobart J, Cano S. Improving the evaluation of therapeutic interventions in multiple sclerosis: the role of new psychometric methods. Health Technol Assessment. 2009;13(12):iii. doi: 10.3310/hta13120.
    1. Pugliatti M, Rosati G, Carton H, Riise T, Drulovic J, Vecsei L, et al. The epidemiology of multiple sclerosis in Europe. Eur J Neurol. 2006;13(7):700–722. doi: 10.1111/j.1468-1331.2006.01342.x.
    1. Fraser C, Polito S. A comparative study of self-efficacy in men and women with multiple sclerosis. J Neurosci Nurs. 2007;39(2):102–106. doi: 10.1097/01376517-200704000-00006.
    1. Baumhackl U, Eibl G, Ganzinger U, Hartung HP, Mamoli B, Pfeiffer KP, et al. Prevalence of multiple sclerosis in Austria. Results of a nationwide survey. Neuroepidemiology. 2002;21(5):226–234. doi: 10.1159/000065640.

Source: PubMed

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