Italian translation and psychometric validation of the Manual Ability Measure-36 (MAM-36) and its correlation with an objective measure of upper limb function in patients with multiple sclerosis.
Activities of Daily Living
Adolescent
Adult
Aged
Aged, 80 and over
Female
Humans
Italy
Male
Middle Aged
Motor Skills
/ physiology
Multiple Sclerosis
/ diagnosis
Neuropsychological Tests
Psychometrics
/ instrumentation
Reproducibility of Results
Severity of Illness Index
Translating
Upper Extremity
/ physiopathology
Young Adult
9-HPT
MAM-36
Multiple sclerosis
Upper limb function
Journal
Neurological sciences : official journal of the Italian Neurological Society and of the Italian Society of Clinical Neurophysiology
ISSN: 1590-3478
Titre abrégé: Neurol Sci
Pays: Italy
ID NLM: 100959175
Informations de publication
Date de publication:
Jun 2020
Jun 2020
Historique:
received:
06
07
2019
accepted:
18
01
2020
pubmed:
25
1
2020
medline:
27
2
2021
entrez:
25
1
2020
Statut:
ppublish
Résumé
Multiple sclerosis (MS) is a chronic autoimmune disease of the central nervous system with an unpredictable course. During its course, deficits affecting upper limb functions may occur. Hence, there is a need for self-administered scales providing a comprehensive assessment of upper limb functions. The Manual Ability Measure-36 (MAM-36), which investigates patients' performance in activities of daily living requiring upper limb function, has not been adapted and validated in the Italian context. We develop an Italian translation and validation of the MAM-36 in a population of people with MS (PwMS), explore its psychometric properties and investigate its associations with clinical data and the Nine Hole Peg Test (9-HPT). The multicentre study involved five Italian neurological centres. Subjects were evaluated using EDSS, 9-HPT and the MAM-36 scale. We used confirmatory factor analysis and Rasch analysis to investigate the properties of the MAM-36. We enrolled 218 PwMS. Results supported the unidimensionality of the MAM-36, and adequate functioning of rating scale and items. Additionally, the MAM-36 showed weak negative associations with age and disease duration, and moderate associations with EDSS and 9-HPT scores. The adapted MAM-36 showed adequate psychometric properties. However, indications of problematic targeting to PwMS with low disability emerged. For this reason, use of the scale appears to be more suitable among patients with moderate-to-severe disability.
Sections du résumé
BACKGROUND
BACKGROUND
Multiple sclerosis (MS) is a chronic autoimmune disease of the central nervous system with an unpredictable course. During its course, deficits affecting upper limb functions may occur. Hence, there is a need for self-administered scales providing a comprehensive assessment of upper limb functions. The Manual Ability Measure-36 (MAM-36), which investigates patients' performance in activities of daily living requiring upper limb function, has not been adapted and validated in the Italian context.
OBJECTIVES
OBJECTIVE
We develop an Italian translation and validation of the MAM-36 in a population of people with MS (PwMS), explore its psychometric properties and investigate its associations with clinical data and the Nine Hole Peg Test (9-HPT).
RESEARCH PLAN AND METHODS
UNASSIGNED
The multicentre study involved five Italian neurological centres. Subjects were evaluated using EDSS, 9-HPT and the MAM-36 scale. We used confirmatory factor analysis and Rasch analysis to investigate the properties of the MAM-36.
RESULTS
RESULTS
We enrolled 218 PwMS. Results supported the unidimensionality of the MAM-36, and adequate functioning of rating scale and items. Additionally, the MAM-36 showed weak negative associations with age and disease duration, and moderate associations with EDSS and 9-HPT scores.
DISCUSSION
CONCLUSIONS
The adapted MAM-36 showed adequate psychometric properties. However, indications of problematic targeting to PwMS with low disability emerged. For this reason, use of the scale appears to be more suitable among patients with moderate-to-severe disability.
Identifiants
pubmed: 31974795
doi: 10.1007/s10072-020-04263-2
pii: 10.1007/s10072-020-04263-2
doi:
Types de publication
Journal Article
Multicenter Study
Validation Study
Langues
eng
Sous-ensembles de citation
IM
Pagination
1539-1546Subventions
Organisme : Fondazione Italiana Sclerosi Multipla
ID : Grant 2014/R20
Références
McDonald I, Compston A (2006) The symptoms and signs of multiple sclerosis. In: Compston A, Ebers G, Lassmann H (eds) McAlpine’s multiple sclerosis, 4th edn. Curchill Livingstone, London, pp 287–346
doi: 10.1016/B978-0-443-07271-0.50008-2
Johansson S, Ytterberg C, Claesson IM, Lindberg J, Hillert J, Andersson M, Widén Holmqvist L, von Koch L (2007) High concurrent presence of disability in multiple sclerosis. Associations with perceived health. J Neurol 254(6):767–773
doi: 10.1007/s00415-006-0431-5
Lamers I, Feys P (2014) Assessing upper limb function in multiple sclerosis. Mult Scler 20:775–784
doi: 10.1177/1352458514525677
Yalachkov Y, Soydaş D, Bergmann J, Frisch S, Behrens M, Foerch C, Gehrig J (2019) Determinants of quality of life in relapsing-remitting and progressive multiple sclerosis. Mult Scler Relat Disord May 30:33–37
doi: 10.1016/j.msard.2019.01.049
Kratz AL, Braley TJ, Foxen-Craft E, Scott E, Murphy JF 3rd, Murphy SL. (2017) How do pain, fatigue, depressive, and cognitive symptoms relate to well-being and social and physical functioning in the daily lives of individuals with multiple sclerosis? Arch Phys Med Rehabil. Nov;98(11):2160–2166
Yozbatiran N, Baskurt F, Baskurt Z, Ozakbas S, Idiman E (2006) Motor assessment of upper extremity function and its relation with fatigue, cognitive function and quality of life in multiple sclerosis patients. J Neurol Sci 246(1-2):117–122
doi: 10.1016/j.jns.2006.02.018
Bertoni R, Lamers I, Chen CC, Feys P, Cattaneo D (2015) Unilateral and bilateral upper limb dysfunction at body functions, activity and participation levels in people with multiple sclerosis. Mult Scler 21(12):1566–1574
doi: 10.1177/1352458514567553
Kurtzke JF (1983) Rating neurologic impairment in multiple sclerosis: an expanded disability status scale (EDSS). Neurology 33(11):1444–1452
pubmed: 6685237
Feys P, Lamers I, Francis G et al (2017) The Nine-Hole Peg Test as a manual dexterity performance measure for multiple sclerosis. Mult Scler 23(5):711–720
doi: 10.1177/1352458517690824
Kierkegaard M, Einarsson U, Gottberg K, von Koch L, Holmqvist LW (2012) The relationship between walking, manual dexterity, cognition and activity/participation in persons with multiple sclerosis. Mult Scler 18(5):639–646
doi: 10.1177/1352458511426736
Solaro C, Cattaneo D, Brichetto G, Castelli L, Tacchino A, Gervasoni E, Prosperini L (2019) Clinical correlates of 9-Hole Peg Test in a large population of people with multiple sclerosis. Mult Scler Relat Disord 30:1–8
doi: 10.1016/j.msard.2019.01.043
Lamers I, Kelchtermans S, Baert I, Feys P (2014) Upper limb assessment in multiple sclerosis: a systematic review of outcome measures and their psychometric properties. Arch Phys Med Rehabil 95(6):1184–1200
doi: 10.1016/j.apmr.2014.02.023
Penta M, Thonnard JL, Tesio L (1998) ABILHAND: a Rasch-built measure of manual ability. Arch Phys Med Rehabil 79(9):1038–1042
doi: 10.1016/S0003-9993(98)90167-8
Brichetto G, Bragadin MM, Fiorini S, Battaglia MA, Konrad G, Ponzio M, Pedullà L, Verri A, Barla A, Tacchino A (2019) The hidden information in patient-reported outcomes and clinician-assessed outcomes: multiple sclerosis as a proof of concept of a machine learning approach. Neurol Sci:1–4
Kahraman T (2018) Performance measures for upper extremity functions in persons with multiple sclerosis. Arch Neuropsychiatry 55(Suppl 1):S41–S45
Poole JL, Huffman M, Hunter A, Mares C, Siegel P (2015) Reliability and validity of the Manual Ability Measure-36 in persons with Charcot-Marie-Tooth disease. J Hand Ther 28(4):364
doi: 10.1016/j.jht.2015.04.003
Tsai CL, Lin CF, Lin HT, Liu MF, Chiu HY, Hsu HY, Kuo LC (2017) How kinematic disturbance in the deformed rheumatoid thumb impacts on hand function: a biomechanical and functional perspective. Disabil Rehabil 39(4):338–345
doi: 10.3109/09638288.2016.1141244
Chen CC, Bode RK (2010) Psychometric validation of the Manual Ability Measure-36 (MAM-36) in patients with neurologic and musculoskeletal disorders. Arch Phys Med Rehabil 91:414–420
doi: 10.1016/j.apmr.2009.11.012
Rallon CR, Chen CC (2008) Relationship between performance-based and self-reported assessment of hand function. Am J Occup Ther:62
Chen CC, Kasven N, Karpatkin HI, Sylvester A (2007) Hand strength and perceived manual ability among patients with multiple sclerosis. Arch Phys Med Rehabil 88(6):794–797
doi: 10.1016/j.apmr.2007.03.010
Polman CH, Reingold SC, Banwell B, Clanet M, Cohen JA, Filippi M et al (2011) Diagnostic criteria for multiple sclerosis: 2010 revisions to the McDonald criteria. Ann Neurol 69(2):292–302
doi: 10.1002/ana.22366
Snijders T, Bosker R (2012) Multilevel analysis: an introduction to basic and advanced multilevel modeling, 2nd edn. Sage, Thousand Oaks
Lai MHC, Kwok O (2015) Examining the rule of thumb of not using multilevel modeling: the “design effect smaller than two” rule. J Exp Educ 83:423–438
doi: 10.1080/00220973.2014.907229
Hu L, Bentler PM (1999) Cutoff criteria for fit indexes in covariance structure analysis: conventional criteria versus new alternatives. Struct Equ Model Multidiscip J 6(1):1–55
doi: 10.1080/10705519909540118
Hair JF Jr, Black WC, Babin BJ, Anderson RE (2009) Multivariate data analysis, 7th edn. Prentice Hall, Upper Saddle River, p 761
McDonald RP (1985) Factor analysis and related methods. Lawrence Erlbaum Associates, Inc, Hillsdale
Fornell C, Larcker DF (1981) Evaluating structural equation models with unobservable variables and measurement error. J Mark Res 18(1):39–50
doi: 10.1177/002224378101800104
Andrich D (1978) A rating formulation for ordered response categories. Psychometrika 43:561–573
doi: 10.1007/BF02293814
Linacre JM (2002a) Optimizing rating scale category effectiveness. J Appl Meas 3(1):85–106
Bond TG, Fox CM (2007) Applying the Rasch model: fundamental measurement in the human sciences. 2nd. Lawrence Erlbaum Associates Publishers. Chapter 12
Linacre JM (2002b) What do Infit and Outfit, mean-square and standardized mean? Rasch Measurement Transactions 16:878
Bland JM, Altman DG (1997) Cronbach’s alpha. BMJ 314(7080):572
doi: 10.1136/bmj.314.7080.572
Fisher WJ (1992) Reliability, separation, strata statistics. Rasch Meas Trans 6:328
Linacre JM (2006) Data variance explained by Rasch measures. Rasch Measurement Transactions 20(1):1045
Smith EV Jr (2002) Detecting and evaluating the impact of multidimensionality using item fit statistics and principal component analysis of residuals. J Appl Meas 3(2):205–231
pubmed: 12011501
Erasmus LP, Sarno S, Albrecht H, Schwecht M, Pöllmann W, König N (2001) Measurement of ataxic symptoms with a graphic tablet: standard values in controls and validity in multiple sclerosis patients. J Neurosci Methods 108(1):25–37
doi: 10.1016/S0165-0270(01)00373-9
Marengo D, Miceli R, Settanni M (2016) Do mixed item formats threaten test unidimensionality? Results from a standardized math achievement Test. TPM: Testing, Psychometrics, Methodology in Applied Psychology 23:25–36
doi: 10.17957/TPMJ/16.3104
Bandalos DL (2014) Relative performance of categorical diagonally weighted least squares and robust maximum likelihood estimation. Struct Equ Model 21:102–116
doi: 10.1080/10705511.2014.859510
Suen HK (1990) Principles of test theories. Lawrence Erlbaum, Hillsdale
Smith AB, Rush R, Fallowfield LJ, Velikova G, Sharpe M (2008) Rasch fit statistics and sample size considerations for polytomous data. BMC Med Res Methodol 8(1):33
doi: 10.1186/1471-2288-8-33