The figure-of-eight walk test is a reliable and valid test for assessing walking skill in people with multiple sclerosis

Published:August 09, 2022DOI:


      • The F8W is a reliable and clinically available tool in assessing walking skill.
      • MDC of 1.25 s on the F8W can be used to determine real change in walking skill for MS.
      • The F8W is associated with MS-related impairments.
      • F8W times differentiate between PwMS and healthy controls.
      • A cut-off time of 8.52 s on the F8W may help clinicians to discriminate fall risk in PwMS.



      The ability to turn while walking is essential for people's activities of daily living. Difficulties in turning while walking are commonly shown in people with multiple sclerosis (PwMS). The figure-of-eight walk test (F8W) is a clinical test assessing walking skill in a curved pathway; however, its reliability and validity have not been systematically examined for PwMS.


      The study is aimed to investigate: (1) the test-retest reliability of the F8W in PwMS; (2) the standard error of measurement and minimum detectable change in the F8W times; (3) the concurrent and known-groups validity of the F8W times; and (4) the cut-off times that best discriminate fallers from non-fallers with MS.


      This cross-sectional study included 41 PwMS and 33 healthy people. The F8W was performed along with the Timed Up and Go Test (TUG), Berg Balance Scale (BBS), Activities-specific Balance Confidence Scale (ABC), and Expanded Disability Status Scale (EDSS). To determine the test-retest reliability, the F8W was conducted twice, 7–10 days apart. The reliability was assessed using the intraclass correlation coefficient (ICC), Bland-Altman plots, standard error of measurement (SEM), and minimal detectable change (MDC). To examine validity, the correlations between the F8W and the TUG, BBS, ABC, and EDSS were assessed using correlation coefficients, and the completion times of the F8W were compared between PwMS and healthy people, and between fallers and non-fallers with MS. The receiver operating characteristic curve was constructed to determine the optimal F8W cut-off time discriminating fallers from non-fallers with MS.


      The F8W had excellent test-retest reliability with an ICC of 0.916. Bland-Altman plots showed high agreement between sessions. The SEM and MDC were found to be 0.45 and 1.25, respectively. The F8W indicated a moderate to strong correlation with other outcome measures (correlation coefficients ranged from -0.596 to 0.839, p<0.05). On the F8W, PwMS had a longer time than healthy people while fallers had a longer time than non-fallers with MS (p<0.001, and p<0.001, respectively). The cut-off time of 8.52 s best discriminated the fallers from non-fallers with MS.


      The F8W is a reliable and clinically available measurement tool for walking skill in PwMS.


      To read this article in full you will need to make a payment

      Purchase one-time access:

      Academic & Personal: 24 hour online accessCorporate R&D Professionals: 24 hour online access
      One-time access price info
      • For academic or personal research use, select 'Academic and Personal'
      • For corporate R&D use, select 'Corporate R&D Professionals'


      Subscribe to Multiple Sclerosis and Related Disorders
      Already a print subscriber? Claim online access
      Already an online subscriber? Sign in
      Institutional Access: Sign in to ScienceDirect


        • Adusumilli G.
        • Lancia S.
        • Levasseur V.A.
        • Amblee V.
        • Orchard M.
        • Wagner J.M.
        • Naismith R.T.
        Turning is an important marker of balance confidence and walking limitation in persons with multiple sclerosis.
        PLoS ONE. 2018; 13e0198178
        • Altman D.G.
        • Bland J.M.
        Statistics Notes: diagnostic tests 2: predictive values.
        BMJ. 1994; 309: 102
        • Berg K.
        • Wood-Dauphine S.
        • Williams J.
        • Gayton D.
        Measuring balance in the elderly: preliminary development of an instrument.
        Physiother. Can. 1989; 41: 304-311
        • Bland J.M.
        • Altman D.
        Statistical methods for assessing agreement between two methods of clinical measurement.
        Lancet. 1986; 327: 307-310
        • Cameron M.H.
        • Wagner J.M.
        Gait abnormalities in multiple sclerosis: pathogenesis, evaluation, and advances in treatment.
        Curr. Neurol Neurosci. Rep. 2011; 11: 507-515
        • Campbell J.D.
        • Ghushchyan V.
        • McQueen R.B.
        • Cahoon-Metzger S.
        • Livingston T.
        • Vollmer T.
        • et al.
        Burden of multiple sclerosis on direct, indirect costs and quality of life: national US estimates.
        Mult. Scler. Relat. Disord. 2014; 3: 227-236
        • Cheng F.Y.
        • Yang Y.R.
        • Wang C.J.
        • Wu Y.R.
        • Cheng S.J.
        • Wang H.C.
        • et al.
        Factors influencing turning and its relationship with falls in individuals with Parkinson's disease.
        PLoS ONE. 2014; 9: e93572
        • Comber L.
        • Galvin R.
        • Coote S.
        Gait deficits in people with multiple sclerosis: a systematic review and meta-analysis.
        Gait Posture. 2017; 51: 25-35
        • Coote S.
        • Sosnoff J.J.
        • Gunn H.
        Fall incidence as the primary outcome in multiple sclerosis falls-prevention trials: recommendation from the International MS Falls Prevention Research Network.
        Int. J. MS Care. 2014; 16: 178-184
        • Courtine G.
        • Schieppati M.
        Human walking along a curved path. I. Body trajectory, segment orientation and the effect of vision.
        Eur. J. Neurosci. 2003; 18: 177-190
        • Courtine G.
        • Schieppati M.
        Human walking along a curved path. II. Gait features and EMG patterns.
        Eur. J. Neurosci. 2003; 18: 191-205
        • Flansbjer U.B.
        • Holmbäck A.M.
        • Downham D.
        • Patten C.
        • Lexell J.
        Reliability of gait performance tests in men and women with hemiparesis after stroke.
        J. Rehabil. Med. 2005; 37: 75-82
        • Fleiss J.L.
        • Levin B.
        • Paik M.C.
        Statistical Methods for Rates and Proportions.
        3rd Ed. John Wiley & Sons, New York, NY2013
        • Ganesan M.
        • Kanekar N.
        • Aruin A.S.
        Direction-specific impairments of limits of stability in individuals with multiple sclerosis.
        Ann. Phys. Rehabil. Med. 2015; 58: 145-150
        • Gianni C.
        • Prosperini L.
        • Jonsdottir J.
        • Cattaneo D.
        A systematic review of factors associated with accidental falls in people with multiple sclerosis: a meta-analytic approach.
        Clin. Rehabil. 2014; 28: 704-716
        • Givon U.
        • Zeilig G.
        • Achiron A.
        Gait analysis in multiple sclerosis: characterization of temporal–spatial parameters using GAITRite functional ambulation system.
        Gait Posture. 2009; 29: 138-142
        • Gunn H.
        • Creanor S.
        • Haas B.
        • Marsden J.
        • Freeman J.
        Frequency, characteristics, and consequences of falls in multiple sclerosis: findings from a cohort study.
        Arch. Phys. Med. Rehabil. 2014; 95: 538-545
        • Heesen C.
        • Böhm J.
        • Reich C.
        • Kasper J.
        • Goebel M.
        • Gold S.M.
        Patient perception of bodily functions in multiple sclerosis: gait and visual function are the most valuable.
        Mult. Scler. 2008; 14: 988-991
        • Hess R.J.
        • Brach J.S.
        • Piva S.R.
        • VanSwearingen J.M.
        Walking skill can be assessed in older adults: validity of the figure-of-8 walk test.
        Phys. Ther. 2010; 90: 89-99
        • Huang S.L.
        • Hsieh C.L.
        • Wu R.M.
        • Tai C.H.
        • Lin C.H.
        • Lu W.S.
        Minimal detectable change of the timed “up & go” test and the dynamic gait index in people with Parkinson disease.
        Phy. Ther. 2011; 91: 114-121
        • Kaipust J.P.
        • Huisinga J.M.
        • Filipi M.
        • Stergiou N.
        Gait variability measures reveal differences between multiple sclerosis patients and healthy controls.
        Motor Control. 2012; 16: 229-244
        • Kurtzke J.F.
        On the origin of EDSS.
        Mult. Scler. Relat. Disord. 2015; 4: 95-103
        • Lam T.
        • Luttmann K.
        Turning capacity in ambulatory individuals poststroke.
        Am. J. Phys. Med. Rehabil. 2009; 88: 873-883
        • Lamb S.E.
        • Jorstad-Stein E.C.
        • Hauer K.
        • Becker C.
        Prevention of falls network europe and outcomes consensus group 2005 development of am common outcome data set for fall injury prevention trials: the prevention of falls network Europe consensus.
        J. Am. Geriatr. Soc. 2005; 53: 1618-1622
        • LaRocca N.G.
        Impact of walking impairment in multiple sclerosis: perspectives of patients and care partners.
        Patient. 2011; 4: 189-201
        • Lexell J.E.
        • Downham D.Y.
        How to assess the reliability of measurements in rehabilitation.
        Am. J. Phys. Med. Rehabil. 2005; 84: 719-723
        • Martin C.L.
        • Phillips B.A.
        • Kilpatrick T.
        • Butzkueven H.
        • Tubridy N.
        • McDonald E.
        • et al.
        Gait and balance impairment in early multiple sclerosis in the absence of clinical disability.
        Mult. Scler. 2006; 12: 620-628
        • Matsuda P.N.
        • Shumway-Cook A.
        • Bamer A.M.
        • Johnson S.L.
        • Amtmann D.
        • Kraft G.H.
        Falls in multiple sclerosis.
        PM&R. 2011; 3: 624-632
        • Montalban X.
        • Graves J.
        • Midaglia L.
        • Mulero P.
        • Julian L.
        • Baker M.
        • et al.
        A smartphone sensor-based digital outcome assessment of multiple sclerosis.
        Mult. Scler. 2021; 14135245852110285
        • Patla A.E.
        • Adkin A.
        • Ballard T.
        Online steering: coordination and control of body center of mass, head and body reorientation.
        Exp. Brain Res. 1999; 129: 629-634
        • Patla A.E.
        • Prentice S.D.
        • Robinson C.
        • Neufeld J.
        Visual control of locomotion: strategies for changing direction and for going over obstacles.
        J. Exp. Psychol. Hum. Percep. Perform. 1991; 17: 603-634
        • Pau M.
        • Porta M.
        • Coghe G.
        • Corona F.
        • Pilloni G.
        • Lorefice L.
        • et al.
        Are static and functional balance abilities related in individuals with multiple sclerosis?.
        Mult. Scler. Relat. Disord. 2017; 15: 1-6
        • Podsiadlo D.
        • Richardson S.
        The timed “Up & Go”: a test of basic functional mobility for frail elderly persons.
        J. Am. Geriatr. Soc. 1991; 39: 142-148
        • Polman C.H.
        • Reingold S.C.
        • Banwell B.
        • Clanet M.
        • Cohen J.A.
        • Filippi M.
        Diagnostic criteria for multiple sclerosis: 2010 revisions to the McDonald criteria.
        Ann. Neurol. 2011; 69: 292-302
        • Portney L.G.
        • Watkins M.P.
        Foundations of Clinical Research: Applications to Practice.
        Pearson/Prentice Hall, Upper Saddle River, NJ2009
        • Powell L.E.
        • Myers A.M.
        The activities-specific balance confidence (ABC) scale.
        J. Gerontol. A. Biol. Sci. Med. Sci. 1995; 50: 28-34
        • Quinn G.
        • Comber L.
        • Galvin R.
        • Coote S.
        The ability of clinical balance measures to identify falls risk in multiple sclerosis: a systematic review and meta-analysis.
        Clin. Rehabil. 2018; 32: 571-582
        • Robinson R.L.
        • Ng S.S.
        The timed 180 turn test for assessing people with hemiplegia from chronic stroke.
        Biomed Res. Int. 2018; 20189629230
        • Segal A.D.
        • Orendurff M.S.
        • Czerniecki J.M.
        • Shofer J.B.
        • Klute G.K.
        Local dynamic stability in turning and straight-line gait.
        J. Biomech. 2008; 41: 1486-1493
        • Shumway-Cook A.
        • Woollacott M.H.
        Motor Control: Theory and Practical Applications.
        2nd Ed. Lippincott Williams & Wilkins, Philadelphia2001
        • Socie M.J.
        • Sosnoff J.J.
        Gait variability and multiple sclerosis.
        Mult. Scler. Int. 2013; 2013645197
        • Soke F.
        • Erkoc Ataoglu N.E.
        • Ozcan Gulsen E.
        • Yilmaz O.
        • Gulsen C.
        • Kocer B.
        • et al.
        The psychometric properties of the figure-of-eight walk test in people with Parkinson's disease.
        Disabil. Rehabil. 2022; : 1-9
        • Soke F.
        • Guclu-Gunduz A.
        • Ozkul C.
        • Cekim K.
        • Irkec C.
        • Gonenli Kocer B.
        Reliability and validity of the timed 360° turn test in people with multiple sclerosis.
        Physiother. Theory Pract. 2021; 37: 736-747
        • Sosnoff J.J.
        • Socie M.J.
        • Boes M.K.
        • Sandroff B.M.
        • Pula J.H.
        • Suh Y.
        • et al.
        Mobility, balance and falls in persons with multiple sclerosis.
        PLoS ONE. 2011; 6: e28021
        • Spain R.
        • George R.S.
        • Salarian A.
        • Mancini M.
        • Wagner J.
        • Horak F.
        • et al.
        Body-worn motion sensors detect balance and gait deficits in people with multiple sclerosis who have normal walking speed.
        Gait Posture. 2012; 35: 573-578
        • Swets J.A.
        Measuring the accuracy of diagnostic systems.
        Science. 1988; 240: 1285-1293
        • Tajali S.
        • Shaterzadeh-Yazdi M.J.
        • Negahban H.
        • van Dieën J.H.
        • Mehravar M.
        • Majdinasab N.
        • et al.
        Predicting falls among patients with multiple sclerosis: comparison of patient-reported outcomes and performance-based measures of lower extremity functions.
        Mult. Scler. Relat. Disord. 2017; 17: 69-74
        • Thigpen M.T.
        • Light K.E.
        • Creel G.L.
        • Flynn S.M.
        Turning difficulty characteristics of adults aged 65 years or older.
        Phys. Ther. 2000; 80: 1174-1187
        • Turner D.
        • Schünemann H.J.
        • Griffith L.E.
        • Beaton D.E.
        • Griffiths A.M.
        • Critch J.N.
        • et al.
        The minimal detectable change cannot reliably replace the minimal important difference.
        J. Clin. Epidemiol. 2010; 63: 28-36
        • Wong S.S.
        • Yam M.S.
        • Ng S.S.
        The Figure-of-Eight Walk test: reliability and associations with stroke-specific impairments.
        Disabil. Rehabil. 2013; 35: 1896-1902
        • Youden W.J.
        Index for rating diagnostic tests.
        Cancer. 1950; 3: 32-35