Getting the measure of spasticity in multiple
sclerosis: the Multiple Sclerosis Spasticity Scale
Brain (2005) Page 1 of 11
J. C. Hobart,1,2,3A. Riazi,2A. J. Thompson,2I. M. Styles,3W. Ingram,1P. J. Vickery,1M. Warner,1
P. J. Fox1and J. P. Zajicek1
1Peninsula Medical School, Plymouth,2Neurological Outcome Measures Unit, Institute of Neurology, London, UK and
3School of Education, Murdoch University, Perth, Western Australia
Correspondence to: Dr Jeremy Hobart, Senior Lecturer and Honorary Consultant Neurologist,
Department of Clinical Neuroscience, Peninsula Medical School, Room N16 ITTC Building, Tamar Science Park,
Davy Road, Plymouth, Devon PL6 8BX, UK
Spasticity is most commonly defined as an inappropriate, velocity dependent, increase in muscle tonic stretch
reflexes, due to the amplified reactivity of motor segments to sensory input. It forms one component of the
upper motor neuron syndrome and often leads to muscle stiffness and disability. Spasticity can, therefore, be
measured through electrophysiological, biomechanical and clinical evaluation, the last most commonly using
the Ashworth scale. None of these techniques incorporate the patient experience of spasticity, nor how it
affects people’s daily lives. Consequently, we set out to construct a rating scale to quantify the perspectives of
the impact of spasticity on people with multiple sclerosis. Qualitative methods (in-depth patient interviews and
focus groups, expert opinion and literature review) were used to develop a conceptual framework of spasticity
impact, and to generate a pool of items with the potential to convert this framework into a rating scale with
multiple sclerosis and spasticity. Guided by Rasch analysis, we constructed and validated a rating scale for each
componentoftheconceptualframework. Decisionsregardingitemselectionwere basedontheintegrationand
assimilation of seven specific analyses including clinical meaning, ordering of thresholds, fit statistics
and differential item functioning. The qualitative phase (17 patient interviews, 3 focus groups) generated
144 potential scale items and a conceptual model with eight components addressing symptoms (muscle stiff-
ness, pain and discomfort and muscle spasms,), physical impact (activities of daily living, walking and body
movements) and psychosocial impact (emotional health, social functioning). The first postal survey was sent to
272peoplewithmultiplesclerosis andhadaresponserateof 88%. Findings supported the developmentofscales
for each component but demonstrated that five item response options were too many. The 144-item ques-
tionnaire, reformatted with four-item response options, was administered with four validating instruments to
an independent sample of 259 people with multiple sclerosis (response rate 78%). From the responses, an 88-
item instrument with eight subscales was developed that satisfied criteria for reliable and valid measurement.
Correlations with other measures were consistent with predictions. The 88-item Multiple Sclerosis Spasticity
Scale (MSSS-88) is a reliable and valid, patient-based, interval-level measure of the impact of spasticity in
multiple sclerosis. It has the potential to advance outcomes measurement in clinical trials and clinical practice,
and provides a new perspective in the clinical evaluation of spasticity.
Spasticity Scale; MSIS-29 = Multiple Sclerosis Impact Scale
Received March 30, 2005. Revised September 30, 2005. Accepted October 4, 2005
#The Author (2005). Published by Oxford University Press on behalf of the Guarantors of Brain. All rights reserved. For Permissions, please email: firstname.lastname@example.org
Brain Advance Access published November 9, 2005
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Spasticity is common, clinically and pathophysiologically
complex, and disabling. It affects at least 35% of people
post-stroke (Watkins et al., 2002) and up to 90% of people
with multiple sclerosis at some point (Paty and Ebers, 1998).
A range of treatments is available including spasticity
reduction strategies, specialist rehabilitation therapy, oral
intrathecal infusions and surgery. Problematic spasticity
typically requires a combination of treatments (Crayton
et al., 2004), and should involve a patient-focused, co-ordi-
nated, multidisciplinary team approach (Thompson et al.,
2005). These facts emphasize that scientifically sound and
clinically meaningful spasticity measurement is indispensable
to clinical practice and research in this area (Voerman
et al., 2005).
Spasticity measurement, like spasticity management, is
complicated. In broad terms, measurement instruments can
be categorized into neurophysiological methods (Voerman
et al., 2005), biomechanical techniques (Wood et al., 2005)
and clinical scales (Platz et al., 2005). The clinical meaning-
fulness of neurophysiological and biomechanical approaches
has been questioned, as they focus on highly specific exam-
inations (e.g. H-reflex or single joint analysis), correlate
poorly with clinical indicators of spasticity and have problems
with reliability and sensitivity (Voerman et al., 2005; Wood
et al., 2005). Clinical scales used in the measurement of
spasticity have also been found wanting (Platz et al., 2005).
Of the 24 scales recently reviewed, (Platz et al., 2005) 18 were
single item measures and, as a consequence, have poor
reliability (McHorney et al., 1992), validity (Manning et al.,
1982; Hobart, 2003) and responsiveness (Sloan et al., 2002).
Only three scales had more than three items: two of these
assessed resistance to passive movement, the third measured
the extensor toe sign. No scale had been developed to address
the broader consequences of spasticity for the patient.
If spasticity management is to be patient-focused, clinical
trials and clinical practice need rigorous measurement
methods that capture patients’ experiences and perceptions
of spasticity, and complement the existing range of measures.
That challenge, which has not been met by existing scales
(Platz et al., 2005), was the aim of this study.
There were three stages. First, we used a range of qualitative studies
to develop a conceptual framework of spasticity impact, and a pool
of potential items hypothesized to convert this framework into a
scale. Second, we administered the items, as a questionnaire, to a
sample of people with multiple sclerosis and spasticity and, using
Rasch analysis, undertook the preliminary steps of constructing a
subscale for each component of the conceptual framework. Third,
we undertook a second survey to finalize and validate the instru-
ment. The research ethics committees of Derriford Hospital and the
National Hospital for Neurology and Neurosurgery (NHNN)
approved the study.
Stage 1: conceptual model formation and
Four pieces of qualitative work were undertaken to develop a con-
ceptual framework of spasticity impact and to generate a pool of
items with the potential to convert (operationalize) this framework
into a scale with multiple subscales. First, in-depth, semi-structured
interviews were conducted with individual multiple sclerosis
patients from NHNN, until no new themes emerged. Second, three
sclerosis patients from Derriford Hospital. Patients were chosen to
and disease type. Interviews and focus groups were tape-recorded,
transcribed and content analysed (WINMAX; Kuckartz, 1996).
Third, a comprehensive literature review was undertaken to identify
relevant health areas and potential items. Lastly, expert opinion on
the impact of spasticity was sought from neurologists, spasticity
nurses, multiple sclerosis nurses and rehabilitation staff.
A preliminary questionnaire was formatted and pre-tested in a
small group of patients with multiple sclerosis and variable degrees
Stage 2: first postal survey
The questionnaire was posted to a random half-sample of the 544
patients from the Cannabinoids in Multiple Sclerosis study (CAMS;
Zajicek et al., 2003) who had commenced trial medication and were
still under follow-up. To encourage high response rates we used
personalized letters, standardized instructions and reminders for
non-responders at 3 and 5 weeks.
Scale development was guided by Rasch measurement principles
(Rasch, 1960) and analyses (Andrich et al., 1997–2004). The key
principle is that the mathematical (Rasch) model articulates a set
of requirements that must be met for rating scale data to generate
internally valid, equal-interval measurements that are stable (invar-
iant) across items and people. In contrast, scales whose development
is guided by traditional psychometric methods generate ordinal
scores whose invariance is unknown (Wright and Linacre, 1989).
We constructed a scale for each area defined as important to
patients by the qualitative studies. The aim was that each scale con-
sisted of a set of clinically meaningful items that satisfied require-
ments for measurement. This goal was achieved by choosing a set of
items hypothesized to constitute a scale for each area, analysing the
observed data against measurement criteria and making decisions
on item selection and deletion. Appraisals according to these criteria
were not conducted singularly and sequentially, but simultaneously
and interactively within the specific context of the item set being
examined. The seven measurement criteria were:
Clinical meaning. We examined all items in each set to judge the
extent to which they were clinically cohesive. Items deemed non-
specific were considered for deletion.
Thresholds for item response options. For each item, the use of
response categories scored with successive integer scores (1 = not
at all to 5 = extremely) implies a continuum of increasing impact,
by examining the ordering of thresholds (or points of crossover
between two adjacent response categories) ascertained by the
Rasch analysis (Andrich, 1978). A threshold is the point on the
Page 2 of 11Brain (2005)J. C. Hobart et al.
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Andrich D. Controversy and the Rasch model: a characteristic of
incompatible paradigms? Med Care 2004; 42: I7–I16.
Andrich D, Sheridan B, Luo G. RUMM 2020. Perth, WA: RUMM Laboratory
Pty Ltd; 1997–2004.
Cella DF, Dineen K, Arnason B, Reder A, Webster KA, Karabatsos G, et al.
Validation of the functional assessment of multiple sclerosis quality of life
instrument. Neurology 1996; 47: 129–39.
Choppin B. An item bank using sample free calibration. Nature 1968; 219:
Crayton H, Heyman R, Rossman H. A multimodal approach to managing the
symptoms of multiple sclerosis. Neurology 2004; 63: S12–S18.
Duncan OD. Probability, disposition and the inconsistency of attitudes and
behaviours. Synthese 1985; 42: 21–34.
Goldberg DP, Hillier VF. A scaled version of the General Health Question-
naire. Psychol Med 1979; 9: 139–45.
Gompertz P, Pound P, Ebrahim S. A postal version of the Barthel Index.
Clin Rehabil 1994; 8: 233–9.
Hagquist C, Andrich D. Is the sense of coherence instrument applicable on
adolescents a latent trait analysis using Rasch modelling. Pers Individ Dif
2004; 36: 955–68.
Hobart JC. Rating scales for neurologists. J Neurol Neurosurg Psychiatr 2003;
Hobart JC, Lamping DL, Thompson AJ. Evaluating neurological outcome
measures: the bare essentials. J Neurol Neurosurg Psychiatr 1996; 60:
in multiple sclerosis: why basic assumptions must be tested. J Neurol
Neurosurg Psychiatr 2001a; 71: 363–70.
Hobart JC, Lamping DL, Fitzpatrick R, Riazi A, Thompson AJ. The multiple
sclerosis impact scale (MSIS-29): a new patient-based outcome measure.
Brain 2001b; 124: 962–73.
Kurtzke JF. On the evaluation of disability in multiple sclerosis. Neurology
1961; 11: 686–94.
Kuckartz U. WINMAX pro ’96 - scientific text analysis. Berlin: Scolari Sage
Linacre JM, Heinemann AW, Wright BD, Granger CV, Hamilton BB. The
structure and stability of the functional independence measure. Arch Phys
Med Rehabil 1994; 75: 127–32.
Manning W, Newhouse J, Ware JE Jr. The status of health in demand estima-
tion: or, beyond excellent, good, fair, and poor. In: Fuchs V, editor.
Economic aspects of health. Chicago: The University of Chicago Press;
1982. p. 143–84.
Massof R. The measurement of vision disability. Optom Vis Sci 2002; 79:
McHorney CA, Tarlov AR. Individual-patient monitoring in clinical
practice: are available health status surveys adequate? Qual Life Res
1995; 4: 293–307.
McHorney CA, Ware JE Jr, Rogers W, Raczek AE, Lu JFR. The validity
and relative precision of MOS short- and long-form health status
scales and DartmouthCOOP
Multiple Sclerosis Council for Clinical Practice Guidelines. Spasticity
management in multiple sclerosis. Consortium of multiple sclerosis
Nunnally JC, Bernstein IH. Psychometric theory. New York: McGraw-Hill;
Paty DW, Ebers GC. Clinical features. In: Paty DW, Ebers GC, editors.
Multiple sclerosis. Philadelphia: F.A. Davis company; 1998.
Platz T, Eickhof C, Nuyens G, Vuadens P. Clinical scales for the assessment
of spasticity, associated phenomena, and function: a systematic review of
the literature. Disabil Rehabil 2005; 27: 7–18.
Rasch G. On general laws and the meaning of measurement in psychology.
In: Neyman J, editor. Proceedings of the Fourth Berkeley Symposium on
Mathematical Statistics and Probability IV. Berkeley CA: University of
California Press; 1961. p. 321–34.
Rasch G. Probabilistic models for some intelligence and attainment tests.
Copenhagen: Danish Institute for Education Research; 1960. Reprinted
Chicago: University of Chicago Press; 1980.
Scientific Advisory Committee of the Medical Outcomes Trust. Assessing
health status and quality of life instruments: attributes and review criteria.
Qual Life Res 2002; 11: 193–205.
Sloan JA, Aaronson N, Cappelleri JC, Fairclough DL, Varricchio C, The
Clinical Significance Consensus Meeting Group. Assessing the clinical sig-
nificanceof single items relativetosummatedscores. MayoClin Proc 2002;
Thompson AJ, Jarrett L, Lockley L, Marsden J, Stevenson V. Clinical
management of spasticity. J Neurol Neurosurg Psychiatr 2005; 76:
Voerman GE, Gregoric M, Hermens HJ. Neurophysiological methods for the
assessment of spasticity: the Hoffmann reflex, the tendon reflex, and the
stretch reflex. Disabil Rehabil 2005; 27: 33–68.
Ware JE Jr, Snow KK, Kosinski M, Gandek B. SF-36 Health Survey manual
and interpretation guide. Boston, MA: Nimrod Press; 1993.
Watkins C, Leathley M, Gregson JM, Moore AP, Smith TL, Sharma A.
Prevalence of spasticity post stroke. Clin Rehabil 2002; 16: 515–22.
Whitaker JN, McFarlandHF,Rudge
assessment in multiple sclerosis trials: a critical analysis. Mult Scler
1995; 1: 37–47.
Wood D, Burridge J, van Wijck F, McFadden C, Hitchcock RA, Pandyan AD,
et al. Biomechanical approaches applied to the lower and upper limb
for the measurement of spasticity: a systematic review of the literature.
Disabil Rehabil 2005; 27: 19–32.
Wright BD. Solving measurement problems with the Rasch model. J Educ
Meas 1977; 14: 97–116.
Wright BD, Linacre JM. Observations are always ordinal: measurements,
however must be interval. Arch Phys Med Rehabil 1989; 70: 857–60.
Wright BD, Masters GN. Rating scale analysis. Chicago: MESA Press; 1982.
Wright BD, Stone MH. Best test design. Chicago: MESA Press; 1979.
Zajicek J, Fox P, Sanders H, Wright D, Vickery J, Nunn A, et al. Cannabinoids
for treatment of spasticity and other symptoms related to multiple sclerosis
(CAMS study): multi-centre randomised placebo-controlled trial. Lancet
2003; 362: 1517–26.
Measuring spasticity in multiple sclerosis: the MSSS-88 Brain (2005) Page 11 of 11
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