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Rating Scales for Clinical Studies in Neurology—Challenges and Opportunities
life, which are particularly relevant to neurological disease—must be
Figure 1: Central Features of All Measurements
measured indirectly through their manifestations. These are often called
latent variables in order to emphasize this fact. The implication is that
A
instruments must be constructed to transform the manifestations of
latent variables into numbers that can be taken as measurements.
6
Less MS disability More
Person
Rating scales are instruments constructed to measure latent variables.
B
Two main types of rating scale are used in health measurement: single-
item and multi-item scales.
7
Figure 2 shows how single-item scales, such
C
as the Kurtzke’s Expanded Disability Status Scale (EDSS),
8
mark out the
variable they purport to measure. Other widely used single-item scales
include Ashworth’s scale for spasticity,
9
the modified Rankin scale,
10
Hauser’s Ambulation index,
11
and the Hoehn and Yar scale.
12
D
Multi-item scales consist of a set of items, each of which has two or more
1.0 2.0 3.0 4.0 5.0 6.0 7.0 8.0 9.0 10
ordered response categories assigned sequential integer scores (e.g.
Barthel Index,
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Functional Independence Measure,
14
Multiple Sclerosis
Less
MS disability
More
Walking Scale).
15
Figure 3 shows the Rivermead Mobility Index (RMI)
16
as
an example of a multi-item scale and how it represents a mobility variable
A shows that a variable, here multiple sclerosis (MS) disability, can be represented as a line, or
as a ‘ruler’ of a count up to 15 points. Typically, item scores are summed
continuum, ranging from less disability to more disability. B shows a ‘mark’ that represents the
location of a person on the variable and indicates the amount of disability that person has. C
to give a single total score for each person (also called raw, summed, or
illustrates that to ‘measure’ a person’s MS disability, the disability continuum must have marks that
scale score), which is taken to be a ‘measure’ of the variable quantified
separate it into units. D shows a ‘ruler’ with equal interval units—the prototype of all measurements.
by the set of items.
Thus, a fundamental requirement for making measurements, and
meaningfully interpreting them, is the presence of a standard consistent
unit. In this example the standard consistent unit is 1 meter.
It is difficult to set up an argument
against scale scores being ordinal
Now consider rating scales. These assign numbers to rank-ordered clinically
distinct magnitudes of unknown interval size. For example, the Rankin
in nature. However, a frequently asked
scale assigns sequential integer scores (0, 1, 2, 3, 4, 5) to a set of ordered
question is: does this really matter
clinical descriptions of worsening ‘disability.’ Likewise, multi-item scales
assign sequential integer scores to progressive (ordered) item response
in practice?
categories (e.g: no/yes; not at all/a little/a lot; mild/moderate/severe), and
these values are summed across items to give a total score. Undeniably,
therefore, rating scale scores are ordinal-level data. More specifically, they
It has long been recognized that single-item scales are scientifically weak,
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are counts of the numbers of item response categories achieved. This tells
while multi-item scales can be scientifically strong. However, the fact that us nothing about the distances between response categories or total scores
a single value, derived from summing the scores from a set of items, is (see Figure 2). Although counting observations is the beginning of
taken to be a ‘measurement’ invokes two fundamental requirements of measurement, as all observations begin as ordinal if not nominal data,
multi-item rating scales: evidence that the values produced satisfy the something must be done to turn counts into measurements.
22
This is
scientific definition of measurements rather than simply being numerals, because a fundamental requirement of the definition of ‘measurement’
and evidence that the set of items maps out the variable it purports to is a constant unit.
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measure. In reality, these requirements are rarely met.
It is difficult to set up an argument against scale scores being ordinal in
Problem 1—Scales Do Not Generate Measurement nature. However, a frequently asked question is: does this really matter in
The first problem with rating scales is that the numbers they generate are practice? This question arises from the logic that the clinical descriptors of
not measurements in the scientific sense of the word. To understand this the different levels of the Ashworth scale, for example, are ordered to
statement we need to consider the definition of measurement and the map out progressive spasticity, and the logic that producing clinical
extent to which the numbers generated by scales meet that definition. descriptors representing near-equal intervals would be unrealistic.
Measurement is defined as the quantitative comparison between two Therefore, why not simply assign sequential scores? The problem arises
magnitudes of the same type, one of which is a standard unit, and in when the data are analyzed. The importance of a constant unit is that the
which the comparison is expressed as a numerical ratio.
18–21
An example numerical meaning of numbers is maintained when they are added,
makes this clinically intangible definition clear. Consider 10 meters in subtracted, divided, or multiplied (i.e. subjected to statistical analysis).
22,25
length. This is the comparison of two magnitudes (10 and 1) of the same By simply assigning sequential integer scores we are implying that there is
type (meters) in which one magnitude is a standard unit (1 meter). The a constant unit, and by analyzing the data statistically and making clinical
comparison is expressed as a numerical ratio (10/1 meters or 10 meters). inferences we are believing it. This is a potentially very dangerous practice.
US NEUROLOGY 13
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