Measuring Pain Behavior

The struggle to bring the abstract, but ever so real, experience of "pain" within the boundaries of quantitative science continues. This is no mere academic exercise. Pain measurement enables the prospect of better understanding of pain-cause and cure.

330 participants in a six to eight week inpatient rehabilitation program for chronic low-back pain were assessed on nine items of pain behavior by staff ratings at: admission to the program, discharge from the program and one-month follow-up. The nine four- category items were: endurance, strength, flexibility, pain expression (gestures and vocalization), muscle tension, sitting tolerance, assertiveness, comprehension of chronic pain treatment, and understanding of the relationship between pain and anxiety.

Conventional analysis of this type of data fails. The chi-square statistic is no help because information about the ordered nature of the scale is lost. Ridit analysis (Bross 1958) begins with the assumption that the ordered response categories represent an approximation to an underlying continuum with successive categories corresponding to consecutive intervals on the variable. But this method requires an arbitrary choice of a standard distribution against which to make comparisons. Results differ dramatically depending on this choice. Chi-square statistics and ridit analysis explore consistency across items within a test, but neither reveals where an individual respondent stands on the underlying concept which the test is intended to measure, or whether the test has done well in providing useful information.

Rasch analysis, in contrast, supplies a mathematically sound basis for interpreting the relationship of each rating to the underlying construct, and for developing a basis for future refinement of the test. Partial Credit analysis shows that the structure of the pain expression scale depends on the occasion of administration. The scale does not define an underlying continuum of pain behavior in the same way at admission as at discharge. At admission, the intermediate categories of "moderate" and "mild" pain provide much less clinical information than the extreme categories of "marked" and "negligible" pain. Yet the same ratings at discharge are related systematically to the overall pattern of behavior. The pain expression (Ow!) is less related to overall pain behavior at admission than after treatment. This seems due to involvement in the program, since modifying inappropriate vocalizations is an explicit goal.

There was a mean improvement for the 330 patients of at least 3 logits on each of nine items, equivalent to an improvement from "marked" to "mild" pain for the group. Details in McArthur et al., Archives of Physical Medicine and Rehabilitation, 1991, 72:296-304.

Measuring Pain Behavior, D McArthur … Rasch Measurement Transactions, 1991, 5:1 p. 129

Rasch Publications
Rasch Measurement Transactions (free, online) Rasch Measurement research papers (free, online) Probabilistic Models for Some Intelligence and Attainment Tests, Georg Rasch Applying the Rasch Model 3rd. Ed., Bond & Fox Best Test Design, Wright & Stone
Rating Scale Analysis, Wright & Masters Introduction to Rasch Measurement, E. Smith & R. Smith Introduction to Many-Facet Rasch Measurement, Thomas Eckes Invariant Measurement: Using Rasch Models in the Social, Behavioral, and Health Sciences, George Engelhard, Jr. Statistical Analyses for Language Testers, Rita Green
Rasch Models: Foundations, Recent Developments, and Applications, Fischer & Molenaar Journal of Applied Measurement Rasch models for measurement, David Andrich Constructing Measures, Mark Wilson Rasch Analysis in the Human Sciences, Boone, Stave, Yale
in Spanish: Análisis de Rasch para todos, Agustín Tristán Mediciones, Posicionamientos y Diagnósticos Competitivos, Juan Ramón Oreja Rodríguez

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