The Use of Rasch Model in Developing a Short Form Based on Self-Reported Activity Measure for Low Back Pain

  • Choi, Bong-Sam (Dept. of Physical Therapy, College of Health and Welfare, Woosong University)
  • 투고 : 2014.09.10
  • 심사 : 2014.11.03
  • 발행 : 2014.11.19


For maintaining adequate psychometric properties when reducing the number of items from an instrument, item level psychometrics is crucial. Strategies such as low item correlation or factor loadings, using classical test theory, have traditionally been advocated. The purpose of this study is to describe the development of a new short form assessing the impact of low back pain on physical activity. Rasch measurement model has been applied to the International Classification of Functioning, Disability and Health Activity Measure (ICF-AM). One hundred and one individuals with low back pain aged 19-89 years (mean age: $48.1{\pm}17.3$) who live in the community were participated in the study. Twenty-seven items of lifting/carrying construct of the ICF-AM were analyzed. Ten items were selected from the construct to create a short form. Item elimination criteria include: 1) high or low mean square (out of the range: .6-1.4 for the fit statistics), 2) similar item calibrations to adjacent items, 3) person separation value, and item-person map for potential gap in person ability continuum. All 10 items of the short form fit to the Rasch model except one item (i.e., carrying toddler on back). Despite its high infit and outfit statistics (1.90/2.17), the item had to be reinstated due to potential gaps at the upper extreme of person ability level. The short form had a slightly better spread of person ability continuum compared to the entire set of item. The created short form separated individuals with low back pain into nearly 4 groups, while the entire set of items separated the individuals into 6 groups. The findings prompted multidimensional models for better explanation of the lifting/carrying domain. The item level psychometrics based on the Rasch model can be useful in developing short forms with rationally retained items.



  1. Bond TG, Fox CM. Applying the Rasch Model:Fundamental measurement in the human sciences. 2nd ed. Mahwah, NJ, Lawrence Erlbaum Associates Publishers, 2001:23-28, 183-184.
  2. Brown TA. Confirmatory factor analysis of the penn state worry questionnaire: Multiple factors or method effects? Behav Res Ther. 2003;41(12):1411-1426.
  3. Caronni A, Zaina F, Negrini S. Improving the measurement of health-related quality of life in adolescent with idiopathic scoliosis: The SRS-7, a rasch-developed short form of the SRS-22 questionnaire. Res Dev Disabil. 2014;35(4):784-799.
  4. Cattell RB. The scree test for the number of factors. Multivar Behav Res. 1966;1:245-276.
  5. Davidson M. Rasch analysis of 24-, 18- and 11-item versions of the roland-morris disability questionnaire. Qual Life Res. 2009;18(4):473-481.
  6. Fisher RA. Theory of statistical estimation. Math Proc Camb Phil Soc. 1925;22(5):700-725.
  7. George D, Mallery P. SPSS for Windows Step by Step: A simple guide and reference, 11.0 update. 4th ed. Boston, Allyn and Bacon, 2002:123-124.
  8. Gum JL, Glassman SD, Carreon LY. Clinically important deterioration in patients undergoing lumbar spine surgery: A choice of evaluation methods using the oswestry disability index, 36-item short form health survey, and pain scales:Clinical article. J Neurosurg Spine. 2013;19(5):564-568.
  9. Haley SM, Andres PL, Coster WJ, et al. Short-form activity measure for post-acute care. Arch Phys Med Rehabil. 2004;85(4):649-660.
  10. Jette AM. Assessing disability in studies on physical activity. Am J Prev Med. 2003;25(3 suppl 2):122-128.
  11. Jette AM, Haley SM. Contemporary measurement techniques for rehabilitation outcomes assessment. J Rehabil Med. 2005;37(6):339-345.
  12. Jette AM, Haley SM, Ni P. Comparison of functional status tools used in post-acute care. Health Care Financ Rev. 2003;24(3):13-24.
  13. Johnsen LG, Hellum C, Nygaard OP, et al. Comparison of the SF6D, the EQ5D, and the oswestry disability index in patients with chronic low back pain and degenerative disc disease. BMC Musculoskelet Disord. 2013;14:148.
  14. Kopec JA, Esdaile JM, Abrahamowicz M, et al. The quebec back pain disability scale: Conceptualization and development. J Clin Epidemiol. 1996;49(2):151-161.
  15. Lee TW, Kang SJ. Development of the short form of the korean health literacy scale for the elderly. Res Nurs Health. 2013;36(5):524-534.
  16. Lerdal A, Kottorp A, Gay CL, et al. Development of a short version of the lee visual analogue fatigue scale in a sample of women with HIV/AIDS: A rasch analysis application. Qual Life Res. 2013;22(6):1467-1472.
  17. Linacre JM. What do infit and outfit, mean-square and standardized mean? Rasch Meas Trans. 2002;16(2):878.
  18. Mallinson T, Stelmack J, Velozo C. A comparison of the separation ratio and coefficient alpha in the creation of minimum item sets. Med Care. 2004;42(1 suppl):I17-I24.
  19. McHorney CA. Generic health measurement: Past accomplishments and a measurement paradigm for the 21st century. Ann Intern Med. 1997;127(8 Pt 2):743-750.
  20. McHorney CA. Health status assessment methods for adults: Past accomplishments and future challenges. Annu Rev Public Health. 1999;20:309-335.
  21. Müller U, Duetz MS, Roeder C, et al. Condition-specific outcome measures for low back pain. Part I: Validation. Eur Spine J. 2004;13(4):301-313.
  22. Muller U, Roder C, Greenough CG. Back related outcome assessment instruments. Eur Spine J. 2006;(15 suppl 1):S25-S31.
  23. Nunnally JC, Bernstein IH. Psychometric Theory. 3rd ed. New York, McGraw-Hill, 1994:275-280.
  24. Raykov T. Alpha if item deleted: A note on loss of criterion validity in scale development if maximizing coefficient alpha. Br J Math Stat Psychol. 2008;61(Pt2):275-285.
  25. Velozo CA, Kielhofner G, Lai JS. The use of rasch analysis to produce scale-free measurement of functional ability. Am J Occup Ther. 1999;53(1):83-90.
  26. Velozo CA, Lai JS, Mallinson T, et al. Maintaining instrument quality while reducing items: Application of rasch analysis to a self-report of visual function. J Outcome Meas. 2000-2001;4(3):667-680.
  27. Wang WC, Chen CT. Item parameter recovery, standard error estimates, and fit statistics of the winsteps program for the family of rasch models. Edu Psychol Meas. 2005;65(3):376-404.
  28. Ware JE Jr, Sherbourne CD. The MOS 36-item short-form health survey (SF-36). I. Conceptual framework and item selection. Med Care. 1992;30(6):473-483.
  29. Wright BD, Linacre JM. Reasonable mean-square fit values. Rasch Meas Trans. 1994;8(3):370.
  30. Wright BD, Masters GN. Rating Scale Analysis: Rasch measurement. Chicago, MESA Press, 1982:8-9.
  31. Wright BD, Masters GN. Number of person or item strata. Rasch Meas Trans. 2002;16(3):888.

피인용 문헌

  1. Selecting Common Items for Linking the Oswestry Low Back Pain Questionnaire and a Short Form of Self-Reported Activity Measure for Low Back Pain vol.22, pp.3, 2014,