Using item response theory to calibrate the Headache Impact Test (HIT™) to the metric of traditional headache scales

Quality of Life Research

Volumn 12, Issue 8, 2003, Pages 981-1002

  Bjorner, Jakob B ^a,b   Kosinski, Mark ^a   Ware Jr , John E ^a,c  

^a QualityMetric Incorporated   (United States)

^b NATIONAL RESEARCH CENTRE FOR THE WORKING ENVIRONMENT   (Denmark)

^c Health Assessment Lab   (United States)

Author keywords

Computerized adaptive assessment; Disability; Headache; Health status; Impact; Item response theory; Migraine; Quality of life; Questionnaires; Severity

Indexed keywords

ADULT; ARTICLE; CALIBRATION; DISABILITY; DISEASE SEVERITY; HEADACHE; HEADACHE IMPACT TEST; HEALTH SURVEY; HUMAN; INTERNET; INTERVIEW; ITEM RESPONSE THEORY; MAJOR CLINICAL STUDY; MIGRAINE; PRIORITY JOURNAL; PSYCHOMETRY; QUALITY OF LIFE; QUESTIONNAIRE; RATING SCALE; SCORING SYSTEM; THEORY;

ADOLESCENT; ADULT; AGED; CALIBRATION; DATA COLLECTION; HEADACHE; HUMANS; MIDDLE AGED; QUALITY OF LIFE; QUESTIONNAIRES; SICKNESS IMPACT PROFILE; TELEPHONE; UNITED STATES;

EID: 0242574569     PISSN: 09629343     EISSN: None     Source Type: Journal    
DOI: 10.1023/A:1026123400242     Document Type: Article

References (31)

1. Martin BC, Pathak DS, Sharfman MI, et al. Validity and reliability of the migraine-specific quality of life questionnaire (MSQ Version 2.1). Headache 2000; 40: 204-215.
2. Ware JE Jr, Kosinski M, Bjorner JB, et al. Applications of computerized adaptive testing (CAT) to the assessment of headache impact. Quality Life Res 2003; 12: 935-952.
3. Jacobson GP, Ramadan NM, Aggarwal SK, Newman CW. The Henry Ford Hospital Headache Disability Inventory (HDI). Neurology 1994; 44: 837-842.
4. Wagner TH, Patrick DL, Galer BS, Berzon RA. A new instrument to assess the long-term quality of life effects from migraine: Development and psychometric testing of the MSQOL. Headache 1996; 36: 484-492.
5. Jacobson GP, Ramadan NM, Norris L, Newman CW. Headache disability inventory (HDI): Short-term test-retest reliability and spouse perceptions. Headache 1995; 35: 534-539.
6. Stewart WF, Lipton RB, Simon D, Liberman J, Von Korff M. Validity of an illness severity measure for headache in a population sample of migraine sufferers. Pain 1999; 79: 291-301.
7. Stewart WF, Lipton RB, Dowson AJ, Sawyer J. Development and testing of the Migraine Disability Assessment (MIDAS) Questionnaire to assess headache-related disability. Neurology 2001; 56: S20-S28.
8. Stewart WF, Lipton RB, Kolodner K, Liberman J, Sawyer J. Reliability of the migraine disability assessment score in a population-based sample of headache sufferers. Cephalalgia 1999; 19: 107-114.
9. Stewart WF, Lipton RB, Kolodner KB, Sawyer J, Lee C, Liberman JN. Validity of the Migraine Disability Assessment (MIDAS) score in comparison to a diary-based measure in a population sample of migraine sufferers. Pain 2000; 88: 41-52.
10. Bjorner JB, Kosinski M, Ware JE Jr. Calibration of an item pool for assessing the burden of headaches: An application of item response theory to the Headache Impact Test (HIT™). Quality Life Res 2003; 12: 913-933.
11. Bjorner JB, Kosinski M, Ware JE Jr. The feasibility of applying item response theory to measures of migraine impact: A re-analysis of three clinical studies. Quality Life Res 2003; 12: 887-902.
12. Kosinski M, Bayliss MS, Bjorner JB, et al. A six-item short-form survey for measuring headache impact: The HIT-6™. Quality Life Res 2003; 12: 963-974.
13. Ware JE Jr, Bjorner JB, Kosinski M. Practical implications of item response theory and computerized adaptive testing: A brief summary of ongoing studies of widely used headache impact scales. Med Care 2000; 38: II73-II82.
14. Mislevy RJ. Linking Educational Assessments: Concepts, Issues, Methods, and Prospects. Princeton, NJ: Educational Testing Service, Policy Information Center, 1992.
15. Linn RL. Linking results of distrinct assessments. Appl Meas Educ 1993; 6: 83-102.
16. Dorans NJ. Scaling and equating. In: Wainer H, Dorans NJ, Eignor D, Flaugher R, Green BF, Mislevy RJ, Steinberg L, Thissen D (eds), Computerized Adaptive Testing: A Primer. Mahwah, NJ: Lawrence Erlbaum Associates, 2000: 135-158.
17. Orlando M, Sherbourne CD, Thissen D. Summed-score linking using item response theory: Application to depression measurement. Psychol Assess 2000; 12: 354-359.
18. Bjorner JB, Petersen MA, Groenvold M, et al. Use of item response theory to develop a shortened version of the EORTC QLQ-C30 emotional function scale. Quality Life Res (Submitted).
19. Muraki E. A generalized partial credit model. In: van der Linden WJ, Hambleton RK (eds), Handbook of Modern Item Response Theory. Berlin: Springer, 1997: 153-164.
20. Muraki E, Bock RD. Parscale - IRT based Test Scoring and Item Analysis for Graded Open-ended Exercises and Performance Tasks. Chicago: Scientific Software Inc., 1996.
21. Thissen D. Multilog - Multiple, Categorical Item Analysis and Test Scoring Using Item Response Theory. Chicago: Scientific Software Inc., 1991.
22. Samejima F. Graded response model. In: van der Linden WJ, Hambleton RK (eds), Handbook of Modern Item Response Theory, Berlin: Springer, 1997: 85-100.
23. Spray JA. Multiple-Attempt, Single-Item Response Models. In: van-der-Linden WJ, Hambleton RK (eds), Handbook of Modern Item Response Theory, New York: Springer, 1996: 209-220.
24. Ruppert D, Stefanski LA, Carrol RJ. Measurement Error in Nonlinear Models. London: Chapman & Hall, 1995.
25. Tsutakawa RK, Soltys MJ. Approximation for Bayesian Ability Estimation. J Educ Stat 1988; 13: 117-130.
26. Tsutakawa RK, Johnson JC. The effect of uncertainty of item parameter estimation on ability estimates. Psychometrika 1990; 55: 371-390.
27. McHorney CA, Cohen AS. Equating health status measures with item response theory: Illustrations with functional status items. Med Care 2000; 38: 1143-1159.
28. Bradburn NM, Rips LJ, Shevell SK. Answering autobiographical questions: The impact of memory and inference on surveys. Science 1987; 236: 157-161.
29. Menon G, Yorkston EA, Stone AA, Turkkan JA, Bachrach CA, Jobe JB, Kurtzman HS, Cain VS (eds), The Science of Self Report: Implications for Research and Practice. Mahwah, NJ: Lawrence Erlbaum Ass., 2000: 63-79.
30. Andrich D. A binomial latent trait model for the study of Likert-style attitude questionnaires. Br J Math Stat Psychol 1978; 31: 84-98.
31. Wright B, Masters GN. Rating Scale Analysis - Rasch Measurement. Chicago: MESA Press, 1982.