Literature DB >> 14651413

Applications of computerized adaptive testing (CAT) to the assessment of headache impact.

John E Ware1, Mark Kosinski, Jakob B Bjorner, Martha S Bayliss, Alice Batenhorst, Carl G H Dahlöf, Stewart Tepper, Andrew Dowson.   

Abstract

OBJECTIVE: To evaluate the feasibility of computerized adaptive testing (CAT) and the reliability and validity of CAT-based estimates of headache impact scores in comparison with 'static' surveys.
METHODS: Responses to the 54-item Headache Impact Test (HIT) were re-analyzed for recent headache sufferers (n = 1016) who completed telephone interviews during the National Survey of Headache Impact (NSHI). Item response theory (IRT) calibrations and the computerized dynamic health assessment (DYNHA) software were used to simulate CAT assessments by selecting the most informative items for each person and estimating impact scores according to pre-set precision standards (CAT-HIT). Results were compared with IRT estimates based on all items (total-HIT), computerized 6-item dynamic estimates (CAT-HIT-6), and a developmental version of a 'static' 6-item form (HIT-6-D). Analyses focused on: respondent burden (survey length and administration time), score distributions ('ceiling' and 'floor' effects), reliability and standard errors, and clinical validity (diagnosis, level of severity). A random sample (n = 245) was re-assessed to test responsiveness. A second study (n = 1103) compared actual CAT surveys and an improved 'static' HIT-6 among current headache sufferers sampled on the Internet. Respondents completed measures from the first study and the generic SF-8 Health Survey; some (n = 540) were re-tested on the Internet after 2 weeks.
RESULTS: In the first study, simulated CAT-HIT and total-HIT scores were highly correlated (r = 0.92) without 'ceiling' or 'floor' effects and with a substantial reduction (90.8%) in respondent burden. Six of the 54 items accounted for the great majority of item administrations (3603/5028, 77.6%). CAT-HIT reliability estimates were very high (0.975-0.992) in the range where 95% of respondents scored, and relative validity (RV) coefficients were high for diagnosis (RV = 0.87) and severity (RV = 0.89); patient-level classifications were accurate 91.3% for a diagnosis of migraine. For all three criteria of change, CAT-HIT scores were more responsive than all other measures. In the second study, estimates of respondent burden, item usage, reliability and clinical validity were replicated. The test-retest reliability of CAT-HIT was 0.79 and alternate forms coefficients ranged from 0.85 to 0.91. All correlations with the generic SF-8 were negative.
CONCLUSIONS: CAT-based administrations of headache impact items achieved very large reductions in respondent burden without compromising validity for purposes of patient screening or monitoring changes in headache impact over time. IRT models and CAT-based dynamic health assessments warrant testing among patients with other conditions.

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Year:  2003        PMID: 14651413     DOI: 10.1023/a:1026115230284

Source DB:  PubMed          Journal:  Qual Life Res        ISSN: 0962-9343            Impact factor:   4.147


  13 in total

1.  Practical implications of item response theory and computerized adaptive testing: a brief summary of ongoing studies of widely used headache impact scales.

Authors:  J E Ware; J B Bjorner; M Kosinski
Journal:  Med Care       Date:  2000-09       Impact factor: 2.983

2.  Development and validation of the Migraine-Specific Quality of Life Questionnaire.

Authors:  P Jhingran; J T Osterhaus; D W Miller; J T Lee; L Kirchdoerfer
Journal:  Headache       Date:  1998-04       Impact factor: 5.887

3.  Migraine in the United States: epidemiology and patterns of health care use.

Authors:  R B Lipton; A I Scher; K Kolodner; J Liberman; T J Steiner; W F Stewart
Journal:  Neurology       Date:  2002-03-26       Impact factor: 9.910

4.  Reliability of the migraine disability assessment score in a population-based sample of headache sufferers.

Authors:  W F Stewart; R B Lipton; K Kolodner; J Liberman; J Sawyer
Journal:  Cephalalgia       Date:  1999-03       Impact factor: 6.292

5.  Migraine diagnosis and treatment: results from the American Migraine Study II.

Authors:  R B Lipton; S Diamond; M Reed; M L Diamond; W F Stewart
Journal:  Headache       Date:  2001 Jul-Aug       Impact factor: 5.887

6.  The Work Limitations Questionnaire.

Authors:  D Lerner; B C Amick; W H Rogers; S Malspeis; K Bungay; D Cynn
Journal:  Med Care       Date:  2001-01       Impact factor: 2.983

7.  A study of the feasibility of Internet administration of a computerized health survey: the headache impact test (HIT).

Authors:  M S Bayliss; J E Dewey; I Dunlap; A S Batenhorst; R Cady; M L Diamond; F Sheftell
Journal:  Qual Life Res       Date:  2003-12       Impact factor: 4.147

8.  A six-item short-form survey for measuring headache impact: the HIT-6.

Authors:  M Kosinski; M S Bayliss; J B Bjorner; J E Ware; W H Garber; A Batenhorst; R Cady; C G H Dahlöf; A Dowson; S Tepper
Journal:  Qual Life Res       Date:  2003-12       Impact factor: 4.147

9.  Calibration of an item pool for assessing the burden of headaches: an application of item response theory to the headache impact test (HIT).

Authors:  Jakob B Bjorner; Mark Kosinski; John E Ware
Journal:  Qual Life Res       Date:  2003-12       Impact factor: 4.147

10.  Headache disability inventory (HDI): short-term test-retest reliability and spouse perceptions.

Authors:  G P Jacobson; N M Ramadan; L Norris; C W Newman
Journal:  Headache       Date:  1995-10       Impact factor: 5.887

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  60 in total

1.  A New Stopping Rule for Computerized Adaptive Testing.

Authors:  Seung W Choi; Matthew W Grady; Barbara G Dodd
Journal:  Educ Psychol Meas       Date:  2010-12-01       Impact factor: 2.821

2.  Content-balancing strategy in bifactor computerized adaptive patient-reported outcome measurement.

Authors:  Yi Zheng; Chih-Hung Chang; Hua-Hua Chang
Journal:  Qual Life Res       Date:  2012-04-27       Impact factor: 4.147

3.  Occurrences and sources of Differential Item Functioning (DIF) in patient-reported outcome measures: Description of DIF methods, and review of measures of depression, quality of life and general health.

Authors:  Jeanne A Teresi; Mildred Ramirez; Jin-Shei Lai; Stephanie Silver
Journal:  Psychol Sci Q       Date:  2008

4.  Grooming a CAT: customizing CAT administration rules to increase response efficiency in specific research and clinical settings.

Authors:  Michael A Kallen; Karon F Cook; Dagmar Amtmann; Elizabeth Knowlton; Richard C Gershon
Journal:  Qual Life Res       Date:  2018-05-05       Impact factor: 4.147

5.  Developing tailored instruments: item banking and computerized adaptive assessment.

Authors:  Jakob Bue Bjorner; Chih-Hung Chang; David Thissen; Bryce B Reeve
Journal:  Qual Life Res       Date:  2007-02-15       Impact factor: 4.147

6.  simpolycat: an SAS program for conducting CAT simulation based on polytomous IRT models.

Authors:  Ssu-Kuang Chen; Karon F Cook
Journal:  Behav Res Methods       Date:  2009-05

7.  A study of the feasibility of Internet administration of a computerized health survey: the headache impact test (HIT).

Authors:  M S Bayliss; J E Dewey; I Dunlap; A S Batenhorst; R Cady; M L Diamond; F Sheftell
Journal:  Qual Life Res       Date:  2003-12       Impact factor: 4.147

8.  The feasibility of applying item response theory to measures of migraine impact: a re-analysis of three clinical studies.

Authors:  Jakob B Bjorner; Mark Kosinski; John E Ware
Journal:  Qual Life Res       Date:  2003-12       Impact factor: 4.147

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

Authors:  Jakob B Bjorner; Mark Kosinski; John E Ware
Journal:  Qual Life Res       Date:  2003-12       Impact factor: 4.147

10.  Calibration of an item pool for assessing the burden of headaches: an application of item response theory to the headache impact test (HIT).

Authors:  Jakob B Bjorner; Mark Kosinski; John E Ware
Journal:  Qual Life Res       Date:  2003-12       Impact factor: 4.147

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