The online version of this article (doi:10.1186/s13075-017-1273-5) contains supplementary material, which is available to authorized users.
Physical function (PF) is a core patient-reported outcome domain in clinical trials in rheumatic diseases. Frequently used PF measures have ceiling effects, leading to large sample size requirements and low sensitivity to change. In most of these instruments, the response category that indicates the highest PF level is the statement that one is able to perform a given physical activity without any limitations or difficulty. This study investigates whether using an item format with an extended response scale, allowing respondents to state that the performance of an activity is easy or very easy, increases the range of precise measurement of self-reported PF.
Three five-item PF short forms were constructed from the Patient-Reported Outcomes Measurement Information System (PROMIS®) wave 1 data. All forms included the same physical activities but varied in item stem and response scale: format A (“Are you able to …”; “without any difficulty”/“unable to do”); format B (“Does your health now limit you …”; “not at all”/“cannot do”); format C (“How difficult is it for you to …”; “very easy”/“impossible”). Each short-form item was answered by 2217–2835 subjects. We evaluated unidimensionality and estimated a graded response model for the 15 short-form items and remaining 119 items of the PROMIS PF bank to compare item and test information for the short forms along the PF continuum. We then used simulated data for five groups with different PF levels to illustrate differences in scoring precision between the short forms using different item formats.
Sufficient unidimensionality of all short-form items and the original PF item bank was supported. Compared to formats A and B, format C increased the range of reliable measurement by about 0.5 standard deviations on the positive side of the PF continuum of the sample, provided more item information, and was more useful in distinguishing known groups with above-average functioning.
Using an item format with an extended response scale is an efficient option to increase the measurement range of self-reported physical function without changing the content of the measure or affecting the latent construct of the instrument.
Oude Voshaar MA, ten Klooster PM, Taal E, Krishnan E, van de Laar MA. Dutch translation and cross-cultural adaptation of the PROMIS® physical function item bank and cognitive pre-test in Dutch arthritis patients. Arthritis Res Ther. 2012;14:1–7. CrossRef
Bruce B, Fries JF. The Stanford Health Assessment Questionnaire: a review of its history, issues, progress, and documentation. J Rheumatol. 2003;30:167–78. PubMed
Embretson SE, Reise SP. Item response theory. Mahwah (NJ): Psychology Press; 2000. CrossRef
Lai J-S, Cella D, Choi S, Junghaenel DU, Christodoulou C, Gershon R, et al. How item banks and their application can influence measurement practice in rehabilitation medicine: A PROMIS fatigue item bank example. Arch Phys Med Rehabil. 2011;92:20–7. CrossRef
Oude Voshaar MA, Ten Klooster PM, Glas CA, Vonkeman HE, Taal E, Krishnan E, et al. Validity and measurement precision of the PROMIS physical function item bank and a content validity-driven 20-item short form in rheumatoid arthritis compared with traditional measures. Rheumatology (Oxford). 2015;54:2221–9.
Fries JF, Bruce B, Cella D. The promise of PROMIS: using item response theory to improve assessment of patient-reported outcomes. Clin Exp Rheumatol. 2005;23:53–7.
Oude Voshaar MAH, ten Klooster PM, Glas CAW, Vonkeman HE, Krishnan E, van de Laar MAFJ. Relative performance of commonly used physical function questionnaires in rheumatoid arthritis and a patient-reported outcomes measurement information system computerized adaptive test. Arthritis Rheumatol. 2014;66:2900–8. CrossRefPubMed
Fries JF, Lingala B, Siemons L, Glas CA, Cella D, Hussain YN, et al. Extending the floor and the ceiling for assessment of physical function. Arthritis Rheumatol (Hoboken, NJ). 2014;66:1378–87.
Fisher Jr WP, Eubanks RL, Marier RL. Equating the MOS SF36 and the LSU HSI physical functioning scales. J Outcome Meas. 1997;1:329–62. PubMed
Ware J, Kosinski M, Dewey J, Gandek B. How to score and interpret single-item health status measures: a manual for users of the SF-8 health survey. Lincoln: QualityMetric Incorporated; 2001.
PROMIS: Dynamic tools to measure health outcomes from the patient perspective. Available at: http://www.nihpromis.com/Measures/domainframework1. Accessed 7 Mar 2017.
Efron B. Better bootstrap confidence intervals. J Am Stat Assoc. 1987;82:171–85. CrossRef
Muthén LK, Muthén BO. Mplus User’s Guide. CA: Muthén & Muthén; 1998-2015
R Core Team. R: A language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria, 2012. ISBN 3-900051-07-0; 2014.
Chalmers RP. mirt: A multidimensional item response theory package for the R environment. J Stat Softw. 2012;48:1–29. CrossRef
Ekstrom C, Ekstrom MC. Package ‘MESS’. 2012.
Wickham H. ggplot2: elegant graphics for data analysis. New York: Springer Science & Business Media; 2009. CrossRef
Dillman DA, Smyth JD, Christian LM. Internet, phone, mail, and mixed-mode surveys: the tailored design method. Hoboken (NJ): Wiley; 2014.
- Varying the item format improved the range of measurement in patient-reported outcome measures assessing physical function
H. Felix Fischer
Jakob B. Bjorner
John E. Ware Jr.
James F. Fries
- BioMed Central
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