Compare methods

	PROMIS Physical Function Item Bank	Computer-Adaptive Functioning Testing
Field	Disability Studies	Disability Studies
Family	Latent structure	Process / pipeline
Year of origin	2008	2008
Originator	Matthias Rose, Jakob Bjorner, John Fries, James Ware; PROMIS network (David Cella et al.)	PROMIS network (Matthias Rose, David Cella, et al.); item response theory adaptive-testing tradition
Type	IRT-calibrated patient-reported outcome item bank	Adaptive measurement pipeline for functioning outcomes
Seminal source	Rose, M., Bjorner, J. B., Becker, J., Fries, J. F., & Ware, J. E. (2008). Evaluation of a preliminary physical function item bank supported the expected advantages of the Patient-Reported Outcomes Measurement Information System (PROMIS). Journal of Clinical Epidemiology, 61(1), 17-33.	Rose, M., Bjorner, J. B., Becker, J., Fries, J. F., & Ware, J. E. (2008). Evaluation of a preliminary physical function item bank supported the expected advantages of the Patient-Reported Outcomes Measurement Information System (PROMIS). Journal of Clinical Epidemiology, 61(1), 17-33.
Aliases	PROMIS PF Item Bank, PROMIS Physical Function Bank, Physical Function Item Bank, PROMIS Mobility Bank	Functional CAT, Adaptive Functioning Assessment, CAT for Disability Outcomes, Adaptive Function Measurement
Related	1	1
Summary	The PROMIS Physical Function item bank is a large, item-response-theory-calibrated collection of self-reported questions about physical functioning and mobility, developed under the United States National Institutes of Health Patient-Reported Outcomes Measurement Information System initiative. Rather than being a fixed questionnaire, it is a bank of items all placed on a single underlying continuum, so that any subset of items measures the same construct on the same metric. Rose and colleagues' 2008 evaluation of the preliminary bank demonstrated the expected advantages of this approach, and Cella and colleagues' 2010 report described the calibration of PROMIS's first wave of adult item banks. The items are calibrated with a graded response model and anchored to a T-score metric with a mean of 50 and a standard deviation of 10 in the United States general population. Because every item sits on the common metric, the bank supports both fixed short forms and computerized adaptive testing, letting researchers and clinicians measure physical function precisely with relatively few questions and compare scores across studies and instruments.	Computer-adaptive functioning testing applies the logic of computerized adaptive testing to the measurement of functioning and disability outcomes, such as physical function, mobility, and daily activity. Instead of administering a fixed list of items to everyone, it draws on a precalibrated item response theory item bank and an algorithm that tailors the test to each respondent in real time. After each answer, the algorithm updates its estimate of the person's underlying function level and selects the next item that will be most informative at that estimate, continuing until a target precision is reached or a maximum number of items is administered. The approach was central to the United States PROMIS initiative, whose physical-function item bank Rose and colleagues evaluated in 2008 and whose first wave of adaptive instruments Cella and colleagues described in 2010. The result, framed here specifically for disability and rehabilitation outcomes, is measurement that achieves high precision with far fewer items than a fixed questionnaire, reducing respondent burden for people who may already face fatigue or communication barriers.