Objective Patient-reported outcomes (PROs) are essential when evaluating many new treatments in health care, yet current measures have been limited by a lack of precision, standardization and comparability of scores across studies and diseases. The Patient-Reported Outcomes Measurement Information System (PROMIS™) provides item banks that offer the potential for PRO measurement that is efficient (minimizes item number without compromising reliability) flexible (enables optional use of interchangeable items), and precise (has minimal error in estimate) measurement of commonly-studied PROs. We report results from the first large-scale testing of PROMIS items. Study Design and Setting Fourteen item pools were tested in the U.S. general population and clinical groups using an online panel and clinic recruitment. A scale-setting sub-sample was created reflecting demographics proportional to the 2000 U.S. census. Results Using item response theory (graded response model), 11 item banks were calibrated on a sample of 21,133, measuring components of self-reported physical, mental and social health, along with a 10-item global health scale. Short forms from each bank were developed and compared to the overall bank as well as with other well-validated and widely accepted (“legacy”) measures. All item banks demonstrated good reliability across the majority of the score distributions. Construct validity was supported by moderate to strong correlations with legacy measures. Conclusion PROMIS item banks and their short forms provide evidence they are reliable and precise measures of generic symptoms and functional reports comparable to legacy instruments. Further testing will continue to validate and test PROMIS items and banks in diverse clinical populations.
The authors report on the development and calibration of item banks for depression, anxiety, and anger as part of the Patient-Reported Outcomes Measurement Information System (PROMIS®). Comprehensive literature searches yielded an initial bank of 1,404 items from 305 instruments. After qualitative item analysis (including focus groups and cognitive interviewing), 168 items (56 for each construct) were written in a first person, past tense format with a 7-day time frame and five response options reflecting frequency. The calibration sample included nearly 15,000 respondents. Final banks of 28, 29, and 29 items were calibrated for depression, anxiety, and anger, respectively, using item response theory. Test information curves showed that the PROMIS item banks provided more information than conventional measures in a range of severity from approximately −1 to +3 standard deviations (with higher scores indicating greater distress). Short forms consisting of seven to eight items provided information comparable to legacy measures containing more items.
This paper describes the psychometric properties of the PROMIS Pain Interference (PROMIS-PI) bank. An initial candidate item pool (n=644) was developed and evaluated based on review of existing instruments, interviews with patients, and consultation with pain experts. From this pool, a candidate item bank of 56 items was selected and responses to the items were collected from large community and clinical samples. A total of 14,848 participants responded to all or a subset of candidate items. The responses were calibrated using an item response theory (IRT) model. A final 41-item bank was evaluated with respect to IRT assumptions, model fit, differential item function (DIF), precision, and construct and concurrent validity. Items of the revised bank had good fit to the IRT model (CFI and NNFI/TLI ranged from 0.974 to 0.997), and the data were strongly unidimensional (e.g., ratio of first and second eigenvalue = 35). Nine items exhibited statistically significant DIF. However, adjusting for DIF had little practical impact on score estimates and the items were retained without modifying scoring. Scores provided substantial information across levels of pain; for scores in the T-score range 50-80, the reliability was equivalent to 0.96 to 0.99. Patterns of correlations with other health outcomes supported the construct validity of the item bank. The scores discriminated among persons with different numbers of chronic conditions, disabling conditions, levels of self-reported health, and pain intensity (p< 0.0001). The results indicated that the PROMIS-PI items constitute a psychometrically sound bank. Computerized adaptive testing and short forms are available.
Logistic regression provides a flexible framework for detecting various types of differential item functioning (DIF). Previous efforts extended the framework by using item response theory (IRT) based trait scores, and by employing an iterative process using group–specific item parameters to account for DIF in the trait scores, analogous to purification approaches used in other DIF detection frameworks. The current investigation advances the technique by developing a computational platform integrating both statistical and IRT procedures into a single program. Furthermore, a Monte Carlo simulation approach was incorporated to derive empirical criteria for various DIF statistics and effect size measures. For purposes of illustration, the procedure was applied to data from a questionnaire of anxiety symptoms for detecting DIF associated with age from the Patient–Reported Outcomes Measurement Information System.
The use of item banks and computerized adaptive testing (CAT) begins with clear definitions of important outcomes, and references those definitions to specific questions gathered into large and well-studied pools, or "banks" of items. Items can be selected from the bank to form customized short scales, or can be administered in a sequence and length determined by a computer programmed for precision and clinical relevance. Although far from perfect, such item banks can form a common definition and understanding of human symptoms and functional problems such as fatigue, pain, depression, mobility, social function, sensory function, and many other health concepts that we can only measure by asking people directly. The support of the National Institutes of Health (NIH), as witnessed by its cooperative agreement with measurement experts through the NIH Roadmap Initiative known as PROMIS (www.nihpromis.org), is a big step in that direction. Our approach to item banking and CAT is practical; as focused on application as it is on science or theory. From a practical perspective, we frequently must decide whether to re-write and retest an item, add more items to fill gaps (often at the ceiling of the measure), re-test a bank after some modifications, or split up a bank into units that are more unidimensional, yet less clinically relevant or complete. These decisions are not easy, and yet they are rarely unforgiving. We encourage people to build practical tools that are capable of producing multiple short form measures and CAT administrations from common banks, and to further our understanding of these banks with various clinical populations and ages, so that with time the scores that emerge from these many activities begin to have not only a common metric and range, but a shared meaning and understanding across users. In this paper, we provide an overview of item banking and CAT, discuss our approach to item banking and its byproducts, describe testing options, discuss an example of CAT for fatigue, and discuss models for long term sustainability of an entity such as PROMIS. Some barriers to success include limitations in the methods themselves, controversies and disagreements across approaches, and end-user reluctance to move away from the familiar.
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