We propose to develop a model-driven, evidence-based pain item bank for use in pain assessment that is
specific to geriatric oncology (gero-oncology) patients. This will build on our Novel Pain Assessment and
Intervention Network (NoPAIN) project (Chang, PI, 1R21CA113191-01), and continue its Clinical Infometrics
approach. This proposed study is designed in response to PA-03-152(Biobehavioral Pain Research) to
"refine existing techniques for measuring pain and develop new techniques that are disease- and outcome-
specific for different populations." We have chosen the condition of pain in this population because: pain is a
complex multidimensional experience; a critical mass of pain instruments now exist and there is an urgent
need to refine and implement them; and pain management in cancer among older adults is a pressing issue
given societal demographics.
We also aim to construct a computerized adaptive testing platform for this item bank that: 1) can reliably
measure the multidimensional pain experience of heterogeneous cancer patients; and 2) is sensitive to
change so that it can assess the effectiveness of treatments over time.
Our four distinct but related specific aims are:1) To identify and refine the domains of pain assessment
for a gero-oncology population, using existing theoretical frameworks in biopsychosocial medicine and
palliative care as a guide; 2) To compile the items for a multidimensional pain item bank, drawing from
existing pain questionnaires and supplementing with newly written items; 3) To develop empirically a pain
item bank applicable to a gero-oncology population; and 4) To pilot test a computerized adaptive testing
(CAT) platform to administer individualized pain assessments in clinical settings.
At the end of this R21 project, we expect that (1) the conceptual model of the gero-oncology pain
measurement can be improved; (2) the initial sets of pain items can be constructed; (3) items displaying
differential item functioning (DIP) can be identified and revised; and (4) the CAT prototype will demonstrate
how the system should be implemented and tested in clinical settings.
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