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Reliability of the Urinary Symptom Questionnaires for people with neurogenic bladder (USQNB) who void or use
Rochelle E Tractenberg1,2,3, Jamie K Frost4, Futoshi Yumoto4
1Collaborative for Research on Outcomes and-Metrics, Washington, DC, USA. rochelle.tractenberg@gmail.com.
Study Design:
This is a descriptive psychometrics study.
Objectives:
Neurogenic lower urinary tract dysfunction (NLUTD), also called Neurogenic Bladder (NB), is a common and disruptive condition in a variety of neurologic diagnoses. Our team developed patient-centered instruments, Urinary Symptom Questionnaires for people with neurogenic bladder (USQNB), specific to people with NLUTD who manage their bladders with intermittent catheterization (IC), indwelling catheters (IDC), or who void (V). This article reports evidence of reliability of the IDC and V instruments.
Setting:
Online surveys completed by individuals in the United States with NLUTD due to spinal cord injury (SCI), or multiple sclerosis (MS) who manage their bladder with IDC (SCI, n = 306), or by voiding (SCI, n = 103; MS, n = 383).
Methods:
Reliability estimates were based on endorsement of the items on the USQNB-IDC and USQNB-V. Reliability evidence was representativeness of these symptoms for a national sample (by determining if endorsement > 10%); internal consistency estimates (by Cronbach's alpha and item correlation coefficient, ICC); and interrelatedness of the items (by inferred Bayesian network, BN). We also tested whether a one-factor conceptualization of "urinary symptoms in NLUTD" was supportable for either instrument.
Results:
All items were endorsed by >20% of our samples. Urine quality symptoms tended to be the most commonly endorsed on both instruments. Cronbach's alpha and ICC estimates were high (>0.74), but not suggestive of redundancy. BNs showed interpretable associations among the items, and did not discover uninterpretable or unexpected associations. Neither instrument fit a one-factor model, as expected.
Conclusions:
The USQNB-IDC and USQNB-V instruments show sufficient, multidimensional reliability for implementation and further study.
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