Introduction-Younger breast cancer survivors often lead extremely busy lives with multiple demands and responsibilities, making them difficult to recruit into clinical trials. African American women are even more difficult to recruit because of additional historical and cultural barriers. In a randomized clinical trial of an intervention, we successfully used culturally informed, population-specific recruitment and retention strategies to engage younger African-American breast cancer survivors.
Through acknowledging gender barriers and taking intentional steps to address them with prenursing and nursing students, schools of nursing may create a more inclusive environment and enhance the profession's diversity. [J Nurs Educ. 2017;56(5):295-299.].
The National Quality Forum uses the term "nurse-sensitive" care to describe health care quality that is influenced by nursing. Identifying this type of care requires useful data and development of measures. Establishing a case for nursing-sensitive performance measurement will facilitate a supportive climate for research and measure development. Interdisciplinary investigations will result in more adequate measures and wider acceptance of the measures in the provider community. This article summarizes existing data sources and recommendations for improving measures, data collection, and research on nurse-sensitive care.
OBJECTIVE
To estimate difference in population-level glycemic control and the emergence of diabetes complications given a theoretical scenario in which non-White youth and young adults (YYA) with type 1 diabetes (T1D) receive and follow an equivalent distribution of diabetes treatment regimens as non-Hispanic White YYA.
RESEARCH DESIGN AND METHODS
Longitudinal data from YYA diagnosed 2002–2005 in the SEARCH for Diabetes in Youth Study were analyzed. Based on self-reported race/ethnicity, YYA were classified as non-White race or Hispanic ethnicity (non-White subgroup) versus non-Hispanic White race (White subgroup). In the White versus non-White subgroups, the propensity score models estimated treatment regimens, including patterns of insulin modality, self-monitored glucose frequency, and continuous glucose monitoring use. An analysis based on policy evaluation techniques in reinforcement learning estimated the effect of each treatment regimen on mean hemoglobin A1c (HbA1c) and the prevalence of diabetes complications for non-White YYA.
RESULTS
The study included 978 YYA. The sample was 47.5% female and 77.5% non-Hispanic White, with a mean age of 12.8 ± 2.4 years at diagnosis. The estimated population mean of longitudinal average HbA1c over visits was 9.2% and 8.2% for the non-White and White subgroup, respectively (difference of 0.9%). Within the non-White subgroup, mean HbA1c across visits was estimated to decrease by 0.33% (95% CI −0.45, −0.21) if these YYA received the distribution of diabetes treatment regimens of the White subgroup, explaining ∼35% of the estimated difference between the two subgroups. The non-White subgroup was also estimated to have a lower risk of developing diabetic retinopathy, diabetic kidney disease, and peripheral neuropathy with the White youth treatment regimen distribution (P < 0.05), although the low proportion of YYA who developed complications limited statistical power for risk estimations.
CONCLUSIONS
Mathematically modeling an equalized distribution of T1D self-management tools and technology accounted for part of but not all disparities in glycemic control between non-White and White YYA, underscoring the complexity of race and ethnicity-based health inequity.
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