Just as the overall NTCC, the CPC will be guided by the principles of the Community-Based Participatory Research (CBPR) and the Empowerment Theory, which are the philosophical underpinnings of the proposed NTCC. CBPR is a partnership approach that equally involves all segments of the community and academia in the programmatic process. One of the strongest roots of CBPR is the Empowerment Theory, which holds that before community members can address goals introduced from the outside, they must be empowered to address their own goals and concerns. This process begins with a true dialogue in which everyone participates equally to identify common problems and solutions. Four principles have been proposed for CBPR: """"""""a) integration of community members as equal partners;b) integration of intervention and evaluation;c) organizational and programmatic flexibility;and d) utilization of the project as a learning opportunity for all.

Agency
National Institute of Health (NIH)
Institute
National Institute on Minority Health and Health Disparities (NIMHD)
Type
Specialized Center--Cooperative Agreements (U54)
Project #
5U54MD008620-03
Application #
8777896
Study Section
Special Emphasis Panel (ZMD1)
Project Start
Project End
Budget Start
2014-07-01
Budget End
2015-06-30
Support Year
3
Fiscal Year
2014
Total Cost
Indirect Cost
Name
University of Alabama Birmingham
Department
Type
DUNS #
City
Birmingham
State
AL
Country
United States
Zip Code
Scarinci, Isabel C; Moore, Artisha; Benjamin, Regina et al. (2017) A participatory evaluation framework in the establishment and implementation of transdisciplinary collaborative centers for health disparities research. Eval Program Plann 60:37-45
Lin, Lifeng; Zhang, Jing; Hodges, James S et al. (2017) Performing Arm-Based Network Meta-Analysis in R with the pcnetmeta Package. J Stat Softw 80:
Chen, Yong; Liu, Yulun; Ning, Jing et al. (2017) A composite likelihood method for bivariate meta-analysis in diagnostic systematic reviews. Stat Methods Med Res 26:914-930
Lin, Lifeng; Chu, Haitao; Hodges, James S (2016) Sensitivity to Excluding Treatments in Network Meta-analysis. Epidemiology 27:562-9
Ho, Yen-Yi; Guan, Weihua; O'Connell, Michael et al. (2016) Powerful association test combining rare variant and gene expression using family data from Genetic Analysis Workshop 19. BMC Proc 10:251-255
Ma, Xiaoye; Chen, Yong; Cole, Stephen R et al. (2016) A hybrid Bayesian hierarchical model combining cohort and case-control studies for meta-analysis of diagnostic tests: Accounting for partial verification bias. Stat Methods Med Res 25:3015-3037
Zhang, Jing; Yuan, Yiping; Chu, Haitao (2016) The Impact of Excluding Trials from Network Meta-Analyses - An Empirical Study. PLoS One 11:e0165889
Hong, Hwanhee; Chu, Haitao; Zhang, Jing et al. (2016) A Bayesian missing data framework for generalized multiple outcome mixed treatment comparisons. Res Synth Methods 7:6-22
Kenigsberg, Tat'Yana A; Winston 3rd, Willie; Gibson, Priscilla A et al. (2016) African American caregivers' resources for support: Implications for children's perceived support from their caregiver. Child Youth Serv Rev 61:337-344
Abbott, Kenneth L; Nyre, Erik T; Abrahante, Juan et al. (2015) The Candidate Cancer Gene Database: a database of cancer driver genes from forward genetic screens in mice. Nucleic Acids Res 43:D844-8

Showing the most recent 10 out of 14 publications