The Center for Complexity and Self-management of Chronic Disease (CSCD Center) advances the science of self-management (SM) by addressing complexity, including the study of complex multi-component interventions and SM for people with complex comorbid conditions. The Pilot Core will focus on the CSCD Specific Aim 2: To expand the number and quality of research investigators who are successful in independently funded careers in self-management research to improve health outcomes. The research development efforts of the PCORE are focused on developing the skills of novice investigators. The following strategies will be employed to accomplish the above aim: (a) linking novice investigators with available resources within UM and the UM School of Nursing to facilitate their successful development as independent researchers who lead interdisciplinary teams focused on self-management, (b) soliciting, reviewing, and awarding pilot study funding to novice investigators to promote research focused on the use of complex interventions and self-management of people with multiple complex chronic diseases, and (c) facilitate the development of successful investigator-initiated programs of research through individual and group mentoring and scientific critique during proposal development.

Agency
National Institute of Health (NIH)
Institute
National Institute of Nursing Research (NINR)
Type
Exploratory Grants (P20)
Project #
1P20NR015331-01
Application #
8821270
Study Section
Special Emphasis Panel (ZNR1-REV-M (17))
Project Start
Project End
Budget Start
2014-09-26
Budget End
2015-07-31
Support Year
1
Fiscal Year
2014
Total Cost
$76,674
Indirect Cost
$27,353
Name
University of Michigan Ann Arbor
Department
Type
DUNS #
073133571
City
Ann Arbor
State
MI
Country
United States
Zip Code
48109
Dinov, Ivo D (2016) Volume and Value of Big Healthcare Data. J Med Stat Inform 4:
Dinov, Ivo D; Heavner, Ben; Tang, Ming et al. (2016) Predictive Big Data Analytics: A Study of Parkinson's Disease Using Large, Complex, Heterogeneous, Incongruent, Multi-Source and Incomplete Observations. PLoS One 11:e0157077
Dinov, Ivo D (2016) Methodological challenges and analytic opportunities for modeling and interpreting Big Healthcare Data. Gigascience 5:12
Dinov, Ivo D; Siegrist, Kyle; Pearl, Dennis K et al. (2016) Probability Distributome: A Web Computational Infrastructure for Exploring the Properties, Interrelations, and Applications of Probability Distributions. Comput Stat 31:559-577
Moon, Seok Woo; Dinov, Ivo D; Hobel, Sam et al. (2015) Structural Brain Changes in Early-Onset Alzheimer's Disease Subjects Using the LONI Pipeline Environment. J Neuroimaging 25:728-37
Moon, Seok Woo; Dinov, Ivo D; Zamanyan, Alen et al. (2015) Gene interactions and structural brain change in early-onset Alzheimer's disease subjects using the pipeline environment. Psychiatry Investig 12:125-35
Moon, Seok Woo; Dinov, Ivo D; Kim, Jaebum et al. (2015) Structural Neuroimaging Genetics Interactions in Alzheimer's Disease. J Alzheimers Dis 48:1051-63
Husain, Syed S; Kalinin, Alexandr; Truong, Anh et al. (2015) SOCR data dashboard: an integrated big data archive mashing medicare, labor, census and econometric information. J Big Data 2:
Toga, Arthur W; Dinov, Ivo D (2015) Sharing big biomedical data. J Big Data 2:
Mandal, Pravat K; Mahajan, Rashima; Dinov, Ivo D (2012) Structural brain atlases: design, rationale, and applications in normal and pathological cohorts. J Alzheimers Dis 31 Suppl 3:S169-88