Abstract

The Health and Behavior Core (formerly the Psychosocial Core) focuses on the social psychological, and behavioral factors relevant to understanding the interactive nature of physical illness and depression and their treatment. This core has 3 service aims and 3 scientific aims. The service aims are (1) to provide consultation to the IRC regarding the conceptualization and measurement of health and behavioral factors as they may account for the health-mood disorder relationship. (2) """"""""Provide guidance in the selection and application of social and behavioral intervention methods and technologies that can be applied to the prevention and treatment of late-life mood disorders."""""""" (3) Consult with IRC training sectors on scientific aspects of Health and Behavior issues. The scientific aims are: (1) Develop and test interventions for primary care and specific-illness patients. (2) Facilitate future intervention research through broadening research populations (including family members) across different health-care settings. (3) """"""""Explore the phenomenology and health-behavioral correlates of late-life mood disorders.""""""""

  Funding Agency

Agency
National Institute of Health (NIH)
Institute
National Institute of Mental Health (NIMH)
Type
Center Core Grants (P30)
Project #
5P30MH052247-08
Application #
6588519
Study Section
Special Emphasis Panel (ZMH1)
Project Start
2002-03-01
Project End
2003-02-28
Budget Start
Budget End
Support Year
8
Fiscal Year
2002
Total Cost
Indirect Cost

  Institution

Name
University of Pittsburgh
Department
Type
DUNS #
053785812
City
Pittsburgh
State
PA
Country
United States
Zip Code
15213

  Publications

Smagula, Stephen F; Beach, Scott; Rosso, Andrea L et al. (2017) Brain Structural Markers and Caregiving Characteristics as Interacting Correlates of Caregiving Strain. Am J Geriatr Psychiatry 25:582-591
Smagula, Stephen F; Wallace, Meredith L; Anderson, Stewart J et al. (2016) Combining moderators to identify clinical profiles of patients who will, and will not, benefit from aripiprazole augmentation for treatment resistant late-life major depressive disorder. J Psychiatr Res 81:112-8
Khalaf, Alexander; Edelman, Kathryn; Tudorascu, Dana et al. (2015) White Matter Hyperintensity Accumulation During Treatment of Late-Life Depression. Neuropsychopharmacology 40:3027-35
Patel, Meenal J; Andreescu, Carmen; Price, Julie C et al. (2015) Machine learning approaches for integrating clinical and imaging features in late-life depression classification and response prediction. Int J Geriatr Psychiatry 30:1056-67
Joel, Ian; Begley, Amy E; Mulsant, Benoit H et al. (2014) Dynamic prediction of treatment response in late-life depression. Am J Geriatr Psychiatry 22:167-76
Diniz, Breno S; Reynolds 3rd, Charles F; Butters, Meryl A et al. (2014) The effect of gender, age, and symptom severity in late-life depression on the risk of all-cause mortality: the Bambuí Cohort Study of Aging. Depress Anxiety 31:787-95
Andreescu, Carmen; Teverovsky, Esther; Fu, Bo et al. (2014) Old worries and new anxieties: behavioral symptoms and mild cognitive impairment in a population study. Am J Geriatr Psychiatry 22:274-84
Chisholm, Denise; Toto, Pamela; Raina, Ketki et al. (2014) Evaluating capacity to live independently and safely in the community: Performance Assessment of Self-care Skills. Br J Occup Ther 77:59-63
Gallo, Joseph J; Morales, Knashawn H; Bogner, Hillary R et al. (2013) Long term effect of depression care management on mortality in older adults: follow-up of cluster randomized clinical trial in primary care. BMJ 346:f2570
Sherer, Eric A; Sale, Mark E; Pollock, Bruce G et al. (2012) Application of a single-objective, hybrid genetic algorithm approach to pharmacokinetic model building. J Pharmacokinet Pharmacodyn 39:393-414

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