The goal of the Research Methods Core (RMC) is to advance the quality and impact of research in """"""""real world settings"""""""" by addressing methodological challenges posed by the clinical complexities of late-life depression and disability as well as the processes of initiation and engagement in treatment, and the coordination and continuity of care. The RMC research program draws from both public health and clinical trials traditions and is advanced by three Teams with distinct methodological expertise. The Teams naturally coalesced because of their common interests and history of collaboration. Each Team targets methodological challenges of high priority to our field, using the expertise of our Center's investigators, the stimuli provided by the studies of the Principal Research Core and the needs of the Research Network Development Core, and the databases of our Center. Analytic Team: The Team is working on methods for approaching bias introduced by sample selection, drop-out, and missing data both at the conceptual/design level and at the level of novel analytic methodology. Similarly, the Team is developing designs and analytic approaches to prevent """"""""contamination"""""""" of comparison groups by the intervention treatments and also identify the impact of specific therapeutic components of various interventions, so that investigators can arrive to parsimonious treatments with a promise of wide use. Design Team: The Team is working on three interrelated areas: 1. The ethical and methodological challenges involved in the use of""""""""usual care"""""""" as a control condition and the formation of guidelines for ensuring risk of participants; 2. The conceptual and methodological implications of patient preferences at the design and the analytic level; and 3. The development of objective aggregates of adverse outcomes of late-life depression that can be applied across many studies in projects aimed to identify the burden of disease and the impact of the available interventions. Technology Team: The Team is developing software providing easy access of community-based agencies data so that they can be used to enhance research data and identify bias introduced by participant recruitment procedures. Moreover, in collaboration with two NIH-funded SBIRs, the Team is developing web-based programs for community-based staff training and decision support. Most of the RMC projects are under way; their progress will be greatly facilitated by the development of the formal ACISR structures. We hope that this work will be of service to our field.

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National Institute of Mental Health (NIMH)
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Weill Medical College of Cornell University
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Morimoto, Sarah Shizuko; Gunning, Faith M; Wexler, Bruce E et al. (2016) Executive Dysfunction Predicts Treatment Response to Neuroplasticity-Based Computerized Cognitive Remediation (nCCR-GD) in Elderly Patients with Major Depression. Am J Geriatr Psychiatry 24:816-20
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