Methodological Issues and Techniques

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Presentation transcript:

Methodological Issues and Techniques Dinner Working Group

Methodologies for Looking at Domains Much on Cognition and Movement Little on emotion and movement Little on all three together Little on components of individual domains, e.g., components of emotion; depression (e.g., apathy) Use of existing longitudinal data sets to explore relationships of domains Innovative approaches to evaluating multiple fluctuating variables over time (eg. simltaneous change models) Methodologies for looking at underlying cause

Developing Phenotypes of Interactions Measuring and defining areas of overlap of domains Bi-directional interactions, multi-directional interactions “Comorbidities” as shared environmental or genetic factors When should this be considered a syndrome? Longitudinal perspective Analytical approaches to account for variations and interactions over time Using clinical intervention studies focusing on one domain to explore effects on others General tools Mechanistic-based

Distinction between Symptoms, Syndromes and Diseases Symptoms and/or risk factors Syndrome: set of symptom/risk factor clusters with statistical properties What are requisite statistical properties? Disease: syndrome plus Epidemiologic profile Shared risk factors Predictable natural history Biological basis with biomarkers Treatment response

Barriers to Development of Interventions Phenotypes poorly defined need better conceptual definitions of conditions (e.g., depression) Need better operational definitions (instruments) to identify areas for clinical trials Need concurrence between conceptual and operational definitions Currently have only operational definitions (scores) in many instances Diagnoses of inclusion vs diagnoses of exclusion (idiopathic conditions) Current taxonomy often depends on specific biomarkers to define diseases/conditions

Research Priorities Inventory of research on overlap of domains as basis for identifying future directions in Meta-analyses Prospective cohorts Clinical trials Encourage interdisciplinary scientists with targeted career development initiatives focusing on these area