Common Data Elements to Facilitate Sharing and Re-use of Participant-Level Data

The Ontario Brain Institute's "Brain-CODE" is a large-scale informatics platform designed to support the collection, storage and integration of diverse types of data across several brain disorders as a means to understand underlying causes of brain dysfunction and developing novel approaches to treatment. By providing access to aggregated datasets on participants with and without different brain disorders, Brain-CODE will facilitate analyses both within and across diseases and cover multiple brain disorders and a wide array of data, including clinical, neuroimaging, and molecular. To help achieve these goals, consensus methodology was used to identify a set of core demographic and clinical variables that should be routinely collected across all participating programs. Establishment of Common Data Elements within Brain-CODE is critical to enable a high degree of consistency in data collection across studies and thus optimize the ability of investigators to analyze pooled participant-level data within and across brain disorders. Results are also presented using selected common data elements pooled across three studies to better understand psychiatric comorbidity in neurological disease (Alzheimer's disease/amnesic mild cognitive impairment, amyotrophic lateral sclerosis, cerebrovascular disease, frontotemporal dementia, and Parkinson's disease)

Comorbidity · Data sharing · Dementia · Disease · Frontotemporal dementia · Informatics · Neuroimaging · Pathology · Psychiatry · Alzheimer's disease research and treatments · Clinical Psychology · Dementia and Cognitive Impairment Research · Medicine · Parkinson's Disease Mechanisms and Treatments · Psychology

• Rasch analyses of the Quick Inventory of Depressive Symptomatology Self-Report in neurodegenerative and major depressive disorders

  Open Access•Anthony L Vaccarino, Sandra E Black et al.•Frontiers in Psychiatry•2023

  Incluir item

• Assessment of anxiety in children with neurodevelopment disorders

  Open Access•Alana Sparks, Susan Gilbert Evans et al.•Frontiers in Psychiatry•2024

  Incluir item

• The Epidemiology of Major Depressive Disorder

  R C Kessler, Patricia Berglund et al.•JAMA•2003

  Incluir item

• An Experimental Application of the DELPHI Method to the Use of Experts

  Open Access•Norman C Dalkey, Norman Dalkey et al.•Management Science•1963

  Incluir item

• The 16-Item quick inventory of depressive symptomatology (Qids), clinician rating (Qids-C), and self-report (Qids-SR)

  Open Access•A John Rush, Madhukar H Trivedi et al.•Biological Psychiatry•2003

  Incluir item

• A Brief Measure for Assessing Generalized Anxiety Disorder

  Robert L Spitzer, Carmen Pérez de los Ríos et al.•A.M.A. Archives of Internal…•2006

  Incluir item

• Gender differences in depression in representative national samples

  Open Access•Rachel H Salk, Janet Shibley Hyde et al.•Psychological Bulletin•2017

  Incluir item

• The disability paradox

  Open Access•Gary L Albrecht, Patrick Devlieger et al.•Social Science & Medicine•1999

  Incluir item