Guidelines for reporting methodological challenges and evaluating potential bias in dementia research

MELODEM Initiative

Research output: Contribution to journalReview articlepeer-review

158 Scopus citations

Abstract

Clinical and population research on dementia and related neurologic conditions, including Alzheimer's disease, faces several unique methodological challenges. Progress to identify preventive and therapeutic strategies rests on valid and rigorous analytic approaches, but the research literature reflects little consensus on "best practices." We present findings from a large scientific working group on research methods for clinical and population studies of dementia, which identified five categories of methodological challenges as follows: (1) attrition/sample selection, including selective survival; (2) measurement, including uncertainty in diagnostic criteria, measurement error in neuropsychological assessments, and practice or retest effects; (3) specification of longitudinal models when participants are followed for months, years, or even decades; (4) time-varying measurements; and (5) high-dimensional data. We explain why each challenge is important in dementia research and how it could compromise the translation of research findings into effective prevention or care strategies. We advance a checklist of potential sources of bias that should be routinely addressed when reporting dementia research.

Original languageEnglish (US)
Article number2048
Pages (from-to)1098-1109
Number of pages12
JournalAlzheimer's and Dementia
Volume11
Issue number9
DOIs
StatePublished - Sep 1 2015
Externally publishedYes

Keywords

  • Alzheimer disease
  • Big data
  • Brain imaging
  • Dementia
  • Epidemiologic factors
  • Genomics
  • Longitudinal studies
  • Neuropsychological tests
  • Selection bias
  • Statistical models
  • Survival bias

ASJC Scopus subject areas

  • Clinical Neurology
  • Geriatrics and Gerontology
  • Psychiatry and Mental health
  • Cellular and Molecular Neuroscience
  • Health Policy
  • Developmental Neuroscience
  • Epidemiology

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