Depression, the Metabolic Syndrome and Neurodegeneration

Leonard, Brian E.

doi:10.1007/978-3-319-13602-8_11

Cited by 2 publications

(2 citation statements)

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“…They fit their model using data for 22,059 participants from the UK Biobank and found support for the idea that targeted and time-sensitive control of blood pressure in mid-late life may be most beneficial to both cognitive and brain health. Complex links exist between depressive, neurodegenerative, and metabolic disorders [ 182 ]. Using data for 11,355 participants from the Brazilian Longitudinal Study of Adult Health (ELSA-Brazil) [ 183 ], Duinkerken et al (2020) used multivariate logistic regression to selectively model several domains (what they refer to as “blocks”) of data, grouped specifically according to their theoretical proximity to a current depressive episode (including classical predictors of depression, e.g.…”

Section: Whole Person Modelingmentioning

confidence: 99%

“…Complex links exist between depressive, neurodegenerative, and metabolic disorders [ 182 ]. Using data for 11,355 participants from the Brazilian Longitudinal Study of Adult Health (ELSA-Brazil) [ 183 ], Duinkerken et al (2020) used multivariate logistic regression to selectively model several domains (what they refer to as “blocks”) of data, grouped specifically according to their theoretical proximity to a current depressive episode (including classical predictors of depression, e.g.…”

Section: Whole Person Modelingmentioning

confidence: 99%

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Whole Person Modeling: a transdisciplinary approach to mental health research

Felsky,

Cannitelli,

Pipitone

2023

Discov Ment Health

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The growing global burden of mental illness has prompted calls for innovative research strategies. Theoretical models of mental health include complex contributions of biological, psychosocial, experiential, and other environmental influences. Accordingly, neuropsychiatric research has self-organized into largely isolated disciplines working to decode each individual contribution. However, research directly modeling objective biological measurements in combination with cognitive, psychological, demographic, or other environmental measurements is only now beginning to proliferate. This review aims to (1) to describe the landscape of modern mental health research and current movement towards integrative study, (2) to provide a concrete framework for quantitative integrative research, which we call Whole Person Modeling, (3) to explore existing and emerging techniques and methods used in Whole Person Modeling, and (4) to discuss our observations about the scarcity, potential value, and untested aspects of highly transdisciplinary research in general. Whole Person Modeling studies have the potential to provide a better understanding of multilevel phenomena, deliver more accurate diagnostic and prognostic tests to aid in clinical decision making, and test long standing theoretical models of mental illness. Some current barriers to progress include challenges with interdisciplinary communication and collaboration, systemic cultural barriers to transdisciplinary career paths, technical challenges in model specification, bias, and data harmonization, and gaps in transdisciplinary educational programs. We hope to ease anxiety in the field surrounding the often mysterious and intimidating world of transdisciplinary, data-driven mental health research and provide a useful orientation for students or highly specialized researchers who are new to this area.

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Section: Whole Person Modelingmentioning

confidence: 99%

Section: Whole Person Modelingmentioning

confidence: 99%