The Identification of Regions of Significance in the Effect of Multimorbidity on Depressive Symptoms Using Longitudinal Data: An Application of the Johnson-Neyman Technique | Zendy

Philippe Rast | Zendy; Jonathan Rush | Zendy; Andrea M. Piccinin | Zendy; Scott M. Hofer | Zendy

Open Access

The Identification of Regions of Significance in the Effect of Multimorbidity on Depressive Symptoms Using Longitudinal Data: An Application of the Johnson-Neyman Technique

Author(s) -

Philippe Rast,

Jonathan Rush,

Andrea M. Piccinin,

Scott M. Hofer

Publication year - 2014

Publication title -

gerontology

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 1.397

H-Index - 94

eISSN - 1423-0003

pISSN - 0304-324X

DOI - 10.1159/000358757

Subject(s) - context (archaeology) , psychology , longitudinal study , distress , quality of life (healthcare) , depressive symptoms , depression (economics) , cognition , multimorbidity , mental health , gerontology , demography , medicine , clinical psychology , comorbidity , psychiatry , statistics , mathematics , biology , paleontology , macroeconomics , sociology , economics , psychotherapist

The investigation of multimorbidity and aging is complex and highly intertwined with aging-related changes in physical and cognitive capabilities, and mental health and is known to affect psychological distress and quality of life. Under these circumstances it is important to understand how the effects of chronic conditions evolve over time relative to aging-related and end-of-life changes. The identification of periods in time where multimorbidity impacts particular outcomes such as depressive symptoms, versus periods of time where this is not the case, reduces the complexity of the phenomenon.

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