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Digital phenotyping: towards replicable findings with comprehensive assessments and integrative models in bipolar disorders

Ebner-Priemer, Ulrich W.; Mühlbauer, Esther; Neubauer, Andreas B.; Hill, Holger; Beier, Fabrice; Santangelo, Philip S.; Ritter, Philipp; Kleindienst, Nikolaus; Bauer, Michael; Schmiedek, Florian; Severus, Emanuel

Abstract (englisch):
Background: Digital phenotyping promises to unobtrusively obtaining a continuous and objective input of symptomatology
from patients’ daily lives. The prime example are bipolar disorders, as smartphone parameters directly
reflect bipolar symptomatology. Empirical studies, however, have yielded inconsistent findings. We believe that three
main shortcomings have to be addressed to fully leverage the potential of digital phenotyping: short assessment
periods, rare outcome assessments, and an extreme fragmentation of parameters without an integrative analytical
Methods: To demonstrate how to overcome these shortcomings, we conducted frequent (biweekly) dimensional
and categorical expert ratings and daily self-ratings over an extensive assessment period (12 months) in 29 patients
with bipolar disorder. Digital phenotypes were monitored continuously. As an integrative analytical strategy, we used
structural equation modelling to build latent psychopathological outcomes (mania, depression) and latent digital
phenotype predictors (sleep, activity, communicativeness).
Outcomes: Combining gold-standard categorical expert ratings with dimensional self and expert ratings resulted in
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Preprint §
DOI: 10.5445/IR/1000126754
Veröffentlicht am 25.11.2020
Cover der Publikation
Zugehörige Institution(en) am KIT Institut für Sport und Sportwissenschaft (IfSS)
Publikationstyp Zeitschriftenaufsatz
Publikationsmonat/-jahr 12.2020
Sprache Englisch
Identifikator ISSN: 2194-7511
KITopen-ID: 1000126754
Erschienen in International Journal of Bipolar Disorders
Band 8
Heft 1
Seiten 35
Vorab online veröffentlicht am 17.11.2020
Schlagwörter Bipolar disorders, Digital phenotyping, Mobile sensing, Ambulatory assessment, Smartphone sensing
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