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

Ebner-Priemer, Ulrich W. 1; Mühlbauer, Esther; Neubauer, Andreas B.; Hill, Holger 1; Beier, Fabrice; Santangelo, Philip S. 1; Ritter, Philipp; Kleindienst, Nikolaus; Bauer, Michael; Schmiedek, Florian; Severus, Emanuel
1 Institut für Sport und Sportwissenschaft (IfSS), Karlsruher Institut für Technologie (KIT)


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 strategy.
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).
Combining gold-standard categorical expert ratings with dimensional self and expert ratings resulted in two latent outcomes (mania and depression) with statistically meaningful factor loadings that dynamically varied over 299 days. ... mehr

Verlagsausgabe §
DOI: 10.5445/IR/1000126754
Veröffentlicht am 25.11.2020
DOI: 10.1186/s40345-020-00210-4
Zitationen: 19
Web of Science
Zitationen: 17
Zitationen: 27
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
Verlag SpringerOpen
Band 8
Heft 1
Seiten Art.Nr. 35
Bemerkung zur Veröffentlichung Gefördert durch den KIT-Publikationsfonds
Vorab online veröffentlicht am 17.11.2020
Schlagwörter Bipolar disorders, Digital phenotyping, Mobile sensing, Ambulatory assessment, Smartphone sensing
Nachgewiesen in Dimensions
Web of Science
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