Literature DB >> 31650093

Digital phenotyping for psychiatry: Accommodating data and theory with network science methodologies.

D M Lydon-Staley1, I Barnett2, T D Satterthwaite3, D S Bassett1,4,5,6.   

Abstract

Digital phenotyping is the moment-by-moment quantification of our interactions with digital devices. With appropriate tools, digital phenotyping data afford unprecedented insight into our transactions with the world and hold promise for developing novel signatures of psychopathology that will aid in diagnosis, prognosis, and treatment selection of psychiatric disorders. In this review, we highlight empirical work merging digital phenotyping data, and particularly experience-sampling data collected via smartphone, with network theories of psychopathology and network science methodologies. The intensive, longitudinal, and multivariate data collected through digital phenotyping designs provide the necessary foundation for the application of network science methodologies to parsimoniously test network theories of psychopathology emphasizing causal interactions among psychiatric symptoms, as well as other phenotypes, across time.

Entities:  

Year:  2018        PMID: 31650093      PMCID: PMC6812649          DOI: 10.1016/j.cobme.2018.12.003

Source DB:  PubMed          Journal:  Curr Opin Biomed Eng        ISSN: 2468-4511


  28 in total

1.  Critical Slowing Down as a Personalized Early Warning Signal for Depression.

Authors:  Marieke Wichers; Peter C Groot
Journal:  Psychother Psychosom       Date:  2016-01-26       Impact factor: 17.659

2.  A network theory of mental disorders.

Authors:  Denny Borsboom
Journal:  World Psychiatry       Date:  2017-02       Impact factor: 49.548

3.  Can We Jump from Cross-Sectional to Dynamic Interpretations of Networks? Implications for the Network Perspective in Psychiatry.

Authors:  Fionneke M Bos; Evelien Snippe; Stijn de Vos; Jessica A Hartmann; Claudia J P Simons; Lian van der Krieke; Peter de Jonge; Marieke Wichers
Journal:  Psychother Psychosom       Date:  2017-05-11       Impact factor: 17.659

4.  What features of psychopathy might be central? A network analysis of the Psychopathy Checklist-Revised (PCL-R) in three large samples.

Authors:  Bruno Verschuere; Sophia van Ghesel Grothe; Lourens Waldorp; Ashley L Watts; Scott O Lilienfeld; John F Edens; Jennifer L Skeem; Arjen Noordhof
Journal:  J Abnorm Psychol       Date:  2017-11-27

5.  The Gaussian Graphical Model in Cross-Sectional and Time-Series Data.

Authors:  Sacha Epskamp; Lourens J Waldorp; René Mõttus; Denny Borsboom
Journal:  Multivariate Behav Res       Date:  2018-04-16       Impact factor: 5.923

6.  Dynamic graph metrics: Tutorial, toolbox, and tale.

Authors:  Ann E Sizemore; Danielle S Bassett
Journal:  Neuroimage       Date:  2017-07-08       Impact factor: 6.556

7.  Structure and inference in annotated networks.

Authors:  M E J Newman; Aaron Clauset
Journal:  Nat Commun       Date:  2016-06-16       Impact factor: 14.919

Review 8.  New dimensions and new tools to realize the potential of RDoC: digital phenotyping via smartphones and connected devices.

Authors:  J Torous; J-P Onnela; M Keshavan
Journal:  Transl Psychiatry       Date:  2017-03-07       Impact factor: 6.222

9.  Personalized Network Modeling in Psychopathology: The Importance of Contemporaneous and Temporal Connections.

Authors:  Sacha Epskamp; Claudia D van Borkulo; Date C van der Veen; Michelle N Servaas; Adela-Maria Isvoranu; Harriëtte Riese; Angélique O J Cramer
Journal:  Clin Psychol Sci       Date:  2018-01-19

10.  The Network Structure of Tobacco Withdrawal in a Community Sample of Smokers Treated With Nicotine Patch and Behavioral Counseling.

Authors:  David M Lydon-Staley; Robert A Schnoll; Brian Hitsman; Danielle S Bassett
Journal:  Nicotine Tob Res       Date:  2020-03-16       Impact factor: 4.244

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  6 in total

1.  Digital Health and Addiction.

Authors:  Lisa A Marsch
Journal:  Curr Opin Syst Biol       Date:  2020-07-07

2.  Auditing the research practices and statistical analyses of the group-level temporal network approach to psychological constructs: A systematic scoping review.

Authors:  M Annelise Blanchard; Alba Contreras; Rana Begum Kalkan; Alexandre Heeren
Journal:  Behav Res Methods       Date:  2022-04-25

3.  The Feasibility and Utility of Harnessing Digital Health to Understand Clinical Trajectories in Medication Treatment for Opioid Use Disorder: D-TECT Study Design and Methodological Considerations.

Authors:  Lisa A Marsch; Ching-Hua Chen; Sara R Adams; Asma Asyyed; Monique B Does; Saeed Hassanpour; Emily Hichborn; Melanie Jackson-Morris; Nicholas C Jacobson; Heather K Jones; David Kotz; Chantal A Lambert-Harris; Zhiguo Li; Bethany McLeman; Varun Mishra; Catherine Stanger; Geetha Subramaniam; Weiyi Wu; Cynthia I Campbell
Journal:  Front Psychiatry       Date:  2022-04-29       Impact factor: 5.435

4.  Deriving symptom networks from digital phenotyping data in serious mental illness.

Authors:  Ryan Hays; Matcheri Keshavan; Hannah Wisniewski; John Torous
Journal:  BJPsych Open       Date:  2020-11-03

5.  Evaluating the utility of digital phenotyping to predict health outcomes in schizophrenia: protocol for the HOPE-S observational study.

Authors:  Nur Amirah Abdul Rashid; Wijaya Martanto; Zixu Yang; Xuancong Wang; Creighton Heaukulani; Nikola Vouk; Thisum Buddhika; Yuan Wei; Swapna Verma; Charmaine Tang; Robert J T Morris; Jimmy Lee
Journal:  BMJ Open       Date:  2021-10-20       Impact factor: 2.692

6.  Digital Phenotyping in Bipolar Disorder: Which Integration with Clinical Endophenotypes and Biomarkers?

Authors:  Laura Orsolini; Michele Fiorani; Umberto Volpe
Journal:  Int J Mol Sci       Date:  2020-10-16       Impact factor: 5.923

  6 in total

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