Literature DB >> 35276573

Ambulatory audio and video recording for digital phenotyping in schizophrenia: Adherence & data usability.

Tovah Cowan1, Alex S Cohen1, Ian M Raugh2, Gregory P Strauss3.   

Abstract

Ambulatory audio and video recording provides a wealth of information which can be used for a broad range of applications, including digital phenotyping, telepsychiatry, and telepsychology. However, these technologies are in their infancy, and guidelines for their use and analysis have yet to be established. The current project used ambulatory assessment data from individuals with schizophrenia (N = 52) and controls (N = 55) over a week to assess factors influencing sufficiency and useability of video and audio data. Logistic multilevel models examined the effect of relevant variables on video provision and video quality. There was no difference by group in video provision or quality. Videos were less likely to be provided later in the study and later in the day. Video quality was lower later in the day, particularly for controls. Participants were more likely to provide videos if alone or at home than in other settings. Black participants were less likely to have analyzable video frames than White participants. These results suggest potential racial disparities in camera technologies and/or facial analysis algorithms. Implications of these findings and recommendations for future study development, such as instructions to provide to participants to optimize video quality, are discussed.
Copyright © 2022 Elsevier B.V. All rights reserved.

Entities:  

Keywords:  acoustic analysis; biobehavioral data; computerized facial analysis; digital phenotyping; ecological momentary assessment

Mesh:

Year:  2022        PMID: 35276573      PMCID: PMC9018573          DOI: 10.1016/j.psychres.2022.114485

Source DB:  PubMed          Journal:  Psychiatry Res        ISSN: 0165-1781            Impact factor:   11.225


  21 in total

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Journal:  Am J Psychiatry       Date:  2008-01-02       Impact factor: 18.112

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Authors:  Alex S Cohen
Journal:  Psychol Assess       Date:  2019-03

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5.  Vocal acoustic analysis as a biometric indicator of information processing: implications for neurological and psychiatric disorders.

Authors:  Alex S Cohen; Thomas J Dinzeo; Neila J Donovan; Caitlin E Brown; Sean C Morrison
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6.  Machine Learning Identifies Digital Phenotyping Measures Most Relevant to Negative Symptoms in Psychotic Disorders: Implications for Clinical Trials.

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7.  How do social factors relate to blunted facial affect in schizophrenia? A digital phenotyping study using ambulatory video recordings.

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8.  Deconstructing emotion regulation in schizophrenia: the nature and consequences of abnormalities at the identification stage.

Authors:  Ian M Raugh; Gregory P Strauss
Journal:  Eur Arch Psychiatry Clin Neurosci       Date:  2021-10-30       Impact factor: 5.760

9.  Digital phenotyping adherence, feasibility, and tolerability in outpatients with schizophrenia.

Authors:  Ian M Raugh; Sydney H James; Cristina M Gonzalez; Hannah C Chapman; Alex S Cohen; Brian Kirkpatrick; Gregory P Strauss
Journal:  J Psychiatr Res       Date:  2021-04-30       Impact factor: 5.250

10.  Cognitive deficits and functional outcome in schizophrenia.

Authors:  Christopher R Bowie; Philip D Harvey
Journal:  Neuropsychiatr Dis Treat       Date:  2006-12       Impact factor: 2.570

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  1 in total

1.  Computerized analysis of facial expressions in serious mental illness.

Authors:  Tovah Cowan; Michael D Masucci; Tina Gupta; Claudia M Haase; Gregory P Strauss; Alex S Cohen
Journal:  Schizophr Res       Date:  2022-01-22       Impact factor: 4.939

  1 in total

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