Ambulatory audio and video recording for digital phenotyping in schizophrenia: Adherence & data usability. (May 2022)

• Record Type: Journal Article
• Authors: Cowan, Tovah; Cohen, Alex S.; Raugh, Ian M.; Strauss, Gregory P.
• Is Part Of: Psychiatry research. Volume 311(2022)
• Publication Date: 2022-05
• Subjects: ecological momentary assessment -- computerized facial analysis -- acoustic analysis -- digital phenotyping -- biobehavioral data; Psychiatry -- Periodicals; Psychiatry -- periodicals; Psychiatrie -- Périodiques; 616.89
• DOI: 10.1016/j.psychres.2022.114485
• Languages: English
• ISSNs: 0165-1781

Abstract

Highlights: Stable outpatients with serious mental illness can complete video selfies, once trained to do so, regardless of comorbid symptoms, cognitive impairments, age, or technological experience. Software developers should improve their technology to better adapt to a variety of skin tones and light conditions. Recording quality can be optimized by requesting videos during daylight hours and when participants are in an undisturbed and private environment. 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.