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用于精神分裂症数字表型分析的动态音频和视频记录:依从性与数据可用性。

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

作者信息

Cowan Tovah, Cohen Alex S, Raugh Ian M, Strauss Gregory P

机构信息

Department of Psychology, Louisiana State University, Baton Rouge, USA; Center for Computation and Technology, Louisiana State University, Baton Rouge, USA.

Department of Psychology, University of Georgia, Athens, USA.

出版信息

Psychiatry Res. 2022 May;311:114485. doi: 10.1016/j.psychres.2022.114485. Epub 2022 Feb 25.

DOI:10.1016/j.psychres.2022.114485
PMID:35276573
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC9018573/
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.

摘要

动态音频和视频记录提供了丰富的信息,可用于广泛的应用,包括数字表型分析、远程精神病学和远程心理学。然而,这些技术尚处于起步阶段,其使用和分析指南尚未建立。当前项目使用了来自精神分裂症患者(N = 52)和对照组(N = 55)的一周动态评估数据,以评估影响视频和音频数据充足性和可用性的因素。逻辑多层模型研究了相关变量对视频提供和视频质量的影响。两组在视频提供或质量方面没有差异。在研究后期和当天晚些时候提供视频的可能性较小。当天晚些时候视频质量较低,尤其是对照组。与其他环境相比,参与者单独或在家时更有可能提供视频。黑人参与者比白人参与者拥有可分析视频帧的可能性更小。这些结果表明在摄像头技术和/或面部分析算法方面可能存在种族差异。讨论了这些发现的意义以及对未来研究发展的建议,例如向参与者提供的优化视频质量的说明。

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本文引用的文献

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Schizophr Bull. 2022 Sep 1;48(5):939-948. doi: 10.1093/schbul/sbac051.
2
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J Psychiatr Res. 2022 Jun;150:96-104. doi: 10.1016/j.jpsychires.2022.03.024. Epub 2022 Mar 24.
3
Deconstructing emotion regulation in schizophrenia: The nature and consequences of abnormalities in monitoring dynamics.精神分裂症中的情绪调节解构:监测动态异常的性质和后果。
Schizophr Res. 2022 Feb;240:135-142. doi: 10.1016/j.schres.2021.12.043. Epub 2022 Jan 10.
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Ecological Momentary Assessment: A Meta-Analysis on Designs, Samples, and Compliance Across Research Fields.生态瞬间评估:跨研究领域的设计、样本和依从性的荟萃分析。
Assessment. 2023 Apr;30(3):825-846. doi: 10.1177/10731911211067538. Epub 2022 Jan 11.
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Machine Learning Identifies Digital Phenotyping Measures Most Relevant to Negative Symptoms in Psychotic Disorders: Implications for Clinical Trials.机器学习确定与精神病性障碍的阴性症状最相关的数字表型测量指标:对临床试验的影响。
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