Department of Psychological and Brain Sciences, Drexel University, Philadelphia, Pennsylvania, USA.
Center for Weight, Eating, and Lifestyle Science, Drexel University, Philadelphia, Pennsylvania, USA.
Int J Eat Disord. 2022 May;55(5):573-624. doi: 10.1002/eat.23715. Epub 2022 Apr 30.
Sensor technologies offer exciting potential to objectively measure psychopathological correlates of eating pathology and eating disorder (ED) research utilizing sensors has rapidly proliferated in the past several years. The aims of the present review are: (1) characterize the types of sensors that have been utilized in ED research, (2) identify the psychopathological factors relevant to EDs that have been assessed using sensors, (3) describe the data supporting the validity and reliability of these sensors, (4) discuss limitations associated with these sensors, and (5) identify gaps that persist within the ED literature with regard to use of sensor technologies.
A systematic search was conducted of PubMed, PsycINFO, Web of Science, ProQuest, and "gray" literature sources. Eligible publications were empirical studies that utilized sensors to measure at least one psychological variable among clinical ED populations.
Sensors have been utilized with ED samples to measure eating behaviors, physical activity, sleep, autonomic nervous system activity, eyeblink startle response, visual attention, and visual-haptic object integration. The reliability and validity of these sensors varies widely and there are a number of significant gaps that remain in the literature with regard to the types of sensors utilized, context in which sensors have been used, and populations studied.
The existing literature utilizing sensors within ED research largely support the feasibility and acceptability of these tools. Sensors should continue to be utilized within the field, with a specific focus on examining the reliability and validity of these tools within ED samples and increasing the diversity of samples studied.
Sensor technologies, such as those included in modern smartwatches, offer new opportunities to measure factors that may maintain or contribute to symptoms of eating disorders. This article describes the types of sensors that have been used in eating disorders research, challenges that may arise in using these sensors, and discusses new applications of these sensors that may be pursued in future research.
传感器技术为客观测量进食障碍相关的心理病理因素提供了令人兴奋的潜力,利用传感器进行进食障碍研究在过去几年中迅速发展。本综述的目的是:(1)描述用于进食障碍研究的传感器类型,(2)确定使用传感器评估的与进食障碍相关的心理病理因素,(3)描述这些传感器的有效性和可靠性数据,(4)讨论这些传感器相关的局限性,(5)确定在利用传感器技术方面,进食障碍文献中仍然存在的差距。
对 PubMed、PsycINFO、Web of Science、ProQuest 和“灰色”文献来源进行了系统检索。符合条件的出版物是利用传感器测量临床进食障碍人群至少一个心理变量的实证研究。
传感器已用于进食障碍样本,以测量进食行为、身体活动、睡眠、自主神经系统活动、眨眼惊跳反应、视觉注意力和视觉触觉物体整合。这些传感器的可靠性和有效性差异很大,在文献中仍存在许多重大差距,涉及使用的传感器类型、传感器使用的环境以及研究的人群。
在进食障碍研究中利用传感器的现有文献在很大程度上支持了这些工具的可行性和可接受性。应继续在该领域利用传感器,特别关注在进食障碍样本中检查这些工具的可靠性和有效性,并增加研究样本的多样性。
传感器技术,如现代智能手表中包含的技术,为测量可能维持或导致进食障碍症状的因素提供了新的机会。本文描述了用于进食障碍研究的传感器类型,使用这些传感器可能出现的挑战,并讨论了这些传感器在未来研究中可能应用的新应用。