Mobile cognitive remote assessment of schizophrenia: a global multi-site pilot study.

IF 4.1 Q2 PSYCHIATRY
Juan Castillo, Jiaee Cheong, Soumya Choudhary, Ameya Bondre, Abhijit R Rozatkar, Urvakhsh Meherwan Mehta, Ritu Shrivastava, Manaal Amir Ahmad, Anshika Malviya, Yogendra Sen, Deepak Tugnawat, Anant Bhan, Tamonud Modak, Nabagata Das, Srilakshmi Nagendra, Preethi Reddy, Ronak Chatterjee, Erlend Lane, John A Naslund, John Torous
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Abstract

Cognition in schizophrenia is difficult to assess in clinical settings due to the time required to administer traditional pen-and-paper tests, among other factors. Digital remote assessments completed on a smartphone offer an alternative that can reduce the burden on healthcare staff and patients, in addition to providing more nuanced cognitive profiles, especially when used in conjunction with smartphone data such as sleep. Building on previous work using the mindLAMP research app in international contexts, this paper presents a global multi-site pilot study to explore the validity of the app's digital cognitive assessments as proxies for traditional in-person assessments such as the gold standard MATRICS Consensus Battery (MCCB). Across one site in the U.S. (Boston) and two sites in India (Bangalore and Bhopal), a total of 56 participants with diagnoses of early-course schizophrenia or schizoaffective disorder were recruited between September 2024 and March 2025 to engage with the mindLAMP app for 30 days. Participants completed 2-3 different cognitive tasks and surveys each day; at the beginning and the end of this period, participants also took the MCCB and surveys related to their diagnosis. mindLAMP cognitive assessments were scored using different metrics that combine speed and accuracy, and correlation analyses were run on these metrics and MCCB domains. Of the scoring metrics used, the Rate-Correct Score (RCS) most consistently correlates with baseline MCCB domains corrected for age, gender, and education. Moderate test-retest reliability was observed across certain cognitive assessments such as a mobile version of Trails-Making Test A and Symbol Digit Substitution, which agrees with previous research done by Keefe et al.; poor test-retest reliability, in contrast, was observed across assessments such as Spatial Span. Additionally, we conducted exploratory mediation analyses using sleep data to see if sleep mediates between the Ecological Momentary Assessment (EMA) survey scores and performance on select digital cognitive assessments on mindLAMP. Our results support the initial accessibility, validity and reliability of using smartphones to assess cognition in schizophrenia. Future research to develop additional smartphone-based cognitive tests, as well as with larger samples and in other psychiatric populations, is warranted.

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精神分裂症的移动认知远程评估:一项全球多地点试点研究。
精神分裂症患者的认知很难在临床环境中进行评估,因为传统的笔和纸测试需要时间,以及其他因素。在智能手机上完成的数字远程评估提供了另一种选择,除了提供更细致的认知概况外,还可以减轻医护人员和患者的负担,特别是在与智能手机数据(如睡眠数据)结合使用时。基于之前在国际背景下使用mindLAMP研究应用程序的工作,本文提出了一项全球多地点试点研究,以探索该应用程序的数字认知评估作为传统面对面评估(如黄金标准matrix共识电池(MCCB))的有效性。在美国(波士顿)和印度(班加罗尔和博帕尔)的两个地点,共有56名被诊断为早期精神分裂症或分裂情感性障碍的参与者在2024年9月至2025年3月期间参与mindLAMP应用程序30天。参与者每天完成2-3个不同的认知任务和调查;在这段时间的开始和结束时,参与者也接受了MCCB和与他们的诊断相关的调查。使用结合速度和准确性的不同指标对mindLAMP认知评估进行评分,并对这些指标和MCCB域进行相关性分析。在使用的评分指标中,正确率评分(RCS)最一致地与根据年龄、性别和教育程度校正的基线MCCB域相关。在某些认知评估中,如移动版的轨迹制作测试a和符号数字替换,观察到适度的测试重测可靠性,这与Keefe等人之前的研究一致;相比之下,在诸如空间跨度等评估中观察到较差的重测信度。此外,我们使用睡眠数据进行了探索性中介分析,以了解睡眠是否在生态瞬时评估(EMA)调查得分和mindLAMP选择数字认知评估的表现之间起中介作用。我们的研究结果支持了使用智能手机评估精神分裂症认知的初步可及性、有效性和可靠性。未来的研究需要开发更多的基于智能手机的认知测试,以及更大的样本和其他精神病学人群。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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