Liu Gang, Henson Philip, Keshavan Matcheri, Pekka-Onnela Jukka, Torous John
Department of Biostatistics, Harvard TH Chan School of Public Health, Boston, MA, United States.
Division of Digital Psychiatry, Department of Psychiatry, Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, MA, United States.
Schizophr Res Cogn. 2019 Apr 18;17:100144. doi: 10.1016/j.scog.2019.100144. eCollection 2019 Sep.
Although cognition is a core symptom of schizophrenia and associated with functional impairment, the degree of training for and time associated with its assessment makes it difficult to routinely monitor in clinic care.Smartphone based cognitive assessments could serve as a tool to measure cognition in real time as well as being easily scalable for broad use.Combined with other data gathered from smartphone sensors such as steps, sleep, and self-reported symptoms - capturing 'cognition in context' could provide a powerful new tool for assessing the functional burden of disease in schizophrenia.
18 participants with schizophrenia and 17 healthy controls completed novel cognitive assessments on their personal smartphones over the course of 12 weeks while also capturing self-reported surveys and step count. No payment or incentives were offered for engaging with the smartphone app. Differing levels of difficulty in cognitive tasks were tested and the results were modeled using a modified Cox proportional hazard model.
On the smartphone cognitive assessments that involved on simple patterns, both controls and those with schizophrenia achieved similar scores. On the more complex assessment that added task switching in addition to pattern recognition, those with schizophrenia achieved scores lower than controls. Collecting other forms of data such as surveys and steps was also feasible using the same smartphone platform.
It is feasible for those with schizophrenia to use their own smartphones to complete cognitive assessments and other measures related to their mental health. While we did not investigate the correlations between these cognitive assessments and other smartphone captured metrics like step count or self-reported symptoms, the potential to longitudinally assess cognition in the context of patients' environments outside of the clinic presents unique opportunities for characterizing cognitive burden in schizophrenia.
尽管认知是精神分裂症的核心症状且与功能损害相关,但其评估所需的训练程度和时间使得在临床护理中难以进行常规监测。基于智能手机的认知评估可作为实时测量认知的工具,并且易于扩展以广泛应用。结合从智能手机传感器收集的其他数据,如步数、睡眠和自我报告的症状——捕捉“情境中的认知”可为评估精神分裂症患者的疾病功能负担提供一个强大的新工具。
18名精神分裂症患者和17名健康对照在12周内通过个人智能手机完成了新颖的认知评估,同时还收集了自我报告的调查和步数。参与智能手机应用程序未提供报酬或激励措施。测试了不同难度水平的认知任务,并使用改良的Cox比例风险模型对结果进行建模。
在涉及简单模式的智能手机认知评估中,对照组和精神分裂症患者的得分相似。在除模式识别外还增加了任务切换的更复杂评估中,精神分裂症患者的得分低于对照组。使用同一智能手机平台收集调查和步数等其他形式的数据也是可行的。
精神分裂症患者使用自己的智能手机完成认知评估和其他与心理健康相关的测量是可行的。虽然我们没有研究这些认知评估与其他智能手机捕获的指标(如步数或自我报告的症状)之间的相关性,但在诊所外患者环境中纵向评估认知的潜力为表征精神分裂症的认知负担提供了独特的机会。