Holmlund Terje B, Chandler Chelsea, Foltz Peter W, Cohen Alex S, Cheng Jian, Bernstein Jared C, Rosenfeld Elizabeth P, Elvevåg Brita
1UiT The Arctic University of Norway, Tromsø, Norway.
2University of Colorado Boulder, Boulder, CO USA.
NPJ Digit Med. 2020 Mar 11;3:33. doi: 10.1038/s41746-020-0241-7. eCollection 2020.
Verbal memory deficits are some of the most profound neurocognitive deficits associated with schizophrenia and serious mental illness in general. As yet, their measurement in clinical settings is limited to traditional tests that allow for limited administrations and require substantial resources to deploy and score. Therefore, we developed a digital ambulatory verbal memory test with automated scoring, and repeated self-administration via smart devices. One hundred and four adults participated, comprising 25 patients with serious mental illness and 79 healthy volunteers. The study design was successful with high quality speech recordings produced to 92% of prompts (Patients: 86%, Healthy: 96%). The story recalls were both transcribed and scored by humans, and scores generated using natural language processing on transcriptions were comparable to human ratings (R = 0.83, within the range of human-to-human correlations of R = 0.73-0.89). A fully automated approach that scored transcripts generated by automatic speech recognition produced comparable and accurate scores (R = 0.82), with very high correlation to scores derived from human transcripts (R = 0.99). This study demonstrates the viability of leveraging speech technologies to facilitate the frequent assessment of verbal memory for clinical monitoring purposes in psychiatry.
言语记忆缺陷是精神分裂症以及一般严重精神疾病相关的一些最严重的神经认知缺陷。到目前为止，在临床环境中对它们的测量仅限于传统测试，这些测试允许的施测次数有限，并且需要大量资源来进行施测和评分。因此，我们开发了一种具有自动评分功能的数字动态言语记忆测试，并可通过智能设备进行重复自我施测。104名成年人参与了研究，其中包括25名患有严重精神疾病的患者和79名健康志愿者。研究设计取得成功，92%的提示产生了高质量的语音记录（患者：86%，健康者：96%）。故事回忆由人工转录和评分，并且使用自然语言处理对转录内容生成的分数与人工评分相当（R = 0.83，在人类之间相关性范围R = 0.73 - 0.89内）。一种对自动语音识别生成的转录内容进行评分的全自动方法产生了可比且准确的分数（R = 0.82），与从人工转录内容得出的分数具有非常高的相关性（R = 0.99）。这项研究证明了利用语音技术促进对言语记忆进行频繁评估以用于精神病学临床监测目的的可行性。
