新的消极症状远程测量工具的原理和挑战。

Schizophrenia bulletin open Pub Date : 2024-10-18 eCollection Date: 2024-01-01 DOI:10.1093/schizbullopen/sgae027
David Gordon Daniel, Alex S Cohen, Philip D Harvey, Dawn I Velligan, William Z Potter, William P Horan, Raeanne C Moore, Stephen R Marder
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引用次数: 0

摘要

人们普遍认为,常用的由临床医生操作的阴性症状评估评分量表都有很大的局限性,包括:(1)依赖于患者和护理人员的准确自我报告和回忆;(2)可能存在抽样偏差,因此不能代表日常生活经验;(3)症状评分过程主观,对变化的敏感性有限。这些局限性促使国际中枢神经系统临床试验和方法学学会(ISCTM)的一个工作小组着手开发一种多模式阴性症状工具。来自学术界和工业界的专家回顾了目前评估消极症状领域的方法,这些领域包括:(1) 情感减退;(2) 社交能力减退;(3) 语言交流能力减退;(4) 目标导向行为减退;以及 (5) 享乐驱动力减退。对于每个领域,他们都记录了当前方法的局限性,并推荐了有可能纳入多模态工具的新方法。推荐的负面症状评估方法包括生态瞬间评估(EMA),即患者在日常生活中收到智能手机或其他设备的周期性提示后,自我报告其状况;以及通过检测和分析患者智能手机或其他设备捕获的音频/视频或传感器(如全球定位系统、行为记录仪)记录中患者的声音、外表或活动,直接推断负面症状。仪器的开发过程可以类似于 NIMH MATRICS 流程,该流程曾用于开发测量精神分裂症认知能力的电池。尽管 EMA 和其他针对阴性症状的数字测量方法还处于相对较早的开发/成熟阶段,开发这样一种工具也面临着巨大的挑战,但这些挑战都不是不可克服的。
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Rationale and Challenges for a New Instrument for Remote Measurement of Negative Symptoms.

There is a broad consensus that the commonly used clinician-administered rating scales for assessment of negative symptoms share significant limitations, including (1) reliance upon accurate self-report and recall from the patient and caregiver; (2) potential for sampling bias and thus being unrepresentative of daily-life experiences; (3) subjectivity of the symptom scoring process and limited sensitivity to change. These limitations led a work group from the International Society of CNS Clinical Trials and Methodology (ISCTM) to initiate the development of a multimodal negative symptom instrument. Experts from academia and industry reviewed the current methods of assessing the domains of negative symptoms including diminished (1) affect; (2) sociality; (3) verbal communication; (4) goal-directed behavior; and (5) Hedonic drives. For each domain, they documented the limitations of the current methods and recommended new approaches that could potentially be included in a multimodal instrument. The recommended methods for assessing negative symptoms included ecological momentary assessment (EMA), in which the patient self-reports their condition upon receipt of periodic prompts from a smartphone or other device during their daily routine; and direct inference of negative symptoms through detection and analysis of the patient's voice, appearance or activity from audio/visual or sensor-based (eg, global positioning systems, actigraphy) recordings captured by the patient's smartphone or other device. The process for developing an instrument could resemble the NIMH MATRICS process that was used to develop a battery for measuring cognition in schizophrenia. Although the EMA and other digital measures for negative symptoms are at relatively early stages of development/maturity and development of such an instrument faces substantial challenges, none of them are insurmountable.

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