Mucci Armida, Leucht Stefan, Giordano Giulia M, Giuliani Luigi, Wehr Sophia, Weigel Lucia, Galderisi Silvana
Department of Mental and Physical Health and Preventive Medicine, School of Medicine, University of Campania Luigi Vanvitelli, Largo Madonna delle Grazie 1, 80135 Naples, Italy.
Department of Psychiatry and Psychotherapy, School of Medicine, Technical University of Munich, Klinikum Rechts der Isar, Ismaningerstrasse 22, 81675 Munich, Germany.
Brain Sci. 2025 Jan 17;15(1):83. doi: 10.3390/brainsci15010083.
The assessment of negative symptoms in schizophrenia has advanced since the 2006 NIMH-MATRICS Consensus Statement, leading to the development of second-generation rating scales like the Brief Negative Symptom Scale and the Clinical Assessment Interview for Negative Symptoms. These scales address the limitations of first-generation tools, such as the inclusion of aspects that are not negative symptoms and the lack of assessment of the subject's internal experience. However, psychometric validation of these scales is still in progress, and they are not yet recommended by regulatory agencies, thus limiting their use in clinical trials and settings. Complementing these traditional methods, remote digital phenotyping offers a novel approach by leveraging smartphones and wearable technology to capture real-time, high-resolution clinical data. Despite the potential to overcome traditional assessment barriers, challenges remain in aligning these digital measures with clinical ratings and ensuring data security. Equally important is patient acceptance, as the success of remote digital phenotyping relies on the willingness of patients to use these technologies. This review provides a critical overview of both second-generation scales and remote digital phenotyping for assessing negative symptoms, highlighting future research needs.
自2006年美国国立精神卫生研究所(NIMH)-测量与治疗研究以改善精神分裂症(MATRICS)共识声明发布以来,精神分裂症阴性症状的评估取得了进展,催生了第二代评定量表,如简明阴性症状量表和阴性症状临床评估访谈。这些量表解决了第一代工具的局限性,比如纳入了并非阴性症状的方面以及缺乏对受试者内心体验的评估。然而,这些量表的心理测量学验证仍在进行中,监管机构尚未推荐使用,因此限制了它们在临床试验和临床环境中的应用。作为这些传统方法的补充,远程数字表型分析通过利用智能手机和可穿戴技术来获取实时、高分辨率的临床数据,提供了一种新颖的方法。尽管有克服传统评估障碍的潜力,但在使这些数字测量与临床评分保持一致以及确保数据安全方面仍存在挑战。同样重要的是患者的接受度,因为远程数字表型分析的成功依赖于患者使用这些技术的意愿。本综述对用于评估阴性症状的第二代量表和远程数字表型分析进行了批判性概述,突出了未来的研究需求。