Louisiana State University, Department of Psychology, 236 Audubon Hall, Baton Rouge, LA 70803, USA.
Louisiana State University, Department of Psychology, 236 Audubon Hall, Baton Rouge, LA 70803, USA.
Schizophr Res. 2020 Jun;220:141-146. doi: 10.1016/j.schres.2020.03.043. Epub 2020 Apr 1.
Negative symptoms reflect one of the most debilitating aspects of one of the most debilitating diseases known to humankind. As yet, our treatments for negative symptoms are palliative at best and our understanding of their causes is relatively superficial. To address this, we are developing objective ambulatory tools for digitally phenotyping their severity which can be used outside the confines of the traditional clinical and research settings. The present study evaluated the feasibility, reliability and validity of ambulatory vocal acoustic and facial emotion expression analysis. Videos were provided by 25 patients with schizophrenia or schizoaffective disorder and 27 nonpsychiatric controls using inexpensive, non-invasive ambulatory recording methods. Controls provided 411 video recordings, and patients provided 377 video recordings; an average of 15.22 and 14.50 per participant per group respectively. The vast majority (over 80%) of these videos were usable for analysis. An empirically-supported, limited-feature vocal (7 features) and facial (3 features) set was examined. Within participants, these features varied considerably over time, but showed moderate to good test-retest reliability in many cases once contextual factors (e.g., activity involved in at the time of testing) were accounted for. Vocal and facial features showed statistically significant convergence with a "gold standard" negative symptom measure. Ambulatory vocal/facial features were more strongly associated with engagement in social or work activities in patients than negative symptom ratings. These data support the use of ambulatory vocal/facial analytic technologies for digital phenotyping of these negative symptoms.
阴性症状反映了人类已知最具破坏性疾病之一的最具致残性方面之一。然而，我们对阴性症状的治疗充其量只是姑息性的，我们对其病因的理解还相对肤浅。为了解决这个问题，我们正在开发用于数字表型分析其严重程度的客观可移动工具，这些工具可以在传统临床和研究环境之外使用。本研究评估了可移动声音声学和面部情感表达分析的可行性、可靠性和有效性。使用廉价、非侵入性的可移动记录方法，由 25 名精神分裂症或分裂情感障碍患者和 27 名非精神病对照者提供视频。对照组提供了 411 个视频记录，患者提供了 377 个视频记录；平均每个参与者每个组分别提供 15.22 和 14.50 个。这些视频中有绝大多数（超过 80%）可用于分析。检查了一个基于经验的、有限特征的声音（7 个特征）和面部（3 个特征）集。在参与者内部，这些特征在时间上变化很大，但在考虑到上下文因素（例如，测试时涉及的活动）后，在许多情况下显示出中等至良好的测试-再测试可靠性。声音和面部特征与“金标准”阴性症状测量值具有统计学上的显著一致性。与阴性症状评分相比，可移动声音/面部特征与患者参与社交或工作活动的相关性更强。这些数据支持使用可移动声音/面部分析技术对这些阴性症状进行数字表型分析。
