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面对变化:使用自动化面部表情分析来考察抑郁症治疗中的情绪灵活性。

Facing Change: Using Automated Facial Expression Analysis to Examine Emotional Flexibility in the Treatment of Depression.

机构信息

Department of Psychology, Bar-Ilan University, Ramat-Gan, Israel.

Department of Psychology, Ben-Gurion University of the Negev, Beer-Sheva, Israel.

出版信息

Adm Policy Ment Health. 2024 Jul;51(4):501-508. doi: 10.1007/s10488-023-01310-w. Epub 2023 Oct 25.

Abstract

OBJECTIVE

Depression involves deficits in emotional flexibility. To date, the varied and dynamic nature of emotional processes during therapy has mostly been measured at discrete time intervals using clients' subjective reports. Because emotions tend to fluctuate and change from moment to moment, the understanding of emotional processes in the treatment of depression depends to a great extent on the existence of sensitive, continuous, and objectively codified measures of emotional expression. In this observational study, we used computerized measures to analyze high-resolution time-series facial expression data as well as self-reports to examine the association between emotional flexibility and depressive symptoms at the client as well as at the session levels.

METHOD

Video recordings from 283 therapy sessions of 58 clients who underwent 16 sessions of manualized psychodynamic psychotherapy for depression were analyzed. Data was collected as part of routine practice in a university clinic that provides treatments to the community. Emotional flexibility was measured in each session using an automated facial expression emotion recognition system. The clients' depression level was assessed at the beginning of each session using the Beck Depression Inventory-II (Beck et al., 1996).

RESULTS

Higher emotional flexibility was associated with lower depressive symptoms at the treatment as well as at the session levels.

CONCLUSION

These findings highlight the centrality of emotional flexibility both as a trait-like as well as a state-like characteristic of depression. The results also demonstrate the usefulness of computerized measures to capture key emotional processes in the treatment of depression at a high scale and specificity.

摘要

目的

抑郁涉及情绪灵活性的缺陷。迄今为止,治疗过程中情绪的多变性和动态性主要是通过客户的主观报告在离散时间间隔进行测量。由于情绪往往会随时间波动和变化,因此对治疗抑郁症过程中情绪的理解在很大程度上取决于是否存在敏感、连续和客观编码的情绪表达测量方法。在这项观察性研究中,我们使用计算机化的方法来分析高分辨率的时间序列面部表情数据以及自我报告,以检查情绪灵活性与客户和会话层面的抑郁症状之间的关联。

方法

对 58 名接受 16 次手动心理动力学心理治疗的抑郁症患者的 283 次治疗会议的视频记录进行了分析。数据是作为为社区提供治疗的大学诊所常规实践的一部分收集的。在每次会议中,使用自动化面部表情情绪识别系统测量情绪灵活性。在每次会议开始时,使用贝克抑郁量表第二版(贝克等人,1996 年)评估客户的抑郁程度。

结果

更高的情绪灵活性与治疗以及会议层面的抑郁症状降低有关。

结论

这些发现强调了情绪灵活性作为抑郁的一种特质和状态特征的核心地位。结果还表明,计算机化的测量方法在大规模和特定范围内捕捉抑郁症治疗中的关键情绪过程非常有用。

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