Ruihua Ma, Meng Zhao, Nan Chen, Panqi Liu, Hua Guo, Sijia Liu, Jing Shi, Ke Zhao, Yunlong Tan, Shuping Tan, Fude Yang, Li Tian, Zhiren Wang
Peking University HuiLongGuan Clinical Medical School, Beijing Huilongguan Hospital, Beijing, China.
Department of Neurosurgery, Sanbo Brain Hospital, Capital Medical University, Beijing, China.
Front Psychol. 2021 Jul 14;12:619368. doi: 10.3389/fpsyg.2021.619368. eCollection 2021.
To explore the differences in facial emotion recognition among patients with unipolar depression (UD), bipolar depression (BD), and normal controls.
Thirty patients with UD and 30 patients with BD, respectively, were recruited in Zhumadian Second People's Hospital from July 2018 to August 2019. Fifteen groups of facial expressions including happiness, sadness, anger, surprise, fear, and disgust were identified.
A single-factor ANOVA was used to analyze the facial expression recognition results of the three groups, and the differences were found in the happy-sad ( = 0.009), happy-angry ( = 0.001), happy-surprised ( = 0.034), and disgust-surprised ( = 0.038) facial expression groups. The independent sample -test analysis showed that compared with the normal control group, there were differences in the happy-sad ( = 0.009) and happy-angry ( = 0.009) groups in patients with BD, and the accuracy of facial expression recognition was lower than the normal control group. Compared with patients with UD, there were differences between the happy-sad ( = 0.005) and happy-angry ( = 0.002) groups, and the identification accuracy of patients with UD was higher than that of patients with BD. The time of facial expression recognition in the normal control group was shorter than that in the patient group. Using happiness-sadness to distinguish unipolar and BDs, the area under the ROC curve (AUC) is 0.933, the specificity is 0.889, and the sensitivity is 0.667. Using happiness-anger to distinguish unipolar and BD, the AUC was 0.733, the specificity was 0.778, and the sensitivity was 0.600.
Patients with UD had lower performance in recognizing negative expressions and had longer recognition times. Those with BD had lower accuracy in recognizing positive expressions and longer recognition times. Rapid facial expression recognition performance may be as a potential endophenotype for early identification of unipolar and BD.
探讨单相抑郁(UD)、双相抑郁(BD)患者及正常对照者面部表情识别能力的差异。
2018年7月至2019年8月,在驻马店市第二人民医院分别招募30例UD患者和30例BD患者。识别出包括快乐、悲伤、愤怒、惊讶、恐惧和厌恶在内的15组面部表情。
采用单因素方差分析对三组的面部表情识别结果进行分析,发现快乐-悲伤(=0.009)、快乐-愤怒(=0.001)、快乐-惊讶(=0.034)和厌恶-惊讶(=0.038)面部表情组存在差异。独立样本检验分析显示,与正常对照组相比,BD患者在快乐-悲伤(=0.009)和快乐-愤怒(=0.009)组存在差异,面部表情识别准确率低于正常对照组。与UD患者相比,快乐-悲伤(=0.005)和快乐-愤怒(=0.002)组存在差异,UD患者的识别准确率高于BD患者。正常对照组面部表情识别时间短于患者组。用快乐-悲伤区分单相和双相抑郁,ROC曲线下面积(AUC)为0.933,特异性为0.889,敏感性为0.667。用快乐-愤怒区分单相和双相抑郁,AUC为0.733,特异性为0.778,敏感性为0.600。
UD患者在识别负面表情方面表现较差,识别时间较长。BD患者在识别正面表情方面准确率较低,识别时间较长。快速面部表情识别能力可能作为早期识别单相和双相抑郁的潜在内表型。