场景对面孔情绪探测的影响：特质性焦虑的调节作用

doi:10.3724/SP.J.1041.2019.00869

摘要/Abstract

摘要：

本研究采用面孔情绪探测任务, 通过状态-特质焦虑问卷筛选出高、低特质性焦虑被试, 考察场景对不同情绪效价以及不同情绪强度的面部表情加工的影响, 并探讨特质性焦虑在其中所发挥的作用。结果发现：(1)对于不同情绪效价的面部表情, 场景对其情绪探测的影响存在差异：对于快乐面部表情, 在100%、80%和20%三个情绪层级上, 在场景与面孔情绪性一致情况下, 被试对面孔情绪探测的正确率显著高于不一致情况; 对于恐惧面部表情, 在80%、60%、40%和20%四个情绪层级上, 均发现一致条件比不一致条件有着更高的情绪探测正确率。(2)对于高特质性焦虑组, 一致条件和不一致条件中的面孔情绪探测正确率并没有显著差异, 即高特质性焦虑组并未表现出显著的场景效应; 而低特质性焦虑组则差异显著, 即出现显著的场景效应。该研究结果表明：(1)对于情绪强度较低的面部表情, 快乐与恐惧面孔情绪探测都更容易受到场景的影响。(2)相比于中等强度快乐面孔, 场景更容易影响中等强度恐惧面孔情绪的探测。(3)特质性焦虑的个体因素在场景对面孔情绪探测的影响中发挥调节作用, 高特质性焦虑者在情绪识别中较少受到场景信息的影响。

关键词: 场景, 面部表情, 特质性焦虑, 场景效应, 调节作用

Abstract:

Facial expressions are fundamental emotional stimuli. They convey important information in social interaction. Most previous studies focused on the processing of isolated facial expressions. However, in everyday life, faces always appear within complex scenes. The emotional meaning of the scenes plays an important role in judging facial expressions. Additionally, facial expressions change constantly from appearance to disappearance. Visual scenes may have different effects on the processing of faces with different emotional intensities. Individual personality traits, such as trait anxiety, also affect the processing of facial expressions. For example, individuals with high trait anxiety have processing bias on negative emotional faces. The present study explored whether previously presented visual scenes affected the identification of emotions in morphed facial expressions, and whether the influences of visual scenes on the identification of facial expressions showed differences between individuals with high and low trait anxiety.

Using the Spielberger State-Trait Anxiety Inventory (STAI), we placed 29 participants who scored in the top 27% in the high trait anxiety group (9 men and 20 women; mean age 19.76 ± 1.3 years) and 28 participants who scored in the bottom 27% in the low trait anxiety group (11 males and 17 females, mean age 19.71 ± 1.2 years). The images of faces (4 models, half male and half female) used in this study were selected from the NimStim Set of Facial Expressions. The face stimuli showed typical happy, neutral, and fearful expressions. Facial expressions were morphed to create a series of gradually varied images of facial expressions. Specifically, fearful face (100%) versus neutral face (0%) and happy face (100%) versus neutral face (0%) were morphed in 20% increments. In addition, 40 surrounding scene images were used, with 20 positive scenes and 20 negative scenes. In the face-emotion detection task, participants were asked to determine whether the emotion from the faces presented after the scenes were fearful, happy, or neutral.

For the repeated measure ANOVA of the accuracy for facial expression detection, the results showed scene effects on the identification of emotions in facial expressions. The scene effects were varied between the different intensity of face emotion: for the emotionally vague faces, the detection of happy and fearful expression showed significant scene effects; for the faces with moderate emotional intensity, only the detection of the fearful faces showed significant scene effects; for the intense emotions on faces, there was a significant effect on happy and neutral faces but not on fearful faces. Trait anxiety as an individual factor was found to play a moderating role in the identification of facial expressions. For the high trait anxiety group, there were no significant differences in the accuracy of emotional detection between congruent and incongruent conditions. This means that the high trait anxiety group did not show significant scene effects. The low trait anxiety group showed a significant difference in the accuracy of identification of emotions in facial expressions between congruent and incongruent conditions, i.e., significant scene effects.In summary, the present study demonstrated that, for facial expressions with low emotional intensity, the identification of happy and fearful faces was more likely to be affected by visual scenes than the identification of neutral faces. Visual scenes were more likely to affect the identification of moderately fearful faces than moderately happy faces. Trait anxiety played a moderating role in the influence of visual scenes on emotional detection of facial expressions. Specifically, individuals with high trait anxiety were less affected by surrounding visual scenes and paid more attention to facial expressions.

Key words: visual scenes, facial expressions, trait anxiety, scene effects, moderating effects

中图分类号:

B842

李婉悦, 韩尚锋, 刘燊, 杨亚平, 张林, 徐强. (2019). 场景对面孔情绪探测的影响：特质性焦虑的调节作用. 心理学报, 51(8), 869-878.

LI Wanyue, HAN Shangfeng, LIU Shen, YANG Yaping, ZHANG Lin, XU Qiang. (2019). Scene effects on facial expression detection: The moderating effects of trait anxiety. Acta Psychologica Sinica, 51(8), 869-878.

图/表 5

表1 高低特质焦虑组被试基本情况

被试类型	年龄		特质性焦虑得分
被试类型	区间	M ± SD	区间	M ± SD
高特质性焦虑组 (n = 29)	[18, 24]	19.76 ± 1.3	[49, 71]	55.48 ± 4.82
低特质性焦虑组 (n = 28)	[18, 24]	19.71 ± 1.2	[24, 38]	31.39 ± 3.94

图1 不同情绪强度的面孔刺激样例

图2 实验流程图

图3 不同情绪强度的面部表情在不同场景中的探测正确率注：误差线表示标准误SE, * p < 0.05, ** p < 0.01

图4 特质性焦虑高组和低组对不同场景中快乐和恐惧面孔情绪的探测正确率注：误差线表示标准误SE, * p < 0.05, ** p < 0.01, ***p < 0.001

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