健康与遗传心理学研究室知识库

重性抑郁障碍是常见的精神疾病之一，其核心症状为心境低落、兴趣减退、 快感缺乏，同时认知和行为也会发生变化。抑郁症患者普遍存在认知损伤，集中体现于记忆、注意、执行功能等神经认知损伤和情绪识别、社会决策等社会 认知损伤。抑郁症患者情绪认知功能受损，继而辨别他人表情的能力减弱，同时自身面部表情也出现改变：其微笑减少、面部活动减少、眨眼频率降低。面部表情作为一种情绪表达和非语言交流的客观参数在抑郁症的辅助诊断中开始起到越来越重要的作用，在临床上通过面部表情辅助诊断的准确率还没有定论，且面部表情和认知的关系也没有被探究。本研究使用元分析等方法，将横断调查与纵向追踪相结合，系统地描述重性抑郁障碍患者的面部表情，并探究其与认知的关系。

研究一首先通过系统性综述和元分析，对近十年关于面部表情和重性抑郁障碍患者抑郁程度的研究做全面地梳理和归纳，在既往研究准确率和相关度不同的情况下，确认二者是否存在相关关系，且分类准确度是否稳定。结果显示面部表情在分类准确率在 73.6%，且较为稳定，与抑郁症状的相关系数 r= 0.306，虽研究间有较大差异，但最终的正相关性显著（p=0.005）。

研究二旨在通过横断研究探究在重性抑郁障碍患者中，面部表情是否可以作为靶点有效分类患者和健康对照组并探究重性抑郁障碍患者面部表情与认知损伤之间的关系。使用问卷调查法和时间线回溯法记录患者的人口学信息和临 床用药、汉密尔顿抑郁量表和汉密尔顿焦虑量表评估患者症状严重程度、多伦多抒情障碍量表和可重复的成套心理状态测量表评估认知损伤情况，并记录面部表情。招募 109 名抑郁患者和 129 名健康对照组，结果发现面部表情的分类准确率高达 85.40%，可以较准确区分抑郁和健康对照组。进一步的相关分析发 现面部表情和 RBANS 中的语言能力显著相关（r= -0.234, p=0.021），表明其面部僵化会影响语言表达能力。进一步分亚组，在中重度抑郁组内，面部表情和抑郁症状呈正相关（r= 0.301, p=0.021），表明抑郁程度对面部表情有影响。

研究三采用纵向设计，在真实世界治疗下对 38 名抑郁患者治疗 8-12 周后的情况进行追踪，并比较在真实世界治疗前后，其临床症状、认知功能以及面部表情是否发生改变。结果显示治疗前后抑郁患者的抑郁症状显著降低（p<0.001），认知功能部分外向性思维、即时记忆、视觉空间能力、延迟记忆和总分维度有一定提升（p<0.05），面部表情也发生改变（p<0.01），进一步的分析发现面部表情对症状及认知改善的预测作用并不显著。

综上，本研究首次梳理了面部表情作为一种鉴别方法用来鉴别抑郁和健康组的有效性，同时探究面部表情与认知是否有关，在真实世界治疗中是否可以有效反应症状的缓解情况。在理论层面上，可以进一步厘清面部表情和抑郁症状、认知之间的关系，为了解抑郁症患者面部表情和认知损伤的潜在机制提供一定的理论支持。在临床实践方面，本研究可为抑郁症诊断提供新颖思路，有助于增加诊疗的准确性和有效性，为多元化防症状隐匿并建立针对性干预方案 提供启发，进而推动领域前沿发展。

Major depressive disorder (MDD) is a prevalent mental health condition characterized by core symptoms such as persistent low mood, diminished interest or pleasure, and alterations in cognition and behavior. Individuals with MDD commonly exhibit cognitive deficits, particularly in memory, attention, executive functions, emotional recognition, social decision-making, and other aspects of social cognition. These cognitive impairments impact the emotional cognitive functions of MDD patients, leading to reduced capability in recognizing facial expressions of others and alterations in their own facial expressions including decreased smiles, diminished facial movements, and reduced blinking frequency. Facial expressions, serving as an objective measure of emotional expression and non-verbal communication, are increasingly recognized for their significant role in aiding the diagnosis of depression. Nonetheless, the accuracy of diagnosing depression based on facial expressions in clinical settings remains inconclusive, and the link between facial expressions and cognition requires further examination. This study utilizes meta-analysis and integrates cross-sectional surveys with longitudinal tracking to meticulously delineate facial expressions in individuals with MDD and investigate their association with cognitive functions.

Study 1 initiates a comprehensive review and meta-analysis of studies conducted within the past decade regarding the severity of depression and facial expressions in individuals with major depressive disorder. Despite variability in the precision and relevance of previous studies, the findings indicate a classification accuracy of facial expressions at 73.6%, correlating stably with depressive symptoms at a coefficient of r = 0.306. Although considerable divergence exists among the studies, the ultimately observed positive correlation is statistically significant (p = 0.005).

Study 2 seeks to examine the feasibility of utilizing facial expressions as effective indicators for categorizing individuals with major depressive disorder and healthy controls, and to investigate the correlation between facial expressions and cognitive impairments. Employing questionnaire surveys and retrospective timelines, the study gathers participants' demographic details, medical treatments, Hamilton Depression Rating Scale, Hamilton Anxiety Rating Scale for symptom severity assessment, Toronto Alexithymia Scale, and RBANS for cognitive impairment evaluation, while also documenting facial expressions. With a recruitment of 109 depressive patients and 129 healthy controls, the study identifies a notable classification accuracy of facial expressions at 85.40%, facilitating a relatively precise differentiation between the depressive and healthy control groups. Further correlation analysis reveals a significant association between facial expressions and language abilities in RBANS (r = -0.234, p = 0.021), illustrating the impact of facial rigidity on language expression. Subgroup analysis within the moderate to severe depression group uncovers a positive correlation between facial expressions and depressive symptoms (r = 0.301, p = 0.021), indicates that the level of depression has an effect on facial expressions.

In Study 3, a longitudinal approach is employed to monitor the progress of 38 depressive patients who underwent 8-12 weeks treatment in real-world settings. Comparative analysis of clinical symptoms, cognitive functions, and facial expressions before and after real-world treatment reveals a marked reduction in depressive symptoms (p < 0.001), improvements in certain cognitive functions (p < 0.01), and facial expressions also changed. (p < 0.01). Further investigation suggests that facial expressions do not significantly forecast symptom and cognitive enhancements.

In conclusion, this study, for the first time, evaluates the efficacy of facial expressions as a discriminatory tool for distinguishing between individuals with depression and healthy cohorts, while delving into the association between facial expressions and cognition. The research may furnish theoretical underpinning for elucidating the correlation between facial expressions and depressive symptoms as well as cognition, enhancing the comprehension of potential mechanisms of facial expressions and cognitive impairments in individuals with depression. From a clinical perspective, this study introduces a pioneering diagnostic approach to depression, enhancing diagnostic accuracy and efficiency, stimulating the development of targeted intervention strategies for a varied symptomatology, and fostering advancements at the forefront of the discipline.