Institute of Education & Child Studies, Section Forensic Family & Youth Care, Leiden University, The Netherlands; Amsterdam UMC, Vrije Universiteit and GGZ inGeest Research & Innovation, The Netherlands.
La Princesa University Hospital, Spain.
Prog Neuropsychopharmacol Biol Psychiatry. 2022 Mar 8;113:110463. doi: 10.1016/j.pnpbp.2021.110463. Epub 2021 Oct 27.
Emotion recognition constitutes a pivotal process of social cognition. It involves decoding social cues (e.g., facial expressions) to maximise social adjustment. Current theoretical models posit the relationship between social withdrawal factors (social disengagement, lack of social interactions and loneliness) and emotion decoding.
To investigate the role of social withdrawal in patients with schizophrenia (SZ) or probable Alzheimer's disease (AD), neuropsychiatric conditions associated with social dysfunction.
A sample of 156 participants was recruited: schizophrenia patients (SZ; n = 53), Alzheimer's disease patients (AD; n = 46), and two age-matched control groups (SZc, n = 29; ADc, n = 28). All participants provided self-report measures of loneliness and social functioning, and completed a facial emotion detection task.
Neuropsychiatric patients (both groups) showed poorer performance in detecting both positive and negative emotions compared with their healthy counterparts (p < .01). Social withdrawal was associated with higher accuracy in negative emotion detection, across all groups. Additionally, neuropsychiatric patients with higher social withdrawal showed lower positive emotion misclassification.
Our findings help to detail the similarities and differences in social function and facial emotion recognition in two disorders rarely studied in parallel, AD and SZ. Transdiagnostic patterns in these results suggest that social withdrawal is associated with heightened sensitivity to negative emotion expressions, potentially reflecting hypervigilance to social threat. Across the neuropsychiatric groups specifically, this hypervigilance associated with social withdrawal extended to positive emotion expressions, an emotional-cognitive bias that may impact social functioning in people with severe mental illness.
情绪识别是社会认知的关键过程。它涉及解码社会线索（例如面部表情）以最大限度地提高社会适应能力。当前的理论模型假设社会回避因素（社会脱离、缺乏社会互动和孤独感）与情绪解码之间存在关系。
调查社会回避在精神分裂症（SZ）或可能的阿尔茨海默病（AD）患者中的作用，这些神经精神疾病与社会功能障碍有关。
招募了 156 名参与者：精神分裂症患者（SZ；n=53）、阿尔茨海默病患者（AD；n=46），以及两个年龄匹配的对照组（SZc，n=29；ADc，n=28）。所有参与者均提供孤独感和社会功能的自我报告测量，并完成了面部情绪检测任务。
神经精神病患者（两组）在检测正性和负性情绪方面的表现均差于健康对照组（p<0.01）。社会回避与所有组的负性情绪检测准确性更高相关。此外，社会回避程度较高的神经精神病患者对正性情绪的错误分类较低。
我们的研究结果有助于详细描述两种很少同时研究的疾病（AD 和 SZ）在社会功能和面部情绪识别方面的异同。这些结果中的跨诊断模式表明，社会回避与对负性情绪表达的敏感性增强有关，这可能反映了对社会威胁的过度警惕。在神经精神病组中，这种与社会回避相关的过度警惕延伸到正性情绪表达，这是一种情绪认知偏差，可能会影响严重精神疾病患者的社会功能。
