Li Yanhui, Ang Mei San, Yee Jie Yin, See Yuen Mei, Lee Jimmy
North Region, Institute of Mental Health, Singapore, Singapore.
Research Division, Institute of Mental Health, Singapore, Singapore.
Front Psychiatry. 2024 Aug 23;15:1444843. doi: 10.3389/fpsyt.2024.1444843. eCollection 2024.
Predictors of functioning are well-studied in schizophrenia, but much less so in treatment-resistant schizophrenia (TRS). In this study, we aim to investigate contributions of schizophrenia symptom domains and neurocognition to predict functioning in a TRS population (n = 146).
Participants were assessed on the Positive and Negative Syndrome Scale (PANSS), to calculate scores for five symptom factors (Positive, Negative, Cognitive, Depressive and Hostility) and two negative symptom constructs (Diminished Expressivity (DE), and Social Anhedonia (SA) as part of the Motivation and Pleasure-related dimension), based on a previously validated model, modified in accordance with EPA guidelines on negative symptoms assessment. Neurocognition was assessed with symbol coding and digit sequencing tasks from the Brief Assessment of Cognition in Schizophrenia (BACS). Functioning was assessed with the Social and Occupational Functioning Assessment Scale (SOFAS), employment status and World Health Organization Disability Assessment Schedule 2.0 (WHODAS 2.0). Multiple regression analyses were performed on psychopathology scores and BACS scores against all three measures of functioning, controlling for age and sex. For WHODAS, regression with PANSS scores of significant symptom factors were also performed.
A lower severity of negative symptoms in the SA dimension was the strongest predictor of higher functioning across all three functioning measures. Neurocognition, in particular processing speed and attention assessed on the symbol coding task, predicted employment. A lower severity of somatic concerns and depressive symptoms was associated with lesser self-reported disability on WHODAS.
This study represents a first attempt at elucidating significant predictors of functioning in TRS. We highlight negative symptoms and neurocognition as important treatment targets to improve functioning in TRS, consistent with previous studies in general schizophrenia.
在精神分裂症中，功能的预测因素已得到充分研究，但在难治性精神分裂症（TRS）中研究较少。在本研究中，我们旨在调查精神分裂症症状领域和神经认知对TRS人群（n = 146）功能预测的贡献。
使用阳性和阴性症状量表（PANSS）对参与者进行评估，根据先前验证的模型计算五个症状因子（阳性、阴性、认知、抑郁和敌对）的得分，以及两个阴性症状结构（表情减少（DE）和社交快感缺失（SA），作为动机和愉悦相关维度的一部分），并根据EPA关于阴性症状评估的指南进行修改。使用精神分裂症认知简短评估（BACS）中的符号编码和数字序列任务评估神经认知。使用社会和职业功能评估量表（SOFAS）、就业状况和世界卫生组织残疾评估量表2.0（WHODAS 2.0）评估功能。对精神病理学得分和BACS得分与所有三种功能测量指标进行多元回归分析，控制年龄和性别。对于WHODAS，还进行了与显著症状因子的PANSS得分的回归分析。
SA维度中较低的阴性症状严重程度是所有三种功能测量指标中功能较高的最强预测因素。神经认知，特别是在符号编码任务中评估的处理速度和注意力，预测就业情况。较低的躯体担忧和抑郁症状严重程度与WHODAS上较低的自我报告残疾相关。
本研究首次尝试阐明TRS中功能的重要预测因素。我们强调阴性症状和神经认知是改善TRS功能的重要治疗靶点，这与先前关于一般精神分裂症的研究一致。
