塑造明天的支持:基线临床特征预测了精神分裂症谱系障碍的晚期社会功能和生活质量
Jiasi Hao1, Natalia Tiles-Sar2,3, Tesfa Dejenie Habtewold2
1Department of Epidemiology, University Medical Centre Groningen, University of Groningen, Hanzeplein 1, 9713 GZ, Groningen, The Netherlands. j.hao@umcg.nl.
Social psychiatry and psychiatric epidemiology
|March 8, 2024
概括
研究人员在精神分裂症患者中确定了五个不同的社会包容子组. 对这些群体的早期预测可能能够提供量身定制的支持,改善精神分裂症谱系障碍患者的结果.
科学领域:
- 精神病学是一个精神病学.
- 社会科学 社会科学 社会科学
- 数据科学数据科学数据科学
背景情况:
- 精神分裂症谱系障碍 (SSD) 显著影响社会功能和生活质量.
- 了解多维社会包容 (mSI) 对于有效的患者支持至关重要.
研究的目的:
- 探索精神分裂症谱系障碍 (SSD) 患者社会包容 (mSI) 的多维性质.
- 确定三年mSI的预测因素,并比较传统与数据驱动的预测模型.
主要方法:
- 利用了基线和3年随访数据,来自于基因风险和精神病结果 (GROUP) 队列中的1119名患者.
- 定义mSI使用K-means集群在社会功能量表和世卫组织生活质量分量表上.
- 开发了使用多项逻辑回归 (MLR) 和随机森林 (RF) 的预测模型,通过引导验证.
主要成果:
- 根据社会功能和生活质量确定了五个不同的mSI子组.
- 关键的mSI预测因素包括遗传倾向,病前调整,症状严重程度,满足需求和基线满意度.
- 随机森林模型在预测mSI子组时显示出超越后勤回归的趋势.
结论:
- 在SSD患者中确定了mSI的有意义的子组,并且可以从基线特征中适度预测.
- 早期预测mSI子组可以促进定制和有影响力的社会支持干预措施.
- 这种方法可以提高精神分裂症谱系障碍患者的康复和福祉.
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