一种概括性理论方法来量化精神病理学变化的超高风险个体中精神病的变化
Zohreh Doborjeh1,2, Oleg N Medvedev3, Maryam Doborjeh4
1Knowledge Engineering and Discovery Research Institute, School of Engineering, Computer, and Mathematical Sciences, Auckland University of Technology, Auckland, New Zealand. zohreh.doborjeh@aut.ac.nz.
在患有精神病超高风险 (UHR) 的年轻人中识别波动的症状是早期干预的关键. 积极和消极症状量表 (PANSS) 可靠地区分稳定和可变的特征,有助于预防精神病.
科学领域:
- 精神病学和心理学 精神病学和心理学
- 心理病理学 心理病理学
- 临床神经科学 临床神经科学
背景情况:
- 在患有精神病超高风险 (UHR) 的年轻人中,区分稳定与波动的精神病理特征对于早期检测和预防至关重要.
- 积极和消极症状量表 (PANSS) 是一种常见的评估工具,但其在UHR人群中的可靠性和通用性需要验证.
研究的目的:
- 在24个月的时间内,在UHR人群中使用通用性理论验证PANSS.
- 在UHR个体中区分稳定和波动的精神病理症状.
- 评估不同PANSS因子模型 (3因子与5因子) 的可靠性和通用性.
主要方法:
- 在24个月内对159名UHR个体进行了长度研究.
- 使用积极和消极症状量表 (PANSS) 进行评估.
- 应用可概括性理论来估计PANSS分数和因子模型的可靠性和可概括性.
主要成果:
- 总的PANSS尺度显示可接受的可靠性和通用性 (Gr = 0.85).
- 波动的症状 (如妄想,幻觉) 显示出高的变化 (50-68%的变化与短暂的状态).
- 稳定的症状包括兴奋,不良关系和焦虑. 三要素PANSS模型显示出强大的可靠性 (G = 0.77-0.93),而一些五要素子尺度的可靠性较低 (G = 0.33-0.66).
结论:
- 三因素PANSS模型可靠地评估UHR个体的精神病风险.
- 波动的症状更容易接受干预,这表明加强精神病预防策略的目标.
- 通过可靠的总尺度和3个子尺度,可以对持久的精神病模式进行准确的评估.
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