预测负面症状:一种用于评估精神病预测性认知机制的新型尺度
Celia Ceballos-Munuera1, Juan Francisco Rodríguez-Testal2
1Department of Personality, Assessment and Psychological Treatments, University of Seville, C/Camilo José Cela s/n, Seville, 41018, Spain.
Annals of general psychiatry
|January 20, 2026
概括
负面症状预测量表 (NSAS) 有效地测量了与负面症状相关的预测性认知. 这种自我报告工具有助于早期的精神病检测和干预,显示出强大的有效性和可靠性.
科学领域:
- 精神病学是一个精神病学.
- 心理学 心理学 心理学
- 临床神经科学 临床神经科学
背景情况:
- 负面症状是精神分裂症谱系障碍和亚临床表现的关键,影响功能结果.
- 自我报告措施提供了效率和对经验的主观洞察力,补充了临床医生评价的评估.
研究的目的:
- 开发和验证消极症状预测量表 (NSAS),一个新的自我报告工具.
- 该NSAS评估与负面症状相关的预测性认知.
主要方法:
- 一个28项级别被改进为一个16项级别的版本,有三个因素:预测社会困难,关系困难和低能量.
- 验证涉及一个大型社区样本 (N=3,237),评估可靠性,因数结构,因数不变性和预测能力.
主要成果:
- 该NSAS显示出出色的内部一致性 (α=0.927) 和测试-重新测试可靠性.
- 确认性探索性分析证实了强大的因子结构 (CFI≥0.997,RMSEA≤0.025).
- 该尺度显示了精神病过渡风险的突出预测能力 (AUC=0.905) 和对负症状变异的显著贡献.
结论:
- 该NSAS是一个有效的自我报告措施,用于评估与负面症状相关的预期认知.
- 它的应用可能有助于早期检测和干预策略的个体处于精神病的风险.
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