根据两波隐性变化得分模型评估治疗效应 - 作为反复测量的替代方案 ANOVA
Eun Seo Park1, Hwa Jin Han2, Young Il Cho3
1Division of Police Administartion, Dongguk University, Seoul, Republic of Korea.
Journal of behavioral medicine
|January 19, 2026
概括
本研究引入了双波潜变评分模型 (2W-LCSM),用于分析行为科学中的治疗效应. 该模型成功地通过捕捉治疗后认知扭曲的变化来预测减少性复发.
科学领域:
- 行为科学 行为科学
- 健康心理学 心理健康心理学
- 量化心理学 量化心理学
背景情况:
- 传统的统计方法,如重复测量ANOVA,在治疗效果研究中与测量误差和个体内变异性作斗争.
- 随着时间的推移,对变化过程的准确建模对于理解行为医学中的治疗疗效至关重要.
研究的目的:
- 介绍和证明双波隐性变化得分模型 (2W-LCSM) 的实用性,用于分析治疗诱导的变化.
- 检查治疗诱导的变化与长期行为结果,特别是性复发之间的关系.
主要方法:
- 采用双波隐性变化得分模型 (2W-LCSM) 来分析经过认知行为治疗的被判犯有性犯罪的个人数据.
- 评估认知扭曲的变化及其与性复发的预测关系.
主要成果:
- 在心理治疗后,认知扭曲显著减少.
- 来自2W-LCSM的潜在变化得分显著预测了性犯罪复发率的减少.
- 2W-LCSM有效地捕捉了个人内部的变化及其与重复犯罪的联系.
结论:
- 双波潜变得分模型 (2W-LCSM) 是一种强大的替代方案,用于在行为医学中建模治疗效应和行为后果.
- 结果强调了该模型在理解干预有效性和为未来的统计方法提供信息方面的实用性.
- 这种方法为定制干预措施以减少重犯提供了有价值的见解.
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