在线认知偏见修改用于解释,以减少COVID-19大流行期间的焦虑思维
Maria A Larrazabal1, Jeremy W Eberle1, Angel Vela de la Garza Evia2
1Department of Psychology, University of Virginia, USA.
Behaviour research and therapy
|January 24, 2024
概括
与精神教育相比,用于解释的认知偏差修改 (CBM-I) 有效地减少了焦虑症状和解释偏差. 这个数字心理健康工具对与COVID-19流行病等不确定的事件相关的高度焦虑的人来说是有前途的.
科学领域:
- 心理学 心理学 心理学
- 数字心理健康数字心理健康
- 临床心理学 临床心理学
背景情况:
- 焦虑症很普遍,在COVID-19大流行期间,焦虑症的发病率有所增加.
- 像耻辱和成本这样的障碍限制了传统焦虑治疗的机会.
- 数字心理健康干预,包括CBM-I,为更广泛获得护理提供了潜力.
研究的目的:
- 为了比较用于解释认知偏差修改 (CBM-I) 与用于减轻焦虑的精神教育的有效性.
- 调查基线COVID-19焦虑是否影响CBM-I和心理教育中的治疗结果.
- 为了确定CBM-I干预的最佳候选人.
主要方法:
- 一项家长试验的子研究随机分配了608名中度至重度焦虑的成年人参加CBM-I或通过MindTrails进行心理教育的五次会议.
- 使用OASIS和DASS-21-AS尺度测量了焦虑症状.
- 解释偏差被评估,以评估干预期间和之后的变化.
主要成果:
- 与精神教育相比,CBM-I显著减少了焦虑症状 (OASIS:d = -0.31) 和负面解释偏差 (d范围 = -0.34至 -0.43).
- 此外,CBM-I还显著增加了积极解释偏差 (d = 0.79).
- 具有较高基线COVID-19焦虑的个体在CBM-I下表现出更大的焦虑减轻,但在心理教育下减少.
结论:
- CBM-I是一种比精神教育更有效的干预措施,可以减少焦虑症状和解释偏见.
- 对于那些经历过与不确定的事件相关的高度焦虑的人来说,CBM-I可能特别有益,例如COVID-19大流行.
- 像CBM-I这样的数字心理健康干预措施可以改善获得有效焦虑治疗的机会.
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