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基于网络的解释偏差培训,以减少焦虑:一个连续的,多重分配的随机试验

Jeremy W Eberle¹, Katharine E Daniel¹, Sonia Baee²

¹University of Virginia, Department of Psychology.

Journal of consulting and clinical psychology

|July 18, 2024

概括

基于网络的认知偏差修改解释 (CBM-I) 有效地减少了解释偏差和焦虑症状. 然而,CBM-I显示了比精神教育更高的学率,并且增加远程教学并没有改善结果.

科学领域:

心理学心理学心理学
临床心理学临床心理学
数字健康数字健康

背景情况:

基于网络的解释认知偏差修改 (CBM-I) 是一种对焦虑的有前途的干预措施.
高退学率是数字心理健康干预措施的重大挑战,如CBM-I.
补充支持的有效性,如远程教练,在减轻学和增强CBM-I有效性需要进一步调查.

研究的目的:

为了评估基于网络的CBM-I的有效性,与积极的精神教育控制条件相比.
检查增加低强度远程教练到CBM-I对学风险较高的参与者的影响.
评估CBM-I和远程教练对解释偏见和焦虑症状的影响.

主要方法:

进行了一项连续的多项随机试验,涉及1,234名焦虑的成年人.
参与者被随机分配到CBM-I或精神教育,高风险的CBM-I完成者然后随机分配到接受远程辅导或没有辅导.
结果包括解释偏差 (识别评分,简短的身体感觉解释问卷) 和焦虑症状 (整体焦虑严重程度和障碍量表,抑郁焦虑压力量表-简短形式).

主要成果:

在改善解释偏见和焦虑症状方面,CBM-I显著优于精神教育,其效果在2个月的随访中保持不变.
与预期相反,CBM-I的中断率明显高于精神教育.
添加远程教练并没有显著提高效率或减少学率,部分原因是参与者与教练的参与度较低.

结论:

基于网络的CBM-I是减少解释偏见和焦虑症状的有效干预措施.
额外的低强度远程教学似乎无法有效地缓解基于网络的CBM-I中的学挑战.
未来的研究应该探索替代策略,以提高参与度,减少在数字心理健康干预中学.

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