Department of Experimental Psychology and Helmholtz Institute, Utrecht University, Heidelberglaan 1, 3584 CS, Utrecht, the Netherlands; Brain Research & Innovation Centre, Ministry of Defence, Lundlaan 1, 3584 EZ, Utrecht, the Netherlands; Department of Psychiatry, UMC Utrecht Brain Center, University Medical Center Utrecht, Heidelberglaan 100, 3584 CX, Utrecht, The Netherlands.
Altrecht Academic Anxiety Center, Nieuwe Houtenseweg 12, 3524 SH Utrecht, The Netherlands.
J Behav Ther Exp Psychiatry. 2021 Sep;72:101653. doi: 10.1016/j.jbtep.2021.101653. Epub 2021 Mar 8.
Studies on the development and treatment of anxiety disorders mostly focus on the comparison of predefined groups. An alternative approach is to use data-driven latent class growth analyses (LCGA) to determine differentiation between groups based on particular mechanistic factors. This study validated the use of LCGA on responses in a compact fear conditioning task and whether specific characteristics are associated with maladaptive fear learning trajectories.
Healthy subjects (N = 300) completed a fear conditioning task that included uninstructed and instructed acquisition and extinction phases. Subjective fearfulness and US expectancy were used as outcome measures. Latent classes in the responses to the CS+ (coupled with a scream) and the CS- (control stimulus) were determined based on trajectories across the experimental phases. State and trait anxiety were measured during testing, and return of fear and intrusions were measured one and six weeks later.
Fear learning trajectories of poor extinction in responding to the CS+ and generalization of fear to the CS- were associated with higher state and trait anxiety. Individuals belonging to these trajectories reported more intrusions, fear and had higher US expectancy ratings after 1 week.
Only 56% of participants completed the six weeks follow-up measures.
Fear learning trajectories are associated with individual characteristics, return of fear and intrusions. Next, this task will be implemented in clinical practice to assess its predictive power for the extent to which patients benefit from exposure treatments.
焦虑障碍的发展和治疗研究大多集中于预设组别的比较。另一种方法是使用基于特定机制因素的基于数据的潜在类别增长分析(LCGA)来确定组间的差异。本研究验证了 LCGA 在紧凑的恐惧条件反射任务中的反应中的使用,以及特定特征是否与适应不良的恐惧学习轨迹相关。
健康受试者(N=300)完成了一个恐惧条件反射任务,其中包括无指导和有指导的获得和消退阶段。主观恐惧和 US 预期被用作结果测量。基于实验阶段的轨迹,确定 CS+(与尖叫相结合)和 CS-(对照刺激)反应中的潜在类别。在测试期间测量状态和特质焦虑,在 1 周和 6 周后测量恐惧的回归和侵入。
对 CS+的反应中消退不良和对 CS-的恐惧泛化的恐惧学习轨迹与较高的状态和特质焦虑相关。属于这些轨迹的个体报告在 1 周后更多的侵入、恐惧和更高的 US 预期评分。
只有 56%的参与者完成了 6 周的随访测量。
恐惧学习轨迹与个体特征、恐惧回归和侵入有关。接下来,将在临床实践中实施此任务,以评估其对患者从暴露治疗中获益程度的预测能力。