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基于网络的解释偏差修正后从社会反馈中学习的变化:对有高度社交焦虑症状个体的数字心理健康干预的二次分析

Changes in Learning From Social Feedback After Web-Based Interpretation Bias Modification: Secondary Analysis of a Digital Mental Health Intervention Among Individuals With High Social Anxiety Symptoms.

作者信息

Beltzer Miranda L, Daniel Katharine E, Daros Alexander R, Teachman Bethany A

机构信息

Center for Behavioral Intervention Technologies, Northwestern University Feinberg School of Medicine, Chicago, IL, United States.

Department of Psychology, University of Virginia, Charlottesville, VA, United States.

出版信息

JMIR Form Res. 2023 Aug 9;7:e44888. doi: 10.2196/44888.

Abstract

BACKGROUND

Biases in social reinforcement learning, or the process of learning to predict and optimize behavior based on rewards and punishments in the social environment, may underlie and maintain some negative cognitive biases that are characteristic of social anxiety. However, little is known about how cognitive and behavioral interventions may change social reinforcement learning in individuals who are anxious.

OBJECTIVE

This study assessed whether a scalable, web-based cognitive bias modification for interpretations (CBM-I) intervention changed social reinforcement learning biases in participants with high social anxiety symptoms. This study focused on 2 types of social reinforcement learning relevant to social anxiety: learning about other people and learning about one's own social performance.

METHODS

Participants (N=106) completed 2 laboratory sessions, separated by 5 weeks of ecological momentary assessment tracking emotion regulation strategy use and affect. Approximately half (n=51, 48.1%) of the participants completed up to 6 brief daily sessions of CBM-I in week 3. Participants completed a task that assessed social reinforcement learning about other people in both laboratory sessions and a task that assessed social reinforcement learning about one's own social performance in the second session. Behavioral data from these tasks were computationally modeled using Q-learning and analyzed using mixed effects models.

RESULTS

After the CBM-I intervention, participants updated their beliefs about others more slowly (P=.04; Cohen d=-0.29) but used what they learned to make more accurate decisions (P=.005; Cohen d=0.20), choosing rewarding faces more frequently. These effects were not observed among participants who did not complete the CBM-I intervention. Participants who completed the CBM-I intervention also showed less-biased updating about their social performance than participants who did not complete the CBM-I intervention, learning similarly from positive and negative feedback and from feedback on items related to poor versus good social performance. Regardless of the intervention condition, participants at session 2 versus session 1 updated their expectancies about others more from rewarding (P=.003; Cohen d=0.43) and less from punishing outcomes (P=.001; Cohen d=-0.47), and they became more accurate at learning to avoid punishing faces (P=.001; Cohen d=0.20).

CONCLUSIONS

Taken together, our results provide initial evidence that there may be some beneficial effects of both the CBM-I intervention and self-tracking of emotion regulation on social reinforcement learning in individuals who are socially anxious, although replication will be important.

摘要

背景

社会强化学习中的偏差,即基于社会环境中的奖励和惩罚来学习预测和优化行为的过程,可能是社会焦虑所特有的一些负面认知偏差的潜在原因并使其持续存在。然而,对于认知和行为干预如何改变焦虑个体的社会强化学习,我们知之甚少。

目的

本研究评估了一种可扩展的、基于网络的解释性认知偏差修正(CBM-I)干预是否会改变具有高社交焦虑症状的参与者的社会强化学习偏差。本研究聚焦于与社交焦虑相关的两种社会强化学习类型:了解他人和了解自己的社交表现。

方法

参与者(N = 106)完成了2次实验室环节,中间间隔5周的生态瞬时评估,以追踪情绪调节策略的使用和情绪。大约一半(n = 51,48.1%)的参与者在第3周完成了多达6次简短的每日CBM-I环节。参与者在两个实验室环节中都完成了一项评估对他人的社会强化学习的任务,在第二个环节中完成了一项评估对自己社交表现的社会强化学习的任务。使用Q学习对这些任务的行为数据进行计算建模,并使用混合效应模型进行分析。

结果

在CBM-I干预后,参与者更新对他人信念的速度更慢(P = 0.04;Cohen d = -0.29),但利用所学做出更准确的决策(P = 0.005;Cohen d = 0.20),更频繁地选择有奖励的面孔。在未完成CBM-I干预的参与者中未观察到这些效果。完成CBM-I干预的参与者在对自己社交表现的更新偏差方面也比未完成CBM-I干预的参与者更小,从正面和负面反馈以及与社交表现好坏相关项目的反馈中学习的情况相似。无论干预条件如何,与第一次环节相比,第二次环节的参与者从奖励中更新对他人期望的程度更高(P = 0.003;Cohen d = 0.43),从惩罚结果中更新期望的程度更低(P = 0.001;Cohen d = -0.47),并且他们在学习避免惩罚性面孔方面变得更加准确(P = 0.001;Cohen d = 0.20)。

结论

综上所述,我们的结果提供了初步证据,表明CBM-I干预和情绪调节的自我追踪对社交焦虑个体的社会强化学习可能有一些有益影响,尽管重复验证很重要。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/32fb/10448289/386afa5e6fdc/formative_v7i1e44888_fig1.jpg

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