Agnes Norbury, Quentin Dercon, Tobias U Hauser, Raymond J Dolan, Quentin J M Huys
{"title":"学习训练作为认知重组干预。","authors":"Agnes Norbury, Quentin Dercon, Tobias U Hauser, Raymond J Dolan, Quentin J M Huys","doi":"10.1016/j.bpsc.2025.04.008","DOIUrl":null,"url":null,"abstract":"<p><strong>Background: </strong>A core part of cognitive therapy for low mood is learning to identify and challenge negative beliefs. However, it is currently unclear whether improved ability to recognise such beliefs, and the biased interpretations of events which may maintain them, is a mechanism of symptom change during treatment.</p><p><strong>Methods: </strong>We investigated the effects of completing a learning task (training to identify and select self-enhancing interpretations of events) and a brief cognitive restructuring intervention (how exploring alternative explanations of events may result in improved mood) on causal attribution tendencies. Studies were conducted online using randomized-controlled experimental designs (N=200 &N=164), and data were analysed using hierarchical Bayesian models.</p><p><strong>Results: </strong>We found that both learning training and the restructuring intervention decreased tendencies to make unhelpful attributions and increased tendencies to make self-enhancing attributions. Across two studies, changes in attribution tendencies were associated with higher learning rates during learning training, an effect specific to learning about different kinds of event attribution. Contrary to expectation, we found no evidence that faster learning was associated specifically to changes in attribution tendencies following cognitive restructuring. Since participants with higher learning rate estimates also provided explicit ratings and free-text descriptions of event causes which were closer to the ground truth, we interpret this as representing a greater benefit of learning training in individuals who were better able to understand the task state space.</p><p><strong>Conclusions: </strong>We suggest that personalized training, in conjunction with feedback based on interpretable computational model output, may provide a useful form of augmentation or learning support tool during therapy.</p>","PeriodicalId":93900,"journal":{"name":"Biological psychiatry. Cognitive neuroscience and neuroimaging","volume":" ","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2025-04-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Learning training as a cognitive restructuring intervention.\",\"authors\":\"Agnes Norbury, Quentin Dercon, Tobias U Hauser, Raymond J Dolan, Quentin J M Huys\",\"doi\":\"10.1016/j.bpsc.2025.04.008\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><strong>Background: </strong>A core part of cognitive therapy for low mood is learning to identify and challenge negative beliefs. However, it is currently unclear whether improved ability to recognise such beliefs, and the biased interpretations of events which may maintain them, is a mechanism of symptom change during treatment.</p><p><strong>Methods: </strong>We investigated the effects of completing a learning task (training to identify and select self-enhancing interpretations of events) and a brief cognitive restructuring intervention (how exploring alternative explanations of events may result in improved mood) on causal attribution tendencies. Studies were conducted online using randomized-controlled experimental designs (N=200 &N=164), and data were analysed using hierarchical Bayesian models.</p><p><strong>Results: </strong>We found that both learning training and the restructuring intervention decreased tendencies to make unhelpful attributions and increased tendencies to make self-enhancing attributions. Across two studies, changes in attribution tendencies were associated with higher learning rates during learning training, an effect specific to learning about different kinds of event attribution. Contrary to expectation, we found no evidence that faster learning was associated specifically to changes in attribution tendencies following cognitive restructuring. Since participants with higher learning rate estimates also provided explicit ratings and free-text descriptions of event causes which were closer to the ground truth, we interpret this as representing a greater benefit of learning training in individuals who were better able to understand the task state space.</p><p><strong>Conclusions: </strong>We suggest that personalized training, in conjunction with feedback based on interpretable computational model output, may provide a useful form of augmentation or learning support tool during therapy.</p>\",\"PeriodicalId\":93900,\"journal\":{\"name\":\"Biological psychiatry. 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Learning training as a cognitive restructuring intervention.
Background: A core part of cognitive therapy for low mood is learning to identify and challenge negative beliefs. However, it is currently unclear whether improved ability to recognise such beliefs, and the biased interpretations of events which may maintain them, is a mechanism of symptom change during treatment.
Methods: We investigated the effects of completing a learning task (training to identify and select self-enhancing interpretations of events) and a brief cognitive restructuring intervention (how exploring alternative explanations of events may result in improved mood) on causal attribution tendencies. Studies were conducted online using randomized-controlled experimental designs (N=200 &N=164), and data were analysed using hierarchical Bayesian models.
Results: We found that both learning training and the restructuring intervention decreased tendencies to make unhelpful attributions and increased tendencies to make self-enhancing attributions. Across two studies, changes in attribution tendencies were associated with higher learning rates during learning training, an effect specific to learning about different kinds of event attribution. Contrary to expectation, we found no evidence that faster learning was associated specifically to changes in attribution tendencies following cognitive restructuring. Since participants with higher learning rate estimates also provided explicit ratings and free-text descriptions of event causes which were closer to the ground truth, we interpret this as representing a greater benefit of learning training in individuals who were better able to understand the task state space.
Conclusions: We suggest that personalized training, in conjunction with feedback based on interpretable computational model output, may provide a useful form of augmentation or learning support tool during therapy.