Jeremy W Eberle, Mehdi Boukhechba, Jianhui Sun, Diheng Zhang, Daniel H Funk, Laura E Barnes, Bethany A Teachman
{"title":"Shifting Episodic Prediction With Online Cognitive Bias Modification: A Randomized Controlled Trial.","authors":"Jeremy W Eberle, Mehdi Boukhechba, Jianhui Sun, Diheng Zhang, Daniel H Funk, Laura E Barnes, Bethany A Teachman","doi":"10.1177/21677026221103128","DOIUrl":null,"url":null,"abstract":"<p><p>Negative future thinking pervades emotional disorders. This hybrid efficacy-effectiveness trial tested a four-session, scalable online cognitive bias modification program for training more positive episodic prediction. 958 adults (73.3% female, 86.5% White, 83.4% from United States) were randomized to positive conditions with ambiguous future scenarios that ended positively, 50/50 conditions that ended positively or negatively, or a control condition with neutral scenarios. As hypothesized (preregistration: https://osf.io/jrst6), positive training participants improved more than control participants in negative expectancy bias (<i>d</i> = -0.58), positive expectancy bias (<i>d</i> = 0.80), and self-efficacy (<i>d</i> = 0.29). Positive training was also superior to 50/50 training for expectancy bias and optimism (<i>d</i> = 0.31). Training gains attenuated yet remained by 1-month follow-up. Unexpectedly, participants across conditions improved comparably in anxiety and depression symptoms and growth mindset. Targeting a transdiagnostic process with a scalable program may improve bias and outlook; however, further validation of outcome measures is required.</p>","PeriodicalId":54234,"journal":{"name":"Clinical Psychological Science","volume":"11 5","pages":"819-840"},"PeriodicalIF":4.8000,"publicationDate":"2023-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10513109/pdf/nihms-1806828.pdf","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Clinical Psychological Science","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.1177/21677026221103128","RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2023/2/16 0:00:00","PubModel":"Epub","JCR":"Q1","JCRName":"PSYCHIATRY","Score":null,"Total":0}
引用次数: 0
Abstract
Negative future thinking pervades emotional disorders. This hybrid efficacy-effectiveness trial tested a four-session, scalable online cognitive bias modification program for training more positive episodic prediction. 958 adults (73.3% female, 86.5% White, 83.4% from United States) were randomized to positive conditions with ambiguous future scenarios that ended positively, 50/50 conditions that ended positively or negatively, or a control condition with neutral scenarios. As hypothesized (preregistration: https://osf.io/jrst6), positive training participants improved more than control participants in negative expectancy bias (d = -0.58), positive expectancy bias (d = 0.80), and self-efficacy (d = 0.29). Positive training was also superior to 50/50 training for expectancy bias and optimism (d = 0.31). Training gains attenuated yet remained by 1-month follow-up. Unexpectedly, participants across conditions improved comparably in anxiety and depression symptoms and growth mindset. Targeting a transdiagnostic process with a scalable program may improve bias and outlook; however, further validation of outcome measures is required.
期刊介绍:
The Association for Psychological Science’s journal, Clinical Psychological Science, emerges from this confluence to provide readers with the best, most innovative research in clinical psychological science, giving researchers of all stripes a home for their work and a place in which to communicate with a broad audience of both clinical and other scientists.