@article{aaf48dcee9e149e6a315d98ec60b85dd,
title = "A multi-country test of brief reappraisal interventions on emotions during the COVID-19 pandemic",
abstract = "The COVID-19 pandemic has increased negative emotions and decreased positive emotions globally. Left unchecked, these emotional changes might have a wide array of adverse impacts. To reduce negative emotions and increase positive emotions, we tested the effectiveness of reappraisal, an emotion regulation strategy which modifies how one thinks about a situation. Participants from 87 countries/regions (n = 21,644) were randomly assigned to one of two brief reappraisal interventions (reconstrual or repurposing) or one of two control conditions (active or passive). Results revealed that both reappraisal interventions (vs. both control conditions) consistently reduced negative emotions and increased positive emotions across different measures. Reconstrual and repurposing had similar effects. Importantly, planned exploratory analyses indicated that reappraisal interventions did not reduce intentions to practice preventive health behaviours. The findings demonstrate the viability of creating scalable, low-cost interventions for use around the world to build resilience during the pandemic and beyond.",
keywords = "Adult, COVID-19/psychology, Emotional Regulation, Emotions, Female, Humans, Male, REGULATION STRATEGIES, METAANALYSIS, ANXIETY, RESILIENCE, NEGATIVE AFFECT, POSITIVE EMOTIONS, COGNITIVE REAPPRAISAL, DIVERGENT ASSOCIATIONS, R PACKAGE, STRESS",
author = "Ke Wang and Amit Goldenberg and Dorison, {Charles A.} and Miller, {Jeremy K.} and Clare Sutherland and {Psychological Science Accelerator study PSACR002 Stage 2}",
note = "Acknowledgements This project was supported by funds from: the Amazon Web Services (AWS) Imagine Grant (to EMB); the Japan Society for the Promotion of Science Grants-in-Aid for Scientific Research (JSPS KAKENHI; 16h03079, 17h00875, 18k12015, and 20h04581 to YY); the research program “Dipartimenti di Eccellenza” from the Ministry of Education University and Research (MIUR to NC and GM and the Department of General Psychology of the University of Padua); statutory funds of the University of Wroclaw (to AS); the Charles University Research Programme {"}PROGRES{"} (Q18 to MV); the Knut and Alice Wallenberg Foundation (2016:0229 to JKO); the Rubicon Grant (019.183sg.007 to KVS) from the Netherlands Organisation for Scientific Research; the Australian Research Council (dp180102384 to RMR); the US National Institutes of Health (NIMH111640 to MN), the Huo Family Foundation to NJ; the NSF Directorate for Social, Behavioral & Economic Sciences, Division of Social and Economic Sciences (1559511 to JSL); the US National Institutes of Health (RO1-CA-224545 to JSL); Eesti Teadusagentuur - Estonian Research Council (PSG525 to AU); the J. William Fulbright Program (to FA); the HSE Basic Research Program (to DD); Dominican University (a Faculty Development Grant to AK); and the French National Research Agency “Investissements d{\textquoteright}avenir” supporting PSF (ANR-15- IDEX-02 to HI); the Slovak Research and Development Agency (project no. APVV-20-0319 to MA); the program FUTURE LEADER of Lorraine Universit{\'e} d{\textquoteright}Excellence within the French National Research Agency “Investissements d{\textquoteright}avenir” (ANR-15-IDEX-04-LUE to SM). Computation for this research was assisted by: the Harvard Business School compute cluster (HBSGrid); and the Open Science Grid. The Open Science Grid is supported by the National Science Foundation award 1148698 and the US Department of Energy{\textquoteright}s Office of Science. As well as by: the compute resources and assistance of the UW-Madison Center For High Throughput Computing (CHTC) in the Department of Computer Sciences. The CHTC is supported by UW-Madison, the Advanced Computing Initiative, the Wisconsin Alumni Research Foundation, the Wisconsin Institutes for Discovery, and the National Science Foundation, and is an active member of the Open Science Grid, which is supported by the National Science Foundation and the U.S. Department of Energy's Office of Science. Our semi-representative panels were made possible by: an in-kind purchase from the Leibniz Institute for Psychology (protocol doi: http://dx.doi.org/10.23668/psycharchives.3012); a special grant from the Association for Psychological Science; and a fee waiver from Prolific. This work was supported by a grant from the American psychological Society (granted to the Psychological Science Accelerator). Further financial support was provided by the Psychological Science Accelerator and a special crowdfunding campaign initiated by the Psychological Science Accelerator. We would like to thank data science specialist Steven Worthington and the research computing environment at the Institute for Quantitative Social Science, Harvard University. We would like to thank Harvard Business School for providing research computing services. We would like to thank Amazon Web Services for help with server needs, the Leibniz Institute for Psychology (ZPID) for help with data collection via the organization and implementation of semi-representative panels, Prolific Inc. for offering discounted recruitment, and Harvard University{\textquoteright}s Institute for Quantitative Social Sciences for statistical consulting. Finally, this research was supported by resources from the Open Science Grid, which is supported by National Science Foundation award 1148698, and the U.S. Department of Energy's Office of Science. Beyond those roles already acknowledged, the funders had no role in study design, data collection and analysis, decision to publish or preparation of the manuscript. ",
year = "2021",
month = aug,
doi = "10.1038/s41562-021-01173-x",
language = "English",
volume = "5",
pages = "1089–1110",
journal = "Nature Human Behaviour",
issn = "2397-3374",
publisher = "Springer Nature",
}