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A multi-country test of brief reappraisal interventions on emotions during the COVID-19 pandemic
Ke Wang, Amit Goldenberg, Charles Dorison, Jeremy K. Miller, Andero Uusberg, Jennifer S. Lerner, James J. Gross, Bamikole Bamikole Agesin, Márcia Bernardo, Olatz Campos, Luis Eudave, Karolina Grzech, Daphna Hausman Ozery, Emily Jackson, Elkin O. Luís, Shira Meir Drexler, Anita Penić Jurković, Kafeel Rana, John Paul Wilson, Maria Antoniadi, Kermeka Desai, Zoi Gialitaki, Elizaveta Kushnir, Khaoula Nadif, Olalla Niño Bravo, Rafia Nauman, Marlies Oosterlinck, Myrto Pantazi, Natalia Pilecka, Anna Szabelska, I. M. M. van Steenkiste, Katarzyna Filip, Andreea Ioana Bozdoc, Gabriela Mariana Marcu, Елена Агадуллина, Matúš Adamkovič, Marta Roczniewska, Cecilia Reyna, Angelos P. Kassianos, Minja Westerlund, Lina Ahlgren, Sara Johanna Pöntinen, Gabriel Agboola Adetula, Pınar Dursun, Azuka Ikechukwu Arinze, Nwadiogo Chisom Arinze, Chisom Ogbonnaya, Izuchukwu L. G. Ndukaihe, İlker Dalḡar, Handan Akkaş, Paulo Manuel Macapagal, Savannah C Lewis, Irem Metin-Orta, Francesco Foroni, Megan Willis, Anabela Caetano Santos, Aviv Mokady, Niv Reggev, Merve A. Kurfali, Martin R. Vasilev, Nora L. Nock, Michał Parzuchowski, Mauricio F. Espinoza Barría, Marek Vranka, Markéta Braun Kohlová, Ivan Ropovik, Mikayel Harutyunyan, Chunhui Wang, Elvin Yao, Maja Becker, Efisio Manunta, Gwenaël Kaminski, Jordane Boudesseu, Dafne Marko, Kortnee C. Evans, David M. G. Lewis, Andrej Findor, Anaïs Thibault Landry, John Jamir Benzon R. Aruta, Manuel S. Ortíz, Zahir Vally, Ekaterina Pronizius, Martin Voracek, Claus Lamm, Maurice Grinberg, Ranran Li, Jaroslava Varella Valentová, Giovanna Mioni, Nicola Cellini, Sau-Chin Chen, Janis Zickfeld, Karis Moon, Habiba Azab, Neil Levy, Alper KARABABA, Jennifer L Beaudry, Leanne Boucher, W. Matthew Collins, Anna Louise Todsen, Kevin van Schie, Jáchym Vintr, Jozef Bavoľár, Lada Kaliská, Valerija Križanić, Lara Samojlenko, Razieh Pourafshari, Sandra J. Geiger, Julia Beitner, Lara Warmelink, Robert M. Ross, Ian D. Stephen, Tom Hostler, Soufian Azouaghe, Randy J. McCarthy, Anna Szala, Caterina Grano, Claudio Singh Solorzano, Gulnaz Anjum, William Jiménez‐Leal, Maria Bradford, Laura Calderón Pérez, Julio E. Cruz Vásquez, Oscar J. Galindo-Caballero, Juan Camilo Vargas-Nieto, Ondřej Kácha, Alexiοs Arvanitis, Qinyu Xiao, Rodrigo A. Cárcamo, Saša Zorjan, Zuzanna Tajchman, Iris Vilares, Jeffrey M. Pavlacic, Jonas R. Kunst, Christian K. Tamnes, Claudia C. von Bastian, Mohammad Atari, MohammadHasan Sharifian, Monika Hricová, Pavol Kačmár, Jana Schrötter, Rima-Maria Rahal, Noga Cohen, Saeideh FatahModares, Miha Zrimsek, Ilya Zakharov, Monica A. Koehn, Celia Esteban‐Serna, Robert Calin‐Jageman, Anthony J. Krafnick, Eva Štrukelj, Peder Mortvedt Isager, Ján Urban, Jaime R. Silva, Marcel Martončik, Sanja Batić Očovaj, Dušana Šakan, A Kuźmińska, Inês Almeida, Ana Lúcia da Silva Ferreira, Ljiljana B. Lazarević, Harry Manley, Renan Pereira Monteiro, Zahra Etabari, Erica D. Musser, Daniel J. Dunleavy, Wei‐Lun Chou, Hendrik Godbersen, Susana Ruiz Fernández, Crystal Reeck, Carlota Batres, Komila Kirgizova, Abdumalik Muminov, Flávio Azevedo, Daniela Serrato Alvarez, Muhammad Mussaffa Butt, Jeong Min Lee, Zhang Chen, Frederick Verbruggen, Ignazio Ziano, Murat Tümer, Abdelilah CHARYATE, Dmitrii Dubrov, María del Carmen M. C. Tejada Rivera, Christopher L. Aberson, Bence Pálfi, Mónica Alarcón Maldonado, Barbora Hubená, Aslı Saçaklı, Chris D. Ceary, Karley Richard, Gage Singer, Jennifer T. Perillo, Tonia Ballantyne, Wilson Cyrus-Lai, Maksim Fedotov, Hongfei Du, Magdalena Wielgus, Ilse L. Pit, Matej Hruška, Daniela Sousa, Balázs Aczél, Nándor Hajdú, Barnabás Szászi, Sylwia Adamus, Krystian Barzykowski, Leticia Micheli, Nadya-Daniela Schmidt, András N. 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Bibliographic record
VenueNature Human Behaviour · 2021
Typearticle
Languageen
FieldPsychology
TopicChild and Adolescent Psychosocial and Emotional Development
Canadian institutionsUniversité du Québec à MontréalUniversity of the Fraser ValleyWilfrid Laurier UniversitySimon Fraser UniversityConcordia University
FundersDivision of Social and Economic SciencesNational Institute of Mental HealthJapan Society for the Promotion of ScienceLeibniz-GemeinschaftNational Institutes of HealthAgentúra na Podporu Výskumu a VývojaNational Cancer InstituteKnut och Alice Wallenbergs StiftelseUniversità degli Studi di PadovaMinistero dell’Istruzione, dell’Università e della RicercaEesti TeadusagentuurOffice of ScienceU.S. Department of EnergyHuo Family FoundationAssociation for Psychological ScienceNederlandse Organisatie voor Wetenschappelijk OnderzoekHarvard UniversityDipartimenti di EccellenzaAustralian Research CouncilUniverzita Karlova v PrazeAgence Nationale de la RechercheHarvard Business SchoolWisconsin Alumni Research FoundationInstitute for Quantitative Social Science, Harvard UniversityAmazon Web ServicesNational Science Foundation
KeywordsCoronavirus disease 2019 (COVID-19)Pandemic2019-20 coronavirus outbreakSevere acute respiratory syndrome coronavirus 2 (SARS-CoV-2)Test (biology)Psychological interventionPsychologyMedicineVirologyPsychiatryBiologyPathology
Abstract
No abstract in any covered source. Its absence is recorded, not treated as a negative.
No abstract. This is not a gap in this database; OpenAlex has none either. 23.3% of the frame is in this state, and the screen finds HALF as much metaresearch here, so the absence is a measured bias rather than a missing field.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
metaresearch head score (Codex)0.008
metaresearch head score (Gemma)0.013
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Randomized trial · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.008
Threshold uncertainty score0.041
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.008 | 0.013 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.001 | 0.003 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
Opus teacher head0.063
GPT teacher head0.394
Teacher spread0.331 · how far apart the two teachers sit on this one work
Validation status
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
The models applied no category: nothing in the taxonomy fit this work.
Study designRandomized trial
Domainnot available
GenreEmpirical
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".
Quick stats
Citations151
Published2021
Admission routes1
Has abstractno