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1. The Confidence Database.

Author

Rahnev, Dobromir, Desender, Kobe, Lee, Alan, Adler, William, Aguilar-Lleyda, David, Akdoğan, Başak, Arbuzova, Polina, Atlas, Lauren, Balcı, Fuat, Bang, Ji, Bègue, Indrit, Birney, Damian, Brady, Timothy, Calder-Travis, Joshua, Chetverikov, Andrey, Clark, Torin, Davranche, Karen, Denison, Rachel, Dildine, Troy, Double, Kit, Duyan, Yalçın, Faivre, Nathan, Fallow, Kaitlyn, Filevich, Elisa, Gajdos, Thibault, Gallagher, Regan, de Gardelle, Vincent, Gherman, Sabina, Haddara, Nadia, Hainguerlot, Marine, Hsu, Tzu-Yu, Hu, Xiao, Iturrate, Iñaki, Jaquiery, Matt, Kantner, Justin, Koculak, Marcin, Konishi, Mahiko, Koß, Christina, Kvam, Peter, Kwok, Sze, Lebreton, Maël, Lempert, Karolina, Ming Lo, Chien, Luo, Liang, Maniscalco, Brian, Martin, Antonio, Massoni, Sébastien, Matthews, Julian, Mazancieux, Audrey, Merfeld, Daniel, OHora, Denis, Palser, Eleanor, Paulewicz, Borysław, Pereira, Michael, Peters, Caroline, Philiastides, Marios, Pfuhl, Gerit, Prieto, Fernanda, Rausch, Manuel, Recht, Samuel, Reyes, Gabriel, Rouault, Marion, Sackur, Jérôme, Sadeghi, Saeedeh, Samaha, Jason, Seow, Tricia, Shekhar, Medha, Sherman, Maxine, Siedlecka, Marta, Skóra, Zuzanna, Song, Chen, Soto, David, Sun, Sai, van Boxtel, Jeroen, Wang, Shuo, Weidemann, Christoph, Weindel, Gabriel, Wierzchoń, Michał, Xu, Xinming, Ye, Qun, Yeon, Jiwon, Zou, Futing, and Zylberberg, Ariel

Subjects
Adult, Choice Behavior, Databases, Factual, Datasets as Topic, Humans, Mental Processes, Metacognition, Psychometrics, Reaction Time, Task Performance and Analysis
Abstract

Understanding how people rate their confidence is critical for the characterization of a wide range of perceptual, memory, motor and cognitive processes. To enable the continued exploration of these processes, we created a large database of confidence studies spanning a broad set of paradigms, participant populations and fields of study. The data from each study are structured in a common, easy-to-use format that can be easily imported and analysed using multiple software packages. Each dataset is accompanied by an explanation regarding the nature of the collected data. At the time of publication, the Confidence Database (which is available at https://osf.io/s46pr/) contained 145 datasets with data from more than 8,700 participants and almost 4 million trials. The database will remain open for new submissions indefinitely and is expected to continue to grow. Here we show the usefulness of this large collection of datasets in four different analyses that provide precise estimations of several foundational confidence-related effects.

Published
2020

3. Follow-up experiment, metacognition and observational learning

Author

Aguilar-Lleyda, David

Subjects
FOS: Psychology, Cognition and Perception, Cognitive Psychology, Psychology, Experimental Analysis of Behavior, Social and Behavioral Sciences
Abstract

This is a pre-registration for a follow-up experiment that aims at disambiguating the results of a first experiment conducted by David Aguilar-Lleyda, Wojciech Zajkowski and Rei Akaishi.

Published
2023
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7. 2020_Aguilar-Lleyda_Lemarchand_deGardelle

Author

Aguilar-Lleyda, David

Subjects
TheoryofComputation_MISCELLANEOUS, Behavior and Behavior Mechanisms, FOS: Psychology, Psychological Phenomena and Processes, Cognition and Perception, Medicine and Health Sciences, Cognitive Psychology, Psychology, Psychiatry and Psychology, Experimental Analysis of Behavior, Social and Behavioral Sciences
Abstract

Repository for the project 'Confidence as a priority signal'

Published
2022
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9. Trust in Institutions, Not in Political Leaders, Determines Compliance in COVID-19 Prevention Measures within Societies across the Globe

Author

Badman, Ryan P. (author), Wang, Ace X. (author), Skrodzki, M. (author), Cho, Heng-Chin (author), Aguilar-Lleyda, David (author), Shiono, Naoko (author), Yoo, Seng Bum Michael (author), Chiang, Yen-Sheng (author), Akaishi, Rei (author), Badman, Ryan P. (author), Wang, Ace X. (author), Skrodzki, M. (author), Cho, Heng-Chin (author), Aguilar-Lleyda, David (author), Shiono, Naoko (author), Yoo, Seng Bum Michael (author), Chiang, Yen-Sheng (author), and Akaishi, Rei (author)

Abstract

A core assumption often heard in public health discourse is that increasing trust in national political leaders is essential for securing public health compliance during crises such as the COVID-19 pandemic (2019–ongoing). However, studies of national government trust are typically too coarse-grained to differentiate between trust in institutions versus more interpersonal trust in political leaders. Here, we present multiscale trust measurements for twelve countries and territories across the West, Oceania and East Asia. These trust results were used to identify which specific domains of government and social trust were most crucial for securing public health compliance (frequency of mask wearing and social distancing) and understanding the reasons for following health measures (belief in effectiveness of public health measures). Through the use of linear regression and structural equation modeling, our cross-cultural survey-based analysis (N = 3369 subjects) revealed that higher trust in national and local public health institutions was a universally consistent predictor of public health compliance, while trust in national political leaders was not predictive of compliance across cultures and geographical regions. Institutional trust was mediated by multiple types of transparency, including providing rationale, securing public feedback, and honestly expressing uncertainty. These results highlight the importance of distinguishing between components of government trust, to better understand which entities the public gives the most attention to during crises., Comp Graphics & Visualisation

Published
2022
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12. Aguilar-Lleyda_Supplemental_Material_rev – Supplemental material for Confidence as a Priority Signal

Author

Aguilar-Lleyda, David, Lemarchand, Maxime, and Gardelle, Vincent De

Subjects
FOS: Psychology, FOS: Clinical medicine, 170199 Psychology not elsewhere classified, 110319 Psychiatry (incl. Psychotherapy), 110904 Neurology and Neuromuscular Diseases, Neuroscience
Abstract

Supplemental material, Aguilar-Lleyda_Supplemental_Material_rev for Confidence as a Priority Signal by David Aguilar-Lleyda, Maxime Lemarchand and Vincent de Gardelle in Psychological Science

Published
2020
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13. The confidence database

Author

Balcı, Fuat (ORCID 0000-0003-3390-9352 & YÖK ID 51269); Duyan, Yalçın Akın; Kvam, Peter D., Rahnev, Dobromir; Desender, Kobe; Lee, Alan L. F.; Adler, William T.; Aguilar-Lleyda, David; Akdoğan, Başak; Arbuzova, Polina; Atlas, Lauren Y.; Bang, Ji Won; Bègue, Indrit; Birney, Damian P; Brady, Timothy F.; Calder-Travis, Joshua; Chetverikov, Andrey; Clark, Torin K.; Davranche, Karen; Denison, Rachel N.; Dildine, Troy C.; Double, Kit S.; Faivre, Nathan; Fallow, Kaitlyn; Filevich, Elisa; Gajdos, Thibault; Gallagher, Regan M.; de Gardelle, Vincent; Gherman, Sabina; Haddara, Nadia; Hainguerlot, Marine; Hsu, Tzu-Yu; Hu, Xiao; Iturrate, Iñaki; Jaquiery, Matt; Kantner, Justin; Koculak, Marcin; Konishi, Mahiko; Koß, Christina; Kwok, Sze Chai; Lebreton, Maël; Lempert, Karolina M.; Ming Lo, Chien; Luo, Liang; Maniscalco, Brian; Martin, Antonio; Massoni, Sébastien; Matthews, Julian; Mazancieux, Audrey; Merfeld, Daniel M.; O’Hora, Denis; Palser, Eleanor R.; Paulewicz, Borysław; Pereira, Michael; Peters, Caroline; Philiastides, Marios G.; Pfuhl, Gerit; Prieto, Fernanda; Rausch, Manuel; Recht, Samuel, Reyes, Gabriel; Rouault, Marion; Sackur, Jérôme; Sadeghi, Saeedeh; Samaha, Jason; Seow, Tricia X. F.; Shekhar, Medha, Sherman, Maxine T.; Siedlecka, Marta; Skóra, Zuzanna; Song, Chen; Soto, David; Sun, Sai; van Boxtel, Jeroen J. A.; Wang, Shuo; Weidemann, Christoph T.; Weindel, Gabriel; Wierzchoń, Michał; Xu, Xinming; Ye, Qun; Yeon, Jiwon; Zou, Futing; Zylberberg, Ariel, College of Social Sciences and Humanities, Department of Psychology, Balcı, Fuat (ORCID 0000-0003-3390-9352 & YÖK ID 51269); Duyan, Yalçın Akın; Kvam, Peter D., Rahnev, Dobromir; Desender, Kobe; Lee, Alan L. F.; Adler, William T.; Aguilar-Lleyda, David; Akdoğan, Başak; Arbuzova, Polina; Atlas, Lauren Y.; Bang, Ji Won; Bègue, Indrit; Birney, Damian P; Brady, Timothy F.; Calder-Travis, Joshua; Chetverikov, Andrey; Clark, Torin K.; Davranche, Karen; Denison, Rachel N.; Dildine, Troy C.; Double, Kit S.; Faivre, Nathan; Fallow, Kaitlyn; Filevich, Elisa; Gajdos, Thibault; Gallagher, Regan M.; de Gardelle, Vincent; Gherman, Sabina; Haddara, Nadia; Hainguerlot, Marine; Hsu, Tzu-Yu; Hu, Xiao; Iturrate, Iñaki; Jaquiery, Matt; Kantner, Justin; Koculak, Marcin; Konishi, Mahiko; Koß, Christina; Kwok, Sze Chai; Lebreton, Maël; Lempert, Karolina M.; Ming Lo, Chien; Luo, Liang; Maniscalco, Brian; Martin, Antonio; Massoni, Sébastien; Matthews, Julian; Mazancieux, Audrey; Merfeld, Daniel M.; O’Hora, Denis; Palser, Eleanor R.; Paulewicz, Borysław; Pereira, Michael; Peters, Caroline; Philiastides, Marios G.; Pfuhl, Gerit; Prieto, Fernanda; Rausch, Manuel; Recht, Samuel, Reyes, Gabriel; Rouault, Marion; Sackur, Jérôme; Sadeghi, Saeedeh; Samaha, Jason; Seow, Tricia X. F.; Shekhar, Medha, Sherman, Maxine T.; Siedlecka, Marta; Skóra, Zuzanna; Song, Chen; Soto, David; Sun, Sai; van Boxtel, Jeroen J. A.; Wang, Shuo; Weidemann, Christoph T.; Weindel, Gabriel; Wierzchoń, Michał; Xu, Xinming; Ye, Qun; Yeon, Jiwon; Zou, Futing; Zylberberg, Ariel, College of Social Sciences and Humanities, and Department of Psychology

Abstract

Understanding how people rate their confidence is critical for the characterization of a wide range of perceptual, memory, motor and cognitive processes. To enable the continued exploration of these processes, we created a large database of confidence studies spanning a broad set of paradigms, participant populations and fields of study. The data from each study are structured in a common, easy-to-use format that can be easily imported and analysed using multiple software packages. Each dataset is accompanied by an explanation regarding the nature of the collected data. At the time of publication, the Confidence Database (which is available at ) contained 145 datasets with data from more than 8,700 participants and almost 4 million trials. The database will remain open for new submissions indefinitely and is expected to continue to grow. Here we show the usefulness of this large collection of datasets in four different analyses that provide precise estimations of several foundational confidence-related effects., NIH National Institute of Mental Health (NIMH)

Published
2020

16. An object-tracking model that combines position and speed explains spatial and temporal responses in a timing task

Author

Aguilar-Lleyda, David, Tubau Sala, Elisabet, López-Moliner, Joan, and Universitat de Barcelona

Subjects
Filtre de Kalman, Visual perception, Presa de decisions, Espai i temps, Percepció visual, Space and time, Kalman filtering, Decision making
Abstract

Many tasks require synchronizing our actions withparticular moments along the path of moving targets.However, it is controversial whether we base theseactions on spatial or temporal information, and whetherusing either can enhance our performance. Weaddressed these questions with a coincidence timingtask. A target varying in speed and motion durationapproached a goal. Participants stopped the target andwere rewarded according to its proximity to the goal.Results showed larger reward for responses temporally(rather than spatially) equidistant to the goal acrossspeeds, and this pattern was promoted by longer motiondurations. We used a Kalman filter to simulate time andspace-based responses, where modeled speeduncertainty depended on motion duration and positionaluncertainty on target speed. The comparison betweensimulated and observed responses revealed that a singleposition-tracking mechanism could account for bothspatial and temporal patterns, providing a unifiedcomputational explanation.

Published
2018

18. The Confidence Database

Author

Rahnev, Dobromir, primary, Desender, Kobe, additional, Lee, Alan L. F., additional, Adler, William T., additional, Aguilar-Lleyda, David, additional, Akdoğan, Başak, additional, Arbuzova, Polina, additional, Atlas, Lauren Yvette, additional, Balcı, Fuat, additional, Bang, Ji Won, additional, Bègue, Indrit, additional, Birney, Damian P., additional, Brady, Timothy F., additional, Calder-Travis, Joshua Michael, additional, Chetverikov, Andrey, additional, Clark, Torin K, additional, Davranche, Karen, additional, Denison, Rachel N., additional, Dildine, Troy, additional, Double, Kit S, additional, Duyan, Yalçın Akın, additional, Faivre, Nathan, additional, Fallow, Kaitlyn Marie, additional, Filevich, Elisa, additional, gajdos, thibault, additional, Gallagher, Regan, additional, de Gardelle, Vincent, additional, Gherman, Sabina, additional, Haddara, Nadia, additional, hainguerlot, marine, additional, Hsu, Tzu-Yu, additional, Hu, Xiao, additional, Jaquiery, Matt, additional, Kantner, Justin, additional, Koculak, Marcin, additional, Konishi, Mahiko, additional, Koß, Christina, additional, Kvam, Peter D., additional, Kwok, Sze Chai, additional, Lebreton, Maël, additional, Lempert, Karolina Maria, additional, Lo, Chien Ming, additional, Luo, Liang, additional, Maniscalco, Brian, additional, Martin, Antonio, additional, Massoni, Sébastien, additional, Matthews, Julian, additional, Mazancieux, Audrey, additional, Merfeld, Daniel M., additional, O'Hora, Denis, additional, Palser, Eleanor, additional, Paulewicz, Borysław, additional, Pereira, Michael, additional, Peters, Caroline, additional, Philiastides, Marios G., additional, Pfuhl, Gerit, additional, Prieto, Fernanda, additional, Rausch, Manuel, additional, Recht, Samuel, additional, Reyes, Gabriel, additional, Rouault, Marion, additional, Sackur, Jérôme, additional, Sadeghi, Saeedeh, additional, Samaha, Jason, additional, Seow, Tricia Xing Fang, additional, Shekhar, Medha, additional, Sherman, Maxine T, additional, Siedlecka, Marta, additional, Skóra, Zuzanna, additional, Song, Chen, additional, Soto, David, additional, Sun, Sai, additional, van Boxtel, Jeroen, additional, Wang, Shuo, additional, Weidemann, Christoph T., additional, Weindel, Gabriel, additional, Wierzchoń, Michał, additional, Xu, Xinming, additional, Ye, Qun, additional, Yeon, Jiwon, additional, Zou, Futing, additional, and Zylberberg, Ariel, additional

Published
2019
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21. Sensorimotor decision-making with moving objects

Author

Aguilar Lleyda, David, López i Moliner, Joan, Tubau Sala, Elisabet, Universitat de Barcelona. Departament de Cognició, Desenvolupament i Psicologia de l'Educació, and López-Moliner, Joan

Subjects
Motor ability, 616.8, Visual perception, Presa de decisions, Percepción visual, Percepció visual, Decision making, Ciències de la Salut, Toma de decisiones, Motricitat, Motricidad
Abstract

[eng] Moving is essential for us to survive, and in countless occasions we move in response to visual information. However, this process is characterized as uncertain, given the variability present both at the sensory and motor stages. A crucial question, then, is how to deal with this uncertainty in order for our actions to lead to the best possible outcomes. Statistical decision theory (SDT) is a normative framework that establishes how people should make decisions in the presence of uncertainty. This theory identifies the optimal action as that which maximizes the expected reward (outcome) of the situation. Movement planning can be reformulated in terms of SDT, so that the focus is placed on the decisional component. Some experimental work making use of this theoretical approach has concluded that humans are optimal movement planners, while other has identified situations where suboptimality arises. However, sensorimotor decision-making within SDT has commonly eluded scenarios of interaction with moving objects. At the same time, the work devoted to moving objects has not focused on the decisional aspect. The present thesis aims at bridging both fields, with each of our three studies trying to answer different questions. Given the spatiotemporal nature of situations with moving objects, we can plan our actions by relying on both temporal and spatial cues provided by the object. In Study I we investigated whether exploiting more one type of these visual cues led to a better performance, as defined by the reward given after each action. In our task we presented a target, which could vary in speed and motion time, approaching a line. Participants responded to stop the target and were rewarded according to its proximity to the line. Responding after the target crossed the line was penalized. We discovered that those participants planning their responses based on time-based motion cues had a better performance than those monitoring the target’s changing spatial position. This was due to the former approach circumventing a limitation imposed by the resolution of the visual system. We also found that viewing the object for longer favored time-based responses, as mediated by longer integration time. Finally, we used existing SDT models to obtain a reference of optimality, but we defend that these models are limited to interpret our data. Study II built on our previous findings to explore whether the use of temporal cues could be learnt. We took our previous paradigm and adapted it so that reward was manipulated after each task in order to foster exploiting temporal information. There was no evidence for learning taking place, since participants using temporal cues did so from the start of the experiment. Whether other methods reward can shape the use of certain cues, and why some people naturally tend to make more use of temporal information, still remain elusive. Study III deepened our knowledge on which variability people consider when planning their responses. We hypothesized that the reason why people are suboptimal (as defined by SDT) in many situations is because they represent only their measurement variability, roughly equivalent to the execution noise, while excluding the variability created by sudden changes in their planning. We took previous data and used a Kalman filter to extract each participant’s measurement variability. We then used it to compute SDT-derived optimal responses, and discovered that they explained well our data, giving support to our hypothesis. We also found evidence for participants using the information provided by reward both to avoid being penalized and to choose the point at which to stabilize their responses. Taken together, our experimental work presents interaction with moving objects as a complex set of situations where different information guides our response planning. Firstly, visual cues of different origin. Secondly, our variability, coming from many sources, some of which may not be considered. Finally, the outcomes related to each action., [cat] Moure’s és essencial per a la nostra supervivència, i en incomptables ocasions ens movem en resposta a informació visual. Tanmateix, aquest procés és incert, donada la variabilitat present tant a l'estadi sensorial com en el motor. Una pregunta crucial, doncs, és com gestionar aquesta incertesa perquè les nostres accions portin a les millors conseqüències possibles. La teoria de la decisió estadística (Statistical decision theory, SDT) és un marc teòric normatiu que estableix com la gent hauria de fer decisions en presència d'incertesa. Aquesta teoria identifica l'acció òptima amb aquella que maximitza la recompensa (entesa com a conseqüència) esperada de la situació. La planificació del moviment pot ser reformulada en termes de SDT, de tal manera que s’emfatitza el component decisional. Diferents treballs experimentals que han fet servir aquesta aproximació teòrica han conclòs que els humans som planificadors de moviment òptims, mentre que altres han identificat situacions on la suboptimalitat sorgeix. No obstant això, la presa de decisions sensoriomotora des de SDT normalment ha ignorat escenaris que requereixen d'interacció com objectes en moviment. Alhora, els treballs dedicats als objectes en moviment no s'han centrat en l'aspecte de decisió. La present tesi es proposa acostar els dos camps, amb cada un dels nostres tres estudis intentant respondre diferents preguntes. L’Estudi I descobrí que, per planificar les nostres decisions, fer servir informació temporal portà a un millor rendiment que fer servir informació espacial, i això fou facilitat per veure l'objecte durant més temps. També vam criticar la limitació de certs models d’SDT per interpretar els nostres dades. L'Estudi II intentà promoure l'ús d'informació temporal, tot i que no s’aconseguí fomentar l’aprenentatge. Finalment, l’'Estudi III trobà que la raó per la qual la gent és subòptima en moltes situacions es deu al fet que representa només la seva variabilitat de mesura, més o menys equivalent al soroll d'execució, mentre que s'exclou la variabilitat creada per sobtats canvis en la planificació de la resposta. També trobàrem que els participants van usar la informació donada per la recompensa tant per evitar ser penalitzats com per escollir el punt on estabilitzar les seves respostes.

Published
2017

26. Reasoning and choice in the Monty Hall Dilemma (MHD): implications for improving Bayesian reasoning

Author

Tubau, Elisabet, Aguilar-Lleyda, David, Johnson, Eric D., and Universitat de Barcelona

Subjects
Bayesian statistical decision, Probabilities, Monty Hall Dilemma, Estadística bayesiana, Bayesian reasoning, Psychology, Probabilitats, cognitive illusions, choice biases, reflection
Abstract

The Monty Hall Dilemma (MHD) is a two-step decision problem involving counterintuitive conditional probabilities. The first choice is made among three equally probable options, whereas the second choice takes place after the elimination of one of the non-selected options which does not hide the prize. Differing from most Bayesian problems, statistical information in the MHD has to be inferred, either by learning outcome probabilities or by reasoning from the presented sequence of events. This often leads to suboptimal decisions and erroneous probability judgments. Specifically, decision makers commonly develop a wrong intuition that final probabilities are equally distributed, together with a preference for their first choice. Several studies have shown that repeated practice enhances sensitivity to the different reward probabilities, but does not facilitate correct Bayesian reasoning. However, modest improvements in probability judgments have been observed after guided explanations. To explain these dissociations, the present review focuses on two types of causes producing the observed biases: Emotional-based choice biases and cognitive limitations in understanding probabilistic information. Among the latter, we identify a crucial cause for the universal difficulty in overcoming the equiprobability illusion: Incomplete representation of prior and conditional probabilities. We conclude that repeated practice and/or high incentives can be effective for overcoming choice biases, but promoting an adequate partitioning of possibilities seems to be necessary for overcoming cognitive illusions and improving Bayesian reasoning.

Published
2015

27. Number line estimation in highly math‐anxious individuals.

Author

Núñez‐Peña, María Isabel, Colomé, Àngels, and Aguilar‐Lleyda, David

Subjects
ANXIETY, MATHEMATICS, MICE (Computers), REGRESSION analysis, STUDENT attitudes, TASK performance
Abstract

In this study, we aimed to investigate the difficulties highly math‐anxious individuals (HMA) may face when having to estimate a number's position in a number line task. Twenty‐four HMA and 24 low math‐anxiety (LMA) individuals were presented with four lines with endpoints 0–100, 0–1,000, 0–100,000, and 267–367 on a computer monitor on which they had to mark the correct position of target numbers using the mouse. Although no differences were found between groups in the frequency of their best‐fit model, which was linear for all lines, the analysis of slopes and intercepts for the linear model showed that the two groups differed in performance on the less familiar lines (267–367 and 0–100,000). Lower values for the slope and higher values for the intercept were found in the HMA group, suggesting that they tended to overestimate small numbers and underestimate large numbers on these non‐familiar lines. Percentage absolute error analyses confirmed that HMA individuals were less accurate than their LMA counterparts on these lines, although no group differences were found in response time. These results indicate that math anxiety is related to worse performance only in the less familiar and more difficult number line tasks. Therefore, our data challenge the idea that HMA individuals might have less precise numerical representations and support the anxiety–complexity effect posited by Ashcraft and colleagues. [ABSTRACT FROM AUTHOR]

Published
2019
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31. The Confidence Database

Author

Alan L. F. Lee, Polina Arbuzova, Torin K. Clark, Nadia Haddara, Damian P. Birney, Tricia X. F. Seow, Gerit Pfuhl, Tzu Yu Hsu, Caroline Peters, Jason Samaha, Maxine T. Sherman, David Soto, Maël Lebreton, Michael Pereira, Manuel Rausch, Ji Won Bang, Fuat Balcı, Gabriel Weindel, Karolina M. Lempert, Sabina Gherman, Antonio Martin, Denis O'Hora, Ariel Zylberberg, Başak Akdoğan, Peter D. Kvam, Matt Jaquiery, Gabriel Reyes, Eleanor R. Palser, Marcin Koculak, Audrey Mazancieux, Joshua Calder-Travis, Jeroen J.A. van Boxtel, Andrey Chetverikov, Yalçın Akın Duyan, Chen Song, Liang Luo, Borysław Paulewicz, Medha Shekhar, Vincent de Gardelle, Saeedeh Sadeghi, Kit S. Double, Karen Davranche, Christina Koß, Nathan Faivre, Troy C. Dildine, Sze Chai Kwok, Marios G. Philiastides, Indrit Bègue, Marion Rouault, Kobe Desender, Marta Siedlecka, Zuzanna Skóra, Lauren Y. Atlas, Fernanda Prieto, Xinming Xu, Justin Kantner, Jiwon Yeon, Brian Maniscalco, David Aguilar-Lleyda, Futing Zou, Timothy F. Brady, Xiao Hu, Mahiko Konishi, Julian Matthews, Sai Sun, Sébastien Massoni, William T. Adler, Shuo Wang, Rachel N. Denison, Samuel Recht, Jérôme Sackur, Thibault Gajdos, Kaitlyn Fallow, Michał Wierzchoń, Daniel M. Merfeld, Chien Ming Lo, Elisa Filevich, Iñaki Iturrate, Marine Hainguerlot, Christoph T. Weidemann, Qun Ye, Regan M. Gallagher, Dobromir Rahnev, Georgia Institute of Technology [Atlanta], Universitaetsklinikum Hamburg-Eppendorf = University Medical Center Hamburg-Eppendorf [Hamburg] (UKE), Universiteit Gent = Ghent University [Belgium] (UGENT), Lingnan Normal University, Department of Psychology and Center for Neural Science, New York University, New York, NY, USA, Centre d'économie de la Sorbonne (CES), Université Paris 1 Panthéon-Sorbonne (UP1)-Centre National de la Recherche Scientifique (CNRS), Columbia University [New York], Bernstein Center for Computational Neuroscience [Berlin], Humboldt-Universität zu Berlin, National Institutes of Health [Bethesda] (NIH), New York University School of Medicine (NYU), New York University School of Medicine, NYU System (NYU)-NYU System (NYU), Geneva University Hospitals and University of Geneva, School of Psychology, The University of Sydney, Department of Psychology (University of California San Diego), University of California [San Diego] (UC San Diego), University of California-University of California, Department of Experimental Psychology, University of Oxford, Oxford, UK, Donders Institute for Brain, Cognition and Behaviour, Radboud university [Nijmegen], Smead Aerospace Engineering Sciences, Centre National de la Recherche Scientifique (CNRS), Aix Marseille Université (AMU), Department of Education, University of Oxford, Applied Economics, Cognitive Psychology, Koç University, Laboratoire de psychologie cognitive (LPC), Centre National de la Recherche Scientifique (CNRS)-Aix Marseille Université (AMU), Laboratoire de Psychologie et NeuroCognition (LPNC ), Université Savoie Mont Blanc (USMB [Université de Savoie] [Université de Chambéry])-Centre National de la Recherche Scientifique (CNRS)-Université Grenoble Alpes (UGA), Department of Psychology, University of Victoria, School of Psychology, University of Queensland, University of Queensland [Brisbane], Department of Experimental & Applied Psychology, Vrije Universiteit Amsterdam (VUPSY), Paris School of Economics (PSE), École des Ponts ParisTech (ENPC)-École normale supérieure - Paris (ENS Paris), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Université Paris 1 Panthéon-Sorbonne (UP1)-Centre National de la Recherche Scientifique (CNRS)-École des hautes études en sciences sociales (EHESS)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), Institute of Neuroscience and Psychology, University of Glasgow, Glasgow, United Kingdom, The Feinstein Institute for Medical Research, Erasmus University Rotterdam, Graduate Institute of Mind, Brain and Consciousness, Taipei Medical University, Taipei, Taiwan, Capital Normal University [Beijing], California State University [Northridge] (CSUN), Uniwersytet Jagielloński w Krakowie = Jagiellonian University (UJ), Laboratoire de sciences cognitives et psycholinguistique (LSCP), Département d'Etudes Cognitives - ENS Paris (DEC), École normale supérieure - Paris (ENS Paris), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-École normale supérieure - Paris (ENS Paris), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-École des hautes études en sciences sociales (EHESS)-Centre National de la Recherche Scientifique (CNRS), Department of Psychology, University of Florida, Key Laboratory of Brain Functional Genomics (MOE & STCSM), School of Psychology and Cognitive Science, East China Normal University, Shanghai, China, Shanghai Key Laboratory of Magnetic Resonance, School of Physics and Materials Science, East China Normal University, Swiss Center for Affective Science, University of Pennsylvania [Philadelphia], Collaborative Innovation Center of Assessment toward Basic Education Quality, Beijing (ENCICABEQ), Department of Bioengineering, University of California, Bureau d'Économie Théorique et Appliquée (BETA), Université de Strasbourg (UNISTRA)-Université de Lorraine (UL)-Centre National de la Recherche Scientifique (CNRS)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), School of Psychological Sciences, Monash University, Ohio State University [Columbus] (OSU), National University of Ireland [Galway] (NUI Galway), University of California [San Francisco] (UCSF), University of California, University College of London [London] (UCL), SWPS University of Social Sciences and Humanities, Partenaires INRAE, Ecole Polytechnique Fédérale de Lausanne (EPFL), University of Glasgow, The Arctic University of Norway (UiT), Universidad del Desarrollo, Catholic University of Eichstätt-Ingolstadt (KU), Laboratoire des systèmes perceptifs (LSP), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Centre National de la Recherche Scientifique (CNRS), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL), Laboratoire d'informatique de l'École polytechnique [Palaiseau] (LIX), Centre National de la Recherche Scientifique (CNRS)-École polytechnique (X), Cornell University [New York], University of California [Santa Cruz] (UCSC), Trinity College Dublin, Sackler Ctr Consciousness Sci, Brighton, E Sussex, University of Sussex, Cardiff University, Basque Ctr Cognit Brain & Language, San Sebastian, Basque Fdn Sci, Ikerbasque, Bilbao, CALTECH, Div Biol, Pasadena, CALTECH, Div Computat & Neural Syst, Pasadena, Monash University [Melbourne], University of Canberra, West Virginia University [Morgantown], Swansea University, East China Normal University [Shangaï] (ECNU), University of Rochester [USA], The organization of the Confidence Database was supported by the National Institute of Mental Health under award number R56MH119189 to D.R., ANR-16-CE28-0002,ImpactMeta,impact de la métacognition sur le comportement(2016), ANR-16-ASTR-0014,MetaStress,Impact du stress sur la décision et la métacognition: applications en aéronautique(2016), Balcı, Fuat (ORCID 0000-0003-3390-9352 & YÖK ID 51269), Duyan, Yalçın Akın, Kvam, Peter D., Rahnev, Dobromir, Desender, Kobe, Lee, Alan L. F., Adler, William T., Aguilar-Lleyda, David, Akdoğan, Başak, Arbuzova, Polina, Atlas, Lauren Y., Bang, Ji Won, Bègue, Indrit, Birney, Damian P, Brady, Timothy F., Calder-Travis, Joshua, Chetverikov, Andrey, Clark, Torin K., Davranche, Karen, Denison, Rachel N., Dildine, Troy C., Double, Kit S., Faivre, Nathan, Fallow, Kaitlyn, Filevich, Elisa, Gajdos, Thibault, Gallagher, Regan M., de Gardelle, Vincent, Gherman, Sabina, Haddara, Nadia, Hainguerlot, Marine, Hsu, Tzu-Yu, Hu, Xiao, Iturrate, Iñaki, Jaquiery, Matt, Kantner, Justin, Koculak, Marcin, Konishi, Mahiko, Koß, Christina, Kwok, Sze Chai, Lebreton, Maël, Lempert, Karolina M., Ming Lo, Chien, Luo, Liang, Maniscalco, Brian, Martin, Antonio, Massoni, Sébastien, Matthews, Julian, Mazancieux, Audrey, Merfeld, Daniel M., O’Hora, Denis, Palser, Eleanor R., Paulewicz, Borysław, Pereira, Michael, Peters, Caroline, Philiastides, Marios G., Pfuhl, Gerit, Prieto, Fernanda, Rausch, Manuel, Recht, Samuel, Reyes, Gabriel, Rouault, Marion, Sackur, Jérôme, Sadeghi, Saeedeh, Samaha, Jason, Seow, Tricia X. F., Shekhar, Medha, Sherman, Maxine T., Siedlecka, Marta, Skóra, Zuzanna, Song, Chen, Soto, David, Sun, Sai, van Boxtel, Jeroen J. A., Wang, Shuo, Weidemann, Christoph T., Weindel, Gabriel, Wierzchoń, Michał, Xu, Xinming, Ye, Qun, Yeon, Jiwon, Zou, Futing, Zylberberg, Ariel, College of Social Sciences and Humanities, Department of Psychology, PSL Univ, Ecole Normale Super, Lab Syst Percetifs, Dept Etud Cognit,CNRS, PSL Univ, Ecole Normale Super, INSERM, Dept Etud Cognit,CNRS,EHESS, École polytechnique (X)-Centre National de la Recherche Scientifique (CNRS), Universiteit Gent = Ghent University (UGENT), Humboldt University Of Berlin, Department of Psychology [Univ California San Diego] (Psycho - UC San Diego), University of California (UC)-University of California (UC), Radboud University [Nijmegen], University of Colorado [Boulder], Aix Marseille Université (AMU)-Centre National de la Recherche Scientifique (CNRS), Université Paris 1 Panthéon-Sorbonne (UP1)-École normale supérieure - Paris (ENS-PSL), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-École des hautes études en sciences sociales (EHESS)-École des Ponts ParisTech (ENPC)-Centre National de la Recherche Scientifique (CNRS)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), École normale supérieure - Paris (ENS-PSL), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-École normale supérieure - Paris (ENS-PSL), University of Florida [Gainesville] (UF), University of Pennsylvania, AgroParisTech-Université de Strasbourg (UNISTRA)-Université de Haute-Alsace (UHA) Mulhouse - Colmar (Université de Haute-Alsace (UHA))-Université de Lorraine (UL)-Centre National de la Recherche Scientifique (CNRS)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), University of California [San Francisco] (UC San Francisco), University of California (UC), SWPS University of Social Sciences and Humanities (SWPS), The Arctic University of Norway [Tromsø, Norway] (UiT), University of California [Santa Cruz] (UC Santa Cruz), and Ikerbasque - Basque Foundation for Science

Subjects
Databases, Factual, SIGNAL-DETECTION, Computer science, Datasets as Topic, Social Sciences, Confidence, INSIGHT, computer.software_genre, Signal-detection, Choice, Availability, Recognition, Insight, Choice Behavior, [SCCO]Cognitive science, Behavioral Neuroscience, ddc:616.89, Mental Processes, 0302 clinical medicine, Software, insight, Task Performance and Analysis, Psychology, choice, media_common, 0303 health sciences, Thesaurus (information retrieval), Psychology, Biological, Database, Psychology, Experimental, Cognition, [SHS.ECO]Humanities and Social Sciences/Economics and Finance, 16. Peace & justice, CHOICE, Multidisciplinary Sciences, ddc:128.37, [SCCO.PSYC]Cognitive science/Psychology, VDP::Samfunnsvitenskap: 200::Psykologi: 260, Science & Technology - Other Topics, recognition, Life Sciences & Biomedicine, Adult, Psychometrics, Social Psychology, VDP::Social science: 200::Psychology: 260, media_common.quotation_subject, availability, MEDLINE, Experimental and Cognitive Psychology, Article, Databases, 03 medical and health sciences, Perception, Reaction Time, Humans, Set (psychology), Factual, 030304 developmental biology, Science & Technology, business.industry, Extramural, AVAILABILITY, Neurosciences, RECOGNITION, signal-detection, Psychology, biological, Multidisciplinary sciences, Psychology, experimental, ddc:616.8, Study, Neurosciences & Neurology, Metacognition, business, computer, 030217 neurology & neurosurgery
Abstract

Understanding how people rate their confidence is critical for the characterization of a wide range of perceptual, memory, motor and cognitive processes. To enable the continued exploration of these processes, we created a large database of confidence studies spanning a broad set of paradigms, participant populations and fields of study. The data from each study are structured in a common, easy-to-use format that can be easily imported and analysed using multiple software packages. Each dataset is accompanied by an explanation regarding the nature of the collected data. At the time of publication, the Confidence Database (which is available at ) contained 145 datasets with data from more than 8,700 participants and almost 4 million trials. The database will remain open for new submissions indefinitely and is expected to continue to grow. Here we show the usefulness of this large collection of datasets in four different analyses that provide precise estimations of several foundational confidence-related effects., NIH National Institute of Mental Health (NIMH)

Published
2020
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