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1. Many Labs 5: Testing Pre-Data-Collection Peer Review as an Intervention to Increase Replicability

Author

Lena F. Aeschbach, Balazs Aczel, Maria Vlachou, Blair Saunders, Jennifer A. Joy-Gaba, Ailsa E. Millen, Christopher R. Chartier, Danielle J. Kellier, Carlo Chiorri, Damian Pieńkosz, Tiago Jessé Souza de Lima, Sean Hughes, Carmel A. Levitan, Luca Andrighetto, Mallory C. Kidwell, Domenico Viganola, Sebastiaan Pessers, Sue Kraus, Claudia Chloe Brumbaugh, John E. Edlund, Ernest Baskin, Anna Fedor, Brett Mercier, Michał J. Białek, Sean Coary, Antonia M. Ciunci, Bence E. Bakos, Jon Grahe, Sabina Kołodziej, Radomir Belopavlović, Emilian Pękala, William J. Chopik, Rosanna E. Guadagno, Don A. Moore, Florian Brühlmann, Gideon Nave, Katarzyna Idzikowska, Rachel L. Shubella, Ryan J. Walker, Orsolya Szöke, Mathias Kauff, Ana Orlić, Sara Steegen, Hans IJzerman, Katarzyna Kuchno, Mitchell M. Metzger, Heather M. Claypool, Michael J. Wood, Samuel Lincoln Bezerra Lins, Michael C. Frank, Benjamin Dering, Iris Žeželj, Erica Baranski, Sophia C. Weissgerber, Timothy Razza, Leanne Boucher, Magnus Johannesson, R. Weylin Sternglanz, Yiling Chen, Maya B. Mathur, Christian Nunnally, Jonathan Ravid, Charles R. Ebersole, Lauren Skorb, Kurt Schuepfer, Łukasz Markiewicz, Thomas Schultze, Katherine S. Corker, Thomas Pfeiffer, Darko Stojilović, Oliver Christ, Kayla Ashbaugh, Alan Jern, Caio Ambrosio Lage, Filipe Falcão, Austin Lee Nichols, Peter Babincak, Mauro Giacomantonio, Sean C. Rife, Rafał Muda, Lacy E. Krueger, Jeremy K. Miller, Juliette Richetin, Martin Corley, Venus Meyet, W. Matthew Collins, Luana Elayne Cunha de Souza, Lynda A. R. Stein, Christopher Day, Erica Casini, Astrid Schütz, Ann-Kathrin Torka, Anna Dreber, Diane-Jo Bart-Plange, Steffen R. Giessner, Holly Arrow, Przemysław Sawicki, Joachim Hüffmeier, Ian R. Ferguson, Anna Dalla Rosa, Natasha Tidwell, Hause Lin, Matthew R. Penner, Boban Petrović, Bojana Bodroža, Janos Salamon, Josiah P. J. King, Mark Zrubka, Diane B. V. Bonfiglio, Stefan Schulz-Hardt, Emily Fryberger, Gabriel Baník, David Zealley, Amanda M. Kimbrough, Ewa Hałasa, William Jiménez-Leal, Angelo Panno, Karolina Krasuska, Michael Inzlicht, Jack Arnal, Madhavi Menon, Jia E. Loy, Vanessa S. Kolb, Nicholas G. Bloxsom, Michael H. Bernstein, Máire B. Ford, Grecia Kessinger, Marija V. Čolić, Wolf Vanpaemel, Barnabas Szaszi, Carly tocco, Nick Buttrick, Emanuele Preti, Andres Montealegre, Brian A. Nosek, Katarzyna Gawryluk, Kaylis Hase Rudy, Leigh Ann Vaughn, Anna Palinkas, Rúben Silva, Daniel Wolf, Sarah A. Novak, Aaron L. Wichman, Manuela Thomae, Adam Siegel, Ivana Pedović, Eleanor V. Langford, Kathleen Schmidt, Daniel Storage, Attila Szuts, Ljiljana B. Lazarević, Paul G. Curran, Rias A. Hilliard, Alexander Garinther, Joshua K. Hartshorne, Ani N. Shabazian, Tiago Ramos, Peter Szecsi, Hugh Rabagliati, Kimberly P. Parks, Lily Feinberg, Dylan Manfredi, Ivan Ropovik, Katrin Rentzsch, Michelangelo Vianello, Barbara Sioma, Marton Kovacs, Francis Tuerlinckx, Peter J. B. Hancock, Bradford J. Wiggins, Gavin Brent Sullivan, Danka Purić, Laboratoire Inter-universitaire de Psychologie : Personnalité, Cognition, Changement Social (LIP-PC2S), Université Pierre Mendès France - Grenoble 2 (UPMF)-Université Savoie Mont Blanc (USMB [Université de Savoie] [Université de Chambéry]), Department of Organisation and Personnel Management, Human Resource Excellence, Ebersole, C, Mathur, M, Baranski, E, Bart-Plange, D, Buttrick, N, Chartier, C, Corker, K, Corley, M, Hartshorne, J, Ijzerman, H, Lazarević, L, Rabagliati, H, Ropovik, I, Aczel, B, Aeschbach, L, Andrighetto, L, Arnal, J, Arrow, H, Babincak, P, Bakos, B, Baník, G, Baskin, E, Belopavlović, R, Bernstein, M, Białek, M, Bloxsom, N, Bodroža, B, Bonfiglio, D, Boucher, L, Brühlmann, F, Brumbaugh, C, Casini, E, Chen, Y, Chiorri, C, Chopik, W, Christ, O, Ciunci, A, Claypool, H, Coary, S, Čolić, M, Collins, W, Curran, P, Day, C, Dering, B, Dreber, A, Edlund, J, Falcão, F, Fedor, A, Feinberg, L, Ferguson, I, Ford, M, Frank, M, Fryberger, E, Garinther, A, Gawryluk, K, Ashbaugh, K, Giacomantonio, M, Giessner, S, Grahe, J, Guadagno, R, Hałasa, E, Hancock, P, Hilliard, R, Hüffmeier, J, Hughes, S, Idzikowska, K, Inzlicht, M, Jern, A, Jiménez-Leal, W, Johannesson, M, Joy-Gaba, J, Kauff, M, Kellier, D, Kessinger, G, Kidwell, M, Kimbrough, A, King, J, Kolb, V, Kołodziej, S, Kovacs, M, Krasuska, K, Kraus, S, Krueger, L, Kuchno, K, Lage, C, Langford, E, Levitan, C, de Lima, T, Lin, H, Lins, S, Loy, J, Manfredi, D, Markiewicz, Ł, Menon, M, Mercier, B, Metzger, M, Meyet, V, Millen, A, Miller, J, Montealegre, A, Moore, D, Muda, R, Nave, G, Nichols, A, Novak, S, Nunnally, C, Orlić, A, Palinkas, A, Panno, A, Parks, K, Pedović, I, Pękala, E, Penner, M, Pessers, S, Petrović, B, Pfeiffer, T, Pieńkosz, D, Preti, E, Purić, D, Ramos, T, Ravid, J, Razza, T, Rentzsch, K, Richetin, J, Rife, S, Rosa, A, Rudy, K, Salamon, J, Saunders, B, Sawicki, P, Schmidt, K, Schuepfer, K, Schultze, T, Schulz-Hardt, S, Schütz, A, Shabazian, A, Shubella, R, Siegel, A, Silva, R, Sioma, B, Skorb, L, de Souza, L, Steegen, S, Stein, L, Sternglanz, R, Stojilović, D, Storage, D, Sullivan, G, Szaszi, B, Szecsi, P, Szöke, O, Szuts, A, Thomae, M, Tidwell, N, Tocco, C, Torka, A, Tuerlinckx, F, Vanpaemel, W, Vaughn, L, Vianello, M, Viganola, D, Vlachou, M, Walker, R, Weissgerber, S, Wichman, A, Wiggins, B, Wolf, D, Wood, M, Zealley, D, Žeželj, I, Zrubka, M, Nosek, B, and Faculdade de Psicologia e de Ciências da Educação

Subjects
replication, metascience, Registered Reports, biology, media_common.quotation_subject, Curran, 05 social sciences, [SHS.PSY]Humanities and Social Sciences/Psychology, open data, Art history, 050109 social psychology, Art, biology.organism_classification, preregistered, 050105 experimental psychology, Attila, [STAT.ML]Statistics [stat]/Machine Learning [stat.ML], 0501 psychology and cognitive sciences, reproducibility, [STAT.ME]Statistics [stat]/Methodology [stat.ME], General Psychology, media_common
Abstract

Additional co-authors: Ivan Ropovik, Balazs Aczel, Lena F. Aeschbach, Luca Andrighetto, Jack D. Arnal, Holly Arrow, Peter Babincak, Bence E. Bakos, Gabriel Banik, Ernest Baskin, Radomir Belopavlovic, Michael H. Bernstein, Michal Bialek, Nicholas G. Bloxsom, Bojana Bodroža, Diane B. V. Bonfiglio, Leanne Boucher, Florian Bruhlmann, Claudia C. Brumbaugh, Erica Casini, Yiling Chen, Carlo Chiorri, William J. Chopik, Oliver Christ, Antonia M. Ciunci, Heather M. Claypool, Sean Coary, Marija V. Cˇolic, W. Matthew Collins, Paul G. Curran, Chris R. Day, Anna Dreber, John E. Edlund, Filipe Falcao, Anna Fedor, Lily Feinberg, Ian R. Ferguson, Maire Ford, Michael C. Frank, Emily Fryberger, Alexander Garinther, Katarzyna Gawryluk, Kayla Ashbaugh, Mauro Giacomantonio, Steffen R. Giessner, Jon E. Grahe, Rosanna E. Guadagno, Ewa Halasa, Rias A. Hilliard, Joachim Huffmeier, Sean Hughes, Katarzyna Idzikowska, Michael Inzlicht, Alan Jern, William Jimenez-Leal, Magnus Johannesson, Jennifer A. Joy-Gaba, Mathias Kauff, Danielle J. Kellier, Grecia Kessinger, Mallory C. Kidwell, Amanda M. Kimbrough, Josiah P. J. King, Vanessa S. Kolb, Sabina Kolodziej, Marton Kovacs, Karolina Krasuska, Sue Kraus, Lacy E. Krueger, Katarzyna Kuchno, Caio Ambrosio Lage, Eleanor V. Langford, Carmel A. Levitan, Tiago Jesse Souza de Lima, Hause Lin, Samuel Lins, Jia E. Loy, Dylan Manfredi, Łukasz Markiewicz, Madhavi Menon, Brett Mercier, Mitchell Metzger, Venus Meyet, Jeremy K. Miller, Andres Montealegre, Don A. Moore, Rafal Muda, Gideon Nave, Austin Lee Nichols, Sarah A. Novak, Christian Nunnally, Ana Orlic, Anna Palinkas, Angelo Panno, Kimberly P. Parks, Ivana Pedovic, Emilian Pekala, Matthew R. Penner, Sebastiaan Pessers, Boban Petrovic, Thomas Pfeiffer, Damian Pienkosz, Emanuele Preti, Danka Puric, Tiago Ramos, Jonathan Ravid, Timothy S. Razza, Katrin Rentzsch, Juliette Richetin, Sean C. Rife, Anna Dalla Rosa, Kaylis Hase Rudy, Janos Salamon, Blair Saunders, Przemyslaw Sawicki, Kathleen Schmidt, Kurt Schuepfer, Thomas Schultze, Stefan Schulz-Hardt, Astrid Schutz, Ani N. Shabazian, Rachel L. Shubella, Adam Siegel, Ruben Silva, Barbara Sioma, Lauren Skorb, Luana Elayne Cunha de Souza, Sara Steegen, L. A. R. Stein, R. Weylin Sternglanz, Darko Stojilovic, Daniel Storage, Gavin Brent Sullivan, Barnabas Szaszi, Peter Szecsi, Orsolya Szoke, Attila Szuts, Manuela Thomae, Natasha D. Tidwell, Carly Tocco, Ann-Kathrin Torka, Francis Tuerlinckx, Wolf Vanpaemel, Leigh Ann Vaughn, Michelangelo Vianello, Domenico Viganola, Maria Vlachou, Ryan J. Walker, Sophia C. Weissgerber, Aaron L. Wichman, Bradford J. Wiggins, Daniel Wolf, Michael J. Wood, David Zealley, Iris Žeželj, Mark Zrubka, and Brian A. Nosek

Published
2020

2. Does discrimination beat association in the IAT? The discrimination-association model reconceived

Author

Michelangelo Vianello, Anna Dalla Rosa, Egidio Robusto, Luca Stefanutti, Pasquale Anselmi, and Yoav Bar-Anan

Subjects
Attractiveness, Single process, implicit measure, Experimental and Cognitive Psychology, 050105 experimental psychology, Association, 03 medical and health sciences, Discrimination, Psychological, 0302 clinical medicine, Arts and Humanities (miscellaneous), Discrimination-association model, Discrimination, Statistics, Reaction Time, Developmental and Educational Psychology, Humans, Computer Simulation, 0501 psychology and cognitive sciences, response time, reproductive and urinary physiology, General Psychology, Implicit Association Test, Poisson race model, Consumer Behavior, 05 social sciences, Association model, Implicit-association test, Psychological, Psychology (miscellaneous), Psychology, 030217 neurology & neurosurgery
Abstract

The discrimination-association model (DAM; Stefanutti et al. 2013) disentangles two components underlying the responses to the implicit association test (IAT), which pertain to stimuli discrimination (the strength of the association of the stimuli with their own category) and automatic association (the strength of the association between targets and attributes). The assumption of the DAM that these two components sum into a single process generates critical drawbacks. The present work provides a new formulation of the model, called DAM-4C, in which stimuli discrimination and automatic association are separate, independent, and competing processes. Results of theoretical and simulation studies suggest that the DAM-4C outperforms the DAM. The IAT effect is found to vary with the association rates of the DAM-4C and not with those of the DAM. The parameters of the DAM-4C fitted on data from a Coca-Pepsi IAT are found to account for variance in brand attractiveness, taste preference, and cola choice that is not accounted for by the D score and the diffusion model. In addition, the association rates estimated on data from a Black-White IAT are in line with expectations.

Published
2020

3. Many Labs 2: Investigating Variation in Replicability Across Samples and Settings

Author

Jesse Chandler, Charles R. Ebersole, Marek A. Vranka, Sharon Coen, David Sirlopú, David Torres, Eva E. Chen, Joshua C. Gandi, Anthony J. Nelson, Robbie C. M. van Aert, Eva G. T. Green, Jeroen Stouten, Elsie Ong, Cheryl Alyssa Welch, Anja Eller, Jen-Ho Chang, Catherine Verniers, Liane Young, Canay Doğulu, Joshua M. Tybur, Jon Grahe, Michelangelo Vianello, German Kurapov, Ingrid P. J. Voermans, Maaike J. de Bruijn, Karin C.H.J. Smolders, William E. Davis, Felix D. Schönbrodt, Stephanie Szeto, Katherine S. Corker, Paul G. Curran, Fernando Mena-pacheco, Julie A. Woodzicka, Leander De Schutter, Ángel Gómez, Elisa Maria Galliani, Mike Friedman, Huajian Cai, Agata Sobkow, Joy E. Losee, Kevin Durrheim, Manuela Thomae, Jennifer A. Coleman, Tanuka Ghoshal, Serdar Karabati, Vanessa Smith-Castro, Konrad Bocian, Hans IJzerman, Mark Aveyard, Janko Međedović, Marta Wrońska, Mark Verschoor, Ho Phi Huynh, Félix Neto, Joshua A. Hicks, Alexandra Vázquez, John E. Edlund, Anna van 't Veer, Zubairu K. Dagona, Thierry Devos, Oskar K. Sundfelt, Philipp Spachtholz, Tripat Gill, Maciej Sekerdej, Jennifer A. Joy-Gaba, Masanori Oikawa, Aaron Ocampo, Sean C. Murphy, Haruna Karick, Kathleen Schmidt, Goran Knežević, Ivan Grahek, Nicolas Kervyn, Grant Packard, Fred Hasselman, Byron G. Adams, Satia A. Marotta, Aaron L. Wichman, Olga Bialobrzeska, Manini Srivastava, Mark J. Brandt, Nikolette P. Lipsey, Carmel A. Levitan, Ewa Szumowska, Gábor Orosz, Michael J. Bernstein, Morgan Conway, Timo Gnambs, Koen Ilja Neijenhuijs, John M. Zelenski, Lysandra Podesta, Esther Maassen, Sinan Alper, Ilker Dalgar, Chris N. H. Street, Alexander K. Saeri, Anna Dalla Rosa, Reginald B. Adams, Ljiljana B. Lazarević, Marcel A.L.M. van Assen, Brian Collisson, Mayowa T. Babalola, Daniel Lakens, Cheryl L. Carmichael, Carrie Kovacs, Yarrow Dunham, Yoel Inbar, Patricio Saavedra, Natalia Frankowska, Austin Lee Nichols, Evans Dami Binan, Samuel Lincoln Bezerra Lins, Marije van der Hulst, Jamie Kurtz, Morgan J. Tear, Brad Pinter, Jeffrey R. Huntsinger, Åse Innes-Ker, Steffen R. Giessner, Kakul Hai, Boban Petrović, Elizabeth L. Haines, Francisco Ceric, Andriy Myachykov, Wendy L. Morris, Jordan Axt, Marieke de Vries, Lacy E. Krueger, Erika Salomon, Heather Barry Kappes, Anna Cabak Rédei, Armand Chatard, Matthew Haigh, Haruka Oikawa, Nick Neave, Monique Pollmann, Daniel R. Berry, Abraham M. Rutchick, Fiery Cushman, David C. Cicero, Brian A. Nosek, Ronaldo Pilati, Zeng Zhijia, Jakub Traczyk, Mihály Berkics, Michael P. Hall, Luis Diego Vega, Nerisa Dozo, Roberto González, Paul A. M. Van Lange, William Jiménez-Leal, Leigh Ann Vaughn, Winnee Cheong, Rolando Pérez-Sánchez, Rishtee Batra, Michael A. Smith, Andrew C. W. Tang, Štěpán Bahník, Małgorzata Osowiecka, Gabrielle Pogge, Lisa A. Williams, Alexander S. English, Robert Busching, Melissa-Sue John, Taciano L. Milfont, Fanny Cambier, Alejandro Vásquez Echeverría, Carolyn Finck, Richard A. Klein, Anna Kende, Norbert K. Tanzer, Victor N. Keller, Marie E. Heffernan, Neil A. Lewis, Jordan Theriault, Walter Sowden, Troy G. Steiner, Kristin Nicole Dukes, Adrienn Ujhelyi, Susan L. O'Donnell, Angela T. Maitner, Michael Wood, Jesse Graham, Winfrida Malingumu, Petr Houdek, Katarzyna Cantarero, Miguel-Ángel Freyre, Jeanine L. M. Skorinko, Roza G. Kamiloğlu, Robyn K. Mallett, Sociale Psychologie (Psychologie, FMG), Amsterdam Interdisciplinary Centre for Emotion (AICE, Psychology, FMG), Laboratoire Inter-universitaire de Psychologie : Personnalité, Cognition, Changement Social (LIP-PC2S ), Université Savoie Mont Blanc (USMB [Université de Savoie] [Université de Chambéry])-Université Grenoble Alpes [2016-2019] (UGA [2016-2019]), Florida International University [Miami] (FIU), Massachusetts Institute of Technology (MIT), Universidad Nacional de Educación a Distancia (UNED), EDF (EDF), Biozentrum [Basel, Suisse], University of Basel (Unibas), Tilburg University [Netherlands], Performance Engineering Laboratory [Dublin] (PEL), Dublin City University [Dublin] (DCU), Department of Rheumatology, Ghent University Hospital, Laboratoire de Psychologie Sociale et Cognitive (LAPSCO), Université Clermont Auvergne [2017-2020] (UCA [2017-2020])-Centre National de la Recherche Scientifique (CNRS), School of Information Technology [Kharagpur], Indian Institute of Technology Kharagpur (IIT Kharagpur), Human Technology Interaction, UCL - SSH/LouRIM - Louvain Research Institute in Management and Organizations, Tilburg University, Social Psychology, IBBA, A-LAB, Faculdade de Psicologia e de Ciências da Educação, Department of Social Psychology, Department of Methodology and Statistics, Department Communication and Cognition, Language, Communication and Cognition, Department of Business-Society Management, Department of Organisation and Personnel Management, Erasmus MC other, Research Methods and Techniques, and IJzerman, Hans

Subjects
Sampling effects, H Social Sciences (General), Culture, Open materials, Learning and Plasticity, [SHS.PSY]Humanities and Social Sciences/Psychology, Replication, Situational effects, 050109 social psychology, Context (language use), Social psychology, Preregistered, 050105 experimental psychology, [SHS.PSY] Humanities and Social Sciences/Psychology, social psychology, cognitive psychology, replication, culture, individual differences, sampling effects, situational effects, meta-analysis, Registered Report, open data, open materials, preregistered, [STAT.ML]Statistics [stat]/Machine Learning [stat.ML], Statistical significance, Cognitive psychology, Statistics, Replication (statistics), Medicine and Health Sciences, 0501 psychology and cognitive sciences, General Psychology, ComputingMilieux_MISCELLANEOUS, [STAT.ME] Statistics [stat]/Methodology [stat.ME], Behaviour Change and Well-being, Data Science, 05 social sciences, Open data, [STAT.ML] Statistics [stat]/Machine Learning [stat.ML], C800, Meta-analysis, Registered Report, Individual differences, Developmental Psychopathology, [STAT.ME]Statistics [stat]/Methodology [stat.ME]
Abstract

We conducted preregistered replications of 28 classic and contemporary published findings, with protocols that were peer reviewed in advance, to examine variation in effect magnitudes across samples and settings. Each protocol was administered to approximately half of 125 samples that comprised 15,305 participants from 36 countries and territories. Using the conventional criterion of statistical significance (p < .05), we found that 15 (54%) of the replications provided evidence of a statistically significant effect in the same direction as the original finding. With a strict significance criterion (p < .0001), 14 (50%) of the replications still provided such evidence, a reflection of the extremely highpowered design. Seven (25%) of the replications yielded effect sizes larger than the original ones, and 21 (75%) yielded effect sizes smaller than the original ones. The median comparable Cohen’s ds were 0.60 for the original findings and 0.15 for the replications. The effect sizes were small (< 0.20) in 16 of the replications (57%), and 9 effects (32%) were in the direction opposite the direction of the original effect. Across settings, the Q statistic indicated significant heterogeneity in 11 (39%) of the replication effects, and most of those were among the findings with the largest overall effect sizes; only 1 effect that was near zero in the aggregate showed significant heterogeneity according to this measure. Only 1 effect had a tau value greater than .20, an indication of moderate heterogeneity. Eight others had tau values near or slightly above .10, an indication of slight heterogeneity. Moderation tests indicated that very little heterogeneity was attributable to the order in which the tasks were performed or whether the tasks were administered in lab versus online. Exploratory comparisons revealed little heterogeneity between Western, educated, industrialized, rich, and democratic (WEIRD) cultures and less WEIRD cultures (i.e., cultures with relatively high and low WEIRDness scores, respectively). Cumulatively, variability in the observed effect sizes was attributable more to the effect being studied than to the sample or setting in which it was studied. UCR::Vicerrectoría de Investigación::Unidades de Investigación::Ciencias Sociales::Instituto de Investigaciones Psicológicas (IIP)

Published
2018

4. Validity and measurement invariance of the Unified Multidimensional Calling Scale (UMCS): A three-wave survey study

Author

Elisa Maria Galliani, Michelangelo Vianello, Anna Dalla Rosa, and Pasquale Anselmi

Subjects
Male, European People, Psychometrics, Economics, Computer science, Social Sciences, Surveys, Chi Square Tests, Mathematical and Statistical Techniques, Surveys and Questionnaires, Summons, Ethnicities, Psychology, Young adult, Invariant (computer science), Components, Measurement invariance, Multidisciplinary, Career Choice, Careers, Statistics, 05 social sciences, Middle Aged, Built Structures, Italian People, Prosocial behavior, Research Design, Scale (social sciences), Career Calling, Physical Sciences, Identity (object-oriented programming), Engineering and Technology, Medicine, Female, Construct (philosophy), Research Article, Cognitive psychology, Adult, Employment, Career Calling, Measurement invariance, Confirmatory Factor Analysis, Components, UMCS, Universities, Structural Engineering, Science, Models, Psychological, Research and Analysis Methods, Young Adult, 0502 economics and business, Humans, 0501 psychology and cognitive sciences, Statistical Methods, Students, Set (psychology), Statistical Hypothesis Testing, Confirmatory Factor Analysis, Aged, Survey Research, Reproducibility of Results, Biology and Life Sciences, UMCS, 050106 general psychology & cognitive sciences, Labor Economics, People and Places, Population Groupings, Factor Analysis, Statistical, Mathematics, 050203 business & management
Abstract

The accumulation of scientific knowledge on calling is limited by the absence of a common theoretical and measurement framework. Many different models of calling have been proposed, and we do not know how much research results that refer to a specific model are generalizable to different theoretical accounts of calling. In this article, we investigate whether two leading models of calling tackle the same construct. The two models were merged into a comprehensive framework that measures calling across seven facets: Passion, Purposefulness, Sacrifice, Pervasiveness, Prosocial Orientation, Transcendent Summons, and Identity. We then developed the Unified Multidimensional Calling Scale (UMCS) drawing from previous published items. Across two surveys involving college students (N = 5886) and adult employees (N = 205) the UMCS was proved to be valid and reliable. We also observed that the UMCS is invariant across time and calling domains. Finally, we found that facets of calling have very different relationships with outcomes and concurrent measures, suggesting that results obtained with a smaller set of facets are not generalizable to the higher-order construct of calling or to a different model that does not share the same facets.

Published
2018

5. Longitudinal predictors of the development of a calling: new evidence for the a posteriori hypothesis

Author

Anna Dalla Rosa, Pasquale Anselmi, and Michelangelo Vianello

Subjects
Antecedents, Organizational Behavior and Human Resource Management, Longitudinal study, Clarity of professional identity, Counseling Psychology, Calling, Longitudinal design, Engaged learning, Social support, Identity (social science), Social and Behavioral Sciences, Structural equation modeling, Education, law.invention, Industrial and Organizational Psychology, law, 0502 economics and business, Psychology, 0501 psychology and cognitive sciences, Life-span and Life-course Studies, Applied Psychology, 05 social sciences, Social environment, Antecedent (grammar), FOS: Psychology, 050106 general psychology & cognitive sciences, CLARITY, Social psychology, 050203 business & management, Reciprocal
Abstract

The literature does not provide a clear answer about the development of callings over time. It has been hypothesized that a calling is a consequence of positive experiences in a domain (a posteriori hypothesis), or that it is the antecedent of career choices and development (a priori hypothesis), or both (reciprocal hypothesis). To investigate which hypothesis better describes the development of a calling, a three-wave longitudinal study was conducted in which we tested the temporal precedence between calling and (1) engagement in learning activities, (2) clarity of professional identity, and (3) presence of a supportive social environment. Four competing structural equation models were estimated and compared. The results suggest that clarity of professional identity, engagement in learning, and social support positively predict calling rather than the opposite, and that they provide support for the a posteriori hypothesis of calling development. Students who are actively engaged in their studies and have a clear idea of their occupational future are more likely to develop a calling over time. In addition, the results suggest that the presence of a supportive environment helps students to develop their calling. Implications for theory and research on calling are discussed.

Published
2018
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6. Estroversione, riflessione e apprendimento: eventi d’apprendimento ed emozioni prevalenti nel processo di apprendimento in ambiente virtuale

Author

Michelangelo Vianello, Anna Dalla Rosa, Daniela Frison, Monica Fedeli, and Anna Serbati

Subjects
apprendimento, 030504 nursing, 05 social sciences, 050301 education, estroversione, Riflessione, Test (assessment), 03 medical and health sciences, Human resource management, simulazione, Pedagogy, Riflessione, apprendimento, estroversione, simulazione, Big Five personality traits, 0305 other medical science, Psychology, 0503 education, Training programme
Abstract

The article presents an experience of simulation-based training developed in 2014 with students enrolled in the master programme in Management of Educational Services at the University of Padova. The training programme, devoted to the development of competences in the field of human resources management, has been integrated with vLeader, an online simulator designed for the improvement of leadership competences. As part of the evaluation of the programme’s effectiveness, a test for measuring personality traits according to the Big Five model and a learning journal to support reflection on simulation have been proposed to the students. Data collected with the two tools were crossed through an automated textual analysis of the learning journal contents in order to explore connections between reflections prompted by learning journals and personality traits of students involved.

Published
2016

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