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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

As part of the Many Labs 5 project, we ran a replication of van Dijk, van Kleef, Steinel, and van Beest’s (2008) study examining the effect of emotions in negotiations. They reported that when the consequences of rejection were low, subjects offered fewer chips to angry bargaining partners than to happy partners. We ran this replication under three protocols: the protocol used in the Reproducibility Project: Psychology, a revised protocol, and an online protocol. The effect averaged one ninth the size of the originally reported effect and was significant only for the revised protocol. However, the difference between the original and revised protocols was not significant.

Although empirical research has investigated what we ideally seek in a romantic partner for decades, the crucial question of whether ideal partner preferences actually guide our mating decisions in real life has remained largely unanswered. One reason for this is the lack of designs that assess individuals' ideal partner preferences before entering a relationship and then follow up on them over an extended period. In the Göttingen Mate Choice Study (GMCS), a preregistered, large-scale online study, we used such a naturalistic prospective design. We investigated partner preferences across 4 preference domains in a large sample of predominantly heterosexual singles (N = 763, aged 18-40 years) and tracked these individuals across a period of 5 months upon a possible transition into romantic relationships. Attesting to their predictive validity, partner preferences prospectively predicted the characteristics of later partners. This was equally true for both sexes, except for vitality-attractiveness where men's preferences were more predictive of their later partners' standing on this dimension than women's. Self-perceived mate value did not moderate the preference-partner characteristics relations. Preferences proved to be relatively stable across the 5 months interval, yet were less stable for those who entered a relationship. Subgroup analyses using a newly developed indicator of preference adjustment toward (vs. away from) partner characteristics revealed that participants adjusted their preferences downward when partners fell short of initial preferences, but showed no consistent adjustment when partners exceeded them. Results and implications are discussed against the background of ongoing controversies in mate choice and romantic relationship research. (PsycINFO Database Record (c) 2019 APA, all rights reserved).

Advice is a powerful means to improve peoples' judgments and decisions. Because advice quality is rarely apparent, decision-makers must infer it from the characteristics of the advisor or the advice itself. Here, we focus on a largely neglected advice characteristic that should signal quality: advice precision. In a preregistered, high-powered study (N = 195), we tested the effects of advice precision on advice taking. Drawing from past research and theorizing on anchor precision, we derived and tested two competing hypotheses for the relation of advice precision and advice taking—one predicting a monotone increase in advice taking when advice precision increases and the other predicting a backfiring effect of overly precise advice resulting in an inverted U-shape. Our results support the notion of a monotone, albeit not a strong monotone, relationship. Higher perceived advice quality correlated with individuals' advice taking. Consistent with the idea that advice precision serves as a cue for advice quality, the effect of advice precision on advice taking was statistically mediated by perceived advice quality. Although the mediation analysis does not allow for causal interpretation because we did not manipulate the mediating variable, it shows that the effect of advice precision on advice taking is not merely a demand effect. Implications of our findings for theory and practice are discussed.

When advice comes from interdependent sources (e.g., from advisors who use the same database), less information should be gained as compared to independent advice. On the other hand, since individuals strive for consistency, they should be more confident in consistent compared to conflicting advice, and interdependent advice should be more consistent than independent advice. In a study investigating the differential effects of interdependent versus independent advice on a judge's accuracy and confidence (Yaniv, Choshen-Hillel, & Milyavsky, 2009), advice interdependence was confounded with another variable, namely closeness of the advice to the judge's estimate. Interdependent advice was not only more consistent than independent advice but also closer to the judge's first estimate. The present study aimed at disentangling the effects of consensus and closeness of the advice by adding a third experimental condition in which interdependent (and, hence, consistent) advice was far from the judge's own estimate. We found that, as suggested by Yaniv et al., accuracy gains were indeed a consequence of advisor interdependence. However, in contrast to Yaniv et al.'s conclusions, confidence in the correctness of one's estimates was mostly a function of the advice's proximity to the participants' initial estimations, thereby indicating a social validation effect. (PsycINFO Database Record

Abstract. Research in the judge-advisor-paradigm suggests that advice is generally utilized less than it should be according to its quality. In a series of four experiments, we challenge this widely held assumption. We hypothesize that when advice quality is low, the opposite phenomenon, namely overutilization of advice, occurs. We further assume that this overutilization effect is the result of anchoring: advice serves as an anchor, thus causing an adjustment toward even useless advice. The data of our four experiments support these hypotheses. Judges systematically adjusted their estimates toward advice that we introduced to them as being useless, and this effect was stable after controlling for intentional utilization of this advice. Furthermore, we demonstrate that anchoring-based adjustment toward advice is independent of advice quality. Our findings enhance our understanding of the processes involved in advice taking and identify a potential threat to judgment accuracy arising from an inability to discount useless advice.

When making judgments and decisions, people suffering from depression are often faced with opinions and advice from others (e.g., from their therapists) but it is unclear how their psychopathology alters the utilization of such information. This study is the first to examine whether depressed people are more or less susceptible to informational social influence. To this end, we employed the Judge–Advisor-System, which allows for a pure test of how people utilize information from others. We found that depressed participants had significantly higher advice taking values than non-depressed participants, which was mediated by self-esteem. A fine-grained analysis of these group differences revealed that depressed participants were more likely to revise their initial estimates after receiving advice than non-depressed people. Yet, once having decided to revise their estimates, depressed people did not weight advice more heavily. Theoretical implications concerning two qualitatively independent effects of depression on advice taking are discussed.

In contrast to the truncated view that replications have only a little to offer beyond what is already known, we suggest a broader understanding of replications: We argue that replications are better conceptualized as a process of conducting consecutive studies that increasingly consider alternative explanations, critical contingencies, and real-world relevance. To reflect this understanding, we collected and summarized the existing literature on replications and combined it into a comprehensive overall typology that simplifies and restructures existing approaches. The resulting typology depicts how multiple, hierarchically structured replication studies guide the integration of laboratory and field research and advance theory. It can be applied to (a) evaluate a theory's current status, (b) guide researchers' decisions, (c) analyze and argue for the necessity of certain types of replication studies, and (d) assess the added value of a replication study at a given state of knowledge. We conclude with practical recommendations for different protagonists in the field (e.g., authors, reviewers, editors, and funding agencies). Together, our comprehensive typology and the related recommendations will contribute to an enhanced replication culture in social psychology and to a stronger real-world impact of the discipline.

Notwithstanding the appeal of the “one size fits all” approach that Baumeister et al. propose, we argue that there is no panacea for improving group performance. The concept of “differentiation of selves” constitutes an umbrella term for similar seeming but actually different constructs. Even the same type of “differentiation of selves” can be beneficial for some and harmful for other tasks.

A growing body of research shows that individual differences in working memory capacity play a pivotal role for a large number of higher order cognitive tasks. Surprisingly, however, the impact of individual differences in working memory capacity on group performance has received little attention. In this conceptual article, we focus on three typical group tasks (group idea generation, group decision making, group judgment) and, for each task, provide an analysis of how individual differences in working memory capacity might affect group performance. Our key idea is that group interaction is a cognitively demanding task as group members have to continuously monitor the ongoing conversation, hold their ideas in memory, integrate the information put forth by others, and update their mental representations accordingly. Therefore, individual differences in working memory capacity are presumed to have a profound impact on how people process information during group interaction.

One prominent finding in research on group judgment is that groups often outperform the average of their members’ individual judgments. Previous research attributed this finding to groups weighting their more competent members more strongly (differential weighting explanation). We postulate an alternative explanation, namely that groups outperform individuals due to group-to-individual (G–I) transfer, which denotes group members becoming more accurate individually during group interaction. In Experiment 1, we demonstrate that individual accuracy in an estimation task strongly increases due to interaction, leading to high accuracy at the group level. Experiment 2 replicates this finding and shows that G–I transfer can be enhanced by expertise feedback. In both experiments, when controlling for G–I transfer during group interaction, group judgments were not better than the average model. The findings imply that previously observed superior performance by groups compared to individuals may have been due to G–I transfer and not necessarily due to differential weighting.

Response to Minson and Mueller (2012) peerReviewed