Saturday, February 19, 2022

Mental speed is high until age 60 as revealed by analysis of over a million participants; response time slowing begins as early as age 20, but this was attributable to increases in decision caution & to slower non-decisional processes

Mental speed is high until age 60 as revealed by analysis of over a million participants. Mischa von Krause, Stefan T. Radev & Andreas Voss. Nature Human Behaviour, Feb 17 2022.

Abstract: Response speeds in simple decision-making tasks begin to decline from early and middle adulthood. However, response times are not pure measures of mental speed but instead represent the sum of multiple processes. Here we apply a Bayesian diffusion model to extract interpretable cognitive components from raw response time data. We apply our model to cross-sectional data from 1.2 million participants to examine age differences in cognitive parameters. To efficiently parse this large dataset, we apply a Bayesian inference method for efficient parameter estimation using specialized neural networks. Our results indicate that response time slowing begins as early as age 20, but this slowing was attributable to increases in decision caution and to slower non-decisional processes, rather than to differences in mental speed. Slowing of mental speed was observed only after approximately age 60. Our research thus challenges widespread beliefs about the relationship between age and mental speed.

Low belief in human evolution associated with higher prejudice, racist attitudes (45 countries, diverse populations & religious settings, across time, nationally representative data); perceived similarity to animals partially mediated the link

Syropoulos, S., Lifshin, U., Greenberg, J., Horner, D. E., & Leidner, B. (2022). Bigotry and the human–animal divide: (Dis)belief in human evolution and bigoted attitudes across different cultures. Journal of Personality and Social Psychology. Feb 2022.

Abstract: The current investigation tested if people’s basic belief in the notion that human beings have developed from other animals (i.e., belief in evolution) can predict human-to-human prejudice and intergroup hostility. Using data from the American General Social Survey and Pew Research Center (Studies 1–4), and from three online samples (Studies 5, 7, 8) we tested this hypothesis across 45 countries, in diverse populations and religious settings, across time, in nationally representative data (N = 60,703), and with more comprehensive measures in online crowdsourced data (N = 2,846). Supporting the hypothesis, low belief in human evolution was associated with higher levels of prejudice, racist attitudes, and support for discriminatory behaviors against Lesbian, Gay, Bisexual, Transgender, and Queer (LGBTQ), Blacks, and immigrants in the United States (Study 1), with higher ingroup biases, prejudicial attitudes toward outgroups, and less support for conflict resolution in samples collected from 19 Eastern European countries (Study 2), 25 Muslim countries (Study 3), and Israel (Study 4). Further, among Americans, lower belief in evolution was associated with greater prejudice and militaristic attitudes toward political outgroups (Study 5). Finally, perceived similarity to animals (a construct distinct from belief in evolution, Study 6) partially mediated the link between belief in evolution and prejudice (Studies 7 and 8), even when controlling for religious beliefs, political views, and other demographic variables, and were also observed for nondominant groups (i.e., religious and racial minorities). Overall, these findings highlight the importance of belief in human evolution as a potentially key individual-difference variable predicting racism and prejudice.

Disapproving evaluations in online discussions provoked negative emotions, and the evaluated authors were less willing to participate in the online discussion further

The Impact of Giving Feedback in Online Discussions: Effects of Evaluative Reply Comments on the Authors of Evaluated User Comments. Teresa K. Naab. Journal of Media Psychology: Theories, Methods, and Applications. Feb 2022.

Abstract: In online discussions, users often evaluate comments from other users. On the basis of face theory, the present study analyzed the effects of evaluative replies on the evaluated comment authors. The investigation complements existing research, which has mainly focused on effects of comments on uninvolved readers. In the experimental study presented here, disapproving evaluations provoked negative and less positive emotions, and the evaluated authors were less willing to participate in the online discussion further. The authors’ perception of face threat mediated these effects. The results contribute to face theory in computer-mediated interactions and to our understanding of online discussions with dissonant standpoints.

Keywords: user comments, face theory, emotion, participation, experiment


Applying face theory, this study conceptualized the face-threatening character of evaluative reply comments in online discussion and its impact on the authors who receive such feedback on their comments. It aimed at expanding existing research, which has mostly examined the effects of user comments on uninvolved readers.
The findings support that valenced reply comments (which are not substantiated by reasons) indeed affect the commenters who receive feedback. Comment authors recognize disapproving replies as more threatening to their positive face, that is, as less appreciating of their comment and person compared to mixed and approving replies. They also view disapproving replies as more threatening to their negative face, which means taking away their independence compared to mixed and approving replies. The valence of the evaluation explains a proper amount of variance in the perception of face threat (positive face threat: R 2 = .67, negative face threat: R 2 = .26). This supports research on face-to-face interactions, which indicates that evaluations are face-threatening acts (Brown & Levinson, 1987Vangelisti, 1994Zhang & Stafford, 2008).
It is an important finding that the concept of face applies to the computer-mediated context of comment sections. Compared with face-to-face interactions, participants in online discussions often interact with people they know little about. They have little status information, and power hierarchies can be lower (Dahlberg, 2001). Additionally, future interactions and the need for justifications are less likely for online discussants. However, online commenting is public and potentially reaches a broad audience; this seems to increase the desire for an advantageous self-image (Lim et al., 2012). While several communication studies have relied on face theory to understand the effects of computer-mediated communication on users (e.g., Chen & Lu, 2017), the present study is the first that tests the mediating role of both positive and negative face threat. Future studies should systematically investigate how various online settings affect the perception of face threats of evaluations, for example, by varying public availability and the relation between the conversation partners (Neubaum & Krämer, 2018).
Evaluative replies affect the emotions of the evaluated authors. Thus, a fundamental assumption in face theory applies to computer-mediated contexts. Although disapproving replies triggered both positive and negative face threats, the effect of evaluative replies on negative emotions was mediated only through negative face threats. This means it is not the contempt and disrespect of bad evaluations but their perceived imposition that provokes negative emotions. Since the tone in many comment sections is harsh, authors might not generally expect much appreciation. Consequently, a lack of positive face might not lower their emotional state. By contrast, a perceived invasion of their right to freely express their standpoint might be more provocative of negative feelings. This points to the phenomenon of reactance, which includes anger (a negative emotion) and is triggered by freedom threats (Rains, 2013). This is in line with the present finding that threats to negative face provoke a negative emotional state.
We gained a somewhat different picture of the influence of evaluative replies on positive emotions. Only a perceived threat to positive face decreased positive feelings. A surprising finding is that a higher threat to negative face triggered by disapproving replies increased positive emotions. It seems that perceived attacks against the freedom to comment as desired made the authors more alert and active. Future studies should examine the relationship between face threats and emotions in detail, for example, through manipulating various threats to negative face.
The results also call for testing the effects of evaluations on discrete emotions. The literature indicates that social media content can influence specific positive or negative emotions. Mostly, scholars have regarded discrete emotions such as anger, aversion, and anxiety (e.g., Gervais, 20152017Lu & Gall Myrick, 2016). In line with appraisal theories, studies also find that discrete emotions can exert different effects on social media behavior (e.g., Lu & Gall Myrick, 2016Valentino et al., 2011). Therefore, empirical tests of the influence of different types of evaluations on discrete emotions, participation behavior, and the mediating role of perceived face threat are needed. Evaluating the relationship between negative face threat and anger seems particularly fruitful; imposition and limitation of one’s freedom lead to the perception of negative face threats. At the same time, when one’s goals are blocked, this can trigger anger (Carver & Harmon-Jones, 2009; on reactance, Rains, 2013). The unexpected finding of the present study, that higher negative face threat increased positive emotions, calls for a distinct analysis of the effects on enthusiasm.
Willingness to participate decreases with disapproving replies. Authors experiencing such sharp evaluation tend to withdraw from the online discussion compared to approving replies. This is in line with findings of deliberation research that disagreement undercuts willingness to prolong an interaction (McDevitt et al., 2003Mutz, 2002Wojcieszak & Price, 2012). Here, I found no direct effects, but the influence of the valence of the evaluation was mediated through perceived threat to positive face. The more depreciating that authors perceived the reply, the less they intended to continue participation. This also mirrors the avoidance strategy reported by face-negotiation theory (Oetzel et al., 2001), which considers that people end interactions to lower the risk of further face threats. The perception of negative face threat did not lower willingness to participate. This is interesting, on the one hand, because feedback-givers who attack the negative face might intend to exclude other commenters. However, such attempts do not seem fruitful. On the other hand, it is surprising because the assumption about reactance (Rains, 2013) would suggest that feedback-receivers would counterargue as a response to a threat to their negative face. We could speculate that attacks toward the negative face might strengthen the willingness to counter the threat for some participants, while for others, it might trigger the wish to avoid further face risks. Future studies should investigate the moderating influence of individual characteristics in more detail.
Positive emotions increased users’ willingness to continue participation in the discussion after receiving evaluative replies to their comments. This supports previous studies indicating that positive social media content increases engagement with the content (Berger & Milkman, 2012) and reinforces the behavior of enthusiastic users (Marcus et al., 2000). Interestingly, in contrast to several previous studies, negative emotions did not increase participation willingness. Several explanations could guide future research. The present study did not differentiate between distinct negative emotions. However, while anger could lead to combating one’s beliefs in the face of disagreement, anxiety could lead to enhanced elaboration and reasoning, which does not necessarily result in further comment posting (Lu & Gall Myrick, 2016). Additionally, the reply comments did not provide arguments for their negative or mixed evaluation. This might make it difficult for the evaluated authors to respond, and negative emotions might trigger processing about one’s ability and opinion instead of countering.
Unexpectedly, the reference of the evaluative reply did not influence any of the dependent variables. This might indicate a deficit of the stimulus material. The pretest suggested proper manipulation of the evaluations that were directed at the comment content and the author’s person. However, in the laboratory setting, participants know that feedback givers cannot access any information about them but their comments. Thus, the participants might have related even those evaluations only to their comments, which addressed them personally in their wording. There is strong evidence that more general criticism and ad hominem attacks are more detrimental. Thus, future studies need to investigate the effect of the reference of evaluations in more natural settings that allow interaction partners to differentiate more clearly between authors and their posts.
The study also adds to existing research on the effects of user replies because it is among the first that not only compared nonpositive evaluations (disapproving, mixed) but also approving evaluations. While disapproving and mixed replies did not cause different levels of positive emotions and of willingness to participate, approving replies actually led to more positive emotions and greater willingness to participate than the two nonpositive conditions. This suggests that user feedback that is not fully positive might have equal consequences to negative feedback eventually. However, this does not hold for the effects on perceived face threat and negative emotions. Here, the study pointed to differences in disapproving and mixed evaluations.


The results should be interpreted only in light of several limitations. First, the study used a mock Facebook page and investigated self-reported reactions to reply comments in a hypothetical situation. This procedure aimed at increasing the internal validity of the results. However, it limits ecological validity because the participants did not engage in a personalized social network site of their choice. They were also limited to one of two topics chosen by the researcher.
Additionally, the study considered only valenced replies, and the manipulated replies comprised merely three (quite extreme) types of evaluations. Future studies need to consider the effects of evaluations that come with justifications and differentiate more nuanced assessments. For example, the present study is not able to differentiate between civil and uncivil disapproving evaluations.
Despite the broad recruitment, the sample was not representative of German Facebook users. Primarily, the respondents had a higher level of education than the actual Facebook user community. Although interest in online discussions is greater among well-educated users (Hölig & Hasebrink, 2015), it would be rash to generalize the findings. Future research should examine the moderating influence of education on the perceived face threat of different types of evaluations in online communication. In face-to-face encounters, the education level of the interactants may affect the implicit hierarchies between discussion partners. By contrast, anonymous online settings provide the chance of more equal participation (Dahlberg, 2001). As power distance is a determinant of face threats (Brown & Levinson, 1987), the effects of the education level are worthy of being tested and can advance face theory. Educational level does not seem to influence the perception of uncivil online content (Kenski et al., 2020). However, it can influence conflict behavior (Bobo & Licari, 1989). Thus, an empirical test of the moderating role on future participation behavior is needed.