Focusing on Values and Ideals Decreased P3a Amplitude: A Confirmation of the Joint Subsystems Hypothesis

Approach - avoidance dichotomy can be found in most of the major psychological theories concerned with motivation (Elliot, 1999). However, to date little is known about the effects that the underlying systems have on each other. The joint subsystems hypothesis (JSH), derived from Reinforcement Sensitivity Theory, proposes that under most circumstances the approach (Behavioural Activation System; BAS) and avoidance (Behavioural Inhibition System; BIS) systems behave in a mutually antagonistic fashion (Corr, 2004). To test this hypothesis, I manipulated state BAS by having participants reflect on their ideals (Study 1; n = 65) and core values (Study 2; n = 62). To measure state BIS, I recorded participants’ electroencephalogram in response to white noise and pure tones from which P3a amplitude was extracted, a BIS related event-related potential. Reflecting on ideals and core values reduced P3a amplitude, as predicted by the JSH. Results are discussed in the context of the general threat and defense framework (Jonas et al., 2014)

On the Accuracy, Media Representation, and Public Perception of Psychological Scientists’ Judgments of Societal Change

At the onset of the COVID-19 pandemic, psychological scientists frequently made on-the-record predictions in public media about how individuals and society would change. Such predictions were often made outside these scientists’ areas of expertise, with justifications based on intuition, heuristics, and analogical reasoning (Study 1; N = 719 statements). How accurate are these kinds of judgments regarding societal change? In Study 2, we obtained predictions from scientists (N = 717) and lay Americans (N = 394) in the spring of 2020 regarding the direction of change for a range of social and psychological phenomena. We compared them to objective data obtained at six months and one year. To further probe how experience impacts such judgments, six months later (Study 3), we obtained retrospective judgments of societal change for the same domains (Nscientists = 270; NlayPeople = 411). Bayesian analysis suggested greater credibility of the null hypothesis that scientists’ judgments were at chance on average for both prospective and retrospective judgments. Moreover, neither domain-general expertise (i.e., judgmental accuracy of scientists compared to laypeople) nor self-identified domain-specific expertise improved accuracy. In a follow-up study on meta-accuracy (Study 4), we show that the public nevertheless expects psychological scientists to make more accurate predictions about individual and societal change compared to most other scientific disciplines, politicians, and non-scientists, and they prefer to follow their recommendations. These findings raise questions about the role psychological scientists could and should play in helping the public and policymakers plan for future events

A Multisite Preregistered Paradigmatic Test of the Ego-Depletion Effect

We conducted a preregistered multilaboratory project (k = 36; N = 3,531) to assess the size and robustness of ego-depletion effects using a novel replication method, termed the paradigmatic replication approach. Each laboratory implemented one of two procedures that was intended to manipulate self-control and tested performance on a subsequent measure of self-control. Confirmatory tests found a nonsignificant result (d = 0.06). Confirmatory Bayesian meta-analyses using an informed-prior hypothesis (δ = 0.30, SD = 0.15) found that the data were 4 times more likely under the null than the alternative hypothesis. Hence, preregistered analyses did not find evidence for a depletion effect. Exploratory analyses on the full sample (i.e., ignoring exclusion criteria) found a statistically significant effect (d = 0.08); Bayesian analyses showed that the data were about equally likely under the null and informed-prior hypotheses. Exploratory moderator tests suggested that the depletion effect was larger for participants who reported more fatigue but was not moderated by trait self-control, willpower beliefs, or action orientation.</p

Insights into the accuracy of social scientists' forecasts of societal change

How well can social scientists predict societal change, and what processes underlie their predictions? To answer these questions, we ran two forecasting tournaments testing the accuracy of predictions of societal change in domains commonly studied in the social sciences: ideological preferences, political polarization, life satisfaction, sentiment on social media, and gender–career and racial bias. After we provided them with historical trend data on the relevant domain, social scientists submitted pre-registered monthly forecasts for a year (Tournament 1; N = 86 teams and 359 forecasts), with an opportunity to update forecasts on the basis of new data six months later (Tournament 2; N = 120 teams and 546 forecasts). Benchmarking forecasting accuracy revealed that social scientists’ forecasts were on average no more accurate than those of simple statistical models (historical means, random walks or linear regressions) or the aggregate forecasts of a sample from the general public (N = 802). However, scientists were more accurate if they had scientific expertise in a prediction domain, were interdisciplinary, used simpler models and based predictions on prior data

STUDY 2 Diary study replication

Replication of a community diary stud

Data and analyses

Data files and R codeboo

Data analyses notebook with results and R scripts for analyses

R code for analyse