Monday, October 26, 2020

The repetition-induced truth effect refers to a phenomenon where people rate repeated statements as more likely true than novel statements; a minority do the opposite—they reliably discount the validity of repeated statements

The truth revisited: Bayesian analysis of individual differences in the truth effect. Martin Schnuerch, Lena Nadarevic & Jeffrey N. Rouder. Psychonomic Bulletin & Review, October 26 2020.

Abstract: The repetition-induced truth effect refers to a phenomenon where people rate repeated statements as more likely true than novel statements. In this paper, we document qualitative individual differences in the effect. While the overwhelming majority of participants display the usual positive truth effect, a minority are the opposite—they reliably discount the validity of repeated statements, what we refer to as negative truth effect. We examine eight truth-effect data sets where individual-level data are curated. These sets are composed of 1105 individuals performing 38,904 judgments. Through Bayes factor model comparison, we show that reliable negative truth effects occur in five of the eight data sets. The negative truth effect is informative because it seems unreasonable that the mechanisms mediating the positive truth effect are the same that lead to a discounting of repeated statements’ validity. Moreover, the presence of qualitative differences motivates a different type of analysis of individual differences based on ordinal (i.e., Which sign does the effect have?) rather than metric measures. To our knowledge, this paper reports the first such reliable qualitative differences in a cognitive task.

General discussion

In this paper, we show a surprising finding. Although the truth effect is reliably obtained across many data sets, the effect itself is inconsistent across people. We are confident that in most experiments some people truly judge repeated statements as more valid than novel ones, while others truly judge them as less so. This effect is not just noise—the models indicate that this inconsistency occurs above and beyond trial-by-trial variation. What makes the finding surprising to us is that the result is in contrast to previous work with these individual-difference models. The modal result is that “everybody does”, that is, there are no qualitative individual differences in common cognitive effects such as Stroop and Flanker effects (Haaf and Rouder, 20172019). In the repetition-induced truth effect, these differences exist, and they occur consistently across several data sets.

Does the presence of qualitative individual differences inform current cognitive theories of the truth effect? We think it should. A number of theoretical explanations have been proposed for the repetition-induced truth effect, for example, the recognition account (Bacon, 1979), the source-dissociation hypothesis (Arkes et al., 1991), the familiarity account (Begg et al., 1992), processing fluency (Reber & Schwarz, 1999), or the referential theory (Unkelbach & Rom, 2017). These accounts assume different underlying cognitive mechanisms, yet, they all make the same core prediction: repetition increases perceived validity. Unkelbach et al., (2019) summarize thusly: “No matter which mental processes may underlie the repetition-induced truth effect, on a functional level, repetition increases subjective truth” (p. 5). We argue, based on our analysis, that this statement is too general. In fact, we show what Davis-Stober and Regenwetter (2019) call the paradox of converging evidence: Across data sets, we find converging evidence that the statement holds on the mean level—yet, at the same time, we accumulate strong evidence that it doesn’t hold for everybody. Consequently, our results present converging evidence against theoretical positions that do not account for negative truthers.

This paper constitutes a first step by providing an answer to the fundamental question if there are qualitative individual differences in the truth effect. Having established such differences, the next step is to understand why they occur. One salient finding in this domain is that the overall truth effect can be reversed, that is, made negative, by certain experimental manipulations. Unkelbach and colleagues started with the proposition that easy-to-process statements are naturally more likely to be true (Unkelbach, 2007; Unkelbach & Stahl, 2009; see also Reber & Unkelbach, 2010; Unkelbach, 2006). In a set of creative experiments, these researchers reversed the correlation between fluency and truth, making difficult-to-read statements more likely to be true. With this correlation reversed, they observed a negative truth effect, that is, repeated statements, which are easier to process than novel statements, were now judged more likely to be false (but see Silva et al.,, 2016). One wonders if some participants have learned in their natural environment that ease-of-processing correlates with falseness, thus resulting in the observed qualitative individual differences.

Likewise, differences in memory ability might account for some of the individual differences patterns. We are most intrigued by the finding that there was evidence against individual differences in data sets where the interval between exposure and judgment lasted several days. Why would individual differences be attenuated or absent with increasing retention intervals? We suspect such a finding reflects an explicit memory-based effect (i.e., source recollection or memory for presented statements). As overall memory performance declines with increasing delay between exposure and judgment phase, these differences may diminish and, correspondingly, individual differences in the truth effect may disappear.

These post hoc explanations presented above are of course speculative. They form hypotheses to be addressed in future research. Based on our results, a promising way to examine the underlying mechanisms and possible covariates of individual differences in the truth effect is with a latent-class approach. Unlike correlational approaches, it relies on ordinal (i.e., In which direction is the effect?) rather than metric (i.e., How large is the effect?) measures. Given the strong evidence for qualitative individual differences in the majority of data sets, questions about who differs, when they differ, and why they differ are suitable to test and inform theories of the repetition-induced truth effect.

Would You Sacrifice Yourself to Save Five Lives? Processing a Foreign Language Increases the Odds of Self-Sacrifice in Moral Dilemmas

Would You Sacrifice Yourself to Save Five Lives? Processing a Foreign Language Increases the Odds of Self-Sacrifice in Moral Dilemmas. Carlos Romero-Rivas, Raúl López-Benítez, Sara Rodríguez-Cuadrado. Psychological Reports, October 25, 2020.

Rolf Degen's take:

Abstract: Foreign languages blunt emotional reactions to moral dilemmas. In this study, we aimed at clarifying whether this reduced emotional response applies to the emotions related to the self, empathy, or both. Participants were presented with moral dilemmas, written in their native or foreign language, in which they could sacrifice one man or themselves in order to save five lives (or do nothing and therefore leave five people to die). They were more willing to sacrifice themselves when processing the dilemmas in their foreign language. Also, empathy scores were reduced when responding in the foreign language, but were no reliable predictors of participants’ responses to the dilemmas. These results suggest that processing a foreign language reduces emotional reactivity due to psychological and emotional self-distance.

Keywords: Bilingualism, foreign language effect, moral dilemmas, self-distance, empathy

There are more similarities than differences between perpetrators of sex crimes & perpetrators of non-sex crimes, but the studies examined a narrow range of risk factors, which can result in somewhat misleading findings

Patrick Lussier, Evan C McCuish, Jesse Cale (Oct 2021) Sex Offenders Under the Microscope: Are They Unique?. In: Understanding Sexual Offending, pp 149-187. Springer, Cham.

Rolf Degen's take:

Abstract: No other offenders have been under as much scrutiny as perpetrators of sex crimes. A vast amount of research has been conducted in hospitals, prisons, and community settings to identify what is unique about these perpetrators. The research has been so extensive that multiple meta-analyses have been conducted to shed light on what is unique about these perpetrators. This chapter provides a review of these meta-analytic findings. In doing so, the chapter also provides a critical examination of research aiming to identify risk factors for sexual offending. While these meta-analytic studies highlight that there are more similarities than differences between perpetrators of sex crimes and perpetrators of non-sex crimes, the poor methodological properties that these studies are based upon and the narrow range of risk factors examined can potentially result in findings that are somewhat misleading. These findings raise the importance of moving away from searching for what is unique and common to all perpetrators of sex crimes and instead examining the multiple paths leading to sexual offending.

Keywords: Child abuse Deviant sexual preferences Intelligence Juvenile sexual offending Mental health Meta-analysis Pornography Risk factors Sexual victimization Social skills Testosterone 

Investigating offenders’ abilities in the context of deception detection: Criminals are not better lie detectors

Are criminals better lie detectors? Investigating offenders’ abilities in the context of deception detection. Simon Schindler  Laura K. Wagner  Marc‐André Reinhard  Nico Ruhara  Stefan Pfattheicher  Joachim Nitschke. Applied Cognitive Psychology, October 24 2020.

Rolf Degen's take:

Summary: The present research examined lie detection abilities of a rarely investigated group, namely offenders. Results of the studies conducted thus far indicated a better performance of offenders compared to non‐offenders when discriminating between true and false messages. With two new studies, we aimed at replicating offenders’ superior abilities in the context of deception detection. Results of Study 1 (N = 76 males), in contrast, revealed that offenders were significantly worse at accurately classifying true and false messages compared to non‐offenders (students). Results of Study 2 (N = 175 males) revealed that offenders’ discrimination performance was not significantly different compared to non‐offenders (clinic staff). An internal meta‐analysis yielded no significant difference between offenders and non‐offenders, questioning the generalizability of previous findings.

Individuals with higher education experienced a more depressive symptoms & more decrease in life satisfaction from before to during COVID-19; those of highest levels of income experienced more decrease in life satisfaction

Wanberg, C. R., Csillag, B., Douglass, R. P., Zhou, L., & Pollard, M. S. (2020). Socioeconomic status and well-being during COVID-19: A resource-based examination. Journal of Applied Psychology, Oct 2020.

Abstract: The authors assess levels and within-person changes in psychological well-being (i.e., depressive symptoms and life satisfaction) from before to during the COVID-19 pandemic for individuals in the United States, in general and by socioeconomic status (SES). The data is from 2 surveys of 1,143 adults from RAND Corporation’s nationally representative American Life Panel, the first administered between April–June, 2019 and the second during the initial peak of the pandemic in the United States in April, 2020. Depressive symptoms during the pandemic were higher than population norms before the pandemic. Depressive symptoms increased from before to during COVID-19 and life satisfaction decreased. Individuals with higher education experienced a greater increase in depressive symptoms and a greater decrease in life satisfaction from before to during COVID-19 in comparison to those with lower education. Supplemental analysis illustrates that income had a curvilinear relationship with changes in well-being, such that individuals at the highest levels of income experienced a greater decrease in life satisfaction from before to during COVID-19 than individuals with lower levels of income. We draw on conservation of resources theory and the theory of fundamental social causes to examine four key mechanisms (perceived financial resources, perceived control, interpersonal resources, and COVID-19-related knowledge/news consumption) underlying the relationship between SES and well-being during COVID-19. These resources explained changes in well-being for the sample as a whole but did not provide insight into why individuals of higher education experienced a greater decline in well-being from before to during COVID-19.

KEYWORDS: socioeconomic status, conservation of resources, well-being, COVID-19


A nationally representative sample in the United States displayed an increase in depressive symptoms and a decrease in life satisfaction from before to during COVID-19. Levels of depressive symptoms during COVID-19 were also higher than previously established norms (Tomitaka et al., 2018).
Contributing to the important goal of illustrating how the pandemic is affecting individuals of lower and higher SES, our study showed that during the first peak of the pandemic in the United States, higher education was positively associated with depressive symptoms and negatively associated with life satisfaction. This was contrary to expectations because individuals with lower SES generally have lower well-being. Consistent with expectations, higher income was associated with lower depressive symptoms and higher life satisfaction during the pandemic.
Assessment of change from before to during the pandemic is important to diagnose how the pandemic affected well-being. Individuals with higher education experienced a greater increase in depressive symptoms and a greater decrease in life satisfaction from before to during COVID-19 than individuals with lower education. Income did not have linear relationship with changes in well-being, but supplemental analysis supported a curvilinear relationship showing that individuals at higher levels of income experienced a greater decrease in life satisfaction from before to during COVID-19 than individuals with lower levels of income (see Figure 2).
These findings provide a partial replication of the Axios-Ipsos poll, which indicated that in the United States, a higher proportion of higher SES individuals reported a decline in their emotional well-being due to the pandemic than those of lower SES (Talev, 2020). A major difference between our study and the Axios-Ipsos poll (beyond our use of comparison data from before the pandemic) is their use of an income and education composite to index SES. Income and education capture different parts of SES and can result in divergent empirical findings (e.g., Christie & Barling, 2009DeGarmo, Forgatch, & Martinez, 1999), which we also reveal in this study.
We examined four resource-based mechanisms to try to explain how SES may transmit to lower and reduced well-being. Tested mediators did not provide good explanatory value, especially for the effect of education. The one significant mediator, COVID-related knowledge, contributed to an increase in life satisfaction from before to during COVID-19, rather than a decrease. As such, COVID-related knowledge was not a valuable explanatory mechanism to explain why individuals with more education displayed an overall well-being decline. Further insight is thus needed. In supplemental analyses, education was not associated with job loss due to COVID-19, r = −.06, p > .05. We also added having experienced job loss (furloughed or laid off) due to COVID-19 as another control variable. Results were consistent with or without this control. An unmeasured explanation is the increase in work responsibility that individuals of higher education may have encountered. The pandemic meant that many managers had to lead their business units and teams through staffing changes such as layoffs or pay cuts, producing substantial stress (Knight, 2020). Further, educational attainment is a key predictor of participation in the stock market (Cooper & Zhu, 2016), which represents a nuanced aspect of financial resources that our measure might not have fully captured. In the few weeks preceding our T2 assessment, the Dow Jones Industrial Average lost one third of its total value (S&P Dow Jones Indices, 2020), which may have contributed to a greater loss of wealth (and fear of loss) among individuals with higher levels of education.
Finally, it is plausible that individuals of higher SES experience adaptation or an endowment effect whereby they have a higher expectation for a constant availability of resources (including ones not incorporated in our theorizing), and therefore experience greater declines in well-being when a crisis contracts or threatens their resource supplies (Diener & Biswas-Diener, 2002Tversky & Kahneman, 1991). This possible explanation is particularly intriguing given that evidence suggests that the pandemic has hit individuals of lower SES very hard. As one of many examples of higher impacts to lower SES individuals, household crowding and higher odds of working on-site have been linked to higher rates of COVID-19 infections (Emeruwa et al., 2020Oppel, Gebeloff, Lai, Wright, & Smith, 2020).
Our study assessed well-being early in the pandemic and it is possible that the findings of more severe well-being decline among individuals of higher SES are temporary. Future research should examine well-being among groups of higher and lower SES over a longer time during the pandemic as well as moderators of the impact of education (e.g., personality traits). For organizational and managerial practice, as well as mental health practitioners, it will be key to identify the groups for whom the impacts are longer lasting in order to address inequities. It would also be intriguing to examine if our findings replicate in other countries, to consider the role of threat of loss versus actual loss of resources, and to theorize the role of factors such as age and general health as more central predictors of psychological well-being during COVID.
There are several unique aspects to our investigation. Available pre–post studies of SES in the context of other crises have relied on data following versus during the event (Norris et al., 2002). Our study also expands collective knowledge by examining the role of resources in explaining SES differences in levels and changes in well-being during a crisis event. An additional major strength of our study is that it features a probability sample-based, nationally representative panel. This broad sampling strategy was essential to represent both low and high levels of SES, and to provide a more rigorous test of our hypotheses.
We contribute to the conversation on socioeconomic inequality by illuminating how a crisis event afflicts well-being across the SES spectrum. The theory of fundamental social causes has primarily been examined with respect to physical health. Our study extends this theory to the examination of psychological well-being. We found more support for this theory with respect to income as an SES indicator than for education. Moreover, our study contributes to the dynamic testing of COR theory, which emphasizes the velocity of loss spirals underlying chronic resource shortages and suggests the primacy of acute resource losses (Ennis, Hobfoll, & Schröder, 2000Hobfoll, 2010). Our findings provide some support for both of these tenets. We found inferior well-being during the pandemic among individuals with lower income and also observed well-being declines to a greater extent among individuals of higher education. Future research is needed to distinguish between the relative impact of chronic resource shortages and acute resource losses. We also invite more managerial research delineating how SES contexts shape psychological experiences in the face of societal and organizational crises (Bapuji, Patel, Ertug, & Allen, 2020Fiske & Markus, 2012).
As a limitation, our sample focused on individuals who participated in the Adult Social Networks and Well Being study that targeted U.S. adults between 30 and 80 years old. Future research can examine whether our results generalize to those under the age of 30. It is also important to qualify our inferences about COVID-19 per se being the definitive cause of well-being changes from 2019 to 2020. These dynamics may plausibly be explained by other factors that are not associated with the pandemic, such as the political environment. The consistent timing of well-being assessments in 2019 and 2020 mostly rule out alternative explanations related to seasonal effects.