Monday, September 5, 2022

Pedestrians gave more than twice as much money to the guy wearing higher-class symbols than they did to the one wearing lower-class symbols, which were perceived as of elevated competence, trustworthiness, similarity to the self, and perceived humanity

The influence of signs of social class on compassionate responses to people in need. Bennett Callaghan, Quinton M. Delgadillo and Michael W. Kraus. Front. Psychol., August 25 2022. https://doi.org/10.3389/fpsyg.2022.936170

Abstract: A field experiment (N = 4,536) examined how signs of social class influence compassionate responses to those in need. Pedestrians in two major cities in the United States were exposed to a confederate wearing symbols of relatively high or low social class who was requesting money to help the homeless. Compassionate responding was assessed by measuring the donation amount of the pedestrians walking past the target. Pedestrians gave more than twice (2.55 times) as much money to the confederate wearing higher-class symbols than they did to the one wearing lower-class symbols. A follow-up study (N = 504) exposed participants to images of the target wearing the same higher- or lower-class symbols and examined the antecedents of compassionate responding. Consistent with theorizing, higher-class symbols elicited perceptions of elevated competence, trustworthiness, similarity to the self, and perceived humanity compared to lower-class symbols. These results indicate that visible signs of social class influence judgments of others’ traits and attributes, as well as in decisions to respond compassionately to the needs of those who are suffering.

General discussion

As economic inequality rises in many parts of the world, and countries such as the United States roll back social safety net programs (Piketty, 2014), the responsibility for dealing with inequality’s deleterious impacts (Wilkinson and Pickett, 2009) has increasingly fallen to economically precarious individuals themselves or to private citizens exercising compassion, defined as concern for the suffering of others and the motivation to help improve their circumstances (e.g., Goetz et al., 2010Gilbert, 2017Mascaro et al., 2020). Building on prior research and theorizing in the rich tradition of research on sympathy, empathy, and compassion (Batson et al., 1989Cialdini et al., 1997Oveis et al., 2010), the current research examined the tendency for people to respond compassionately (or not) in the presence of those who were apparently suffering or, at least, made salient a concern with suffering related to poverty and homelessness (i.e., a panhandler), in two cities in the United States. The current research suggests that people respond more compassionately, and perceive such individuals more favorably, when they signal higher–relative to lower–social status through physical appearance. This pattern of results arose even though all confederates and targets appeared to be generally low in status, and it arose in an experimental, but ecologically valid, context where participants shared their own money.

This research also contributes to a longstanding body of research suggesting that non-verbal status cues influence behavior on the part of others (e.g., Bickman, 1971Tracy et al., 2018). That symbols of high social class more than doubled the donations of pedestrians over a 4-h period indicates their power in shaping initial judgments of others’ basic human traits and in eliciting compassionate responses in everyday life. Importantly, our results align with past theory and research suggesting that high status signaling provides many direct benefits to individuals, including grooming and mating partners in non-human primates (Sapolsky, 2004). This research adds received generosity, among humans, to this list of benefits.

Interestingly, mere novelty and noticeability of the higher status confederate do not seem to explain observed differences in generosity. In the field experiment, the mere frequency of the interactions did not differ by condition; in Study 2, in fact, participants were in fact more likely to attend to the lower status target. Instead, the quality of these interactions and their outcomes (as indicated by the analysis of extreme donations) differed. Anecdotally, this qualitative distinction bears out. When people did go out of their way to speak to the confederate, the higher status one received comments such as “I usually don’t give money to people on the street, but you seem like a nice guy.” In one case, a pedestrian (also donned in a business suit) even dropped a business card into the higher status confederate’s collection cup–a tacit invitation for the confederate to seek employment, rather than a trivial one-time donation.

As discussed, the large donations of $5 or $10, given their size and exclusive presence in the relatively higher status trials, likely contribute substantially to some of the effects we observe in the field study. Much like the interactions sketched above, these donations might also represent a qualitative shift in how donors approached the situation: they may have donated $5 or $10 in the hopes of more effectively meeting the confederate’s immediate perceived needs, as such an amount would be more appropriate than more common donation amounts (e.g., $1 or less) for most self-care and survival needs, such as purchasing a meal. Thus, these donations might be particularly representative of compassionate responding insofar as they are intended to effectively and (depending on participants’ construal of the situation) immediately alleviate suffering. However, they also suggest the possibility of theoretical accounts we did not fully theorize. For instance, it is possible that status signaling is most effective at eliciting high-variance responding; in other words, signaling higher status might not strongly impact tendencies to engage in compassion in general, but, rather, impacts tendencies to engage in extreme–as defined in relation to more typical donation amounts–acts of compassion (again, however, use of the word “extreme” might be misleading, as these donations might also be described as simply independently sufficient to meeting the goals at hand).

It is also possible that this pattern of results reflects an unobservable moderation effect. Perhaps, for instance, the effects of status signaling are most pronounced among those who are more inclined to acts of extreme generosity to begin with. Alternatively, this effect might be attributable to the presence of stronger effects among participants who are higher in SES themselves. The design of the field experiment study did not allow us to assess the SES of passersby, and, thus, whether participants’ own social class characteristics contributed to decisions to respond compassionately to the confederate. As indicated by the overall low levels of subjective SES attributed to the target in the perceptual study, it is likely that the higher status confederate was perceived as closer to participants, in terms of socioeconomic standing, than the lower status confederate across the board (excluding those who are themselves poor or unhoused). Still, however, the perceptual study does suggest meaningful differences in self-other similarity according to status signaling condition, and the possibility that signalers who better “match” the status of perceivers benefit from even greater compassion than those who merely signal higher status has received mixed empirical support (see, e.g., Goodman and Gareis, 1993). Thus, it is possible that high status signals appealed specifically to passersby of particularly high SES and who, due to greater access to financial resources, may have stood to lose less through larger donations or simply regarded higher amounts of money as an appropriate default for donation (as a proportion of the money they had on hand, for instance). Though it may be difficult to measure individual differences such as predispositions toward extreme generosity in a field study context, future replications of this research might employ methods of subjectively coding participant SES (e.g., Bickman, 1971) or systematically varying the SES characteristics of the research sites (e.g., Goodman and Gareis, 1993) in order to determine the regularity with which these extreme donations occur and whether they are given disproportionately by those of higher socioeconomic standing.

Together, these qualitative experiences and extreme donation profile provide some support for the general pattern observed in Study 2, and support a central tenet of theories of compassion: that compassionate responding hinges on the reputation of targets, especially with respect to their likelihood of engaging in reciprocal cooperation with other prosocial individuals (Goetz et al., 2010). The present research adds signals of social class as a possible cue that reliably elicits such reputational perceptions.

Moreover, high status signals increased specific judgments of competence, trustworthiness, humanity, and self-other similarity. Thus, the results of the current studies suggest that poor individuals who adopt these symbols might be seen as more effective at converting gifts into intended outcomes (such as personal advancement or care), as less likely to engage in behaviors that might be seen as making them blameworthy for their plight (e.g., drug or alcohol use; see Goetz et al., 2010), and as more likely to use those gifts for intended means rather than as a strategy to accrue undeserved wealth. In short, such signals may make one appear more deserving of compassion (Goetz et al., 2010).

A closely related alternative explanation for the current set of results, which more strongly emphasizes the perceived ability (rather than the inclination) to engage in future prosocial behavior by the confederate, is that participants were more likely to see the higher status confederate’s need state as temporary, rather than chronic. Consistent with certain evolutionary accounts of reciprocal altruism (e.g., Sugiyama and Sugiyama, 2003Tracy et al., 2018), the perceived combination of high temporary need and high baseline competence may have biased individuals toward helping the higher status confederate in his time of need because he was perceived as more able to help others, or “pay it forward,” when he had the opportunity to do so. Given that the high and low status targets were strongly discriminated along the lines of competence, this alternative explanation is plausible. Future research is needed, however, to determine whether such perceptions of ability to engage in future acts influence compassionate responding independent of perceptions of deservingness.

In a similar vein, our field study operationalizes compassion as costly helping behavior–a common method of doing so within the social-psychological literature and one that avoids many of the biases inherent in self-report measures (Mascaro et al., 2020). Our second study also includes a number of social perceptions that index deservingness, an antecedent to compassion in prevailing theoretical accounts of the construct (e.g., Goetz et al., 2010). While this research demonstrates the influence of status signaling on theoretically important perceptions of a target (Study 2) and responses toward a confederate (Study 1), this research does not measure compassion, as a subjective psychological state, directly. Nor does the second study measure compassionate responding directly, as in Study 1. Thus, the two studies taken together show a pattern that is consistent with a theoretical account emphasizing compassion: one in which status signaling affects particular theoretical antecedents of compassionate responding (i.e., warmth, competence, self-other similarity, and ascribed humanity), which then influence compassion and compassionate responding. However, these results do not necessarily confirm that status signaling directly influences perceptions linked to deservingness and, subsequently, compassion and compassionate responding.

To address this theoretical gap, future research might attempt to measure compassion directly and demonstrate that signaling relatively higher (as compared to lower) status–by way of heightened perceptions of deservingness–heightens self-reported compassion for those suffering in the relevant context as well as subsequent compassionate responding (i.e., donations). In doing so, researchers should be mindful of best-practices in the measurement and definition of this complex emotion (Gilbert, 2017Mascaro et al., 2020). For instance, such research might attempt a multi-method approach to conceptualizing and measuring compassion that synthesizes quantitative reports of one’s own and others’ mental states, physiological measurements, and observations of behavior (e.g., Mascaro et al., 2020). Additionally, such research might take care to distinguish compassion from subjective and emotional states–such as distress, sadness, and love–that are sometimes used interchangeably with compassion in the literature (e.g., Goetz et al., 2010Gilbert, 2017). Second, in order to test the full theoretical model we have proposed here, future research should manipulate status signaling and measure both the antecedents we propose and compassion (or compassionate responding) within the same study. Such a study could at least determine whether the key variables related to deservingness mediate the effect of status signaling on compassion. Ideally, future research could also manipulate these mediators to establish a truly causal chain of effects (Spencer et al., 2005).

It is also possible, however, that conditional differences in confederate behavior contributed to differences in generosity on the part of passersby. The confederate was not blind to condition or hypotheses, and previous research suggests that donning high status sartorial signals can change the behavior of even naïve participants (Kraus and Mendes, 2014). Though this is a possibility, we minimized this likelihood by having the confederate behave consistent with standardized instructions. Moreover, that a follow-up study elicited theoretically relevant patterns of perception from passive observers suggests that the effect of status signaling on generosity observed in the field is at least partially driven by perceiver judgments. Finally, even if the behavior of the confederate did subtly differ between conditions, such subtle differences would need to compete with the cacophony of stimuli that individuals normally encounter when walking down a busy street in New York or Chicago, so the context in which we chose to conduct our field experiment also mitigates concerns with experimenter effects.

Indeed, it was partially because we expected multiple competing demands on the attention of passersby that we chose to manipulate comparatively obvious visual cues (combined with spoken statements to draw attention), rather than other cues that also signal status, such as vocal pitch (e.g., Gregory and Webster, 1996), accent (e.g., Labov, 2006Kraus et al., 2019), or cultural signifiers of aesthetic taste (Bourdieu, 1984). Nonetheless, these other modalities represent interesting potential avenues for future research.

Similarly, those who did attend to visual cues of status also likely perceived other superficial but potentially important characteristics, such as those that indicate membership in particular social identity groups. It is interesting to speculate about how these other characteristics of the confederate (i.e., an individual generally perceived to be White and male) may have impacted the effect of status signaling on compassionate responding. For example, membership in other social categories might modify the results observed in these experiments. Theoretical accounts suggest that symbols of social status influence perception similarly across race and gender (Major and O’Brien, 2005), but previous research also finds that social status and race or gender may interact in subtle ways to produce marked differences in status-linked outcomes, such as health and mortality rates (Case and Deaton, 2015) or experienced bias and discrimination (e.g., Goff and Kahn, 2013Rivera and Tilcsik, 2016). Future research would need to determine if high status symbols confer the same benefits to members of other intersecting social groups as they apparently do for White men.

Future research might also measure how different characteristics of the giving context moderate how status symbols influence outcomes. For instance, some research has found that in contexts where individuals are already motivated to engage in prosocial behavior and are deciding how to distribute their resources, symbols of high status are negatively related to the receipt of altruism (Tracy et al., 2018). These researchers suggest that opposite patterns of effect with respect to status and altruistic behavior might arise depending on whether potential actors are deciding to engage in altruistic behavior in the first place or are deciding how to engage in such behavior. We echo these researchers’ calls for further investigation into this distinction as a potential moderator of the effect of status signaling on compassionate responding (p. 527). We also note that our results regarding the influence of status signaling manipulations on compassionate responses are perhaps bounded to compassionate responding in contexts involving the alleviation of suffering related to poverty and homelessness and to such responses enacted through brief, interpersonal exchanges. Thus, we caution generalizing these results to compassion directed toward other ends or within impersonal contexts, such as online behavior (see, e.g., Tracy et al., 2018).

Finally, we also acknowledge some ambiguity with respect to how participants themselves interpreted donating in the field experiment. As noted, the confederate only told participants that collected funds would be donated to charity if they had asked; few people interacted directly with the confederate in this way, and this pattern did not differ by condition. However, because we were constrained by ethical considerations in terms of what we could tell participants and the field context of the experiment made us unable to probe participants about their inferences regarding the confederate at the time they decided to donate (or not), we still do not know (as discussed) whether individual participants perceived the confederate as the primary benefactor of their donations or as an intermediary.

Even for participants operating under the latter assumption, however, the relevant behavior of donating nonetheless reflects the broader construct of compassionate responding, as those who donated were either donating directly to the target or helping him in his objective to raise money for charity (a goal that is aligned with the reduction of suffering). To this point, previous research has treated explicit contributions to third-party charities as an index for helping behavior directed toward a confederate (Pandey, 1979), and even those who donated under the assumption that the funds would be donated placed significantly more trust in the higher status than the lower status confederate–despite the lack of any guarantee the money would go to charity. Again, such a result is consistent with our overall theoretical expectation that relevant compassionate responding would be directed toward those presumed to be more honest and prosocial themselves, and it would at least appear that signaling status influenced decisions to engage in costly helping behavior (likely driven by differential patterns of social perception) regardless of how participants interpreted the situation. Still, the influence of status signaling on compassionate responding might depend on whether those signaling higher status themselves or third parties are the primary beneficiaries. Future research might investigate this distinction more explicitly.

These limitations and open questions notwithstanding, this research adds to existing models that highlight compassion, sympathy, and perceptions of deservingness as primary causes of compassionate responding (e.g., Goetz et al., 2010). Importantly, our results suggest that social status–and its accompanying interpersonal judgments–enters prominently into such processes. Ironically, low status individuals who appear to need the most help may end up receiving less of it than those who appear higher in status and more abundant in resources.

These results also have direct implications for rising levels of economic inequality in society. Given research suggesting that economic inequality and its negative consequences increase when social status is more visible (Nishi et al., 2015DeCelles and Norton, 2016), the current findings suggest that status symbols expressed through sartorial displays or other non-verbal behaviors are potential mechanisms for the perpetuation of economic inequality. We found that even among those engaging in ostensibly selfless behavior, individuals were more likely to enter into economic relationships with others who appeared higher, rather than lower, in social status. Given the high degree to which neighborhoods, professional networks, and daily life are stratified by social class, behaviors guided by status signaling can accrue and concentrate wealth and opportunity among a privileged few–further perpetuating inequality (see also Kraus et al., 2019).

These results may also hold implications for addressing economic inequality on a broader societal scale. As indicated by similar research in this domain, cross-status interactions in everyday life can perpetuate inequality by impacting support for social policy aimed at addressing it (Sands, 2017). Nonetheless, such policies are arguably likely to garner the most efficient redistributive outcomes, especially when one considers the alternatives. If subtle interpersonal cues, like clothing or similar indicators of status, shape the behavior of individual actors outside the context investigated in the current research, mechanisms of redistribution that rely on idiosyncratic preferences or the behavior of well-meaning individuals more broadly–such as large donations from wealthy donors to particular individuals or organizations–may be inefficient or underserve those who need the most assistance, whether such needs are met directly or through intermediaries (e.g., charities).

Those from denigrated groups, such as those suffering from homelessness, need monetary assistance despite lacking the ability to transmit status symbols that, as our results suggest, may make certain forms of compassionate responding (i.e., spur-of-the-moment donations) more likely. Moreover, not all charitable organizations aimed at helping such individuals may be equally adept at appealing to wealthy donors or motivating such individuals to donate in the first place. Depending on how far one may extrapolate the results reported here, our research suggests that such a process might require an understanding of how to leverage high status signals (on the part of charities themselves) or how to portray those in need in ways that emphasize their humanity, warmth, competence, and similarity to potential givers. By contrast, codified inequality-reducing policies (such as progressive taxation) do not rely on the generosity of individuals to meet their aims. Unfortunately, even well-meaning generosity, if dispatched at the level of individuals, may be biased by processes of person-perception that direct resources on the basis of attributes other than who is most needy or how resources can best be distributed.

IQ is a positive predictor of participation and spending in horse wagering; in addition, high IQ is associated with choosing more complex (high variance) betting products

Does IQ predict engagement with skill-based gambling? Large-scale evidence from horserace betting. Niko Suhonen, Jani Saastamoinen, David Forrest, Tuomo Kainulainen. Journal of Behavioral Decision Making, September 4 2022. https://doi.org/10.1002/bdm.2300

Abstract: We examine how measured intelligence, referred to as IQ, predicts a consumer's decisions on whether to participate in online horse wagering, how much to spend on those bets, and which horserace betting products to consume. We combine three individual-level archival data sets from Finland, including all online horse bets during a 1-year period from the state-sanctioned monopoly operator, the Finnish Defence Forces' IQ test scores from male conscripts born between 1962 and 1990 (N = 705,809), and administrative registry data on socioeconomic status, income, and education for these men. An analysis of male bettors (N = 15,488) shows that IQ is a positive predictor of participation and spending. In addition, high IQ is associated with choosing more complex (high variance) betting products. We find that these results are driven primarily by numerical IQ.

6 CONCLUSION

6.1 Discussion

This paper demonstrates that IQ, and especially its numerical ability subcomponent, is positively associated with an individual's decisions relating to participation in and expenditure on horse betting, and with a relative preference for complex betting formats. It is plausible that intelligent persons and those with numerical ability gain satisfaction from absorbing themselves in tasks involving “crunching numbers,” such as horse wagering. Consequently, our study provides empirical support for treating decisions on gambling as aspects of consumer behavior (Conlisk, 1993), at least in the case of skill-based gambling, as opposed to the proposition that gambling stems from behavioral biases (Barberis, 2012).

Consistent with Forrest and McHale (2018), our analyses suggest that IQ, and particularly numerical IQ, predicts participation in horse wagering. To some extent, this result is also congruent with Grinblatt et al. (2011) who find that IQ is positively correlated with an individual's decision to invest in the stock market, because skill-based forms of gambling and stock markets tend to attract similar individuals in terms of motivation and personality attributes (Arthur et al., 2016). As high-IQ men tend to spend more on horse betting products than low-IQ men do, our findings may also reflect the intellectual challenge quality of horse betting, as suggested by Binde (2013).

On the other hand, our results appear to be at odds with Gong and Zhu (2019), as none of their three measures of cognitive ability were significant predictors of which gamblers choose to engage in skill-and-chance games (as opposed to pure chance games, defined by them as comprising bingo, scratchcards, lottery, and keno). However, their list of skill-and-chance products included slot machines. Slot machines typically offer games where the outcome is random and tends to be generally regarded as a chance-based game (Stevens & Young, 2010). Furthermore, their data were a self-reported survey. Consequently, these aspects warrant caution when our results are compared with those presented in Gong and Zhu (2019).

Consistent with the hypothesis that a motivation for betting is the intellectual challenge (Binde, 2013; Johnson & Bruce, 1997, 1998), our results suggest that individuals seek to match their betting choice to their own level of IQ. Since high-IQ individuals appear to respond more to price (Grinblatt et al., 2016), it is fair to assume that these individuals in our context are likely to be aware of the lower take-out on easy products and in any case the different levels of take-out are clearly signaled by the operator. In particular, this result suggests that high numerical IQ consumers enjoy the intellectual challenge provided by complex betting formats and are willing to pay a greater take-out to play them. Consequently, their stronger preference for complex bets could reflect a genuine preference, which is consistent with intelligent persons exhibiting preference for performing challenging tasks (Cacioppo & Petty, 1981).

It is also possible to define the take-out rate as one of several “structural characteristics” which distinguish different gambling products from each other (Newall et al., 2021). When viewed purely through the lens of expected value, complex betting formats might appear as less attractive than simple ones (Newall et al., 2021), particularly for those bettors with a high numerical ability. In our approach, however, take-out is not regarded as a structural characteristic of the product, because it is not inherent to the product, but rather is a price chosen by the supplier in response to the nature of demand. In our findings, bettors with higher cognitive skills choose to purchase more complex products despite their high take-out rate. This implies that degree of complexity is the “structural characteristic,” and it is one for which they are willing to pay a higher price.

The administrative registry data facilitated the inclusion of controls reflecting demographic and socioeconomic status, which allowed us to draw conclusions about horse betting. For example, spending tends to increase with income, but slowly. This mirrors previous findings for gambling spend in general (Rude et al., 2014) and for lottery games (Combs & Spry, 2019) and implies that lower income individuals tend to allocate a higher share of their income to gambling (Castrén et al., 2018). Regarding age, engagement with horse betting appears to peak in middle-age, again similar to findings about participation in gambling generally (Welte et al., 2011). But whether the relatively greater engagement with horse betting in Finland among the middle-aged represents a cohort effect or a generational effect cannot be inferred from 1 year of data.

6.2 Limitations and future research

This paper has some limitations. Foremost, our data set includes only data on horse betting. Hence, our results may not generalize to other forms of gambling, most notably chance-based gambling. Further, we are unable to analyze propensities to problem gambling. Although some studies suggest that low IQ correlates with problem gambling (e.g., Hodgins et al., 2012; Rai et al., 2014), other factors that we could not observe are also likely to be relevant. For example, Parker et al. (2008) highlighted the role of emotional intelligence as a protective factor against the risk of developing problems.

The FDF data set also has some limitations. First, individuals have different incentives to effort when completing the test, which may bias IQ test scores. That is, if a conscript wishes to avoid training for a non-commissioned officer, which is more likely if he or she performs well in the IQ test, he or she may purposely underperform in the test. In addition, our measures of IQ may not be directly comparable to other studies, as IQ or cognitive ability is often operationalized in very different ways, depending on a study and its context. Second, some males are exempt from military service and some opt for non-military service instead. Third, the sample excludes the female population. Fourth, IQ scores were measured between 6 and 34 years prior to the betting transactions recorded in the study. To the extent that IQ can change over an adult's lifetime, this introduces measurement error into the analysis. Finally, the data are from a limited time interval and from a single country.

Our results open avenues for future studies. Rather than examining only a general measure of IQ, future studies should examine how the separate subcomponents of IQ predict consumer decision making. Intelligence and numerical ability could be instrumental in decisions relating to consumption, investment, and life outcomes in general. Future studies could also yield insight into theories of risk-taking behavior by addressing correlations between IQ and a person's risk preferences.

6.3 Concluding remarks

This paper demonstrates that a person's IQ predicts his engagement with horse betting. Our results show that IQ, and especially its numerical ability subcomponent, is positively correlated with participation in and expenditure on horse betting, and a relative preference for complex betting formats. These findings are consistent with skill-based gambling, or at least horse betting, being consumption of entertainment, which intelligent individuals enjoy. Thus, it is plausible that intelligent persons and those with numerical ability gain satisfaction from absorbing themselves in tasks involving “crunching numbers,” such as horse wagering.

Exogenous administration of testosterone increased impulsivity in heterosexual men, increasing preference for the smaller-sooner option, and inducing steeper discounting for the delayed option

Exogeneous testosterone increases sexual impulsivity in heterosexual men. Yin Wu et al. Psychoneuroendocrinology, September 5 2022, 105914. https://doi.org/10.1016/j.psyneuen.2022.105914

Highlights

• Exogenous administration of testosterone increased preference for the smaller-sooner option.

• Exogenous administration of testosterone induced steeper discounting for the delayed option.

• Exogenous administration of testosterone increases impulsivity for sexual rewards in heterosexual men.

Abstract: Testosterone has been hypothesized to promote sexual motivation and behavior. However, experimental evidence in healthy humans is sparse and rarely establishes causality. The present study investigated how testosterone affects delay of gratification for sexual rewards. We administered a single dose of testosterone to healthy young males in a double-blind, placebo-controlled, between-participant design (N = 140). Participants underwent a sexual delay discounting task, in which they made a choice between a variable larger-later option (i.e., waiting longer to view a sexual picture for a longer duration) and a smaller-sooner option (i.e., waiting for a fixed shorter period of time to view the same picture for a shorter duration). We found that testosterone administration increased preference for the smaller-sooner option and induced steeper discounting for the delayed option. These findings provide direct experimental evidence that rapid testosterone elevations increase impulsivity for sexual rewards and represent an important step towards a better understanding of the neuroendocrine basis of sexual motivation in humans.

Keywords: androgenimpulsivitysexual rewardintertemporal choicemating


Sunday, September 4, 2022

A machine-predicted brain sex score explains individual differences in cognitive intelligence and genetic influence in young children; sex identified with a 93pct success

The sexual brain, genes, and cognition: A machine-predicted brain sex score explains individual differences in cognitive intelligence and genetic influence in young children. Kakyeong Kim, Yoonjung Yoonie Joo, Gun Ahn, Hee-Hwan Wang, Seo-Yoon Moon, Hyeonjin Kim, Woo-Young Ahn, Jiook Cha. Human Brain Mapping, April 26 2022. https://doi.org/10.1002/hbm.25888


Abstract: Sex impacts the development of the brain and cognition differently across individuals. However, the literature on brain sex dimorphism in humans is mixed. We aim to investigate the biological underpinnings of the individual variability of sexual dimorphism in the brain and its impact on cognitive performance. To this end, we tested whether the individual difference in brain sex would be linked to that in cognitive performance that is influenced by genetic factors in prepubertal children (N = 9,658, ages 9–10 years old; the Adolescent Brain Cognitive Development study). To capture the interindividual variability of the brain, we estimated the probability of being male or female based on the brain morphometry and connectivity features using machine learning (herein called a brain sex score). The models accurately classified the biological sex with a test ROC–AUC of 93.32%. As a result, a greater brain sex score correlated significantly with greater intelligence (rho-fdr < .001, (eta sub p)**2= .011–.034; adjusted for covariates) and higher cognitive genome-wide polygenic scores (GPSs) (rho-fdr < .001,  (eta sub p)**2 < .005). Structural equation models revealed that the GPS-intelligence association was significantly modulated by the brain sex score, such that a brain with a higher maleness score (or a lower femaleness score) mediated a positive GPS effect on intelligence (indirect effects = .006–.009; p = .002–.022; sex-stratified analysis). The finding of the sex modulatory effect on the gene–brain–cognition relationship presents a likely biological pathway to the individual and sex differences in the brain and cognitive performance in preadolescence.


4 DISCUSSION

We report the novel relationship between brain sex difference, cognitive performance, and shared genetic influence in an admixed American population of prepubertal children. As trained on the grey matter morphometric and white matter connectomes, our machine learning models showed the accurate classification of sex with over 93.32% ROC–AUC in a replication set. Furthermore, the individual variability of the sexual brain development, indexed by the brain-based sex score, showed significant correlations with general intelligence and the inherited genetic influence on general intelligence, the cognitive GPSs. Moreover, the SEM showed that the effect of the cognitive GPSs on cognitive outcomes was modulated by the brain sex score significantly in females and with a similar trend in males. Thus, this study indicates the critical role of brain sex in cognitive performance in prepubertal children, influenced by genetic factors, providing a biological account for the individual variability of neurocognition.

Our study departs from the prior literature on sex differences in intelligence in children by showing the role of the continuum of brain sex on cognitive performance. Literature shows that the group sex differences in mind and behaviors, such as hormonal influences (Vuoksimaa, Kaprio, Eriksson, & Rose, 2012), brain differences (Ostatníková et al., 2010), cultural influences (Penner & Paret, 2008), gender stereotypes (Stoet & Geary, 2012), and biopsychosocial interactions (Haier, Karama, Leyba, & Jung, 2009; Miller & Halpern, 2014). In intelligence, however, literature shows mixed findings of sex differences (Dykiert, Gale, & Deary, 2009). Some show that males have advantages (Irwing & Lynn, 2005; Jackson & Philippe Rushton, 2006; van der Linden, van der Linden, Dunkel, & Madison, 2017) in general intelligence over females, while others show females have advantages over males (Keith, Reynolds, Patel, & Ridley, 2008). These mixed findings may allude to large individual variability in intelligence within sex. Indeed, a recent seminal study shows the biological underpinnings of the individual variability in behavioral phenotypes in adolescents (Vosberg et al., 2020). This study presents an estimate of the continuum of sex based on the brain and body traits, which predicts within each sex the individual variability in sex hormones, personality traits, and internalizing–externalizing behaviors. In line with this, our study further demonstrates the utility of multimodal brain imaging combined with machine learning in estimating an individual status of brain sex. For example, our method permitted the accurate estimation of an individual's developmental status of the brain sex and revealed that the brain sex estimates varied across individuals even within the narrow age range. The discovery of the correlation of the brain sex variability with the genetic and cognitive variables further reflects that this novel estimate may represent a critical neurobiological process.

Another pattern to note is the greater association of crystallized intelligence (the ability that is acquired throughout life: i.e., knowledge, facts, and skills) with the brain-based sex, as well as GPSs for cognitive capacity, compared with fluid intelligence (the ability to reason and solve problems in novel situations; a trend towards significance). These findings are partially in line with prior genetic research showing that crystallized intelligence is greatly associated with genetic influence than fluid intelligence (Christoforou et al., 2014; Genç et al., 2021). Furthermore, since learning attitude (i.e., reading books) may be genetically inherited (Krapohl et al., 2014; Olson, Vernon, Harris, & Jang, 2001), it adds to the genetic propensity of crystallized intelligence. Taken together, these empirical findings including ours may challenge the historical conceptualization that fluid intelligence may be more driven by genes and crystallized intelligence by the environment (Cattell, 1971).

Our structural equation models show the potential relationships among the genes, brain sex, and cognition. The results indicate that a higher brain maleness score (a lower femaleness score) positively modulates the positive effect of the cognitive GPS on general intelligence significantly in both sexes. Considering that the modulatory effect remains significant after controlling for several potential confounding factors of the brain and cognitive performance, this GPS-brain sex-intelligence pathway has a significant statistical association. These results thus suggest the novel role of brain sex in children, linking the genetic influence to cognitive performance.

Then, what is the biological account of the modulatory effects of the brain sex on the genetic influence on cognitive performance: that is, positive toward maleness and negative toward femaleness? Literature shows that sex chromosomes play a crucial role in cognitive performance (Bender, Puck, Salbenblatt, & Robinson, 1990; Hong & Reiss, 2014; Warling et al., 2020). However, since we did not include the sex chromosomes when constructing the GPSs (following the common practice of the GWAS designs to boost statistical power), it might not fully explain the differences in the mediation effects across sex. Alternatively, we speculate that the different expression patterns of autosomal variants across sex (Boraska et al., 2012; Wijchers & Festenstein, 2011; Zuo et al., 2015) may account for the modulatory effects of sex. Indeed, in line with this speculation, recent literature highlights sex differences in brain transcriptomes related to schizophrenia and alcohol effects (Hitzemann et al., 2021; Hoffman et al., 2022). Future research may test the association between sex differences in genetic expression in the brain and neurocognitive development.

Note that only females showed a significant correlation between brain-based sex score and cognitive GPSs, whereas males showed a marginally significant correlation after correction for multiple comparisons. We think this should not be interpreted as the female-only effect of the cognitive GPSs in the brain sex development. Rather, it should be noted that their effect sizes were similar across sex (in educational attainment GPS) and the models combining males and females showed the significant correlations of the brain-based sex score and cognitive GPSs (in educational attainment and cognitive performance GPSs). Furthermore, regardless of the modulatory effects of sex, in both females and males, the influence of the cognitive GPSs on cognition was positive. This is in line with the literature in adults (Lee et al., 2018; Savage et al., 2018). Taken together, we think that the genetic underpinnings of cognitive development might be related to sex differentiation in the brain. Therefore, our integrative analysis reveals the subtle relationships among sex, genes, brains, and cognition, otherwise undetectable. We suggest this is a novel biological pathway to individual differences in brain sex. It may be interesting to test whether this pathway is related to epigenetic effects of environmental factors, such as early life stress.

This study confirms that biological sex can be classified accurately based on morphometric and white matter connectivity. A recent study with ABCD data show that the biological sex was classified with 89.6% accuracy in the replication set using a deep neural network trained on ABCD T1-weighted structural MRI (Adeli et al., 2020). Our study extends this prior work by showing the additive classification performance increase with the diffusion white matter connectomes. This performance increase perhaps presents that the multimodal MRI effectively accounts for the heterogeneous developmental trajectories of grey and white matter (Giedd et al., 1999). It further shows the importance of the multimodal MRI approach in accurate delineation of brain development status.

Our brain features exclude the total volumes of the brain, grey and white matter, of which the sex differences have been reported (Ruigrok et al., 2014). Though the whole brain volume difference between sexes may be a biological aspect, we reasoned that the measures of gross anatomy would confound the brain–cognition relationship. Therefore, beyond the sex difference in the gross anatomy, this study shows that the patterns of the grey matter and white matter fibers are associated with the continuum of brain sex.

In testing the relationships among the brain sex, cognitive ability, and the genetic influence on cognitive ability, we focused on the cognitive GPSs. However, our discovery of the significant tripartite correlation among the brain-based sex score, total brain volume, and intelligence may lead to a question whether the genetic underpinning of cognitive ability is related to that of the total brain size. Indeed, a recent GWAS meta-analysis reveals an overlap of GWAS hits between cognitive intelligence and brain size in 5 genomic loci (Jansen et al., 2020). We hope that future research may test the moderation effect of sex on the genetic influence on brain size and its impact on cognitive intelligence.

In our study, we found no significant relationship among our key variables with salivary measures of sex hormones. Given the prepubertal stages of the participants, the negative statistical findings may reflect that the gene–brain sex–cognition relationship is not significantly related to the effects of sex hormones. Literature shows a complex relationship between the level of sex hormones and cognitive intelligence (Castanho et al., 2014; Gurvich, Hoy, Thomas, & Kulkarni, 2018). Though different sex hormonal levels across the sexes are observed from the prepubertal ages (Courant et al., 2010), the actual effect of the sex hormones on cognitive intelligence (or its modulation) may not appear until puberty (Shangguan & Shi, 2009).

This study shows a novel relationship among genetic factors, brain sex, and cognitive intelligence. The link between genome-wide factors and cognitive ability has been shown in previous studies. Cognitive GPSs account for general cognitive ability up to 3.5% in pre-adolescence children (Allegrini et al., 2019), 11% of the variance in general intelligence, and 16% of the variance in educational achievement in adolescents (Selzam et al., 2017). Extending this literature, our study shows that an individual's degree of brain sex may modulate the impact of the genetic factor on cognitive intelligence. Since this modulatory effect is positive toward brain maleness and negative toward brain femaleness, it adds another source of sex and individual variability in intelligence. This inference also presents the benefit of using the brain data as an endophenotype in assessing the genotype–phenotype association (Glahn, Thompson, & Blangero, 2007). Taken together, brain sex is linked to the inherited genetic influence of cognition, accounting for a novel pathway to the individual difference in cognitive intelligence in preadolescence.

In contrast to the multiethnic participants, the SEM in the European-ancestry participants only showed nonsignificant indirect effects of brain sex score. The discrepant results may not be easily reconciled. It should be noted that the cross-ethnic transferability of our cognitive GPS based on the European-ancestry GWAS remains to be validated. However, our cognitive GPS was rigorously adjusted for the potential ethnic confounding. Our result of the significant modulatory effects in the admixed American participants needs to be interpreted with caution.

This study shows the novel relationships among brain sex, cognition, and cognitive GPSs. The brain sex score based on grey matter morphometric and white matter connectivity may represent a neurodevelopmental process in preadolescence related to the inherited genetic influence on cognitive intelligence and unrelated to sex hormonal levels. This study thus provides a novel framework for future research in neurocognitive development and mental disorders.

Hire ambitious people: Bright- and dark-side personality and work engagement

Furnham, A., Robinson, C., & Haakonsen, J. M. F. (2022). Hire ambitious people: Bright- and dark-side personality and work engagement. Journal of Individual Differences, Sep 2022. https://doi.org/10.1027/1614-0001/a000380

Abstract: Is work engagement, like job satisfaction, primarily a function of personality? In total, 397 working adults completed a short, reliable, three-facet model of work engagement, a short IQ test, various self-ratings, a Big Five (bright-side) personality scale, and a measure of the personality disorders (dark-side). Work engagement was related to age, intelligence, positive self-ratings, and all the personality variables. A regression analysis revealed six variables significantly related to total work engagement: sex, age, IQ, ratings of personal ambitiousness, trait Neuroticism and Cluster A personality disorders. Regressions onto each of the three facets of work engagement showed slightly different findings, yet in each, older people with lower Cluster A scores and who rated themselves as ambitious scored higher on all facets. Over a third of the variance was explained in each regression. In every analysis, the rating of ambitiousness was most strongly related to work engagement. Implications and limitations are acknowledged.


The current findings provide support for mild but robust cognitive dysfunction in first-degree relatives of late-onset Alzheimer's disease affected individuals

Cognitive Functioning of Unaffected First-degree Relatives of Individuals With Late-onset Alzheimer's Disease: A Systematic Literature Review and Meta-analysis. Ari Alex Ramos, Noelia Galiano-Castillo & Liana Machado. Neuropsychology Review, Sep 3 2022. https://rd.springer.com/article/10.1007/s11065-022-09555-2

Abstract: First-degree relatives of individuals with late-onset Alzheimer's disease (LOAD) are at increased risk for developing dementia, yet the associations between family history of LOAD and cognitive dysfunction remain unclear. In this quantitative review, we provide the first meta-analysis on the cognitive profile of unaffected first-degree blood relatives of LOAD-affected individuals compared to controls without a family history of LOAD. A systematic literature search was conducted in PsycINFO, PubMed /MEDLINE, and Scopus. We fitted a three-level structural equation modeling meta-analysis to control for non-independent effect sizes. Heterogeneity and risk of publication bias were also investigated. Thirty-four studies enabled us to estimate 218 effect sizes across several cognitive domains. Overall, first-degree relatives (n = 4,086, mean age = 57.40, SD = 4.71) showed significantly inferior cognitive performance (Hedges’ g = -0.16; 95% CI, -0.25 to -0.08; p < .001) compared to controls (n = 2,388, mean age = 58.43, SD = 5.69). Specifically, controls outperformed first-degree relatives in language, visuospatial and verbal long-term memory, executive functions, verbal short-term memory, and verbal IQ. Among the first-degree relatives, APOE ɛ4 carriership was associated with more significant dysfunction in cognition (g = -0.24; 95% CI, -0.38 to -0.11; p < .001) compared to non-carriers (g = -0.14; 95% CI, -0.28 to -0.01; p = .04). Cognitive test type was significantly associated with between-group differences, accounting for 65% (R23 = .6499) of the effect size heterogeneity in the fitted regression model. No evidence of publication bias was found. The current findings provide support for mild but robust cognitive dysfunction in first-degree relatives of LOAD-affected individuals that appears to be moderated by cognitive domain, cognitive test type, and APOE ɛ4.

Discussion

To our knowledge, this is the first meta-analysis to quantify the impact of family history of LOAD on cognition, summarizing 218 effect sizes from 34 empirical studies. The results provide compelling evidence that first-degree relatives show a mild but robust amount of overall cognitive dysfunction compared to controls without LOAD-affected relatives. Cognitive deficits in first-degree relatives were evident in executive functions, language, verbal IQ, verbal and visuospatial LTM, and verbal STM or IM. These outcomes indicate that, compared to controls without a family history of LOAD, first-degree relatives have higher chances of obtaining lower scores on neuropsychological measures across multiple cognitive domains. One plausible explanation for these findings relates to altered biomarkers in probands of LOAD-affected individuals. For instance, previous studies have indicated that unaffected offspring of individuals with LOAD show morphological and metabolic brain changes that resemble the preclinical manifestations of LOAD-related pathology (Dubois et al., 2016), including increased global brain atrophy rates (Debette et al., 2009), reduced medial temporal lobe activation (Donix et al., 2010; Johnson et al., 2006), higher levels of beta-amyloid deposition (Clark et al., 2016; Duarte-Abritta et al., 2018), and decreased gray matter volume (Berti et al., 2011; Honea et al., 2010). On the other hand, the lack of significant group differences in premorbid intelligence and visuospatial STM or IM, and especially the near null effects in performance IQ and visual perception, suggest that having a family history of LOAD does not seem to be associated with significant decline in these domains. Alternatively, first-degree relatives may exhibit distinct patterns of cognitive dysfunction related to phenotypic differences in LOAD (Carrasquillo et al., 2014; Ferreira et al., 2020; Snowden et al., 2007; Vogel et al., 2021). For example, recent research indicated that the limbic-predominant phenotype is strongly associated with the amnestic presentation of the disease (e.g., LTM dysfunction), whereas the posterior phenotype is characterized by visuospatial or perceptual abnormalities (Vogel et al., 2021).

Notably, subgroup analyses revealed that the APOE ɛ4 genotype moderates performance differences between first-degree relatives and controls without a family history of LOAD, which makes sense given that the APOE ɛ4 genotype is the most replicated risk factor for LOAD in genetics studies (Cacabelos, 2003; Yang et al., 2021). Specifically, relative groups documented as ɛ4 carriers exhibited more significant dysfunction in cognition (g = -0.24) compared to relative groups documented as non-ɛ4 carriers (g = -0.14). This finding is consistent with preliminary research (Debette et al., 2009; Tsai et al., 2021) demonstrating that first-degree relatives with both risk factors (APOE ɛ4 genotype and a family history of LOAD) are more likely to present with deficits in cognition (e.g., executive dysfunction and verbal and visuospatial LTM difficulties). Evidence also suggests that first-degree relatives with both risk factors exhibit greater beta-amyloid deposition (Yi et al., 2018), higher brain atrophy rates (Debette et al., 2009), and reduced gray matter volume (Ten Kate et al., 2016) compared to those with only one risk factor. Nevertheless, the current systematic synthesis revealed that few studies on the topic document separate scores for ɛ4 carriers verses non-carriers. Hence, the lack of control for APOE ɛ4 status might help account for the contradictory findings from empirical studies on cognition of first-degree relatives of LOAD-affected individuals previously noted in the introduction, and if factored in to analyses of cognitive domains, could potentially paint a different picture with regard to the domains that did not reach statistical significance. Moving forward from the current outcomes, a major challenge for future research on the topic is to determine the combined effects and parse out the unique contributions of APOE ɛ4 carriership and a family history of LOAD in profiling cognitive dysfunction in first-degree relatives. Importantly, the APOE ε4 effect on cognition reported here is based on a specific sample (first-degree relatives of LOAD-affected individuals) and hence our results do not apply to the general population of APOE ε4 carriers.

Although relative group mean age was not a significant moderator and the null hypothesis on the equality of effect sizes in the subgroup analysis on age category was not rejected, the dysfunction effect size for samples intermixing middle-aged (40–65 years) and older (> 65 years) first-degree relatives (g = -0.23, 95% CI [-0.37, -0.09], p = 0.002) was statistically significant and nearly twice the size of the dysfunction effect for samples including only middle-aged individuals (g = -0.12, 95% CI [-0.26, 0.02], p = 0.081). This suggests that the inclusion of a large percentage of middle-aged individuals in the studies analyzed here may have led to an overall smaller dysfunction effect size (g = -0.16, 95% CI [-0.25, -0.08], p < 0.001) than might be expected in older cohorts, thus calling into question the generalizability of the current findings. This conjecture seems in line with findings from a previous study noted in the introduction (Zeng et al., 2013), in which, compared to controls, family members of LOAD-affected individuals showed substantial differences on neuropsychological measures only quite late in life (70 or more years).

The effects of a family history of LOAD on cognition remain poorly understood. Cognitive dysfunction in first-degree relatives of AD-affected individuals has gained attention only in the last two decades. Figure 2 shows that out of 34 empirical works, only three studies (Green & Levey, 1999; La Rue et al., 19951996) were published before the current century, and all of the studies were published within the past 30 years. As previously noted, LOAD-related neuropathological changes precede the clinical diagnosis of LOAD by many years, hence, an increasing number of studies has attempted to longitudinally follow cognitive changes and brain abnormalities in earlier first-degree relatives. In this meta-analytic review, some included studies were drawn from ongoing prospective studies, thus, follow-up research on these cohorts as they grow older is expected. This will allow investigation of cognitive dysfunction in older cohorts of first-degree relatives with a family history of LOAD.


Implications

Findings from the current quantitative review may have important clinical and theoretical implications. LOAD is an age-dependent dementing disease with cognitive symptoms that appear after a lengthy period of evolving neuropathophysiological abnormalities, and thus the effect sizes for between-group differences in several cognitive domains reported here may assist in establishing sensitive cognitive markers for first-degree relatives. This assertion builds on previous empirical research indicating that impairments in cognitive abilities such as premorbid intelligence, memory, and language are deemed potential markers for future development of LOAD (Blacker et al., 2007; Chen et al., 2000; Rapp & Reischies, 2005; Yeo et al., 2011). Equally important, executive dysfunction can be detected in middle-aged offspring many years before the affected parent develops dementia (Debette et al., 2009; Eyigoz et al., 2020). Hence, developing cognitive-based interventions for first-degree relatives, especially APOE ɛ4 carriers, is a pressing need. In relation to this, recent randomized controlled trials have shown that cognitive training benefits individuals at the early stages of LOAD (Cavallo et al., 2016; Kang et al., 2019; Lee et al., 2013). To our knowledge, however, no study has addressed the potential benefit of such a therapeutic strategy in buffering against cognitive decline in unaffected first-degree relatives of LOAD-affected individuals.