Friday, December 17, 2021

The greater male variability in personality (boldness, aggression, activity, sociality and exploration) cannot be found in 220 species examined

A meta-analysis of sex differences in animal personality: no evidence for the greater male variability hypothesis. Lauren M. Harrison,Daniel W. A. Noble,Michael D. Jennions. Biological Reviews, December 14 2021. https://doi.org/10.1111/brv.12818

Abstract: The notion that men are more variable than women has become embedded into scientific thinking. For mental traits like personality, greater male variability has been partly attributed to biology, underpinned by claims that there is generally greater variation among males than females in non-human animals due to stronger sexual selection on males. However, evidence for greater male variability is limited to morphological traits, and there is little information regarding sex differences in personality-like behaviours for non-human animals. Here, we meta-analysed sex differences in means and variances for over 2100 effects (204 studies) from 220 species (covering five broad taxonomic groups) across five personality traits: boldness, aggression, activity, sociality and exploration. We also tested if sexual size dimorphism, a proxy for sex-specific sexual selection, explains variation in the magnitude of sex differences in personality. We found no significant differences in personality between the sexes. In addition, sexual size dimorphism did not explain variation in the magnitude of the observed sex differences in the mean or variance in personality for any taxonomic group. In sum, we find no evidence for widespread sex differences in variability in non-human animal personality.


Pupil Size Predicts Partner Choices in Online Dating

Pupil Size Predicts Partner Choices in Online Dating. Tila M. Pronk, Rebecca I. Bogaers, Mara S. Verheijen and Willem W. A. Sleegers. Social Cognition, Vol. 39, No. 6, December 2021. https://doi.org/10.1521/soco.2021.39.6.773

Abstract: People's choices for specific romantic partners can have far reaching consequences, but very little is known about the process of partner selection. In the current study, we tested whether a measure of physiological arousal, pupillometry (i.e., changes in pupil size), can predict partner choices in an online dating setting. A total of 239 heterosexual participants took part in an online dating task in which they accepted or rejected hypothetical potential partners, while pupil size response was registered using an eye tracker. In line with our main hypothesis, the results indicated a positive association between pupil size and partner acceptance. This association was not found to depend on relationship status, relationship quality, gender, or sociosexual orientation. These findings show that the body (i.e., the pupils) provides an automatic cue of whether a potential partner will be selected as a mate, or rejected.


AI processing of fMRI data knows with a 94+ pct accuracy when are the subjects seeing sexual images

The Brain Activation-Based Sexual Image Classifier (BASIC): A Sensitive and Specific fMRI Activity Pattern for Sexual Image Processing. Sophie R van ’t Hof, Lukas Van Oudenhove, Erick Janssen, Sanja Klein, Marianne C Reddan, Philip A Kragel, Rudolf Stark, Tor D Wager. Cerebral Cortex, bhab397, December 16 2021. https://doi.org/10.1093/cercor/bhab397

Abstract: Previous studies suggest there is a complex relationship between sexual and general affective stimulus processing, which varies across individuals and situations. We examined whether sexual and general affective processing can be distinguished at the brain level. In addition, we explored to what degree possible distinctions are generalizable across individuals and different types of sexual stimuli, and whether they are limited to the engagement of lower-level processes, such as the detection of visual features. Data on sexual images, nonsexual positive and negative images, and neutral images from Wehrum et al. (2013) (N = 100) were reanalyzed using multivariate support vector machine models to create the brain activation-based sexual image classifier (BASIC) model. This model was tested for sensitivity, specificity, and generalizability in cross-validation (N = 100) and an independent test cohort (N = 18; Kragel et al. 2019). The BASIC model showed highly accurate performance (94–100%) in classifying sexual versus neutral or nonsexual affective images in both datasets with forced choice tests. Virtual lesions and tests of individual large-scale networks (e.g., visual or attention networks) show that individual networks are neither necessary nor sufficient to classify sexual versus nonsexual stimulus processing. Thus, responses to sexual images are distributed across brain systems.

Keywords: erotic images, machine learning prediction model, multivariate analysis, neuroimaging, sexual stimuli processing, support vector machine classification

Discussion

Sexual stimulus processing is a core component of human affective and motivational systems, and part of a fundamental repertoire of motivations conserved across nearly all animal species. Previous work using sexual stimuli has made important advances (e.g., Georgiadis et al. 2006Walter et al. 2008bAbler et al. 2013Borg et al. 2014Stark et al. 2019), but these studies have generally included small sample sizes and have focused on characterizing responses in individual brain regions using standard brain-mapping approaches. Findings have been variable across studies (for meta-analyses, see Stoléru et al. 2012Poeppl et al. 2016), and it remained unclear whether brain responses to sexual stimuli are robustly and reproducibly different from responses to nonsexual positive or negative affective stimuli.

Here, we employed a multivariate predictive model grounded in population-coding concepts in neuroscience (Pouget et al. 2000Shadlen and Kiani 2007Kragel et al. 2018) and systems-level characterization, based on growing evidence that various psychological processes are grounded in distributed networks rather than local regions or isolated circuits (Kamitani and Tong 2005Kuhl et al. 2012Arbabshirani et al. 2017). We identified a generalizable pattern of brain responses to sexual stimuli whose organization is conserved across individual participants, but which is distinct from responses to other conceptually related (nonsexual) affective images. We used cross-validated machine learning analyses to identify a brain model, which we termed the BASIC model (for purposes of sharing and reuse), that can classify sexual from neutral, positive, and negative affective images with nearly perfect accuracy in forced-choice tests, including an independent validation cohort tested on a different population (US vs. Europe), scanner, and stimulus set from those used to develop the model. Together with previous smaller-sample analyses that differentiate multivariate brain responses to romantic or sexual stimuli from responses to other types of affective and emotional events (Kassam et al. 2013Kragel et al. 2019), our results suggest that sexual stimuli are represented by a relatively unique brain “signature” that is not shared by other types of affective stimuli.

Furthermore, our virtual lesion analysis suggests that the classifications of sexual versus neutral/affective conditions are not solely due to differences in visual or attention processing, as predictions are intact even leaving out large-scale cortical networks devoted to attention and vision. In addition, the spatial scale evaluation demonstrates that whole-brain level classification (both voxel- and parcel-wise) shows the highest model performance compared with individual large-scale network parcels. The BASIC model shows effects not only in subcortical but also in cortical areas, in line with previous human (for meta-analyses, see Stoléru et al. 2012Poeppl et al. 2016) and animal research (for meta-analysis, see Pfaus 2009). From a basic biological perspective, this might be surprising. Evolutionarily relevant key features of sexual signals in nonhuman primates may include sex calls, pheromones, and the presentation of genitals. The sexual signals presented here are, in comparison, highly complex visual scenes containing a variety of sexual content, triggering valuation processes accompanied by neural activity on the cortical level. Even though our and previous research shows strong evidence for large cortical involvement, there still seems to be a bias in picking brain areas for region of interest (ROI) analyses toward subcortical regions. This is reflected in the neurosynth “sexual” brain map, based on an automated meta-analysis that includes coordinates from a priori ROI analyses. For example, the study with the highest loading on the term “sexual” in neurosynth (Strahler et al. 2018) used ROI analyses that included almost exclusively subcortical areas.

Many types of validation are beyond the scope of this study, but we were able to provide validation of several key elements. First is the application to a new cohort with different population characteristics, equipment, and paradigm details, with large effect sizes for sexual versus nonsexual affective images. Second, we investigated the effects of globally distributed signal in white matter and ventricle spaces, which can capture complex effects of head movement and task-correlated physiological noise and have been found to drive some multivariate predictive models in the past. Lack of relationships with these non–gray matter areas, along with significant contributions to the model in known affective/motivational systems, increases confidence that the model is driven by neuroscientific relevant systems. Third, we investigated whether the model showed differential effects for male versus female subgroups or varied with age. It did not, supporting the notion that despite individual differences there is a generalizable brain response across individuals (note, this study did not include nonheterosexual, noncis individuals, and individuals of different age groups). This is in line with the findings of previous neuroimaging meta-analyses that revealed common “unisex” brain responses to sexual stimuli (Poeppl et al. 2016Mitricheva et al. 2019).

Interpretation of a machine learning–based model is complex because the classification is not explained by one region or network, but by a combination across regions. One set of regions may encode one aspect, for example the positive valance aspect, another set may encode the arousal aspect, and yet another set the concept of personal closeness. All these sets then jointly contribute to the overall discrimination of sexual from general affective images. The studies we analyzed do not have sufficient information to link specific brain areas to specific component processes underlying response to sexual images, but we do evaluate our model in light of previous neuroscientific literature here to examine the neurobiological plausibility of the model (Kohoutová et al. 2020).

Brain areas included in the BASIC model are also present in the most recent meta-analytical model of brain responses to sexual stimuli (Stoléru et al. 2012), although the BASIC model presents a more comprehensive and precisely specified set of hypotheses about which voxels, with which relative activity pattern across them, to test and validate in future studies. In terms of resting-state networks (see Fig. 5), we see positive and negative weight effects emerge: negative weights (relative decreases in activity associated with sexual image processing) in somatomotor networks and positive weights (relative increases) in dorsal and ventral attention networks. In addition, weights in the default mode network (DMN) are near-zero when averaging across the entire DMN. However, when looking at default mode subnetworks, DMN A (ventral medial PFC and posterior cingulate areas) shows strong positive weights, whereas DMN C (hippocampal and more posterior occipital areas) shows strong negative weights. This relates to previous research linking DMN to drug, gambling, and food craving and their regulation, which generally involve DMN A regions, and the vmPFC and NAc in particular (Hare et al. 2009Kober et al. 2010Hutcherson et al. 2012Kearney-Ramos et al. 2018Aronson Fischell et al. 2020Schmidt et al. 2020). Both these areas are involved in the BASIC model, in line with previous research linking these areas to sexual stimuli. For instance, previous studies have reported significant vmPFC activation during sexual compared with monetary rewards (Schmidt et al. 2020), and neural reactivity to sexual stimuli in the NAc was positively correlated with sexual arousal ratings (Klein et al. 2020). In addition, activation of both regions to food and sex cues has been found to predict subsequent risky sexual behavior (Demos et al. 2012).

The BASIC model included positive weights (a higher likelihood that the image was sexual with increasing activity) in several additional regions thought to be important for sexual responses: the hypothalamus, amygdala, somatomotor cortices, and insula. The hypothalamus is a small area near the ventricles and sinus spaces, and this likely introduces substantial variability. A preliminary study by Walter et al. (2008b) using ultra high-resolution imaging at 7 T, which is likely to have superior ability to detect hypothalamic activity, found signal dropouts in ventral subcortical structures such as the hypothalamus. Similar dropout may have limited sensitivity in the hypothalamus in this study. However, findings of hypothalamic activation in sexual stimulus processing have varied across studies. The meta-analysis by Stoléru et al. (2012) found that 37.8% of studies reported hypothalamic responses to visual sexual stimuli. A motivational role for hypothalamus is included in the model of Stoléru et al. (2012) as well, although this has only been found in animal studies. Responses of the hypothalamus have been related to the regulation of autonomic responses, and in particular the physiological aspect of sexual arousal (Ferretti et al. 2005). Here, we did not measure genital responses and can therefore not know if the stimuli triggered a physiological response. Further research, including genital response measures, could therefore shed more light on the role of the hypothalamus in sexual behavior.

The amygdala and somatomotor cortices are part of the emotional component of the model of sexual stimuli processing by Stoléru et al. (2012). All these show positive weights in the BASIC model. Within the amygdala, positive weights were found in the corticomedial division, in contrast from emotions more generally, which most often show central nucleus and sometimes basolateral activation (Wager et al. 2008Yarkoni et al. 2010). The insula has previously been reported to sex, food, and drug craving (Pelchat et al. 2004Yokum et al. 2011Murdaugh et al. 2012Tang et al. 2012), as well as interoception (Paulus and Stewart 2014). The insula is, however, large and heterogeneous region. Within the insula, the BASIC model included positive weights in two areas: the right ventral anterior insula and posterior insula PoI2 (from Glasser et al. 2016). The posterior insula is held to be important for somatosensory representations, multisensory information, and pleasant touch (Olausson et al. 2002Cera et al. 2020). The anterior insula seems to play a role in visceral information processing and subjective feelings (Craig 2002Uddin 2015). However, the ventral anterior insula is distinct from the dorsal anterior insula identified in most studies and has stronger associations with ventromedial prefrontal and subcortical structures including the amygdala, and functional associations with emotion and gustation (Chang et al. 2013Wager and Barrett 2017).

In addition, another subcortical region little discussed in the Stoléru et al. (2012) meta-analysis but involved in the BASIC model is the midbrain periaqueductal gray (PAG). The PAG is best-known for its role in pain and defensive behaviors, but animal literature also shows effects of lesions on sexual behavior (Lonstein and Stern 1998), particularly lordosis. Many PAG neurons express estrogen receptors, and areas where these neurons are concentrated are targeted by inputs from the hypothalamus (Bandler and Shipley 1994). This and related pathways through the PAG are thought to be involved in sexual readiness (Holstege and Georgiadis 2004). In humans, nearby areas of the midbrain are activated during male ejaculation (Holstege et al. 2003Georgiadis et al. 2009), though precise localization is difficult, and other studies have related human PAG activity more to bonding than sex (Ortigue et al. 2010).

The overlap of areas in BASIC model with some drug- and food-cue reactivity studies, but not others, suggests that different types of appetitive stimuli and responses may activate dissociable systems in some cases. Exploring these differences in depth is beyond the scope of this study but very interesting for future studies. An interesting next step, for instance, would for example be to test BASIC model on a different set of rewarding stimuli.

Thus, future validation for BASIC model can involve testing it on many other types of stimuli but our work already shows that based on brain data, we can distinguish sexual from general affective processing. Previous research has associated sexual stimuli with positive affect, as the wide use of IAPS, where sexual images are placed under positive affect, indicates. This strong link between positive affect and sexual stimuli might be the result of the assessment method of affect. Most studies have used a bipolar scale (i.e., negative to positive affect/valence) but when using to separate unipolar scales, both positive and negative affect have been reported during sexual stimuli (Peterson and Janssen 2007). Here, we show that the BASIC model has the highest cosine similarity with the sexual condition as expected (see Supplementary Figure 1) but shows more cosine similarity to the negative condition in Study 1 than the positive condition. Hence, in line with previous research, this work therefore demonstrates that the intuitive link between positive affect and sexual stimuli is much more complicated.

In addition to the link between sexual stimuli and general affect, we were able to gain some insight into whether the BASIC model captures general arousal or valence. To examine the role of general arousal and valence in the prediction of BASIC model, we adopted two strategies. First, we measured valence and arousal in Study 1 and performed a sensitivity analysis, testing whether the BASIC model was sensitive to valence and arousal of nonsexual images. Second, we applied the BASIC model to an independent test dataset (Study 2), in which sexual and nonsexual images were matched on valence and arousal. Regarding the first strategy, the self-reported data showed that sexual images had a significantly lower arousal than the negative images, but significantly higher BASIC responses. In addition, positive images had a higher valence than neutral or negative images but did not produce higher BASIC responses. Regarding the second strategy, the BASIC model responded more strongly to sexual than nonsexual images matched on valence and arousal and did not respond to either positively or negatively valenced nonsexual images. In addition, the strong classification performance was replicated in both Study 1 and Study 2 despite differences in the content of sexual images (Study 1 showed explicit sex scenes with couples, whereas Study 2 showed both clothed and naked couples and individuals) and likely general arousal levels. Together, these findings indicate that it is not sensitive to general arousal and valence per se but is instead sensitive to sexual content. This is in line with a previous study by Walter et al. (2008a), demonstrating that during a sexual stimulus, activation patterns modulated by general emotional arousal differed from activation patterns modulated by sexual stimulus intensity.

Sexual stimuli have often been used by researchers to study sexual arousal, although it is unclear if a state of sexual arousal is elicited by short visual sexual stimuli and therefore whether it was present during conditions used in BASIC model. In Study 1, the sexual images consisted of heterosexual couples engaged in sexual interactions, and self-reported sexual arousal was significantly higher in the sexual conditions versus the other conditions. Based on these results, we might suspect that the images, although presented for a short duration, might have induced a certain level of sexual arousal, at least at the subjective self-report level. However, in Study 2, participants were presented not only with couples, but also sexual or romantic images of an individual man or woman. Assuming that not all participants were bisexual, participants were presented with sexual images depicting both individuals consistent and inconsistent with their preferred sex. Thus, even though the images might not have induced high levels of sexual arousal in all participants, we can distinguish sexual from general affective processing in the brain, which was the aim of our study. For future research, it would be interesting to examine whether the BASIC model can also differentiate between longer visual sexual stimuli, whether sexual arousal is more likely to be induced by long than short-duration, and whether the BASIC model responds to sexual stimuli of other modalities, for example, sensory (genital stimulation), cognitive (fantasy), or auditory.

Ponseti et al. (2012) conducted one of the few studies on sexual stimulus processing that used multivariate analysis. They classified preferred and nonpreferred (e.g., child nudity vs. adult nudity) sexual stimuli based on brain data in participants with and without pedophilia using nude frontal images of adults and children. This classification might be more linked to sexual arousal, although it is still hard to evaluate whether sexual arousal was induced. In order to gain additional insight into sexual arousal specifically, future research could examine if sexual arousal is elicited during sexual image presentation, and to identify the brain processes generating it, multivariate analysis could be used to predict sexual arousal ratings based on brain data collected during sexual image presentation. In our study, this was not possible due to a lack of within-subject variability in the sexual arousal ratings during the sexual image blocks. Parada et al. (2016) presents large variability of sexual arousal ratings and, using a parametric modulation analysis, found various subregions of the parietal cortex that showed significant changes in activation corresponding to the degree of self-reported sexual arousal with no gender differences. Future studies could further examine role of the parietal cortex in the subjective experience of sexual arousal.

Besides self-reported sexual arousal, genital responses are often assessed in psychophysiological studies to examine sexual arousal (Rosen and Beck 1988Janssen and Prause 2016). The assessment of genital response in neuroimaging studies is sparse (Arnow et al. 2009Parada et al. 2018). Parada et al. (2018) presents several brain regions (supramarginal gyri, frontal pole, lateral occipital cortex, and middle frontal gyri in men; same regions plus the ACC/PCC, right cerebellum, insula, frontal operculum, and paracingulate gyrus) to be correlated with changes in genital response, with a stronger brain–genital relation in women compared with men in several regions. Assessment of genital response during fMRI research could improve our understanding of the interaction between brain and genital and the gender differences between this interaction. In addition, multivariate analysis could be used to predict genital arousal levels and self-reported sexual arousal based on brain data, and these patterns could be compared. This type of study design would allow for a mediation analysis, which could give more insight into the brain organization by examining the distributed, network-level patterns that mediate the stimulus intensity effects on sexual arousal (Geuter et al. 2020).

A limitation of this study is that although the BASIC model can accurately classify sexual and nonsexual images with forced choice tests, we did not identify one absolute threshold that could be used as a quantitative measure across studies. Future studies thus have to establish a threshold in a study-specific manner and make relative comparisons across conditions within-study, which is a limitation. However, we do show that the BASIC model can be generalized to individuals studied in other research centers with forced choice tests, though the absolute scale of the response is likely to vary across studies as a function of scanner field strength, signal-to-noise ratio, and other signal properties.

To summarize, in this study, we applied multivariate neuroimaging analyses to investigate sexual stimulus processing in the brain. This approach allowed for the development of the BASIC model, which can accurately classify sexual versus neutral and positive and negative affective images in two separate datasets, consisting of different types of sexual stimuli and individuals. The BASIC model includes a precisely specified pattern of cortical and subcortical areas, some of which have received relatively little attention in the literature on human sexual responses (e.g., cortical networks). Some may be shared across other appetitive responses (e.g., vmPFC and NAc for drug cues), but the BASIC model may also diverge from studies of other appetitive responses as well (e.g., in the insula). The work gives insight into the complex processing of sexual stimuli and supports the notion that processing sexual stimuli is a neurologically complex, potentially unique mental event that involves multiple networks distributed in the brain. There are many avenues open for future validation and further development, such as testing the BASIC model to nonsexual rewarding stimuli or sexual stimuli of other modalities, and linking the work to sexual arousal.

Thursday, December 16, 2021

Surprisingly, we found change in national personality traits after the onset of the COVID-19 pandemic, specifically increases in trait Extraversion and associated narrow traits (e.g., Sociability, Humor, and Sensation Seeking)

Personality States of the Union. David M. Condon, Sara J. Weston. Collabra: Psychology (2021) 7 (1): 30140. Dec 2021. https://doi.org/10.1525/collabra.30140

Fluctuations in the average daily personality of the United States capture both meaningful affective responses to world events (e.g., changes in anxiety or well-being) and broader psychological responses. We estimate the change in national personality in the months following the onset of the COVID-19 pandemic and investigate fluctuations in personality states during the year 2020 using data from an ongoing personality assessment project. We find significant and meaningful change in personality traits since the beginning of the pandemic, as well as evidence of instability in personality states. When evaluating changes from the first few months of 2020 to the period of social distancing related to COVID-19 restrictions, the social traits reflected an unexpected “deprivation” effect such that mean self-ratings increased in the wake of restricted opportunities for social interaction. Changes in mean levels of the affective traits were not significant over the same months, but they did differ significantly from the average levels of prior years when looking at shorter time intervals (rolling 7-day averages) around prominent national events. This instability may reflect meaningful fluctuations in national personality, as we find that daily personality states are associated with other indices of national health, including daily COVID-19 cases and the S&P index. Overall, the use of personality measures to capture responses to global events offers a more holistic picture of the U.S. psyche and of personality change at the national level.

Keywords:personality, states, traits, personality change

In summary, the present research found evidence for change in national personality traits after the onset of the COVID-19 pandemic, specifically increases in trait Extraversion and associated narrow traits (e.g., Sociability, Humor, and Sensation Seeking). Fluctuations in social traits were also associated with increased numbers of new daily COVID-19 cases and drops in the S&P500, suggesting that these changes and fluctuations in national personality are connected with larger psychological processes that impact both daily lives and long-term outcomes for the country. There was no supporting evidence that these changes were driven by annual or seasonal changes. While it remains a possibility that some or all of this change was driven by a shift in sampling characteristics (i.e., lockdowns increased the likelihood that more extraverted individuals participated in the survey because they could no longer socialize), other changes during the lockdown period suggest that more substantive factors were involved. These changes include increases in Art Appreciation, Compassion, and Emotional Expressiveness, and decreases in Emotional Stability and Authoritarianism. Changes in these traits are less readily explained by shifts in participant sampling than the circumstantial factors of pandemic-induced restrictions and suffering.

Mean-level increases in affective traits (e.g., Neuroticism) were not found, but analysis of personality state dynamics revealed substantial instability in daily national state Neuroticism and related traits, such as Well-Being, Anxiety, and Irritability. These fluctuations are meaningful (i.e., not simple sampling error), as evidenced by their substantial correlations with other national indices, though challenging to interpret with respect to personality theory. One explanation is methodological. Consistent with recognition that affective traits are more labile than other personality traits (Gross et al., 1998), the appropriate time frame for assessing change in these traits is likely distinction from the months-long window used to compare trends before and after the lockdown.

These findings shed light on another methodological issue as well. Unlike short-term fluctuations in the affective traits, mean-level changes in social traits during the lockdown run counter to expectations based on the behavioral or “act frequency” conception of traits (Buss & Craik, 1983). Mean self-ratings increased due to the deprivation of opportunities to engage in social behaviors, whether due to a change in the make-up of respondents and/or increased self-appraisals of social tendencies. This highlights the merits of informant-reports with respect to convergent validity. The use of national indices of personality traits for tracking changes over time (Baugh et al., 2021) would be substantially improved by the inclusion of informant-reports as a means of distinguishing these deprivation effects from changes in behavioral frequency. The collection of informant-reports should be prioritized in subsequent research on changes in personality at the national level.

This study adds to the growing literature on regional personality (Rentfrow et al., 2008), especially national personality, by being among the first to consider how national personality changes over short intervals and in response to a significant global crisis. Our work points to the utility of measures of narrow traits in this field, as the narrow and unidimensional state fluctuations were those most highly correlated with daily national outcomes. Future research should examine the associations of daily fluctuations in national personality with other metrics of import to economists, public health advisors, and others who work in policy, to understand the psychological underpinnings of these outcomes. Moreover, additional work should seek to model the underlying causal processes; it remains unknown whether fluctuations in traits cause these outcomes or are reflections of other processes.

Changes and fluctuations in Humor speak to the possibility of the bidirectional processes. We propose that changes in traits provide insight into how a nation chooses to react to emergencies. Humor is used to facilitate interpersonal relationships (Ziv, 2010); compare the relatively higher levels of humor during the spring of 2020 to the low levels in the fall and winter. Humor rose when the nation faced an emergency that was perceived to affect all its citizens. It can be argued that no person’s life was untouched by the pandemic, at least in terms of day-to-day routines. However, as the summer approached, it became apparent that all citizens were not affected equally. By the time of the presidential election, American citizens were no longer fighting a pandemic together, but fighting each other for control of the federal government. Correspondingly, Humor – and attempts to build community – plummeted.

The current study only examines change through December 31, so a remaining question is the extent to which the observed changes in national personality are lasting. However, regardless of the long-term impact on personality, even short-term changes in these traits may have substantial impact on national outcomes, given the associations between daily fluctuations and other indices. Especially if there is evidence that some personality states cause outcomes (rather than the other way around), even changes lasting a week or only a few days could have repercussions lasting months or years. For example, it was notable to see no change in affective traits (Neuroticism, Anxiety, etcetera) over longer intervals, but to see substantial short-term instability in these traits and strong associations with national indices of health.

Statistical power in this study was limited by the length of data collection (Ndays = 366 days in 2020), despite the large number of participants who provided data. While greater statistical power could be achieved by widening the time frame, we believe that days outside this time period constitute a different population from the days of interest to this study, at least with regard to historical years. The year 2020 was a unique time in the nation’s history, with major news related to (1) the COVID-19 pandemic, the national emergency, and state-ordered lockdowns, (2) social unrest and injustice, and (3) a major political election in which a sitting president refused to support a peaceful transfer of power. While the United States has been troubled by public health, political, and civil emergencies in the past, we cannot think of a time when we have grappled with all three simultaneously. Moreover, the Internet and social media have connected the average citizen to these issues with more regularity and intimacy than ever before. With that in mind, we do not view the current study as an attempt to find the definitive and context-independent associations between personality fluctuations and outcomes, but rather a demonstration that change and fluctuations in nation-level personality are meaningful, informative, and worthy of consideration by researchers and policymakers alike.

Importantly, the cross-sectional design of the current work is a significant limitation. Given this design, we cannot make strong claims about personality change within individuals, nor can we say definitively that the findings herein are not driven by a shift in sampling characteristics during this period. To do so would require either large-scale longitudinal data collection with high frequency assessments or, in cross-sectional data, carefully randomized sampling of participants to reduce the potential of bias due to “opt-in” participation.

While much attention has been paid to the well-being of the nation during the COVID-19 pandemic, the present research points to the importance and utility of national personality as a focus of study. Our findings suggest that national personality is impermanent, and that fluctuations in personality states are meaningfully linked to important outcomes. Future research may be able to harness this information for better understanding of national health and psychology-informed policy intervention

Experience-expectant plasticity: Experiences at a specific developmental stage trigger major and rapid neurobiological changes that are difficult to reverse, as those responses are thought to occur only when dealing with species-typical conditions

What is the expected human childhood? Insights from evolutionary anthropology. Willem E. Frankenhuis and Dorsa Amir. Development and Psychopathology (2021), 1–25, Dec 2021. https://doi.org/10.1017/S0954579421001401

Abstract: In psychological research, there are often assumptions about the conditions that children expect to encounter during their development. These assumptions shape prevailing ideas about the experiences that children are capable of adjusting to, and whether their responses are viewed as impairments or adaptations. Specifically, the expected childhood is often depicted as nurturing and safe, and characterized by high levels of caregiver investment. Here, we synthesize evidence from history, anthropology, and primatology to challenge this view. We integrate the findings of systematic reviews, meta-analyses, and cross-cultural investigations on three forms of threat (infanticide, violent conflict, and predation) and three forms of deprivation (social, cognitive, and nutritional) that children have faced throughout human evolution. Our results show that mean levels of threat and deprivation were higher than is typical in industrialized societies, and that our species has experienced much variation in the levels of these adversities across space and time. These conditions likely favored a high degree of phenotypic plasticity, or the ability to tailor development to different conditions. This body of evidence has implications for recognizing developmental adaptations to adversity, for cultural variation in responses to adverse experiences, and for definitions of adversity and deprivation as deviation from the expected human childhood.

Keywords: dimensions of adversity; expected childhood; human evolution; deprivation; threat

5. Associations between dimensions of adversity
We have argued that, over evolutionary time, human infants and children have on average been exposed to higher levels of threat and nutritional deprivation than is typical in industrialized societies, and that because these levels were variable over time and space, natural selection has likely favored phenotypic plasticity. In this section, we explore the co-occurrence of different forms of adversities within lifetimes during human evolution. Were individuals who were exposed to higher levels of threat also exposed to higher levels of deprivation and vice versa?

What do we know about adversity co-occurrence?
In contemporary industrialized (WEIRD) societies, correlations between different forms of adversity are consistently small to moderate (Dong et al., 2004; Finkelhor et al., 2007; Green et al., 2010; Matsumoto et al., 2020; McLaughlin et al., 2012; McLaughlin et al., 2021; Smith & Pollak, 2021a), though which forms of adversity cluster together is inconsistent across studies (Jacobs et al., 2012). The existence of correlations among forms of adversity is not surprising. For instance, receiving lower levels of parental investment implies being less protected, thus increasing vulnerability to threats (Callaghan & Tottenham, 2016; Hanson & Nacewicz, 2021); and, low-quality nutrition increases vulnerability to infectious disease (Katona & Katona-Apte, 2008). Consistent with such dependencies are findings showing that children who experience energy sufficiency but receive low levels of parental care tend to mature faster and toward more adult-like functioning in physiological and neurobiological processes related to fear and stress (Callaghan & Tottenham, 2016; Gee et al., 2013; Gee, 2020; Tooley et al., 2021; see also Belsky et al., 1991; Ellis et al., 2009). Recent evidence suggests that such reprioritization may even be passed down to subsequent generations. For instance, babies of mothers who experienced neglect as children might become predisposed to detecting threat in their environment (Hendrix et al., 2020). It is tempting to speculate that natural selection favored this developmental response – which takes one form of adversity (neglect) as input to adapt to another (threat) – because deprivation and threat were correlated in human evolution.
Nonetheless, we urge researchers to be cautious. First, a meta-analysis and systematic review shows that exposure to threat (e.g., violence) is associated with accelerated maturation in humans, whereas exposure to deprivation (e.g., neglect) is not (Colich et al., 2020). Second, there is evidence suggesting that correlations between threat and deprivation do not generalize across primates. For instance, in a longitudinal study of wild baboons, the correlations between different forms of adversity were weak or even absent (Snyder-Mackler et al., 2020; Tung et al., 2016). Third, the evidence basis on correlations between different forms of adversity in both historical and contemporary non-WEIRD societies is too limited to afford confident conclusions. Fourth, because human social organization and provisioning systems are highly flexible, our species may have evolved sensitivity to a broader range of social cues than other primates (Kuzawa & Bragg, 2012), and the correlations between such cues and forms of adversity likely varied by cultural context (see Section 6).

Genes, environment, and the gene–environment correlation all contribute significantly to sociopolitical attitudes; largest genetic effects for religiousness & social liberalism, largest influence of parental environment was for political orientation & egalitarianism

Parent Contributions to the Development of Political Attitudes in Adoptive and Biological Families. Emily A. Willoughby et al. Psychological Science, November 18, 2021. https://doi.org/10.1177/09567976211021844

Abstract: Where do our political attitudes originate? Although early research attributed the formation of such beliefs to parent and peer socialization, genetically sensitive designs later clarified the substantial role of genes in the development of sociopolitical attitudes. However, it has remained unclear whether parental influence on offspring attitudes persists beyond adolescence. In a unique sample of 394 adoptive and biological families with offspring more than 30 years old, biometric modeling revealed significant evidence for genetic and nongenetic transmission from both parents for the majority of seven political-attitude phenotypes. We found the largest genetic effects for religiousness and social liberalism, whereas the largest influence of parental environment was seen for political orientation and egalitarianism. Together, these findings indicate that genes, environment, and the gene–environment correlation all contribute significantly to sociopolitical attitudes held in adulthood, and the etiology and development of those attitudes may be more important than ever in today’s rapidly changing sociopolitical landscape.

Keywords: political attitudes, adoption, behavioral genetics, environment, open data, open materials, preregistered


Wednesday, December 15, 2021

People’s perceptions of their partner’s sexual goals were indeed accurate, but that accuracy was not associated with relationship quality or sexual satisfaction for the perceiver or their partner

Accuracy in perceptions of a partner’s sexual goals. Norhan Elsaadawy et al. Journal of Social and Personal Relationships, December 11, 2021. https://doi.org/10.1177/02654075211051788

Abstract: Intimate partners engage in sex for a variety of reasons, and their perceptions of each other’s sexual goals play an important role in intimate relationships. How accurate are these perceptions of a partner’s sexual goals and is accuracy associated with relationship quality and sexual satisfaction for the couple? To answer these questions, we conducted a 21-day dyadic daily experience study of 121 couples, which we analyzed using two different approaches to examine accuracy: the profile approach and the Truth and Bias Model. Results from these two approaches demonstrated that people’s perceptions of their partner’s sexual goals were indeed accurate, but that accuracy was not associated with relationship quality or sexual satisfaction for the perceiver or their partner. Rather, perceiving a partner’s sexual goals in normative (or socially desirable) ways was associated with relationship quality and sexual satisfaction for both the perceiver and their partner. Implications of these findings are discussed.

Keywords: accuracy, sexual goals, intimate relationships, romantic relationships, partner perceptions, dyadic daily experience


There is evidence for the efficacy and effectiveness of digital interventions for the treatment of depression for a variety of populations; however, reported effect sizes may be exaggerated because of publication bias

Moshe, I., Terhorst, Y., Philippi, P., Domhardt, M., Cuijpers, P., Cristea, I., Pulkki-Råback, L., Baumeister, H., & Sander, L. B. (2021). Digital interventions for the treatment of depression: A meta-analytic review. Psychological Bulletin, 147(8), 749–786. https://doi.org/10.1037/bul0000334

Abstract: The high global prevalence of depression, together with the recent acceleration of remote care owing to the COVID-19 pandemic, has prompted increased interest in the efficacy of digital interventions for the treatment of depression. We provide a summary of the latest evidence base for digital interventions in the treatment of depression based on the largest study sample to date. A systematic literature search identified 83 studies (N = 15,530) that randomly allocated participants to a digital intervention for depression versus an active or inactive control condition. Overall heterogeneity was very high (I2 = 84%). Using a random-effects multilevel metaregression model, we found a significant medium overall effect size of digital interventions compared with all control conditions (g = .52). Subgroup analyses revealed significant differences between interventions and different control conditions (WLC: g = .70; attention: g = .36; TAU: g = .31), significantly higher effect sizes in interventions that involved human therapeutic guidance (g = .63) compared with self-help interventions (g = .34), and significantly lower effect sizes for effectiveness trials (g = .30) compared with efficacy trials (g = .59). We found no significant difference in outcomes between smartphone-based apps and computer- and Internet-based interventions and no significant difference between human-guided digital interventions and face-to-face psychotherapy for depression, although the number of studies in both comparisons was low. Findings from the current meta-analysis provide evidence for the efficacy and effectiveness of digital interventions for the treatment of depression for a variety of populations. However, reported effect sizes may be exaggerated because of publication bias, and compliance with digital interventions outside of highly controlled settings remains a significant challenge


How to Tell the Boss You’re Burned Out (Without Derailing Your Career)

How to Tell the Boss You’re Burned Out (Without Derailing Your Career). By Rachel Feintzeig. The Wall Street Journal, Dec 13 2021. https://www.wsj.com/articles/how-to-tell-the-boss-youre-burned-out-without-derailing-your-career-11639371663

We’re sharing more at work these days, but it can be risky to confess to being overwhelmed. Here’s how and when to speak up.

You’re burned out at work. Does your manager need to know?

[...]

Still, talking about burnout with a boss isn’t the same as talking about it with a friend. Stigma around mental-health challenges is real, psychologists warn. How can you get some breathing room, and back to feeling like yourself, without jeopardizing your career?

You don’t need to share just for the sake of sharing, Dr. Caldwell-Harvey says. “The goal is to share so that you can ask for what you need.”

Assess what it would take to stop feeling overwhelmed, and think about whether you really require permission to get it. Can you attend virtual therapy on Thursday mornings without telling your boss? Do you need a deadline extension, different work hours or a leave of absence? Speak up if you need to, and mention burnout by name if your colleagues seem supportive of diverging viewpoints and mental-health struggles, Dr. Caldwell-Harvey says.

But keep it simple. Your manager isn’t your therapist, she adds.

For all the risk, a lot of positives can come from sharing how you’re really doing—deeper trust with colleagues, permission for others to open up, a nudge away from a pressure-cooker work culture toward something more humane. You could be less miserable, and so could everyone else.

Elizabeth Rosenberg, 42, felt herself approaching burnout a couple of years ago while working for an advertising firm. An earlier bout had landed her in the emergency room, suffering from an intense migraine that left her unable to move. She didn’t want to go back to that. But she worried she’d be perceived as weak or unable to handle her job if she confessed how she was feeling.

She came up with a specific ask: She wanted to take off an entire month. She picked August, when business tended to be slowest, and approached her boss in January, giving him plenty of time to prepare for her absence.

“There was no emotion in it,” she says of how she presented the idea. She told him she was burned out and would have to leave the company later that year if she couldn’t take a break. To her surprise, he said sure.

“If you don’t say something, nothing will change,” says Ms. Rosenberg, who went on to found the Good Advice Company, a marketing and communications consultancy in Los Angeles. “But you have to be brave enough to say something.”

Burnout can feel like a uniquely individual experience, as if you’re the only one who can’t keep pace. But workplace researchers say it isn’t just you.

Employees across industries feel worn down and used up because what they are being asked to do is unrealistic, says Erin Kelly, a professor at the MIT Sloan School of Management and co-author of the book “Overload: How Good Jobs Went Bad and What We Can Do About It.” The backlog of tasks, the lack of resources—it isn’t sustainable for long.

“There had already been a speedup in many jobs before the pandemic, and then we turned up that volume,” she says.

A yoga class or a meditation session isn’t going to fix the problem. Instead, Dr. Kelly’s research examining an overworked IT division at a Fortune 500 firm before the pandemic found that team interventions are what make a difference. Employees whose managers were trained to check in to see how they were doing personally and professionally, and to give them flexibility to work how they wanted, had significantly lower levels of burnout and psychological distress than a control group. They were also 40% less likely to quit.

Another thing that helped: workshops where folks shared their stress and plotted what the team could let go of, like superfluous meetings clogging their calendars.

“Employees reported that they just felt free,” Dr. Kelly says. “It’s going to be easier to approach as a collective project than to stick your own neck out as an individual.”

Anne Ngo started struggling last fall as the second wave of the pandemic hit Toronto, where she lives. Isolated in her apartment, working 12-hour days, she began having anxiety attacks, difficulty sleeping and back and shoulder pain. Demand at her job as a recruiter at Ada, which provides clients with AI chat bots, had come roaring back, and she was tasked with trying to fill 40 to 50 roles a quarter instead of the usual 20.

“I was just one person,” the 33-year-old said. She began to feel like a cog, never really having an impact as colleagues ordered up an ever-increasing number of new hires. Yet the job became her life.

“I just couldn’t shut off,” she says.

She waited until she had hit her goals for the quarter before approaching Chelsea MacDonald, the company’s senior vice president of operations.

“I needed to have leverage of, ‘I did well, but I did well compromising my own well-being, and I don’t think this is ok,’ ” Ms. Ngo says. “I’m pretty sure I just blurted out everything I’d been holding for months.”

Ms. MacDonald says she’s happy Ms. Ngo spoke up. Ms. Ngo started therapy and acupuncture, while Ms. MacDonald talked to other teams to help reduce the demands on her.

“The honest answer is the workload just has to change,” Ms. MacDonald says. Instead of workers suffering, “the business needs to feel a little bit of pain.”

By January, Ms. Ngo had won a promotion and was able to hire for her own team, to spread the load. She sometimes wishes she had said something earlier about her burnout.

Talking about it, she says, “was a relief.”

Men overperceive women's attractiveness, while women underperceive men's attractiveness

Error Management Theory and biased first impressions: How do people perceive potential mates under conditions of uncertainty? David M.G. Lewis et al. Evolution and Human Behavior, December 15 2021. https://doi.org/10.1016/j.evolhumbehav.2021.10.001

Abstract: People must make inferences about a potential mate's desirability based on incomplete information. Under such uncertainty, there are two possible errors: people could overperceive a mate’s desirability, which might lead to regrettable mating behavior, or they could underperceive the mate’s desirability, which might lead to missing a valuable opportunity. How do people balance the risks of these errors, and do men and women respond differently? Based on an analysis of the relative costs of these two types of error, we generated two new hypotheses about biases in initial person perception: the Male Overperception of Attractiveness Bias (MOAB) and the Female Underperception of Attractive Bias (FUAB). Participants (N = 398), who were recruited via social media, an email distribution list, and snowball sampling, rated the attractiveness of unfamiliar opposite-sex targets twice: once from a blurred image, and once from a clear image. By randomizing order of presentation (blurred first vs. clear first), we isolated the unique effects of uncertainty—which was only present when the participant saw the blurred image first. As predicted, men overperceived women's attractiveness, on average. By contrast, as predicted, women underperceived men's attractiveness, on average. Because multiple possible decision rules could produce these effects, the effects do not reveal the algorithm responsible for them. We explicitly addressed this level of analysis by identifying multiple candidate algorithms and testing the divergent predictions they yield. This suggested the existence of more nuanced biases: men overperceived the attractiveness of unattractive (but not attractive) women, whereas women underperceived the attractiveness of attractive (but not unattractive) men. These findings highlight the importance of incorporating algorithm in analyses of cognitive biases.

Keywords: Error Management TheoryCognitive biasesHuman matingPerson perceptionAlgorithmLevels of analysis