Sunday, July 24, 2022

Rolf Degen summarizing... Borderline personality disorder has become a kind of fetish diagnosis in the world of psychotherapy, but it is as intangible as a soap bubble

Gutiérrez, F., Aluja, A., Ruiz Rodríguez, J., Peri, J. M., Gárriz, M., Garcia, L. F., Sorrel, M. A., Sureda, B., Vall, G., Ferrer, M., & Calvo, N. (2022). Borderline, where are you? A psychometric approach to the personality domains in the International Classification of Diseases, 11th Revision (ICD-11). Personality Disorders: Theory, Research, and Treatment, Jul 2022.

Abstract: The inclusion of the borderline pattern in the International Classification of Diseases, 11th Revision (ICD-11) dimensional classification of personality disorders (PDs) has caused controversy. Unease about leaving out these clinically challenging patients seems to conflict with the need of an evidence-based and credible diagnostic system. However, the accommodation of borderline within the new diagnostic system has not yet been studied in depth. To this end, we examine in a sample of 1799 general population and clinical subjects the joint structure of the five initial ICD-11 domains and the borderline pattern. Regression and item-level factor analyses reveal that borderline criteria do not form a separate construct and are indissociable from negative affectivity. Furthermore, borderline adds nothing to the remaining domains when it comes to predict PD severity. The borderline pattern appears as largely superfluous and even misguiding, unless their criteria are properly integrated within the structure of personality pathology. 

Moderate beer consumption and metabolic health: A comprehensive review from the lipoprotein perspective

Moderate beer consumption and metabolic health: A comprehensive review from the lipoprotein perspective. Elena M.Grao-Cruces et al. Journal of Functional Foods, Volume 95, August 2022, 105188.


• Moderate beer consumption modulates cardiovascular health parameters.

• Moderate beer consumption modulates the blood lipid profile.

• Beer components and matrix are essential for its properties.

• It is not clear whether alcohol or phenols are the main responsible of beer effects.

Abstract: Beer intake is part of our society lifestyle but still a controversial topic due to the lack of consensus regarding its effects on our health. Regarding cardiovascular disease, research needs to consider the amount consumed but also drinking thresholds, frequency of drinking, age and gender of consumers, lifestyle, or non-alcoholic components of beers. Nevertheless, epidemiological evidence points to healthy effects of low or moderate beer consumption and even a protective action for cardiovascular risk and diabetes, discouraging heavy intakes without any exception. Beer components include alcohol and phenolics, both of which alter high- or low-density-lipoprotein levels and their oxidation status in blood. This review aims to highlight the importance of the metabolic mechanism by which beer components may influence lipid profile in terms of quantity and functionality, modulating cardiovascular risk. This is a major challenge for our society in light of the remarkable impact of cardiovascular diseases in all-cause mortality.

4. Conclusions

The purpose of the current review was to focus on the composition of beers, which are very popular drinks, as the source of metabolites, including alcohol, phenols and melanoidins, which influence our cardiovascular health. Many data demonstrate so far that low to moderate beer intake exerts a beneficial effect in terms of cardiovascular risk. This study provides a new understanding regarding the molecular profile involved in beer components healthy effects. Circulating lipids in blood may alter their levels or oxidation status, anticipating cardioprotective microenvironments. What is more, populations of high-density or low-density lipoproteins may exert different functions in our cardiovascular health after beer intake, in order to diminish cardiovascular risk. Nevertheless, further research is needed to elucidate the complex mechanisms underlying beer components behavior to contribute to reduce cardiovascular disease mortality. However, it is important to highlight that the benefits of beer intake does not outweigh the risks, the WHO discourages of any alcohol consumption.

The political right and left are, on balance, equally susceptible to conspiracy theories

Are Republicans and Conservatives More Likely to Believe Conspiracy Theories? Adam Enders, Christina Farhart, Joanne Miller, Joseph Uscinski, Kyle Saunders & Hugo Drochon. Political Behavior, Jul 22 2022.

Abstract: A sizable literature tracing back to Richard Hofstadter’s The Paranoid Style (1964) argues that Republicans and conservatives are more likely to believe conspiracy theories than Democrats and liberals. However, the evidence for this proposition is mixed. Since conspiracy theory beliefs are associated with dangerous orientations and behaviors, it is imperative that social scientists better understand the connection between conspiracy theories and political orientations. Employing 20 surveys of Americans from 2012 to 2021 (total n = 37,776), as well as surveys of 20 additional countries spanning six continents (total n = 26,416), we undertake an expansive investigation of the asymmetry thesis. First, we examine the relationship between beliefs in 52 conspiracy theories and both partisanship and ideology in the U.S.; this analysis is buttressed by an examination of beliefs in 11 conspiracy theories across 20 more countries. In our second test, we hold constant the content of the conspiracy theories investigated—manipulating only the partisanship of the theorized villains—to decipher whether those on the left or right are more likely to accuse political out-groups of conspiring. Finally, we inspect correlations between political orientations and the general predisposition to believe in conspiracy theories over the span of a decade. In no instance do we observe systematic evidence of a political asymmetry. Instead, the strength and direction of the relationship between political orientations and conspiricism is dependent on the characteristics of the specific conspiracy beliefs employed by researchers and the socio-political context in which those ideas are considered.

Discussion and Conclusion

Are those on the political right (Republicans/conservatives) more prone to conspiracy theorizing than those on the left (Democrats/liberals)? The smattering of evidence across the literature provides conflicting answers to this question. We surmise that disagreement in the literature is substantially the product of limitations regarding both the operationalizations of conspiracy theorizing and the context––both temporal and socio-political––in which beliefs are assessed in previous work. Given the imperative of better understanding conspiracy theories and the people who believe them, we compiled a robust body of evidence for testing the asymmetry thesis. Across multiple surveys and measurement strategies, we found more evidence for partisan and ideological symmetry in conspiricism, however operationalized, than for asymmetry.

First, we found that the relationship between political orientations and beliefs in specific conspiracy theories varied considerably across 52 specific conspiracy theories. Conspiracy theories containing partisan/ideological content or that have been endorsed by prominent partisan/ideological elites will find more support among those in one political camp or the other, while theories without such content or endorsements tend to be unrelated to partisanship and ideology in the U.S. We also observed considerable variability in the relationship between left–right ideology and 11 conspiracy theory beliefs across 20 additional countries spanning six continents; this variability suggests that the relationship between left–right ideology and conspiracy theory belief is also affected by the political context in which conspiracy theories are polled. To account for the potential impact of idiosyncratic factors associated with specific conspiracy theories, we next examined the relationship between beliefs in “content-controlled” conspiracy theories and political orientations. We found that both Democrats/liberals and Republicans/conservatives engage in motivated conspiracy endorsement at similar rates, with Democrats/liberals occasionally exhibiting stronger motivations than Republicans/conservatives. Finally, we observed only inconsistent evidence for an asymmetric relationship between conspiracy thinking and either partisanship, symbolic ideology, or operational ideology across 18 polls administered between 2012 and 2021. Even though the average correlations across studies were positive, indicating a relationship with conservatism/Republicanism (owing mostly to data collected in 2016), they were negligible in magnitude and individual correlations varied in sign and statistical significance over time.

Equally important as our substantive conclusions is an exploration of why we reached them, which can shed light on existing inconsistencies in the literature. While the core inferences we make from our investigation may deviate from the conclusions of others, empirical patterns are not irreconcilable. Take, for example, the study conducted by van der Linden and colleagues (2021). They infer from a strong, positive correlation between beliefs that “climate change is a hoax” and conservatism that conservatives are inherently more conspiratorial than liberals. However, we demonstrate that such conclusions cannot be made using beliefs in a single conspiracy theory. As can be seen in Fig. 1, climate change conspiracy theories show one of the highest levels of asymmetry; therefore, exclusive examination of almost any other conspiracy theory would lead to a result less supportive of the asymmetry argument.

Van der Linden et al. (2021) also find a positive, albeit weak, correlation between conservatism and generalized conspiracy thinking. While this relationship is statistically significant, liberals still exhibit high levels of conspiracism. Indeed, even strong liberals score above the 50-point midpoint on their 101-point measure (between 60 and 65, on average), whereas strong conservatives typically score about 10 points higher (see Figs. 1b and 3b). In other words, liberals, like conservatives, are more conspiratorial than not. Moreover, van der Linden et al.’s data hail from 2016 and 2018––years in which we also observed relatively elevated levels of conspiracy thinking among conservatives. However, this was not the case in other years and samples we examined. This is exactly what we might expect of a disposition that is not inherently connected to partisanship and ideology, but which may be sporadically activated by political circumstances. We do not question the veracity of van der Linden et al.’s empirical findings or those of any other study with conclusions that disagree with ours; rather, we argue that differences largely stem from the inferences made from empirical relationships, which are frequently more general than the data allows.

Despite the magnitude of data we employ, our study is not without limitations, and we wish to emphasize that ours should not be the final word on this topic. Although our data spans a decade, it was collected over the course of only three U.S. presidential administrations. As political culture changes so, too, might the relationship between political orientations and conspiracy theories. Unfortunately, measures of general conspiracy thinking (to our knowledge) were not deployed on national surveys until 2012 and specific conspiracy beliefs were only intermittently polled in the past 70 years, severely limiting how much we can know about conspiracy theorizing in the past. We encourage researchers to track multiple operationalizations of conspiracy theorizing into the future so that we may better understand their political dynamics and consequences.

We also recognize that, while an investigation of the asymmetry thesis across 21 countries constitutes a robust test, the more tests the asymmetry thesis undergoes the more confident we can be about its (lack of) veracity. We encourage an examination of more conspiracy theory beliefs across socio-political contexts, especially those that are closely tethered to each country’s political culture. We also recommend more robust examinations of the asymmetry thesis in regions that have been understudied, such as South America, Africa, and Asia. Even though we included countries from each of these continents, very little is known about the basic nature and scope of conspiracy theorizing outside of North America and Europe.

In a similar vein, conspiracy theories differ not only in who believes them, where, and when, but in their consequences and dangers. As such, it may be useful for researchers to consider categorizing conspiracy beliefs by various attributes, such as their consequences, just as they do for political attitudes (e.g., issue attitudes, affective versus ideological attitudes, etc.)––perhaps the asymmetry thesis finds stronger evidence among certain “classes” of conspiracy theories. Recent events in American politics are suggestive of this possibility. Donald Trump and his allies in government and media fostered election fraud conspiracy theory beliefs to the point of the violent intimidation of elected representatives attempting to certify the 2020 election. In this way, election fraud conspiracy theories––at least under the particular circumstances that Trump and colleagues nurtured––are of more consequence than, for example, conspiracy theories regarding the moon landing or lizard people. While forecasting which conspiracy theories will result in tangible consequences and when is surely difficult, we nevertheless note that symmetry of tendency to believe in conspiracy theories need not equal symmetry in consequence of conspiracy theories, along political lines or otherwise.

Finally, we believe it is critical that work on beliefs, like that presented here, be reconciled with related research examining political asymmetries in the tendency to interact with or “spread” conspiracy theories on social media. Related work by Guess, Nagler and Tucker (2019), Garrett and Bond (2021), and Grinberg et al. (2019), for example, finds evidence for minor asymmetries in the extent to which Democrats/liberals and Republicans/conservatives share misinformation or distinguish between fake and true news stories online. By fusing social media data with survey data researchers can gain greater leverage over questions about the conditions under which online behaviors are reflective of, or even impact, beliefs and offline behaviors. For now, we simply note that findings of asymmetries online may not generalize to the broader population, as politically active social media users are not representative of average Americans when it comes to various political and psychological characteristics (Lawson & Kakkar, 2021). Just as social media data can be fused with survey data, so, too, can top-down data on conspiratorial rhetorical strategies employed by political elites. Few studies of this sort have been undertaken, particularly in the U.S. (see Oliver & Rahn, 2016 for an example), but they are sorely needed––especially to test earlier studies on the rhetoric of conspiratorial elites (Adorno, 2000; Lowenthal & Guterman, 1948).

The last five years have witnessed Republican elites in government and media (most notably Donald Trump) utilizing conspiracy theories in a way unprecedented in the last half century of American politics, and with severe, deleterious consequences for democratic institutions. This alone has encouraged renewed conjecture about an asymmetry in conspiracy theory beliefs. However, elites are an imperfect reflection of the public––they have different goals, incentives, and knowledge about politics. Moreover, elite rhetoric rarely changes predispositions, such as conspiracy thinking, so much as it activates predispositions and connects them to salient political choices (Leeper & Slothuus, 2014). In other words, while Republican elites may have recently activated conspiratorial predispositions among supporters in the mass public––where they exist––in a way that Democratic elites did not, they are unlikely to be able to cause once non-conspiratorial supporters to become highly conspiratorial.

That we find little difference in conspiracy theorizing between the right and left among the mass public does not indicate that there are no differences between partisan elites on this score, nor does it imply that there will not be asymmetries in beliefs in specific conspiracy theories at any given point in time. Specific conspiracy theories can find more support among one partisan/ideological side than the other even though partisan/ideological motivated reasoning and conspiratorial predispositions operate, on balance, in a symmetric fashion. Likewise, the content of those theories and the way they are deployed, particularly by elites, can result in asymmetrical consequences, such as political violence and the undermining of democratic institutions. We encourage future work to integrate the conspiratorial rhetoric of elites with studies of mass beliefs and investigate elite conspiratorial rhetoric from actors including and beyond Donald Trump.

Fluctuating asymmetry, a measure of small random deviations from perfect bodily symmetry, was previously considered an honest indicator of genetic quality, but this paper says it is not

Formal models for the study of the relationship between fluctuating asymmetry and fitness in humans. Arodi Farrera. American Journal of Biological Anthropology, July 21 2022.


Objectives: To evaluate three of the main verbal models that have been proposed to explain the relationship between fluctuating asymmetry and fitness in humans: the “good genes,” the “good development,” and the “growth” hypotheses.

Materials and Methods: A formal model was generated for each verbal model following three steps. First, based on the literature, a theoretical causal model and the theoretical object of inquiry were outlined. Second, an empirical causal model and the targets of inference were defined using observational data of facial asymmetries and life-history traits related to fitness. Third, generalized linear models and causal inference were used as the estimation strategy.

Results: The results suggest that the theoretical and empirical assumptions of the “good genes” hypothesis should be reformulated. The results were compatible with most of the empirical assumptions of “the good development” hypothesis but suggest that further discussion of its theoretical assumptions is needed. The results were less informative about the “growth” hypothesis, both theoretically and empirically. There was a positive association between facial fluctuating asymmetry and the number of offspring that was not compatible with any of the empirical causal models evaluated.

Conclusions: Although the three hypotheses focus on different aspects of the link between asymmetry and fitness, their overlap opens the possibility of a unified theory on the subject. The results of this study make explicit which assumptions need to be updated and discussed, facilitating the advancement of this area of research. Overall, this study elucidates the potential benefit of using formal models for theory revision and development.


In this contribution, I evaluated three of the most common verbal models used to understand the relationship between FA and fitness in humans: the “good genes,” the “good development,” and the “growth” hypotheses. For this purpose, I generated formal models (i.e., estimands and causal frameworks) for each hypothesis and tested them in the particular case of facial asymmetries and reproductive success.

4.1 Theoretical assumptions

The present study shows that even if the approaches are different, some of the theoretical assumptions overlap across hypotheses (Figure 1), opening the opportunity for a unified formal model. Nonetheless, they show differences in two key assumptions. First, these hypotheses differ in whether they consider that FA reflects some cost to the individual, distinguishing between FA as a reliable signal of DS that reflects the quality of the individual (H1 and H2: symmetrical traits are costly) and as a reliable signal that requires no additional cost because it is tightly associated with some attribute of the individual (H3: allometric constraints that link body size and FA). This distinction has been discussed mainly in the framework of signaling theory (Barker et al., 2019), but in the context of human asymmetries and fitness, this discussion is currently problematic primarily because the way these concepts have been applied overlooks recent conceptual advances.

From the framework of signaling theory, attributes other than physiological information are recognized as signals (e.g., embodied capital or noetic attributes, Barker et al., 2019). A broader concept like this would allow for more comprehensive verbal models of the relationship between FA and fitness in humans, in which cultural practices such as the use of makeup (Killian et al., 2018), and social norms like standards of beauty (Kleisner et al., 2017) are also included in the interpretation and scope of the research. Signaling theory also recognizes that the way multiple signals are integrated with each other and with socioecological factors is an important source of information (Patricelli & Hebets, 2016). This would promote studying asymmetry along with other types of signals, as has been done during the last decade on topics such as mate choice (Jones & Jaeger, 2019; van Dogen et al., 2020) or the individual's health status (Foo et al., 2017; Mogilski & Welling, 2017). Addressing multiple signals as an integrated signaling phenotype or explaining how they are theoretically related to each other (e.g., Luoto et al., 2021) could improve and extend our understanding of the topic. Moreover, instead of being considered a static measurement (i.e., values computed at one point in time), individual asymmetries could be explored over different timescales. In the dynamic context of face-to-face interaction, for instance, asymmetric facial movement can be perceived as unattractive, regardless of the static asymmetry score of the individual (Hughes & Aung, 2018) because, for example, it conveys information about the sender's age (Kamachi et al., 2019). Taking into account that the causes and effects of asymmetry can be different in static and dynamic contexts could also clarify some of the contradictory evidence on the subject.

Another theoretical assumption in which the hypotheses evaluated differ is whether they highlight the role of developmental plasticity (i.e., phenotypic adjustments in response to the environment) on the expression of phenotypic variation and, particularly, on the production of asymmetric traits. Specifically, this assumption differentiates between research on FA variation that focuses on its genetic basis (H1: symmetry reflects good genes) and research that focuses on the development pathways that lead to such within-individual variation (H2 and H3: symmetry reflects the interplay between the organism and its circumstances). Although the former ignores the idea that has been present since the 1980s in the field of evolutionary developmental biology (Müller, 2007) that the influence of genotype on the phenotype is structured by developmental processes, the role of development in the latter is not entirely clear either. New verbal and formal models with a different set of theoretical assumptions are needed to get a better, refined representation of the role of development in the relationship between FA and fitness in humans.

4.2 Empirical assumptions

This study also shows some similarities and differences between hypotheses when the results are compared with the expectations derived from the empirical assumptions. In the case of the “good genes” hypothesis, the corresponding empirical causal model expects that individuals with greater facial FA values have less reproductive success than individuals with less asymmetry. Moreover, it expects that part of the phenotypic variance of facial FA is explained by genetic variation. In contrast, I found that individuals with greater facial FA values have more offspring and a heritability close to zero (i.e., almost none or little facial FA variation is explained by genetic variation). The latter result is the first report of heritability of FA in the human face and is consistent with previous research showing very low or no heritability of other traits in humans and other species (Johnson et al., 2008; Leamy & Klingenberg, 2005). These results suggest that the empirical causal model for this hypothesis needs to be revised and refined.

The empirical causal model derived from the “good development” hypothesis posits that because FA is the result of poor health, no direct link should be found between facial FA and the number of offspring. In contrast, the results showed a positive effect of facial FA on the number of offspring. On the other hand, based on the intergenerational maternal effect (Wells, 2018), this empirical causal model assumes that the short stature of some individuals is the result of a suboptimal maternal niche and that individuals who develop under these conditions may favor quantity over quality of offspring, and vice versa. The results of this study were compatible with this assumption. Specifically, it was found that, regardless of asymmetry, individuals with poor health status (measured as adult height) had more children, an effect reported in some previous studies (e.g., Krzyzanowska et al., 2015), but not in others (e.g., Helle, 2008). The results were also compatible with the expected negative effect of height on facial FA in this hypothesis, an effect reported in previous studies (Kirchengast, 2019; Özener & Ertuğrul, 2011) using FA measurements of non-facial traits. In other words, these results are compatible with most of the assumptions derived from the empirical causal model for this hypothesis, except for the assumption of no direct link between facial FA and the number of offspring, which should be refined to include potential mechanisms that may explain the relationship between these variables.

The empirical assumptions of the “growth” hypothesis are unclear as to whether facial FA directly and/or indirectly influences the number of offspring, what would be the expected direction of this effect, or what mechanism would be responsible. Therefore, it is currently not possible to interpret the results obtained on this assumption. Nonetheless, this empirical causal model posits two additional assumptions. First, that body and face size are allometrically related in adults and that facial FA is a by-product of individual growth. In contrast to previous studies (e.g., Gateño et al., 2018; Mitteroecker et al., 2013), the results were compatible, with high uncertainty, with an effect close to zero. These results suggest that more discussion is needed on the empirical causal model derived for this hypothesis.

In all hypotheses, I found a positive association between facial FA and the number of offspring, which is not consistent with any of the three empirical causal models evaluated. This result suggests that additional explanatory variables should be formally included in these models to further understand and test this relationship. One candidate variable could be the age-dependent pattern of FA expression (e.g., Wilson & Manning, 1996). Since facial FA can be a by-product of soft tissue aging, older individuals may express higher values. Further, this link could be related to the number of offspring in two ways. First, in line with the “good development” hypothesis, since reproduction takes time and considerable metabolic demands, individuals who have reproduced more and are older may also be more asymmetric. Second, in line with the “growth” hypothesis, fully developed (older and bigger) and therefore more asymmetric individuals could be those who have also had more opportunities to reproduce. Datasets collected specifically for testing these verbal models and updated formal models are needed to confirm the role of aging or any other variable outside those proposed in this work.

There are at least two factors related to the estimation strategy that limit the interpretation of these results (section 4.2). One of them is the sample over which inferences were drawn. The dataset used in this study was not explicitly collected to answer the theoretical object of inquiry (i.e., the relationship between FA and fitness), and thus, the empirical causal models were designed after data collection, instead of before as required to warrant causal claims (Rohrer, 2018). Other potential factors are related to bias in the computation of FA values, which have been extensively reviewed elsewhere (Graham, 2021b; Graham et al., 2010), including the presence of other forms of asymmetry, measurement error, or mixtures of additive and multiplicative errors. These limitations suggest that these results (section 4.1) must be replicated using more rigorous estimation strategies and other databases that allow comparing the three hypotheses.

Future studies could further benefit from revising, in light of theory development, the statistical practice associated with FA. For instance, rethinking isolated FA values as a target of inquiry when evidence suggests that in some contexts it is common to find different forms of asymmetry together (e.g., human face: Farrera et al., 2015; Quinto-Sánchez et al., 2015). Formal models of descriptive explanations that instead address the dynamics that could give rise to patterns of asymmetric mixtures (e.g., Graham et al., 1993; Hallgrímsson, 1998) could shed new light on the topic or clarify existent evidence.