Effect of olfactory disgust: Disgust might hamper behavioral actions motivated by sexual arousal (e.g., poor judgment, coercive sexual behavior)

The influence of olfactory disgust on (Genital) sexual arousal in men. Charmaine Borg, Tamara A. Oosterwijk, Dominika Lisy, Sanne Boesveldt, Peter J. de Jong. PLOS, February 28, 2019. https://doi.org/10.1371/journal.pone.0213059

Abstract
Background: The generation or persistence of sexual arousal may be compromised when inhibitory processes such as negative emotions, outweigh sexual excitation. Disgust particularly, has been proposed as one of the emotions that may counteract sexual arousal. In support of this view, previous research has shown that disgust priming can reduce subsequent sexual arousal. As a crucial next step, this experimental study tested whether disgust (by means of odor) can also diminish sexual arousal in individuals who are already in a state of heightened sexual excitation.

Methodology: In this study, participants were all men (N = 78). To elicit sexual arousal, participants watched a pornographic video. Following 4.30 minutes from the start of the video clip, they were exposed to either a highly aversive/disgusting odor (n = 42), or an odorless diluent/solvent (n = 36), that was delivered via an olfactometer, while the pornographic video continued. In both conditions the presentation of the odor lasted 1 second and was repeated 11 times with intervals of 26 seconds. Sexual arousal was indexed by both self-reports and penile circumference.

Principal findings: The disgusting odor (released when the participants were already sexually aroused) resulted in a significant decrease of both subjective and genital sexual arousal compared to the control (odorless) condition.

Significance: The finding that the inhibitory effect of disgust was not only expressed in self-report but also expressed on the penile response further strengthens the idea that disgust might hamper behavioral actions motivated by sexual arousal (e.g., poor judgment, coercive sexual behavior). Thus, the current findings indicate that exposure to an aversive odor is sufficiently potent to reduce already present (subjective and) genital sexual arousal. This finding may also have practical relevance for disgust to be used as a tool for self-defence (e.g., Invi Bracelet).

Nations that scored higher on democracy indices, especially emerging ones, experienced increased mortality due to violence; women possessed higher rates of homicide & suicide in democracies

Government political structure and gender differences in violent death: A longitudinal analysis of forty-three countries, 1960–2008. Morkeh Blay-Tofey et al. Aggression and Violent Behavior, Feb 28 2019. https://doi.org/10.1016/j.avb.2019.02.011

Highlights
• The purpose of this study is to examine the effect of democracy on violent death rates (homicide, suicide, and combined) by gender (men and women).
• Multi-level regression analyses examined associations between regime-type characteristics and logged rates of violent deaths using homicide and suicide. Models were adjusted for unemployment and economic inequality
• Violent deaths appear to be more prevalent even in stable democracies, and women are more affected than men.
• Although the analysis provided depicts a strong picture anchored in regime type changes and violent death rates, violence is inherently complex and more research is needed to determine what aspects within democracies may lead to increased violent death rates.

Abstract
Objectives: Little global and longitudinal scholarship exists on the relationship between regime type and mortality on a global level. The purpose of this study is to examine the effect of democracy on violent death rates (homicide, suicide, and combined) by gender (men and women).

Methods: Three measures of democracy were used to quantify regime type. Homicide and suicide rates were obtained from the World Health Organization. Multi-level regression analyses examined associations between regime characteristics and logged rates of homicide, suicide, and violent deaths. Models were adjusted for unemployment and economic inequality.

Results: Nations that scored higher on democracy indices, especially emerging democracies, experienced increased mortality due to violence. Women possessed higher rates of homicide and suicide in democracies compared to men.

Conclusions: Violent deaths appear to be more prevalent even in stable democracies, and women are more affected than men. This overturns the common assumption that democracies bring greater equality, and therefore lower death rates over long-term. Future analyses might examine the aspects of democracies that lead to higher rates of violent death so as to help mitigate them.

Keywords: Homicide suicide violence democracy autocracy regime gender

Males from Drosophila m. populations with higher competitive mating success produce sons with lower fitness; male investment in enhanced mating success comes at the cost of reduced offspring quality

Males from populations with higher competitive mating success produce sons with lower fitness. Trinh T. X. Nguyen  Amanda J. Moehring. Journal of Evolutionary Biology, Feb 27 2019, https://doi.org/10.1111/jeb.13433

Abstract: Female mate choice can result in direct benefits to the female or indirect benefits through her offspring. Females can increase their fitness by mating with males whose genes encode increased survivorship and reproductive output. Alternatively, male investment in enhanced mating success may come at the cost of reduced investment in offspring fitness. Here, we measure male mating success in a mating arena that allows for male‐male, male‐female, and female‐female interactions in Drosophila melanogaster. We then use isofemale line population measurements to correlate male mating success with sperm competitive ability, the number of offspring produced, and the indirect benefits of the number of offspring produced by daughters and sons. We find that males from populations that gain more copulations do not increase female fitness through increased offspring production, nor do these males fare better in sperm competition. Instead, we find that these populations have a reduced reproductive output of sons, indicating a potential reproductive trade‐off between male mating success and offspring quality.

The wrong belief in the exceptionalism of human cortex has caused to prematurely assign functions distributed widely in the brain to the cortex, & to fail to explore subcortical sources of brain evolution, inter alia

Human exceptionalism, our ordinary cortex and our research futures. Barbara L. Finlay. Developmental Psychobiology, February 27 2019, https://doi.org/10.1002/dev.21838

Abstract: The widely held belief that the human cortex is exceptionally large for our brain size is wrong, resulting from basic errors in how best to compare evolving brains. This misapprehension arises from the comparison of only a few laboratory species, failure to appreciate differences in brain scaling in rodents versus primates, but most important, the false assumption that linear extrapolation can be used to predict changes from small to large brains. Belief in the exceptionalism of human cortex has propagated itself into genomic analysis of the cortex, where cortex has been studied as if it were an example of innovation rather than predictable scaling. Further, this belief has caused both neuroscientists and psychologists to prematurely assign functions distributed widely in the brain to the cortex, to fail to explore subcortical sources of brain evolution, and to neglect genuinely novel features of human infancy and childhood.

“Dysrationalia” Among University Students: Intelligence & rational thinking, although related, represent two fundamentally different constructs; the intelligent have the same inability to think rationally

“Dysrationalia” Among University Students: The Role of Cognitive Abilities, Different Aspects of Rational Thought and Self-Control in Explaining Epistemically Suspect Beliefs
Nikola Erceg, Zvonimir Galić, Andreja Bubić. Europe's Journal of Psychology, Vol 15, No 1 (2019), https://ejop.psychopen.eu/article/view/1696

Abstract: The aim of the study was to investigate the role that cognitive abilities, rational thinking abilities, cognitive styles and self-control play in explaining the endorsement of epistemically suspect beliefs among university students. A total of 159 students participated in the study. We found that different aspects of rational thought (i.e. rational thinking abilities and cognitive styles) and self-control, but not intelligence, significantly predicted the endorsement of epistemically suspect beliefs. Based on these findings, it may be suggested that intelligence and rational thinking, although related, represent two fundamentally different constructs. Thus, deviations from rational thinking could be well described by the term “dysrationalia”, meaning the inability to think rationally despite having adequate intelligence. We discuss the implications of the results, as well as some drawbacks of the study.

Keywords: dysrationalia; epistemically suspect beliefs; cognitive abilities; rational thinking; self-control

Low replicability damages public trust in psychology; neither information about increased transparency nor explanations for low replicability, nor recovered replicability repaired public trust

Wingen, Tobias, Jana Berkessel, and Birte Englich. 2019. “No Replication, No Trust? How Low Replicability Influences Trust in Psychology.” OSF Preprints. February 22. doi:10.31219/osf.io/4ukq5

Abstract: In the current psychological debate, low replicability of psychological findings is the central topic. While this discussion about the replication crisis has a huge impact on psychological research, we know less about how it impacts lay people’s trust in psychology. In the current paper, we examine whether low replicability damages public trust in psychology and whether this damaged trust can be repaired. Study 1 and 2 provide correlational and experimental evidence that low replicability reduces public trust in psychological science. Additionally, Studies 3, 4, and 5 evaluate whether and how damaged trust in psychological science could be repaired. Critically, neither information about increased transparency (Study 3), nor explanations for low replicability (either QRPs or hidden moderators; Study 4), nor recovered replicability (Study 5) repaired public trust. Overall, our studies highlight the crucial importance of replicability for public trust, as well as the importance of balanced communication of low replicability.

It is unlikely that we will find strong relationships between what individuals are reporting about themselves and how they objectively behave

The Challenges and Opportunities of Small EffectsThe New Normal in Academic Psychiatry. Martin P. Paulus, Wesley K. Thompson. JAMA Psychiatry. February 27, 2019. doi:10.1001/jamapsychiatry.2018.4540

Full text in the link above.

Explanations and accurate predictions are the fundamental deliverables for a mechanistic or pragmatic approach that academic psychiatric research can provide to stakeholders. Starting with this issue, we are publishing a series of Viewpoints describing the research boundaries and challenges to progress in our field. In this issue, Simon1 raises the need for better explanatory model using data from electronic health records. This Viewpoint acknowledges an important issue: variables or constructs that are used to help explain the current state of individuals or to generate predictions need to account for a substantial proportion of the variance of the dependent variable or outcome measure to be clinically useful. However, similar to findings from genetics literature, systems neuroscience approaches using brain imaging are beginning to show that variability in structural and functional brain imaging only accounts for a small percentage of the explained variance when considering a variety of clinical phenotypes, especially in large population-representative samples.2 For example, in a 2016 analysis of UK Biobank data,3 the functional activation related to a face processing task, which activated the fusiform gyrus and amygdala, accounted for a maximum of 1.8% of the variance of 1100 nonimaging variables. These findings are in line with emerging results from the Adolescent Brain Cognitive Development study4 focused on the association between screen media behavior and structural MRI characteristics. Importantly, these large-scale studies have used robust and reliable estimators to reduce false-positive discoveries. Thus, similar to genetics literature, it appears that individual processing differences as measured by neuroimaging account for little symptomatic or behavioral variance.

There is evidence that the association between individual variation on self-assessed symptoms and behavioral performance on neurocognitive tasks is weak.5,6 Moreover, many behavioral tasks show limited test-retest reliability and little agreement between task conceptualization and actual agreement with emerging latent variables of these tasks. Therefore, it is unlikely that we will find strong relationships between what individuals are reporting about themselves and how they objectively behave. It seems that the individual experience of a person with a mental health condition, which has been proposed to be an important end point for explanatory approaches,7 is not well approximated by the behavioral probes that are currently available.

These and other findings have profound implications for our theoretical understanding of psychiatric diseases. Specifically, small effect sizes make it unlikely that psychiatric disorders can be explained by unicausal or oligocausal theories. In other words, there is not going to be a unifying glutamatergic or inflammatory disease model of mood disorders. What’s more, even if there is a relationship between markers for these disease processes and the state of a psychiatric disorder, as currently conceived, it may not be sufficiently strong to be used by itself to make useful person-level predictions. This is not to say that these processes are not contributing to the etiology or pathophysiology of the disorder but rather that their impact is likely to be small so as to not be individually useful in helping patients and other stakeholders explain their current disease state. As a consequence, there is a low probability of a generic disease process for a group of psychiatric disorders or a final common pathway for a disease.

One possible reason for the lack of a strong relationship between units of analyses, ie, between brain circuits and behavior or behavior and symptoms, is many-to-one and one-to-many mapping. In other words, the brain has many ways of producing the same symptoms, and very similar brain dysfunctions can produce a number of different clinical symptoms. An example of one-to-many mapping is the phenotypic heterogeneity of Huntington disease, which, as an autosomal dominant disorder, has a simple genetic basis but enormous clinical variability via the modulation of multiple biochemical pathways.8 In comparison, the clinical homogeneity of motor neuron disease is betrayed by a significant genetic variability, leading to similar symptoms.9 Therefore, it is quite possible that phenotypically similar groups result from different processes and phenotypically heterogeneous individuals actually share broadly similar underlying pathophysiology.

These many-to-one and one-to-many mappings put a profound strain on case-control studies, ie, comparing individuals diagnosed with a particular psychiatric disease with controls that are matched on a limited number of variables. Case-control designs have very limited explanatory depth and are fundamentally uninformative of the disease process because they are correlational, provide little specificity and questionable sensitivity, and have questionable generalizability to populations.10 Single-case designs together with hierarchical inferential procedures might provide a reasonable alternative.11 Single-case designs use individuals as their own control, can use controlled interventions to examine causality, and are well suited to uncover individual differences across phenotypically similar participants. However, care must be taken not to subdivide studies so finely that defects of small sample sizes, including elevated rates of type I and II errors, become problematic even for large epidemiologically informed samples.

Latent variable approaches, such as principal components or factor analyses, can be useful unsupervised statistical methods to uncover relationships between variables within and across units of analyses. However, the underlying assumption is that these latent variables reflect common relationships among all individuals. Instead, it is more likely that relationships differ across individuals and may even differ across states within an individual. Recent approaches to this problem use both latent variable and mixture approaches to differentiate different subgroups of individuals with depression.12 Others have used deviation from normative regression models to identify heterogeneity in schizophrenia and bipolar disorder.13 Both sets of approaches support the hypothesis that there are no generic depressive, bipolar, or schizophrenia diseases. At the other extreme, considering that psychiatric diseases emerge from causal factors that vary across units of analyses ranging from molecular to social,7 one might hypothesize that each individual patient with a mental health condition is an exemplar of a rare disease model. In this case, no generalizable model might be possible, and useful individual-level predictions would be elusive.

Thus, we are facing the classical problem of variance-bias trade-off,14 which has been examined in great detail in the statistical literature. Specifically, how do we arbitrate between generating a few generic models with useful explanatory or predictive values vs multiple models that may tend to overexplain and overfit individual patient’s disease etiology, pathophysiology, and clinical course? This decision cannot be arbitrated solely on statistical grounds but will need to judiciously incorporate expert knowledge about the disease and candidate processes on different units of analyses because the permutational complexity of the variables to be considered is so large that even data sets with thousands of individuals may not provide a sufficient sample size to approach this using exploratory techniques resistant to overfitting.

At this time, we are standing at a precipice: our explanatory disease models are woefully insufficient, and our predictive approaches have not yielded robust individual-level predictions that can be used by clinicians. Yet there is room for hope. Larger data sets will be widely available, multilevel data sets that span assessments from genes to social factors are being released, new statistical tools are being developed, within-subject statistical designs are being rediscovered, and attempts to include expert knowledge into latent variable approaches might help arbitrating the variance-bias trade-off. Fundamentally, academic psychiatry cannot continue to move forward with small n case-control studies to provide tangible results to stakeholders.

References
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