From 2011... False-Positive Psychology: Undisclosed Flexibility in Data Collection and Analysis Allows Presenting Anything as Significant

From 2011... False-Positive Psychology: Undisclosed Flexibility in Data Collection and Analysis Allows Presenting Anything as Significant. Joseph P. Simmons, Leif D. Nelson, Uri Simonsohn. Psychological Science, October, 2011. https://doi.org/10.1177/0956797611417632

Abstract: In this article, we accomplish two things. First, we show that despite empirical psychologists’ nominal endorsement of a low rate of false-positive findings (≤ .05), flexibility in data collection, analysis, and reporting dramatically increases actual false-positive rates. In many cases, a researcher is more likely to falsely find evidence that an effect exists than to correctly find evidence that it does not. We present computer simulations and a pair of actual experiments that demonstrate how unacceptably easy it is to accumulate (and report) statistically significant evidence for a false hypothesis. Second, we suggest a simple, low-cost, and straightforwardly effective disclosure-based solution to this problem. The solution involves six concrete requirements for authors and four guidelines for reviewers, all of which impose a minimal burden on the publication process.

Keywords: methodology, motivated reasoning, publication, disclosure

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In this article, we show that despite the nominal endorsement of a maximum false-positive rate of 5% (i.e., p ≤ .05), current standards for disclosing details of data collection and analyses make false positives vastly more likely. In fact, it is unacceptably easy to publish “statistically significant” evidence consistent with any hypothesis.

The culprit is a construct we refer to as researcher degrees of freedom. In the course of collecting and analyzing data, researchers have many decisions to make: Should more data be collected? Should some observations be excluded? Which conditions should be combined and which ones compared? Which control variables should be considered? Should specific measures be combined or transformed or both?

It is rare, and sometimes impractical, for researchers to make all these decisions beforehand. Rather, it is common (and accepted practice) for researchers to explore various analytic alternatives, to search for a combination that yields “statistical significance,” and to then report only what “worked.” The problem, of course, is that the likelihood of at least one (of many) analyses producing a falsely positive finding at the 5% level is necessarily greater than 5%.

This exploratory behavior is not the by-product of malicious intent, but rather the result of two factors: (a) ambiguity in how best to make these decisions and (b) the researcher’s desire to find a statistically significant result. A large literature documents that people are self-serving in their interpretation of ambiguous information and remarkably adept at reaching justifiable conclusions that mesh with their desires (Babcock & Loewenstein, 1997; Dawson, Gilovich, & Regan, 2002; Gilovich, 1983; Hastorf & Cantril, 1954; Kunda, 1990; Zuckerman, 1979). This literature suggests that when we as researchers face ambiguous analytic decisions, we will tend to conclude, with convincing self-justification, that the appropriate decisions are those that result in statistical significance (p ≤ .05).

Ambiguity is rampant in empirical research. As an example, consider a very simple decision faced by researchers analyzing reaction times: how to treat outliers. In a perusal of roughly 30 Psychological Science articles, we discovered considerable inconsistency in, and hence considerable ambiguity about, this decision. Most (but not all) researchers excluded some responses for being too fast, but what constituted “too fast” varied enormously: the fastest 2.5%, or faster than 2 standard deviations from the mean, or faster than 100 or 150 or 200 or 300 ms. Similarly, what constituted “too slow” varied enormously: the slowest 2.5% or 10%, or 2 or 2.5 or 3 standard deviations slower than the mean, or 1.5 standard deviations slower from that condition’s mean, or slower than 1,000 or 1,200 or 1,500 or 2,000 or 3,000 or 5,000 ms. None of these decisions is necessarily incorrect, but that fact makes any of them justifiable and hence potential fodder for self-serving justifications.

From 2015... Estimating the reproducibility of psychological science: Innovation points out paths that are possible; replication points out paths that are likely; progress relies on both

From 2015... Estimating the reproducibility of psychological science. "Open Science Collaboration." Science, Vol. 349, Issue 6251, aac4716. Aug 28 2015, http://dx.doi.org/10.1126/science.aac4716

Empirically analyzing empirical evidence: One of the central goals in any scientific endeavor is to understand causality. Experiments that seek to demonstrate a cause/effect relation most often manipulate the postulated causal factor. Aarts et al. describe the replication of 100 experiments reported in papers published in 2008 in three high-ranking psychology journals. Assessing whether the replication and the original experiment yielded the same result according to several criteria, they find that about one-third to one-half of the original findings were also observed in the replication study.

Structured Abstract
INTRODUCTION Reproducibility is a defining feature of science, but the extent to which it characterizes current research is unknown. Scientific claims should not gain credence because of the status or authority of their originator but by the replicability of their supporting evidence. Even research of exemplary quality may have irreproducible empirical findings because of random or systematic error.

RATIONALE There is concern about the rate and predictors of reproducibility, but limited evidence. Potentially problematic practices include selective reporting, selective analysis, and insufficient specification of the conditions necessary or sufficient to obtain the results. Direct replication is the attempt to recreate the conditions believed sufficient for obtaining a previously observed finding and is the means of establishing reproducibility of a finding with new data. We conducted a large-scale, collaborative effort to obtain an initial estimate of the reproducibility of psychological science.

RESULTS We conducted replications of 100 experimental and correlational studies published in three psychology journals using high-powered designs and original materials when available. There is no single standard for evaluating replication success. Here, we evaluated reproducibility using significance and P values, effect sizes, subjective assessments of replication teams, and meta-analysis of effect sizes. The mean effect size (r) of the replication effects (Mr = 0.197, SD = 0.257) was half the magnitude of the mean effect size of the original effects (Mr = 0.403, SD = 0.188), representing a substantial decline. Ninety-seven percent of original studies had significant results (P < .05). Thirty-six percent of replications had significant results; 47% of original effect sizes were in the 95% confidence interval of the replication effect size; 39% of effects were subjectively rated to have replicated the original result; and if no bias in original results is assumed, combining original and replication results left 68% with statistically significant effects. Correlational tests suggest that replication success was better predicted by the strength of original evidence than by characteristics of the original and replication teams.

CONCLUSION No single indicator sufficiently describes replication success, and the five indicators examined here are not the only ways to evaluate reproducibility. Nonetheless, collectively these results offer a clear conclusion: A large portion of replications produced weaker evidence for the original findings despite using materials provided by the original authors, review in advance for methodological fidelity, and high statistical power to detect the original effect sizes. Moreover, correlational evidence is consistent with the conclusion that variation in the strength of initial evidence (such as original P value) was more predictive of replication success than variation in the characteristics of the teams conducting the research (such as experience and expertise). The latter factors certainly can influence replication success, but they did not appear to do so here.

Reproducibility is not well understood because the incentives for individual scientists prioritize novelty over replication. Innovation is the engine of discovery and is vital for a productive, effective scientific enterprise. However, innovative ideas become old news fast. Journal reviewers and editors may dismiss a new test of a published idea as unoriginal. The claim that “we already know this” belies the uncertainty of scientific evidence. Innovation points out paths that are possible; replication points out paths that are likely; progress relies on both. Replication can increase certainty when findings are reproduced and promote innovation when they are not. This project provides accumulating evidence for many findings in psychological research and suggests that there is still more work to do to verify whether we know what we think we know.

Why not release honest statements for research fields that are messy, inconsistent, have systematic methodological weaknesses or that may be outright unreproducible? https://www.bipartisanalliance.com/2019/02/why-not-release-honest-statements-for.html
Copenhaver, A. & Ferguson, C.J. (in press). Selling violent video game solutions: A look inside the APA’s internal notes leading to the creation of the APA’s 2005 resolution on violence in video games and interactive media. International Journal of Law and Psychiatry.
Ferguson, C.J. (2015). ‘Everybody knows psychology is not a real science’: Public perceptions of psychology and how we can improve our relationship with policymakers, the scientific community, and the general public. American Psychologist, 70, 527–542.
Fiske, S. (2016). Mob rule or wisdom of crowds [Draft of article for APS Observer]. Available at http://datacolada.org/wp-content/uploads/2016/09/Fiske-presidential-guest-column_APS-Observer_copy-edited.pdf
Gilbert, D.T., King, G., Pettigrew, S. & Wilson, T.D. (2016). Comment on ‘Estimating the reproducibility of psychological science’. Science, 351(6277), 1037.
Nosek, B.A., Ebersole, C.R., DeHaven, A.C. & Mellor, D.T. (2018). The preregistration revolution. Proceedings of the National Academy of Sciences of the United States of America, 115(11), 2600–2606.
Nelson, L.D., Simmons, J. & Simonsohn, U. (2018). Psychology’s renaissance. Annual Review of Psychology, 69, 511–534.
Simmons, J.P., Nelson, L.D. & Simonsohn, U. (2011). False-positive psychology: Undisclosed flexibility in data collection and analysis allows presenting anything as significant. Psychological Science, 22(11), 1359–1366. https://www.bipartisanalliance.com/2020/01/from-2011-false-positive-psychology.html
Weir, K. (2014). Translating psychological science. APA Monitor, 45(9), 32. Available at www.apa.org/monitor/2014/10/translating-science.aspx

The Effects of Militarized Interstate Disputes on Incumbent Voting Across Genders

The Effects of Militarized Interstate Disputes on Incumbent Voting Across Genders. Shane P. Singh, Jaroslav Tir. Political Behavior, December 2019, Volume 41, Issue 4, pp 975–999. https://link.springer.com/article/10.1007/s11109-018-9479-z

Abstract: Gender and politics research argues that men are more hawkish and supportive of militarized confrontations with foreign foes, while women ostensibly prefer more diplomatic approaches. This suggests that, after a militarized confrontation with a foreign power, women’s likelihood of voting for the incumbent will both decrease and be lower than that of men. Our individual-level, cross-national examinations cover 87 elections in 40 countries, 1996–2011, and show only some support for such notions. Women punish incumbents when their country is targeted in a low-hostility militarized interstate dispute (MID) or when their country is the initiator of a high-hostility MID. The low-hostility MID initiation and high-hostility MID targeting scenarios, meanwhile, prompt women to be more likely to vote for the incumbent. Importantly, men’s reactions rarely differ from women’s, casting doubt on the existence of a gender gap in electoral responses to international conflict.

Keywords: Voting behavior Gender Conflict Diversion Rally

Replication code and data for this paper are available in the Political Behavior Dataverse at:  https://doi.org/10.7910/DVN/O9UVFU

Young adults who expect to do worse than their parents in the future are indeed more likely to locate themselves at the extreme ends of the ideological scale, and most of them are in the Left

Extreme Pessimists? Expected Socioeconomic Downward Mobility and the Political Attitudes of Young Adults. Elena Cristina Mitrea, Monika Mühlböck,  Julia Warmuth. Political Behavior, January 18 2020. https://link.springer.com/article/10.1007/s11109-020-09593-7

Abstract: In recent decades, and especially since the economic crisis, young people have been finding it more difficult to maintain or exceed the living standards of their parents. As a result, they increasingly expect socioeconomic downward mobility. We study the influence of such a pessimistic view on political attitudes, assuming that it is not so much young adults’ current economic status, but rather their anxiety concerning a prospective socioeconomic decline that affects their ideological positions. Drawing on data from a survey among young adults aged 18–35 in eleven European countries, we explore to what extent expected intergenerational downward mobility correlates with right-wing and left-wing self-placement. We find that young adults who expect to do worse than their parents in the future are indeed more likely to locate themselves at the extreme ends of the ideological scale.

Keywords: Socioeconomic mobility Intergenerational European Political attitudes Left–right self-placement

A Cross-Sectional and Longitudinal Analysis: Current tests find no effect of light and moderate alcohol drinking in cognitive performance (memory, planning, & reasoning)

Alcohol Consumption, Drinking Patterns, and Cognitive Performance in Young Adults: A Cross-Sectional and Longitudinal Analysis. Henk Hendriks et al. Nutrients 2020, 12(1), 200. January 13 2020. https://doi.org/10.3390/nu12010200

Abstract: Long-term alcohol abuse is associated with poorer cognitive performance. However, the associations between light and moderate drinking and cognitive performance are less clear. We assessed this association via cross-sectional and longitudinal analyses in a sample of 702 Dutch students. At baseline, alcohol consumption was assessed using questionnaires and ecological momentary assessment (EMA) across four weeks (‘Wave 1’). Subsequently, cognitive performance, including memory, planning, and reasoning, was assessed at home using six standard cognition tests presented through an online platform. A year later, 436 students completed the four weeks of EMA and online cognitive testing (‘Wave 2’). In both waves, there was no association between alcohol consumption and cognitive performance. Further, alcohol consumption during Wave 1 was not related to cognitive performance at Wave 2. In addition, EMA-data-based drinking patterns, which varied widely between persons but were relatively consistent over time within persons, were also not associated with cognitive performance. Post-hoc analyses of cognitive performance revealed higher within-person variance scores (from Wave 1 to Wave 2) than between-person variance scores (both Wave 1 and Wave 2). In conclusion, no association was observed between alcohol consumption and cognitive performance in a large Dutch student sample. However, the online cognitive tests performed at home may not have been sensitive enough to pick up differences in cognitive performance associated with alcohol consumption.

Keywords: young adult; alcohol consumption; cognitive performance

4. Discussion

We hypothesized that light to moderate drinkers would obtain similar cognitive task scores as
compared to abstainers, whereas heavy drinkers would obtain lower cognitive task scores. While the
first part of our hypothesis was retained, we did not find lower cognitive task scores for heavy drinkers.
In this study, we did not find any consistent association between alcohol consumption and cognitive
performance in a large population-based sample of young Dutch adults. This observation was made
both cross-sectionally as well as longitudinally after a one-year follow-up. These null findings were
observed for both the average amount of alcohol consumed as well as for the various drinking patterns.
However, the results of this study should be interpreted with caution, because the null findings of this
study have to be viewed in light of the high variance of the cognition scores.
The strengths of this study are the use of a large and homogeneous group of young adults: all
students of similar age and similar level of education. This is relevant because cognitive performance
largely depends on age and educational level. The group, however, spanned a large range of alcohol
consumption and included various drinking patterns. Both the cross-sectional and longitudinal
analysis used validated and well-recognized cognition tests. We selected these cognitive tests, since we
considered them to provide a somewhat better indicator for day-to-day functioning and brain health
as compared to functional MRI images showing changing patterns of blood circulation [14,15].
EMA may be a suitable methodology for alcohol consumption evaluation. EMA encompasses
the brief but intensive repeated assessment of people’s thoughts, feelings, and behaviors in their
real-world settings. The ecological validity of EMA data is considered high [19]. EMA reduces
retrospective bias when assessing alcohol consumption, as suggested by higher consumptions as
compared to consumptions recorded by regular questionnaire. EMA also has a low cognitive bias
due to direct retrieval [33]. Furthermore, the repetitive data collection allowed the study of drinking
patterns in addition to commonly reported average consumption levels. This is relevant since
alcohol-drinking pattern may be an important determinant for the harmful effects of drinking, such as
binge drinking [11,12,20].
Population surveys using questionnaires typically report underestimates of alcohol consumption
of approximately 40–50%. Researchers adjust alcohol survey data to weight estimates such that
they match alcohol sales or alcohol tax data. The current study suggests that underestimation of
alcohol consumption in this population exists, but to a lesser extent than assumed in population
surveys. EMA has been recognized as an alternative for assessing alcohol consumption in the natural
environment [34].
Previous studies found inconsistent results on the relation between alcohol consumption and
cognitive performance. The majority of studies indicate that long-term heavy drinking has strong
negative associations with diseases of the brain such as dementia [35]. Many short-term studies
indicate cognitive impairment in heavy binge drinkers as compared to nondrinking controls [8–13].
The outcome of comparing two groups differing in drinking habits, however, may depend on the
selection criteria and may potentially be hampered by confounding. Excessive heavy drinking is
usually accompanied by impulsive behaviors, risk-seeking behavior [36], and other traits [16] that may
confound the association between alcohol consumption and cognitive performance. Some authors
suggest that impaired cognitive performance may partly predict excessive alcohol consumption,
whereas excessive alcohol consumption does not always predict impaired cognitive functioning [37].
Contrary to the differences in cognitive performance between heavy binge-drinkers and
nonbinge-drinking controls, long-term moderate drinking has been associated with a reduced risk
of dementia and a reduced risk of cognitive decline. Reviews of prospective studies showed that
moderately drinking elderly have a decreased risk of dementia and cognitive decline [38,39]. Thus,
after a very long follow-up, moderately drinking persons may be expected to show a less severe decline
in cognitive performance as compared to those that drink excessively and abstainers. This suggests
that there may be a J-shaped association between alcohol consumption and dementia and cognition, as
has been described for cardiovascular diseases [40]. The risk reduction for dementia and age-related
cognitive decline observed in the elderly may occur through a mechanism related to cardiovascular
disease risk factors, whereas the cognitive impairment observed in young binge-drinking adults may
occur through a mechanism related to neurotoxicity.
Our results correspond with those reported previously by Boelema et al. [18]. The null findings
regarding the association between alcohol consumption and cognitive performance in that study were
interpreted as being methodological in nature; the tests used may not have been sensitive enough
to detect a potential cognitive performance reduction as a consequence of alcohol consumption. We
also used conventional standard tests that are routinely used for cognitive performance evaluations.
However, some aspects of our testing differed. Firstly, the tests were performed in an ‘at home situation’
as opposed to ‘at a testing facility’, which may have affected the results in various ways. For some
individuals, performing cognitive tests in an environment that they are familiar with may positively
influence performance. For others, the at home environment may have provided more distraction, or
the lack of experimental control and the fact that no experimenter was present may have reduced focus
and motivation, negatively affecting performance. All these factors may have affected test results and
might explain the high within-person variability. Secondly, cognitive tests employed in the present
study did not allow evaluation of aspects like reaction time, which may have contributed to a less
complete test result.
The cognition tests did seem to detect differences, since small significant differences were observed
for education level. It is important, however, to extend these studies to enable detection of small
differences in cognitive performance that may be induced by light and moderate alcohol drinking.
Significant differences in cognition tests may be detected by decreasing the variability in the cognition
test outcomes.
Although the study was set up with a group of students to obtain a high degree of homogeneity,
this also has its limitations. The results obtained in this group cannot be generalized to the general
population nor to specific other groups like persons with a low socioeconomic status. Specific groups
may respond differently to alcohol consumption and may have more difficulty in adapting their
drinking pattern whenever needed. In general, it has been extensively described that adolescents are
less sensitive to the negative effects of alcohol, including cues that influence self-regulation of intake,
but are more sensitive to positive effects, which may serve to reinforce or promote excessive intake [41].
This response to alcohol may promote the development of alcohol use disorders, a development
university students may be less vulnerable to as compared to other groups of adolescents [7].
Our study design, however, had several limitations that warrant consideration. The null findings
of this study have to be viewed in light of the high variance of the cognition scores. Whereas in
the ‘real-life’ study, the within-person variability was higher than the between-person variability, in
the laboratory study, the within-person variability was lower than the between-person variability.
This suggests that the use of cognition tests in a ‘real-life’ setting may not have been suitable or
sufficiently sensitive to detect a possible reduction in cognitive performance in association with alcohol
consumption. Some of the tasks were, however, sensitive to education level, as university students
outperformed polytechnic students, which would be expected as the former is a higher level of
education. Furthermore, it is expected that the cognition tests used in this study might have been
adequate to detect (possible) small differences in cognitive performance when used in a laboratory
setting, provided a sufficiently large participants population.
In the present study, follow-up time was only one year. It would have been interesting to show
in the same cohort that students who keep on drinking in a hazardous way will show cognitive
impairment after many years. Boelema et al. [18], however, did report on cognitive performance after
a four-year follow-up yet did not find indications for cognitive impairment in adolescent drinkers,
including heavy drinkers.
In conclusion, it is important to build on this study by reducing variance in online cognitive
testing or by testing in a laboratory setting to better assess the association between light and moderate
alcohol drinking and cognitive performance. In the present study, variance in cognitive performance
was too large to detect an association, if any, between alcohol consumption and cognitive performance.
Future studies should carefully consider both the context in which cognition is assessed as well as the
type of tasks that are used.

Body mass index is a highly heritable trait, but heritability estimates of BMI are lower in childhood because of the influence of shared environmental factors, in old-age because of unique environmental factors

Obesity and eating behavior from the perspective of twin and genetic research. Karri Silventoinen, Hanna Konttinen. Neuroscience & Biobehavioral Reviews, Volume 109, February 2020, Pages 150-165. https://doi.org/10.1016/j.neubiorev.2019.12.012

Highlights
• Body mass index (BMI, kg/m2) is a highly heritable and polygenic trait.
• Heritability increases after early childhood and is highest in early adulthood.
• Obesogenic micro- and macro-environments reinforce genetic variation.
• Candidate genes of BMI express in brain tissue, suggesting the importance of behavior.
• Emerging evidence suggests that genes can affect BMI through eating behavior traits.

Abstract: Obesity has dramatically increased during the last decades and is currently one of the most serious global health problems. We present a hypothesis that obesity is a neuro-behavioral disease having a strong genetic background mediated largely by eating behavior and is sensitive to the macro-environment; we study this hypothesis from the perspective of genetic research. Genetic family and genome-wide-association studies have shown well that body mass index (BMI, kg/m2) is a highly heritable and polygenic trait. New genetic variation of BMI emerges after early childhood. Candidate genes of BMI notably express in brain tissue, supporting that this new variation is related to behavior. Obesogenic environments at both childhood family and societal levels reinforce the genetic susceptibility to obesity. Genetic factors have a clear influence on macro-nutrient intake and appetite-related eating behavior traits. Results on the gene-by-diet interactions in obesity are mixed, but emerging evidence suggests that eating behavior traits partly mediate the effect of genes on BMI. However, more rigorous prospective study designs controlling for measurement bias are still needed.

Keywords: TwinsGeneticsObesityBMIEating behavior

7. Conclusions

A century of genetic family studies and a decade of GWA studies have dramatically increased our understanding on the genetic architecture of common obesity, eating behavior and their mutual associations. However, this increasing knowledge has also clearly demonstrated the challenges, especially when trying to understand the mechanisms of how genes affect BMI and other obesity indicators. BMI has been shown to be a highly heritable trait, but the heritability changes over the life course. The heritability estimates of BMI are lower in childhood and in old age as compared to early adulthood and middle-age. In childhood, the lower heritability is because of the influence of environmental factors shared by co-twins and in old-age because of environmental factors unique to each twin. The similar pattern of increasing influence of genetic factors and diminishing effect of the shared environment during late childhood and adolescence has been reported for many psychological traits, such as intelligence (Plomin and Deary, 2015), and probably reflects the changing dynamics of the interplay between genes and the environment. During adolescence, dependence on parents decreases, social networks widen, influence from peers become stronger and sensation-seeking increases (Ahmed et al., 2015; Kilford et al., 2016). This probably leads to the possibility to more freely create one’s own environment, including the environment influencing BMI, which is partly affected by genetically influenced preferences. There is a lot of evidence for this so-called active gene–environment correlation for psychiatric traits (Jaffee and Price, 2007), and genetic factors have been found to influence life events, also demonstrating the dependence of genes and environment (Kendler and Baker, 2007). However, for BMI the direct evidence on gene–environment correlations is still suggestive. Studies on the heritability of macro-nutrient intake and eating patterns suggest that shared environmental factors have effect on eating behavior in childhood and adolescence, and this influence disappears until adulthood. Twin and molecular genetic studies have shown that after early childhood new genetic variance emerges. It is very possible that this genetic variance is related to eating behavior when children can more independently regulate their own eating, but direct evidence is still lacking. There is some evidence that eating behaviors can modify the genetic effects of obesity, but most of these studies are based on cross-sectional data and the results are somewhat mixed. Thus, more studies on how the interplay between genes and the environment modifies the genetic architecture of BMI during the formative years of childhood and adolescence are still needed. The strong effect of genetic factors on BMI does not mean, however, that the family environment does not have effect on BMI. Adoption studies have clearly shown that the adoptive family also has an effect on BMI. A likely explanation for these results is that the family environment affects BMI by reinforcing the effect of genes affecting BMI. There is direct evidence on this based mainly on twin studies since both the micro-level environment (e.g., parental education) and the macro-level environment (measured as the level of obesity between countries and measurement years) affect the genetic variation of BMI. Thus, those children having a genetic susceptibility to obesity gain more weight in family environments or societies predisposing to obesity. These results underline the importance of community food environments, since they can suppress or reinforce the effects of genetic variants associated with obesity. There has been a lot of discussion on which specific community-level factors are behind the obesogenic environments, but there is no clear consensus (Kirk et al., 2009). The associations are also likely to be very complex, as found in a previous study demonstrating that the community food environment can modify how health counseling affects eating behavior (Lorts et al., 2019). There is a lack on studies whether the micro- and macro-environment can modify the genetic variation of macro-nutrient intake in a similar way as they affect the genetic variation of BMI. Thus, more research is needed to specify which community-level factors reinforce the genetic variation of BMI and analyze the role of eating behavior behind these associations. GWA studies have clearly shown that BMI is a highly polygenic trait and thus confirms the basic principle of genetic family studies. The mechanisms of how genes affect BMI are still poorly understood, but the expression of the candidate genes of BMI in the brain tissue suggests that they affect BMI through behavioral factors. There is also evidence based on both twin and GWA studies that genetic factors affect macronutrient intake and appetite-related eating behavior traits. However, to date, there is only limited direct evidence on the overlap of genes affecting BMI and eating behavior which would suggest that the genes affect BMI through eating behavior. Some studies have shown this mediation effect, but they can explain only a fraction of the association between genetic factors and BMI. This area is, however, very challenging because of the well-known difficulties to measure dietary intake and reliance on self-report scales to assess eating behavior traits. Some sex differences in the genetic architecture of obesity indicators were identified. In BMI the proportion of genetic variation was roughly similar in males and females from infancy to old age, but especially after puberty, somewhat different sets of genes started to affect BMI in males and females and this difference increased during adulthood. It is likely that this reflects differences in body composition since somewhat different sets of genes affect muscle and fat body tissues. Accordingly, the SNPs associated with WHR adjusted for BMI showed different effect sizes in males and females. Very little is still known on sex differences in the genetic architecture of eating behavior. Thus, it is too early to argue whether genetic factors affect obesity traits in males and females differently through eating behavior or whether the found differences reflect only endocrinological differences between the sexes. At the beginning of this review we presented the hypothesis: Obesity is a neuro-behavioral disease having a strong genetic background mediated largely by eating behavior and being sensitive to the macroenvironment. There is strong evidence for this hypothesis based on previous genetic research, but the evidence that the genes affect especially through eating behavior is still emerging and mainly indirect at the moment. More rigorous prospective study designs controlling the well-known biases of measuring food intake would be necessary to prove this part of the hypothesis or to show that other behavioral mechanisms are also important when explaining the effect of genes on BMI.

High-IT-adoption banks originated mortgages with better performance & did not offload low-quality loans; banks led by more “tech-oriented” managers experienced lower non-performing loans during the crisis

Tech in Fin before FinTech: Blessing or Curse for Financial Stability? Nicola Pierri; Yannick Timmer. IMF Working Paper No. 20/14, January 17, 2020. https://www.imf.org/en/Publications/WP/Issues/2020/01/17/Tech-in-Fin-before-FinTech-Blessing-or-Curse-for-Financial-Stability-48797

Summary: Motivated by the world-wide surge of FinTech lending, we analyze the implications of lenders’ information technology adoption for financial stability. We estimate bank-level intensity of IT adoption before the global financial crisis using a novel dataset that provides information on hardware used in US commercial bank branches after mapping them to their parent bank. We find that higher intensity of IT-adoption led to significantly lower non-performing loans when the crisis hit: banks with a one standard deviation higher IT-adoption experienced 10% lower non-performing loans. High-IT-adoption banks were not less exposed to the crisis through their geographical footprint, business model, funding sources, or other observable characteristics. Loan-level analysis indicates that high-IT-adoption banks originated mortgages with better performance and did not offload low-quality loans. We apply a simple text-analysis algorithm to the biographies of top executives and find that banks led by more “tech-oriented” managers adopted IT more intensively and experienced lower non-performing loans during the crisis. Our results suggest that technology adoption in lending can enhance financial stability through the production of more resilient loans.

Victims, perpetrators, or both? The vicious cycle of disrespect and cynical beliefs about human nature

Stavrova, O., Ehlebracht, D., & Vohs, K. D. (2020). Victims, perpetrators, or both? The vicious cycle of disrespect and cynical beliefs about human nature. Journal of Experimental Psychology: General. Jan 2020. https://doi.org/10.1037/xge0000738

Abstract: We tested how cynicism emerges and what maintains it. Cynicism is the tendency to believe that people are morally bankrupt and behave treacherously to maximize self-interest. Drawing on literatures on norms of respectful treatment, we proposed that being the target of disrespect gives rise to cynical views, which predisposes people to further disrespect. The end result is a vicious cycle: cynicism and disrespect fuel one another. Study 1’s nationally representative survey showed that disrespect and cynicism are positively related to each other in 28 of 29 countries studied, and that cynicism’s associations with disrespect were independent of (and stronger than) associations with lacking social support. Study 2 used a nationally representative longitudinal dataset, spanning 4 years. In line with the vicious cycle hypothesis, feeling disrespected and holding cynical views gave rise to each other over time. Five preregistered experiments (including 2 in the online supplemental materials) provided causal evidence. Study 3 showed that bringing to mind previous experiences of being disrespected heightened cynical beliefs subsequently. Studies 4 and 5 showed that to the extent that people endorsed cynical beliefs, others were inclined to treat them disrespectfully. Study 6’s weeklong daily diary study replicated the vicious cycle pattern. Everyday experiences of disrespect elevated cynical beliefs and vice versa. Moreover, cynical individuals tended to treat others with disrespect, which in turn predicted more disrespectful treatment by others. In short, experiencing disrespect gives rise to cynicism and cynicism elicits disrespect from others, thereby reinforcing the worldview that caused these negative reactions in the first place.

Check also Competent individuals endorsed cynicism only if it was warranted in a given sociocultural environment; less competent individuals embraced cynicism unconditionally, maybe an adaptive default strategy to avoid the potential costs of falling prey to others’ cunning:

The Cynical Genius Illusion: Exploring and Debunking Lay Beliefs About Cynicism and Competence. Olga Stavrova, Daniel Ehlebracht. Personality and Social Psychology Bulletin, Jul 2018. https://www.bipartisanalliance.com/2018/07/competent-individuals-endorsed-cynicism.html

Male individuals are more willing to forgive all forms of infidelity to a greater extent than female individuals; attachment insecurity moderated this relationship

Understanding Infidelity Forgiveness: An Application of Implicit Theories of Relationships. Ashley E. Thompson, Dallas Capesius, Danica Kulibert and Randi A. DoyleJournal of Relationships Research, Volume 112020, e2, Jan 17 2020. https://doi.org/10.1017/jrr.2019.21

Abstract: Two studies were conducted to identify variables associated with hypothetical infidelity forgiveness and promote forgiveness by manipulating implicit theories of relationships (ITRs; destiny/growth beliefs). Study 1 assessed the relationship between the type of behaviour, sex of the forgiver, ITRs and infidelity forgiveness. Study 2 investigated the causal relationship between ITRs and infidelity forgiveness (including attachment insecurity as a moderator). Results revealed that male participants forgave a partner's infidelity to a greater extent than female participants and that solitary behaviours were rated as most forgivable, followed by emotional/affectionate and technology/online behaviours, and sexual/explicit behaviours as least forgivable. Male participants (not female participants) induced to endorse growth beliefs forgave a partner's emotional/affectionate and solitary infidelity to a greater extent than those induced to endorse destiny beliefs; attachment insecurity moderated this relationship. These results have important implications for researchers and practitioners working with couples in distress.

Becoming sexy: Contrapposto pose increases attractiveness ratings and modulates observers’ brain activity

Becoming sexy: Contrapposto pose increases attractiveness ratings and modulates observers’ brain activity. Farid Pazhoohi et al. Biological Psychology, January 17 2020, 107842. https://doi.org/10.1016/j.biopsycho.2020.107842

Highlights
• contrapposto pose is considered more attractive than neutral standing pose
• body posture modulates the visual information in early and late components
• middle temporal and angular gyri respond to body posture

Abstract: Previous neurophysiological studies have revealed the neural correlates of human body form perception, as well as those related to the perception of attractive body sizes. In the current study we aimed to extend the neurophysiological studies regarding body perception by investigating the perception of human body posture to provide insights into the cognitive mechanisms responsive to bodily form, and the processing of its attractiveness. To achieve these aims, we used the contrapposto posture which creates an exaggeration of low waist to hip ratio (WHR), an indicator of women's attractiveness. Electroencephalogram (EEG) signals were recorded while participants completed both (i) an oddball task presenting female body forms differing in pose (contrapposto vs. standing) and viewing angle (anterior vs. posterior), and (ii) a subsequent active attractiveness judgement task. Behavioral results showed that a contrapposto pose is considered more attractive than a neutral standing pose. Result at the neural level showed that body posture modulates the visual information processing in early ERP components, indicating attentional variations depending on human body posture; as well as in late components, indicating further differences in attention and attractiveness judgement of stimuli varying in body pose. Furthermore, the LORETA results identified the middle temporal gyrus as well as angular gyrus as the key brain regions activated in association with the perception and attractiveness judgment of females’ bodies with different body poses. Overall, the current paper suggests the evolutionary adaptive preference for lower WHRs as in the contrapposto pose activating brain regions associated with visual perception and attractiveness judgement.

Keywords: body postureattractivenesssupernormal stimuliEEGERP

Check also Men looking at women: The contrapposto pose was perceived as more attractive than the standing pose

Waist-to-Hip Ratio as Supernormal Stimuli: Effect of Contrapposto Pose and Viewing Angle. Farid Pazhoohi. Archives of Sexual Behavior, June 18 2019. https://www.bipartisanalliance.com/2019/06/men-looking-at-women-contrapposto-pose.html

Perceived versus actual autism knowledge: Participants least knowledgeable about ASD overestimated their own knowledge; those most knowledgeable underestimated it

Perceived versus actual autism knowledge in the general population. Camilla M. McMahon, Brianna Stoll, Meghan Linthicum. Research in Autism Spectrum Disorders, Volume 71, March 2020, 101499. https://doi.org/10.1016/j.rasd.2019.101499

Highlights
• Participants’ perceived ASD knowledge was not related to their actual ASD knowledge.
• Participants least knowledgeable about ASD overestimated their own knowledge.
• Participants most knowledgeable about ASD underestimated their own knowledge.

Abstract
Background In recent years, there has been a growing interest in assessing the general public’s knowledge and awareness of Autism Spectrum Disorders (ASD). A variety of methods have been used to measure participants’ ASD knowledge, including self-report of ASD knowledge and objective assessment of ASD knowledge. The goals of the current study are twofold: (1) To determine whether there is a relationship between participants’ self-reported, perceived ASD knowledge and objectively-measured, actual ASD knowledge and (2) to examine the degree to which participants are aware of and can accurately monitor their own ASD knowledge.

Method Participants in the general population completed a subjective, self-report questionnaire on their perceived knowledge of ASD and an objective assessment measuring their actual knowledge of ASD. After completing the objective assessment, they estimated their raw score and percentile performance on the assessment.

Results Participants’ perceived knowledge of ASD was not related to their actual knowledge of ASD. Participants least knowledgeable about ASD overestimated their performance, and participants most knowledgeable about ASD underestimated their performance.

Conclusions These results suggest that perceived and actual ASD knowledge are theoretically distinct constructs, such that self-reported ASD knowledge cannot serve as a proxy variable for actual ASD knowledge. Furthermore, individuals with low ASD knowledge are often not aware of their own ignorance, such that it is unlikely that they will independently seek additional knowledge or training in this area.

Keywords: Autism Spectrum Disorder (ASD)Autism knowledgeOverconfidenceDunning-Kruger effectUnskilled and unawareMetacognitive monitoring


Check also Participants with the lowest assessed weather knowledge do overestimate their weather knowledge, a result consistent with previous psychological studies:

What People Know About the Weather. Christopher Nunley, Kathleen Sherman-Morris. Bulletin of the American Meteorological Society, Jan 2020. https://www.bipartisanalliance.com/2020/01/participants-with-lowest-assessed.html

And In self-judgment, the "best option illusion" leads to Dunning-Kruger (failure to recognize our own incompetence). In social judgment, it leads to the Cassandra quandary (failure to identify when another person’s competence exceeds our own):

The best option illusion in self and social assessment. David Dunning. Self and Identity, Apr 2018. https://www.bipartisanalliance.com/2018/04/in-self-judgment-best-option-illusion.html

Black Americans, relative to White Americans, generate images of police officers’ faces that are more negative, less positive, & more dominant

Good Cop, Bad Cop: Race-Based Differences in Mental Representations of Police. E. Paige Lloyd et al. Personality and Social Psychology Bulletin, January 16, 2020. https://doi.org/10.1177/0146167219898562

Abstract: The current work investigates race-based biases in conceptualization of the facial appearance of police. We employ a reverse correlation procedure to demonstrate that Black Americans, relative to White Americans, conceptualize police officers’ faces as more negative, less positive, and more dominant. We further find that these differential representations have implications for interactions with police. When naïve participants (of various races) viewed images of police officers generated by Black Americans (relative to those generated by White Americans), they responded with greater anticipated anxiety and reported more fight-or-flight behavioral intentions. Across four studies, findings suggest Black and White Americans conceptualize police and police–citizen interactions fundamentally differently. These findings have important theoretical (e.g., using reverse correlation to document the mental representations held by minority group members) and practical implications (e.g., identifying race-based differences in representations of police that may affect community–police relations).

Keywords: person perception, intergroup relations, prejudice/stereotyping, social cognition


From Good Cop Bad Cop Methodology https://osf.io/hyfnk/

Study 1
Face rating dimensions:
“Please rate the person picture above on the following dimensions:”
Traits: (presented in random order)
How friendly does this person appear? (1=Not at all, 9=Extremely)
How warm does this person appear? (1=Not at all, 9=Extremely)
How empathetic does this person appear? (1=Not at all, 9=Extremely)
How fearful does this person appear? (1=Not at all, 9=Extremely)
How hostile does this person appear? (1=Not at all, 9=Extremely)
How dominant does this person appear? (1=Not at all, 9=Extremely)
How dominant does this person appear? (1=Not at all, 9=Extremely)
How authoritative does this person appear? (1=Not at all, 9=Extremely)
How powerful does this person appear? (1=Not at all, 9=Extremely)

Study 2
Face rating instructions:
“Thank You for participating in today's experiment!
In this study, we are interested in people's perceptions of different groups. You will be presented with
blurry face images and you will be asked to rate those images on a variety of traits.
Although these faces may seem similar, they are not identical. There are subtle differences. Please judge
each face independent of the previous. Past research indicates that even in these blurry faces people are
quite accurate in identifying characteristics and qualities about the person.
Please click continue.”

Face rating dimensions:
“Please rate the person picture above on the following dimensions:”
Traits: (presented in random order)
How friendly does this person appear? (1=Not at all, 9=Extremely)
How warm does this person appear? (1=Not at all, 9=Extremely)
How empathetic does this person appear? (1=Not at all, 9=Extremely)
How fearful does this person appear? (1=Not at all, 9=Extremely)
How hostile does this person appear? (1=Not at all, 9=Extremely)
How dominant does this person appear? (1=Not at all, 9=Extremely)
How dominant does this person appear? (1=Not at all, 9=Extremely)
How authoritative does this person appear? (1=Not at all, 9=Extremely)
How powerful does this person appear? (1=Not at all, 9=Extremely)
Group membership: (presented in order shown below)
How Eurocentric (White) does this person appear? (1=Not at all, 9=Extremely)
How Afrocentric (Black) does this person appear? (1=Not at all, 9=Extremely)
How feminine does this person appear? (1=Not at all, 9=Extremely)
How masculine does this person appear? (1=Not at all, 9=Extremely)

Study 3
Face rating instructions:
“In this study, we are interested in people's perceptions of different individuals. You will be presented
with one blurry face and a scenario. The face you see will be randomly selected. Pay close attention to
cues in the face, imagine yourself in the scenario, and then respond to the questions.
Please click continue.”

Imagined scenario instructions:
“Look carefully at the face above and imagine the following scenario:
You're walking home alone at night when the person pictured above says to stop walking. They are a
police officer. They are armed. They begin to approach you. To your knowledge you are doing nothing
wrong and are breaking no laws.
Feelings of anxiety measure: (presented in random order)
How tense would you feel? (1=Not at all, 9=Extremely)
How frightened would feel? (1=Not at all, 9=Extremely)
How anxious would you feel? (1=Not at all, 9=Extremely)
How scared would you feel? (1=Not at all, 9=Extremely)
How worried would you feel? (1=Not at all, 9=Extremely)
How safe would you feel? (1=Not at all, 9=Extremely)
How at ease would you feel? (1=Not at all, 9=Extremely)
How relaxed would you feel? (1=Not at all, 9=Extremely)
How protected would you feel? (1=Not at all, 9=Extremely)
How comfortable would you feel? (1=Not at all, 9=Extremely)
Fight-and-flight behavioral intentions measure: (presented in random order)
“Again look carefully at the face above and continue to imagine the scenario.”
To what extent would you be preparing to physically defend yourself, in case it became
necessary? (1=Not at all, 9=Extremely)
To what extent would you be preparing to run away, in case it became necessary? (1=Not at all,
9=Extremely)
Quantity and quality of contact with police questionnaire:
5.
How much contact have you had with police officers? (1=None, 7=A great deal)
6.
How positive has your contact with police been? (1=Not at all positive, 7=Extremely positive)
7.
How many police officers do you know? (1=None, 7=Know a lot)
8.
How well do you know those police officers (1=Do not know those officers well, 7=Know those
officers very well)



Attitudes toward police questionnaire:

7.
To what extent do you feel police officers listen to community members and understand the
issues that affect your community? (1=Not at all, 7=Extremely)
8.
To what extent are polices officers effective at fighting crime? (1=Not at all, 7=Extremely)
9.
To what extent do you feel police officers listen to community members and understand the
issues that affect your community? (1=Not at all, 7=Extremely)
10.
To what extent do you feel police officers try to treat people fairly regardless of who they are?
(1=Not at all, 7=Extremely)
11.
To what extent do you feel police officers can be relied on to be there when you need them?
(1=Not at all, 7=Extremely)
12.
To what extent do you trust police officers to make decisions that are good for everyone in your
community? (1=Not at all, 7=Extremely)

Study 4
Face rating instructions:
“In this study, we are interested in people's perceptions of different groups. You will be presented with 2
images of blurry faces and you will be asked to rate those images on a variety of traits.
Although these faces may seem similar, they are not identical. There are subtle differences. Please judge
each face independent of the previous. Past research indicates that even in these blurry faces people are
quite accurate in identifying characteristics and qualities about the person.
Please click continue.”

Face rating dimensions:
“Please rate the person picture above on the following dimensions:”
Traits: (presented in random order)
How friendly does this person appear? (1=Not at all, 9=Extremely)
How warm does this person appear? (1=Not at all, 9=Extremely)
How empathetic does this person appear? (1=Not at all, 9=Extremely)
How fearful does this person appear? (1=Not at all, 9=Extremely)
How hostile does this person appear? (1=Not at all, 9=Extremely)
How dominant does this person appear? (1=Not at all, 9=Extremely)
How dominant does this person appear? (1=Not at all, 9=Extremely)
How authoritative does this person appear? (1=Not at all, 9=Extremely)
How powerful does this person appear? (1=Not at all, 9=Extremely)
Imagined scenario instructions:
“Look carefully at the face above and imagine the following scenario:
You're walking home alone at night when the person pictured above says to stop walking. They are a
police officer. They are armed. They begin to approach you. To your knowledge you are doing nothing
wrong and are breaking no laws.
Feelings of anxiety measure: (presented in random order)
How tense would you feel? (1=Not at all, 9=Extremely)
How frightened would feel? (1=Not at all, 9=Extremely)
How anxious would you feel? (1=Not at all, 9=Extremely)
How scared would you feel? (1=Not at all, 9=Extremely)
How worried would you feel? (1=Not at all, 9=Extremely)
How safe would you feel? (1=Not at all, 9=Extremely)
How at ease would you feel? (1=Not at all, 9=Extremely)
How relaxed would you feel? (1=Not at all, 9=Extremely)
How protected would you feel? (1=Not at all, 9=Extremely)
How comfortable would you feel? (1=Not at all, 9=Extremely)

Fight-and-flight behavioral intentions measure: (presented in random order)
“Again look carefully at the face above and again imagine the scenario.
You're walking home alone at night when the person pictured above says to stop walking. They
are a police officer. They are armed. They begin to approach you. To your knowledge you are
doing nothing wrong and are breaking no laws.”
To what extent would you be preparing to physically defend yourself, in case it became
necessary? (1=Not at all, 9=Extremely)
To what extent would you be preparing to run away, in case it became necessary? (1=Not at all,
9=Extremely)
Quantity and quality of contact with police questionnaire:
9.
How much contact have you had with police officers? (1=None, 7=A great deal)
10.
How positive has your contact with police been? (1=Not at all positive, 7=Extremely positive)
11.
How many police officers do you know? (1=None, 7=Know a lot)
12.
How well do you know those police officers (1=Do not know those officers well, 7=Know those
officers very well)
Attitudes toward police questionnaire:
13.
To what extent do you feel police officers listen to community members and understand the
issues that affect your community? (1=Not at all, 7=Extremely)
14.
To what extent are polices officers effective at fighting crime? (1=Not at all, 7=Extremely)
15.
To what extent do you feel police officers listen to community members and understand the
issues that affect your community? (1=Not at all, 7=Extremely)
16.
To what extent do you feel police officers try to treat people fairly regardless of who they are?
(1=Not at all, 7=Extremely)
17.
To what extent do you feel police officers can be relied on to be there when you need them?
(1=Not at all, 7=Extremely)
18.
To what extent do you trust police officers to make decisions that are good for everyone in your
community? (1=Not at all, 7=Extremely)

In total, our results are consistent with the likelihood of considerable genetic variation in the expression of male gender nonconformity, and possibly even in its causes

Familiality of Gender Nonconformity Among Homosexual Men. J. Michael Bailey. Archives of Sexual Behavior, January 16 2020. https://link.springer.com/article/10.1007/s10508-020-01626-w

Abstract: We examined whether recalled childhood gender nonconformity and self-reported adult gender nonconformity is familial, using data from 1154 families selected for having at least two homosexual brothers. Specifically, we examined the extent to which homosexual men’s variation in gender nonconformity runs in families by examining pairs of genetic brothers who were both homosexual (N = 672–697 full sibling concordant pairs). We also examined similarity between homosexual and heterosexual brothers (N = 79–82 full sibling discordant pairs). Consistent with past studies, concordant pairs yielded modest positive correlations consistent with moderate genetic and/or familial environmental effects on gender nonconformity. Unlike results of smaller past studies, discordant pairs also yielded modest positive, though nonsignificant, correlations. Our results support the feasibility of supplementing genetic studies of male sexual orientation with analyses of gender nonconformity variation.

Keywords: Sexual orientation Homosexuality Gender nonconformity Familiality Genetics

Young men had higher proportions of sexual abstinence than middle-aged men due to unavailability of a partner, lower educational levels, low socioeconomic status, conservative & religious conditions

Irfan M, Hussain NHN, Noor NM, et al. Sexual Abstinence and Associated Factors Among Young and Middle-Aged Men: A Systematic Review. J Sex Med 2020;XX:XXX–XXX. https://doi.org/10.1016/j.jsxm.2019.12.003

Abstract
Introduction Sexual activity is an essential human need and an important predictor of other aspects of human life. A literature review was conducted to investigate whether sexual abstinence in young and middle-aged men is generally considered a deliberate, healthy behavior and whether it has other causes and consequences.

Aim To review the prevalence and factors associated with sexual abstinence in young (10–24 years) and middle-aged (25–59 years) men.

Methods Studies were retrieved from Science Direct, PubMed, and EBSCOhost published from 2008 to 2019. The selection criteria were original population- or community-based articles, published in the English language, on sexual abstinence, and in young and middle-aged men.

Main Outcome Measure This article reviewed the literature on the proportions of and factors associated with sexual abstinence in young and middle-aged men.

Results A total of 13,154 studies were retrieved, from which data were extracted for 37 population- or community-based studies. The prevalence of sexual abstinence varied from 0% to 83.6% in men younger than 60 years. The prevalence of primary sexual abstinence was 3.4%–83.3% for young men and 12.5%–15.5% for middle-aged men. The prevalence of secondary abstinence for young men ranged from 1.3% to 83.6%, while for middle-aged men, it was from 1.2% to 67.7%. The prevalence of sexual abstinence decreased with increasing age in young men but increased with increasing age in middle-aged men. The significant factors reported were age, single status, poor relationships, low socioeconomic status, sex education, religious practices, caring and monitoring parents, and not using alcohol, cigarettes, or drugs. Although the variations in findings from different studies can be explained by different regions and cultures, the information cannot be generalized worldwide because of a lack of studies in Asian and Australian populations.

Clinical Implications The studies on sexual abstinence in the future should use a consistent and standard definition, cover all sexual behaviors, and investigate all related factors.

Strength & Limitations The restricted timeframe (2008–2019), English language, availability of full text, and variability in definition and time duration may be the sources of bias.

Conclusion Young men had higher proportions of sexual abstinence than middle-aged men, and age, unavailability of a partner, lower educational levels, low socioeconomic status, conservative and religious conditions, and no or less knowledge about sexually transmitted infections were common predictors of sexual abstinence in most of the men. Although determinants of sexual abstinence were identified, further investigation of biological factors in men younger than 60 years is needed.

Key Words: Sexual InactivitySexual AbstinencePrimary Sexual AbstinenceSecondary Sexual AbstinenceSex Education

Discussion

The present systematic review aimed to investigate the proportions of sexual abstinence in young and middle-aged men younger than 60 years. We identified a previous, nonsystematic, descriptive review of the lack of sexuality in young men, with no information on the included studies,45 but proper systematic reviews were more focused on the effectiveness of various sexual abstinence programs.46,47

Sexual abstinence has previously been stressed in youth, but it is currently considered that protected (using condom) sexual activity is important for a healthy psychosocial life of men.24 In the literature review, the unavailability of a partner, lower educational levels, low socioeconomic status, conservative and religious conditions, and no or less knowledge about STIs were common predictors of sexual abstinence in most of the young and middle-aged men.

Most of the studies published on sexual abstinence in young and middle-aged men were focused on North American and African populations, but Asia (the most populated continent) and Australia had limited publications, and South America had none. Primary sexual abstinence was mostly studied in young men, and no study was found in the 45- to 59-year age group. However, primary sexual inactivity could persist until later ages if caused by no or low sexual desire, asexuality, or homosexuality, which should be investigated in the future.

Most of the studies were focused on the absence or cessation of penile-vaginal sexual intercourse, which underestimates sexual activity in young men. Adolescents and young adults who may have difficulties in finding a partner, be threatened by negative outcomes (pregnancy and STIs) or face social taboos may be involved in other sexual activities, such as solitary or mutual masturbation, caressing, or oral-genital sexual activities.

The present review shows that the reported prevalence of sexual abstinence varies considerably based on various factors. Most of the studies defined sexual abstinence differently and used different tools of assessment (questionnaires, interviews) and different methods of administration of those tools. Similarly, variations were also attributed to the different durations (a few days to 5 years) of sexual abstinence.

The proportions reported in the included studies for the same or similar age groups were wide, and there were inconsistencies in the associated factors, possibly due to differences in methodologies, research designs, participant characteristics, sample sizes, variables investigated, and presentation of results.

The studies used a self-administered questionnaire reported relatively increased proportions of primary and secondary sexual abstinence as compared with the interview or interviewer-assisted questionnaire. The reason behind this may be the men found it difficult to describe their sexual inactivity to the interviewer. The prevalence of sexual abstinence decreased with the increasing age in young men because they can consent and have greater chances to have sexual partners through a casual encounter, commitment, or marriage.48 The other factors of decreased sexual abstinence in young men include physical and mental growth and increased sexual desire with age.2,14,19 However, in middle-aged men, the onset of self and partners' health issues, divorce, and low sexual functions due to the process of aging may increase the prevalence of sexual abstinence.49

The present review established evidence that as in elderly men, young and middle-aged men also have physical and mental health–related issues that lead to sexual abstinence. Similarly, young and middle-aged men also have sexual abstinence due to the difficulties to have a sexual partner or have an estranged relationship with the partner. The other factors may be related to socioeconomics, lifestyle, behavioral, relationship status, and involvement in religion. Therefore, it is suspected that the assessment of success in any sexual abstinence program may not be correct without considering the role of these factors.

The studies for adolescents and young men were more focused on the prevention of STIs and unwanted pregnancies in specific populations and circumstances,16,17,29,30,32 and the results were more dependent on the characteristics of the participants in each study. Therefore, the factors identified are not generalizable to the wider population of young men. The variations due to different populations and different methods could not be separated, and a direct comparison of rates of prevalence reported in the different studies could not be performed.

Recommendations for Future Research

First, the definition and time period for which sexual abstinence is defined in future research should be consistent and standard. Second, the studies should include the proportions of sexual activities other than penile-vaginal sexual intercourse and investigate the role of biological factors in men younger than 60 years. Third, there is a need to review studies conducted before 2008 also and compare decade-wise to get information on the trends of sexual abstinence. Fourth, while assessment of the success of a sexual abstinent program, the other factors should also be considered. Finally, primary sexual inactivity should also be investigated in middle-aged men older than 45 years in the future.

Limitations

The review was limited to the published studies that may create bias because of the increased probability of the publication of studies with significant results. The other sources of bias were that studies published in language other than English and full text not available were not included in the review. There were also a few studies that had a nonrandom sampling design. Furthermore, we picked age groups less than 60 years from among studies that focused on men of all age groups, which may have affected the accuracy of the findings and compromised generalizability. Only 12.5% (n = 4) of the studies were from Asia and 6.3% (n = 2) from Australia, affecting the generalizability of the findings to Asian, Australian, and South American men. Most of the studies on young men defined sexual inactivity as no sexual intercourse with a partner but did not consider other sexual activities (masturbation, noncoital, and so on), yet the studies on middle-aged men defined sexual inactivity as including some of coital and noncoital behavior.

Failure to replicate: We found no short-term or long-term effects of the 4th of July on social distance from partisan and ideological ingroups or outgroups

Brandt, Mark J., and Felicity M. Turner-Zwinkels. 2020. “Proximity to the July 4th Holiday Does Not Affect Affective Polarization.” PsyArXiv. January 16. doi:10.31234/osf.io/7yqkd

Abstract: One promising approach for reducing affective polarization is priming a shared American identity and one promising event to prime that identity is the 4th of July. Prior work showed that proximity to the 4th of July reduced affective polarization. We conceptually replicated this study using a 9-wave longitudinal design in 2019. We found no short-term or long-term effects of the 4th of July on social distance from partisan and ideological ingroups or outgroups. There were individual differences in social distance trajectories across time, but there were not individual differences in short-terms changes in social distance in close proximity to the 4th of July. Although priming a shared American identity may be effective, these findings suggest that the salutary effects of the 4th of July holiday do not emerge in 2019, suggesting that the effectiveness of primes of American identity are not consistent overtime.

Replication data: https://osf.io/26bua/?view_only=a85cb58461c34a59b8db8d2eb5666bfc

This manuscript has not been peer-reviewed. Comments are appreciated. Send any to
m.j.brandt at tilburguniversity.edu


General Discussion

We found no clear effects of proximity to the 4th of July on social distance from partisan and
ideological outgroups, ingroups, or ideological moderates using a preregistered 9-wave panel study.
Although individual differences exist on a number of the relevant longitudinal trajectories, we did
not find individual differences on any of the factors representing short terms changes in social
distance near the 4th of July. These results should cast doubt on the effectiveness of the 4th of July to
reduce affective polarization.
There are important differences from Levendusky’s (2018) original finding. Levendusky used
a between-subjects design in the election year of 2008 and asked participants to evaluate candidates.
We used a within-subjects design in the off-election year of 2019 and asked participants to evaluate
partisan and ideological ingroups and outgroups. All of these methodological differences should not
theoretically cause a problem. For example, the original paper was about affective polarization
broadly (i.e. not just about candidates) and the theorizing should apply to our measures of social
distance. Similarly, it seems that, if anything, a non-election year might be less polarizing because the
political context is less competitive. Nonetheless, the political system in the United States is in a
different place in 2019 compared to 2008. In the summer of 2008, both presidential candidates
expressed support for working with members of the other party and bridging American divides. In
the summer of 2019, Donald Trump advocated for a polarizing military-style parade to help
celebrate the 4th of July. These different political contexts may be enough to shift the meaning of the
4th of July and reduce its potential depolarizing impact.
Levedusky’s (2018) original theoretical insight was that a common ingroup identity might
reduce affective polarization. Although we did not find support for the idea that this might occur via
proximity to the 4th of July, common ingroup identity could still be an effective depolarization
strategy. This suggests that what serves as an effective prime of common ingroup identity is subject
to change. According to Hornsey and Hogg (2000), making the superordinate identity salient while
ignoring subgroup identities might induce identity threat and therefore perpetuate intergroup bias.
As such, future application of Levendusky’s (2018) July the 4th paradigm may find it useful to
acknowledge the American, Democrat and Republican identities simultaneously. However, it is
possible that growing differences between Democrats and Republicans limit the effectiveness of the
American identity to function as a common ingroup. Rutchick and Eccleston (2010) argue that
because Democrats and Republicans have rather different ideas about what the American identity
means, it may be less able to harmoniously unite these subgroups. If this is the case, then carefully
constructing primes to work their current context is important for replicating and extending the
work on American identity primes, as well as using this work in practical settings.
The longitudinal design allowed us to identify the existence of individual differences in
response to the proximity of the 4th of July. However, this came at the cost of nonrepresentativeness. Although our analyses suggest little heterogeneity in the effects of proximity to
the 4th of July, an even more heterogenous sample may identify the predicted effects. We were also
only able to include a single-item measure of affective polarization, although we were able to use this
measure for both ideological and partisan groups. Our results suggest that proximity to the 4th of
July does not impact social distance from ideological and partisan outgroups, ingroups, or
ideological moderates in 2019. Other primes of American identity may be more effective.

Age trends for all dark personality features were progressive through adolescence, but negative through adulthood; trends for agreeableness partly mirrored these trends & changes in dark personality features & agreeableness were correlated

The Unfolding Dark Side: Age Trends in Dark Personality Features. Theo A.Klimstra et al. Journal of Research in Personality, January 16 2020, 103915. https://doi.org/10.1016/j.jrp.2020.103915

Highlights
•    Gender differences in Dirty Dozen scale scores varied by age and by feature.
•    Age trends were progressive through adolescence, but negative through adulthood.
•    Gender and age trends in agreeableness partly mirrored those of the Dirty Dozen.
•    Longitudinal changes in Dirty Dozen scales and agreeableness were correlated.

Abstract: Age and gender differences across the lifespan in dark personality features could provide hints regarding these features’ functions. We measured manipulation, callous affect, and egocentricity using the Dirty Dozen and their links with agreeableness in a pooled cross-sectional dataset (N = 4,292) and a longitudinal dataset (N = 325). Age trends for all dark personality features were progressive through adolescence, but negative through adulthood. Men scored higher than women, but the gender gap varied with age. Trends for agreeableness partly mirrored these trends and changes in dark personality features and agreeableness were correlated. Results are discussed in light of the maturity principle of personality, gender role socialization processes, and issues regarding incremental validity of dark personality over traditional antagonism measures.

A comparison of men’s and women’s perceptions of the female body using a multidimensional scaling analysis of naturalistic stimuli

A comparison of men’s and women’s perceptions of the female body using a multidimensional scaling analysis of naturalistic stimuli. Deana D Diekhoff, George M Diekhoff, Michael A Vandehey. Health Psychology Open, June 5, 2019. https://doi.org/10.1177/2055102919854665

Abstract: Men and women worked with 25 naturalistic photos of females representing varied physiques. Similarity judgments of the photos were analyzed using multidimensional scaling analysis to produce composite maps for male and female participants. A comparison of the maps showed gender similarities and differences. Both genders used almost identical attributes in judging similarities and identified almost identical body types, but men were more inclusive in identifying ideal females; men included curvaceous females that were rejected by women. Women identified very thin females that were rejected by men. Men were affectively most positive toward female ideals; women were most positive to near-ideals.

Keywords: body image, categorical perception, female body ideals, female body perception, multidimensional scaling analysis

Discussion

We found both similarities and differences in men’s and women’s perceptions of the female body, including female ideals. Consider first which perceptual attributes were most salient in their stimulus maps. Men and women in our study were similar in that their perceptions of female bodies were organized using the potency semantic differential dimensions of large-small and masculine-feminine. However, men and women differed in their choice of evaluative dimensions. Men used the more sexually connoted dimension of beautiful-ugly, while women used the sexually neutral dimension of good-bad. Both men’s and women’s maps also showed that size was important in judging female bodies for similarity, as were the three affective reactions of fear, happiness, and disgust. We concluded from all of this that men and women used many but not all the same perceptual filters as they judged female bodies for similarity, except that sexual attractiveness (beautiful-ugly) was more salient for men than women, as might be expected in a predominantly heterosexual population. Men’s and women’s stimulus maps also revealed the use of nearly identical body perception categories. Both men and women used the categories of average, larger size, obese, muscular, underweight, and ideal females. Women added a near-ideal category that was not apparent in the men’s map. Some of these categories were imposed by the researchers’ use of marker stimuli for Average Body and Ideal Body, but the other categories were used spontaneously by our participants. Not only were the body categories nearly identical, the body stimuli that were included in those categories were very similar for men and women. Men and women included exactly the same body stimuli in the larger size, obese, and muscular female body categories. As discussed next, there were some interesting differences in the classification of female body stimuli to the ideal, near-ideal, and average categories.
In the women’s map, only five body stimuli (i.e. 6, 12, 17, 18, 22) were included in the ideal female body cluster; the men’s ideal female cluster included nine stimuli (i.e. 1, 6, 9, 10, 12, 14, 17, 21, 22). Men were more inclusive than women in identifying female ideals. This finding is consistent with Buss’ (2016) observations about men’s choice of partners for casual sexual encounters: “Yet another psychological solution to securing a variety of casual sex partners is men’s relaxation of their standards for acceptable partners … Relaxed standards ensure the presence of more eligible players” (p. 78).
Two body stimuli that women in our study considered average (i.e. 10, 14) were included by men in their ideal category. Three additional stimuli (i.e. 1, 9, 21) that formed a near-ideal cluster in the women’s map (midway between the ideals and the averages) were also included in the ideal cluster by men. Women, but not men, included the very lean stimulus 18 in the ideal cluster. Although some previous studies reported that men and women both preferred the same thin female ideal (Koscinski, 2013; Swami et al., 2010; Willinge et al., 2006), our study showed noticeable gender differences. Men, but not women, identified female stimulus photos as ideal that displayed the classic hourglass shape, wider hips, larger breasts, more body fat, and less muscle definition. In contrast, female bodies that were selected by women as ideal were relatively thin, more athletically fit, with thinner legs, narrow hips, smaller breasts, and increased muscle definition. Put simply, men tended to judge on sexual attractiveness and fitness to deliver children (sexual attractiveness and health). In contrast, women were inclined to judge on physical fitness (health only). This finding confirms other research reflective of women’s preference for a physically fit, healthy ideal (Ahern et al., 2011; Asendorpf et al., 2011; MacNeill and Best, 2015; Stephen and Perera, 2014), but contrasts with Smith et al., 2007) who found no correspondence between female models’ cardiovascular fitness levels and ratings of attractiveness from male and female observers. However, those researchers used a physiological measure of fitness (a 6-minute submaximal cycle ergometry test measuring maximal oxygen consumption) whereas fitness was inferred from visual body characteristics in our study.
One last difference between men’s and women’s perceptions of the ideal female body is suggested by the location of the ideal female cluster along the affective reaction dimensions in the two maps. Both men and women responded with positive affect toward ideal female bodies, but that positivity was somewhat muted among women, who located some non-ideal female stimulus bodies (i.e. 1, 9 10, 14, 21) more positively than their female ideals. In contrast, ideal females were at the maximally positive ends of the affective reaction dimensions in the men’s map. Why would women show less positive affect toward ideal female bodies than near-ideal ideal bodies? The explanation may be found in the literature on mate selection and competition and in appearance-based social comparisons. First, female bodies that are slightly off-ideal present less competition in mate selection than do fully ideal females and would elicit more positive affective responses because of this (Davies and Shackelford, 2017). Second, upward social comparisons (in this study, comparisons of one’s own body to bodies deemed to be more desirable, based on internalized cultural beauty standards) lead to body dissatisfaction, increased negative affect toward the more desirable bodies, and increased body self-surveillance (Feltman and Szymanski, 2018; Janelle et al., 2009; Moreno-Domínguez et al., 2019; Stronge et al., 2015; Thøgersen-Ntoumani et al., 2017).