The Sexual Mind: Exploring the Origins of Arousal

The Sexual Mind: Exploring the Origins of Arousal. Osmo Kontula, May 2021 (Finnish 2017). https://www.vaestoliitto.fi/uploads/2021/05/ccafc96b-sexual-mind_final.pdf

The sexual mind

The sexual mind is always active during the course of our daily lives – if we allow this for ourselves. A substantial portion of the processing of sexually evocative situations takes place in the subconscious. Our awareness of them depends partially on whether we are prepared in the given circumstances and moment to allow ourselves to have sexually charged thoughts. The mind may block this awareness because it is fastened onto something else – perhaps a grave or serious problem that immerses us.

New things are constantly being introduced in our sexual lives, for us to ponder in our various life situations and seek novel ways to implement. Many of us would like to discover ways to increase the pleasure we feel. Others wonder how they might preserve even the smallest spark of passion in their long-term relationship. Many others crave confirmation that they are sexually normal – whatever that means for each individual. Some want solutions to sexual problems, while others would like to understand why their minds and bodies do not travel in tandem with their own expectations of their sexual desire, or with their partner’s desire. The sexual mind presents a major challenge and an enormous opportunity.

The mind is the conduit to the awakening of sexual interest and desire, and launches our individual processes of sexual arousal. The mind comprises both our conscious and unconscious interest in sexual matters. Exploring our own sexual mind helps to open new pathways to sexuality that often remain unknown even to ourselves. The exploration also gives us a deeper understanding of our sexual motives. 

Sexuality is present in our lives from the moment of birth until death. Each of us is an expert in our own sexuality. It is therefore strange that we know the least and have the least awareness of the very things that are most important to us in terms of sexuality – for example, why we are especially captivated by certain sexual phenomena and not others, and why some of them are nearly irresistible to us. [...]

Substantial percentages of people do not want to receive information even when it bears on health, sustainability, & consumer welfare; , substantial percentages of people also do want to receive that information

Sunstein, Cass R. and Reisch, Lucia and Kaiser, Micha, What Do People Want to Know? Information Avoidance and Food Policy Implications (May 4, 2021). SSRN: https://ssrn.com/abstract=3839513

Abstract: What information would people like to have? What information would they prefer to avoid? How does the provision of information bear on welfare? And what does this mean for food policy? Representative surveys in eleven nations find that substantial percentages of people do not want to receive information even when it bears on health, sustainability, and consumer welfare. Nonetheless, substantial percentages of people also do want to receive that information, and people’s willingness to pay for information, contingent on their wanting it, is mostly higher than people’s willingness to pay not to receive information, contingent on their not wanting it. We develop a model and estimate the welfare effects of information provision. We find substantial benefits and costs, with the former outweighing the latter. The results suggest that in principle, policymakers should take both instrumental and hedonic effects into account when deciding whether to impose disclosure requirements for food, whether the domain involves health, safety, or moral considerations. If policymakers fail to consider either instrumental or hedonic effects, and if they fail to consider the magnitude of those effects, they will not capture the welfare consequences of disclosure requirements. Our evidence has concrete implications for how to think about, and capture, the welfare consequences of such requirements with respect to food.

Keywords: Information avoidance, information seeking, willingness to pay, belief-based utility

JEL Classification: D00, D9, D11, D90, D91

The uses and abuses of tree thinking in cultural evolution

The uses and abuses of tree thinking in cultural evolution. Cara L. Evans, Simon J. Greenhill, Joseph Watts, Johann-Mattis List, Carlos A. Botero, Russell D. Gray and Kathryn R. Kirby. Philosophical Transactions of the Royal Society B: Biological Sciences, July 5 2021, Volume 376Issue 1828, online May 17 2021, https://doi.org/10.1098/rstb.2020.0056

Abstract: Modern phylogenetic methods are increasingly being used to address questions about macro-level patterns in cultural evolution. These methods can illuminate the unobservable histories of cultural traits and identify the evolutionary drivers of trait change over time, but their application is not without pitfalls. Here, we outline the current scope of research in cultural tree thinking, highlighting a toolkit of best practices to navigate and avoid the pitfalls and ‘abuses' associated with their application. We emphasize two principles that support the appropriate application of phylogenetic methodologies in cross-cultural research: researchers should (1) draw on multiple lines of evidence when deciding if and which types of phylogenetic methods and models are suitable for their cross-cultural data, and (2) carefully consider how different cultural traits might have different evolutionary histories across space and time. When used appropriately phylogenetic methods can provide powerful insights into the processes of evolutionary change that have shaped the broad patterns of human history.

1. Introduction

Theories of cultural evolution are built on the observation that cultural features undergo innovation, modification and transmission. Over time, these processes have generated remarkable variation in human cultures. Humans speak around 7000 distinct languages, affiliate with hundreds of religions, employ a range of kinship systems, engage in an array of subsistence practices and adhere to a bewildering number of social conventions [1]. Phylogenetic methods provide a powerful approach to studying macro-evolutionary patterns of innovation, modification and transmission [2–4]. Their application to human culture has helped reinvigorate cross-cultural comparative research but has also been subject to criticism—both valid and misguided.

Phylogenies, also known as evolutionary trees, represent the common ancestry of populations and the splitting events that have occurred over the course of their history. Phylogenetic methods encompass a broad family of mathematical approaches that can be used to construct, analyse and incorporate phylogenies (figure 1). Originally developed to study the evolution of biological organisms, these methods offer a general toolkit with the potential to provide answers to a range of cultural evolutionary questions.

Figure 1. Phylogenetic methods that can be used to study cultural macro-evolution. Black arrows indicate that the preceding methodological steps are directly incorporated in later methods: (a) tree construction [5] is required for all subsequent steps; (b) testing for phylogenetic signal (e.g. [6–8]) forms an integral part of phylogenetic regression (e.g. [9–11]), which in turn forms the basis of phylogenetic path analysis which can identify causal relationships; (c) ancestral state reconstruction (e.g. [12]), estimated in conjunction with rates of trait change and transformation (e.g. [13,14]), is required for models of trait correlation [15–17] and diversification ([18,19]; but see [20]). Red arrows indicate that suitable tests of phylogenetic signal (i.e. that the trait data fit sufficiently to the history inferred by the tree) should be conducted by the researcher before using methods detailed in (c); (see also §2). Shading: grey shading indicates methods that both assume and require inferred historical relationships between the cultural units (tree taxa) to sufficiently reflect the history of the trait; green shading denotes methods that detect and quantify tree-like structure in cross-cultural data; blue shading denotes methods that detect and control for tree-like data structure among societies, but do not require it.

An important distinction in cultural phylogenetics research is between methods of building trees (i.e. reconstructing the histories of cultural units based on assumptions of vertical transmission of cultural features (traits); figure 1a) and methods that use previously constructed trees in models that investigate the evolution and distribution of other cultural traits (figure 1b-c). A further important division in tree thinking occurs between those methods and questions that simply detect and control for tree-like structure when examining variation in cross-cultural data (e.g. What does the distribution of traits among societies tell us about the history of those societies and/or traits? Does horizontal or vertical transmission better explain the observed distribution of traits?figure 1b), and those methods that require that the modelled data are tree-like (i.e. methods that ask: What was the ancestral form of a cultural feature?figure 1c).

Phylogenetic methods offer exciting possibilities for a wide range of questions, only some of which explicitly require tree-like data. For data that are sufficiently tree-like, one of the strongest appeals of phylogenetic methods is that they offer the possibility to illuminate the unobservable past. Phylogenetic methods can reconstruct the ancestry of a vertically transmitted trait from the evolutionary signatures detected in its present-day distribution, even when archaeological records are entirely unavailable. However, despite this exciting potential, debate continues over how best to integrate cultural heterogeneity, disentangle the signatures of vertical transmission, horizontal diffusion and local socio-ecological drivers, and demonstrate that a cultural trait exhibits enough tree-like structure to justify using methods that reconstruct its evolutionary past.

Here, we review the application of phylogenetic methods in cross-cultural research. We focus specifically on the questions researchers should ask in order to avoid common methodological pitfalls when (i) deciding about the units of the underlying cultural data, (ii) constructing trees and (iii) assuming tree-like transmission of other cultural features. Throughout, we outline a series of best practices and highlight emerging methods that promise to advance our understanding of macro-evolutionary patterns of mechanism and causation in culture.

Girls know how to choose: Fathers lived in larger cities, had higher education, were heavier and taller , more attractive & masculine, had lighter eyes, darker hair, & were more agreeable, conscientious, & emotionally stable than non-fathers

She Always Steps in the Same River: Similarity Among Long-Term Partners in Their Demographic, Physical, and Personality Characteristics. Zuzana Štěrbová, Petr Tureček and Karel Kleisner. Front. Psychol., February 5 2019. https://doi.org/10.3389/fpsyg.2019.00052

Abstract: In mate choice, individuals consider a wide pool of potential partners. It has been found that people have certain preferences, but intraindividual stability of mate choice over time remains little explored. We tested individual consistency of mate choice with respect to a number of demographic, physical, and personality characteristics. Only mothers were recruited for this study, because we wanted to find out not only whether women choose long-term partners with certain characteristics but also whether the father of their child(ren) differs from their other long-term (ex-)partners. Women (N = 537) of 19–45 years of age indicated the demographic, physical (by using image stimuli), and personality characteristics of all of their long-term partners (partners per respondent: mean = 2.98, SD = 1.32). Then we compared the average difference between an individual’s long-term partners with the expected average difference using a permutation test. We also evaluated differences between partners who had children with the participants (fathers) and other long-term partners (non-fathers) using permutation tests and mixed-effect models. Our results revealed that women choose long-term partners consistently with respect to all types of characteristics. Although effect sizes for the individual characteristics were rather weak, maximal cumulative effect size for all characteristics together was high, which suggests that relatively low effect sizes were caused by high variability with low correlations between characteristics, and not by inconsistent mate choice. Furthermore, we found that despite some differences between partners, fathers of participants’ child(ren) do fit their ‘type’. These results suggest that mate choice may be guided by relatively stable but to some degree flexible preferences, which makes mate choice cognitively less demanding and less time-consuming. Further longitudinal studies are needed to confirm this conclusion.

Results

Mate choice consistency was higher than expected in all assessed qualities except for facial masculinity and beardedness. Difference between observed and expected consistency was statistically significant in most qualities, but effect sizes differed substantially. While consistency of mate choice in residence or weight was substantial, it was only medium-sized or small with respect to hair or eye color. Complete results are summarized in Table 1 and Figure 1.

Table 1. Mate choice consistency: complete results.

Figure 1. Visualization of permutation tests of mate choice consistency centered around observed image and normalized along the SD of expected image distribution. Difference between the observed and expected value is expressed in standard deviations from the expected value distribution. The higher the bell curve above the Observed image value, the higher the actual mate choice consistency. Bell curve below Observed image value indicates a trait where the observed mate choice was less consistent than expected.

The average effect size was highest in demographic variables, but none of the pairwise comparisons between groups of variables (demographic, physical, and psychological) was statistically significant (p > 0.1). Permutation test results are visualized in Figure 1. All sample sizes and descriptive statistics of all variables are listed in the Appendix. The different estimates of effect size were highly correlated. The proportion of males who had to be relocated between respondents correlated with the variance accounted for by the respondent at 0.93, whereby a linear model of relationship between these two measures supports the idea that the latter is approximately double of the former. The slope in the model where respondent-attributable variance regressed on the proportion of partners to relocate was 2.08 (95% CI = 1.72–2.45) with minimal (not significantly different from 0) intercept of -0.18 (95% CI = -3.19–2.83). Results yielded by the simple Pearson correlation correlated at 0.91 with the percentage of partners to relocate and at 0.98 with respondent-attributable variance. All of these measures can be thus treated as functionally equivalent.

Links between pairs of partners’ qualities are summarized in Table 2. In total, 103 out of 210 correlations were significant even after Benjamini–Hochberg correction for multiple comparisons. Maximal cumulative effect size was 50.95% (expressed in the proportion of partners to switch between individuals). The first 10 variables ordered according to their unique contribution starting with the highest (residence, weight, relative height, age difference, attractiveness, hair color, openness, BMI, height, agreeableness, in this order) explained 48.30% of partner assignment. The other 11 variables contributed little (their unique contributions were less than 1%) or not at all (after the inclusion of all other variables, facial masculinity and beardedness failed to show any positive numbers). Full results are visualized in Figure 2.

Table 2. Relations between investigated qualities of romantic partners expressed in shared effect sizes and Pearson correlations.

Figure 2. Visualization of maximal cumulative effect size. Variables are added in order given by maximal unique contribution to overall consistency.

Reaching maximal possible effect size suggests that adding yet other variables to a similar model of cumulative consistency would add little to our current sum. On the other hand, it is conceivable that one might select precisely those variables which are not intercorrelated and explain a majority of mate choice consistency in just a handful independent dimensions. In theory, complex interaction patterns may lead to an even higher cumulative effect size since 50% of partners to relocate as an effect size limit applies to a single variable with two levels and represents the difference between maximal and minimal consistency (i.e., not maximal and expected). The high proportion of significantly correlated pairs of variables (49%), does, however, fit well within the impression of a substantial redundancy in our model.

Permutation test of changes in mate choice consistency revealed that fathers are significantly exceptional amongst participants’ long-term partners in beardedness, muscularity, hirsuteness, extraversion, and openness. The average image without these individuals was lower than the image in permutation runs where an equivalent proportion of random partners (i.e., fathers and non-fathers) was excluded. Fathers were not significantly typical long-term partners in any of the assessed qualities. Complete results of these tests are summarized in Table 3 and visualization is provided in Figure 3.

Table 3. Permutation test of father exceptionality, complete results.

Figure 3. Visualization of permutation tests of father exceptionality centered around the observed image when fathers were excluded from the sample of partners and normalized along the SD of expected image distribution in such a situation. Difference between observed and expected values is expressed in standard deviations of expected value distribution. The higher the bell curve above the observed image value, the more exceptional were the fathers among the long-term partners of an individual. Bell curve below the observed image value indicates a trait where fathers were more typical representatives of an individual’s long-term partners.

In qualities where fathers were indicated as exceptional individuals (except for extraversion), mean trait values differed between fathers and non-fathers, while variances differed in beardedness, muscularity, and hirsuteness. Fathers were more bearded, hairier, more muscular, and showed a higher openness to experience. These differences might explain the overall exceptionality of fathers except for extraversion. It seems that fathers are outliers within partner sets even where the group means and variances of father and non-father sets do not differ. Moreover, fathers lived in larger cities, had higher education, were heavier and taller (although relatively, their height was closer to the height of respondents), more attractive and masculine, had lighter eyes, darker hair, more masculine faces, and were more agreeable, conscientious, and emotionally stable than non-fathers.

Group variances differed in several qualities. Fathers were significantly more variable than non-fathers with respect to age difference from the respondent and less variable in attractiveness, masculinity (general and facial), BMI, conscientiousness, and agreeableness. It seems that along these variables, either or both of the extremes are not the right for the ‘father material’. A graphic overview which compares densities that indicate differences between group means and variances is presented in Figure 4. Complete results in a textual form are listed in Table 4.

Figure 4. Visualization of differences between fathers and non-fathers. Significance of difference between group means and variances is estimated from mixed effect models with respondent ID treated as a random factor. Significance levels are indicated as follows: ∗p < 0.05, ∗∗p < 0.01, ∗∗∗p < 0.001.

Table 4. Results of Mixed effect models comparing father/non-father means and variances.

Bias Is a Big Problem, But So Is ‘Noise’

Bias Is a Big Problem. But So Is ‘Noise.’ Daniel Kahneman, Olivier Sibony and Cass R. Sunstein. TNYT, May 15, 2021. https://www.nytimes.com/2021/05/15/opinion/noise-bias-kahneman.html

The word “bias” commonly appears in conversations about mistaken judgments and unfortunate decisions. We use it when there is discrimination, for instance against women or in favor of Ivy League graduates. But the meaning of the word is broader: A bias is any predictable error that inclines your judgment in a particular direction. For instance, we speak of bias when forecasts of sales are consistently optimistic or investment decisions overly cautious.

Society has devoted a lot of attention to the problem of bias — and rightly so. But when it comes to mistaken judgments and unfortunate decisions, there is another type of error that attracts far less attention: noise.

To see the difference between bias and noise, consider your bathroom scale. If on average the readings it gives are too high (or too low), the scale is biased. If it shows different readings when you step on it several times in quick succession, the scale is noisy. (Cheap scales are likely to be both biased and noisy.) While bias is the average of errors, noise is their variability.

Although it is often ignored, noise is a large source of malfunction in society. In a 1981 study, for example, 208 federal judges were asked to determine the appropriate sentences for the same 16 cases. The cases were described by the characteristics of the offense (robbery or fraud, violent or not) and of the defendant (young or old, repeat or first-time offender, accomplice or principal). You might have expected judges to agree closely about such vignettes, which were stripped of distracting details and contained only relevant information.

But the judges did not agree. The average difference between the sentences that two randomly chosen judges gave for the same crime was more than 3.5 years. Considering that the mean sentence was seven years, that was a disconcerting amount of noise.

Noise in real courtrooms is surely only worse, as actual cases are more complex and difficult to judge than stylized vignettes. It is hard to escape the conclusion that sentencing is in part a lottery, because the punishment can vary by many years depending on which judge is assigned to the case and on the judge’s state of mind on that day. The judicial system is unacceptably noisy.

Consider another noisy system, this time in the private sector. In 2015, we conducted a study of underwriters in a large insurance company. Forty-eight underwriters were shown realistic summaries of risks to which they assigned premiums, just as they did in their jobs.

How much of a difference would you expect to find between the premium values that two competent underwriters assigned to the same risk? Executives in the insurance company said they expected about a 10 percent difference. But the typical difference we found between two underwriters was an astonishing 55 percent of their average premium — more than five times as large as the executives had expected.

Many other studies demonstrate noise in professional judgments. Radiologists disagree on their readings of images and cardiologists on their surgery decisions. Forecasts of economic outcomes are notoriously noisy. Sometimes fingerprint experts disagree about whether there is a “match.” Wherever there is judgment, there is noise — and more of it than you think.

Noise causes error, as does bias, but the two kinds of error are separate and independent. A company’s hiring decisions could be unbiased overall if some of its recruiters favor men and others favor women. However, its hiring decisions would be noisy, and the company would make many bad choices. Likewise, if one insurance policy is overpriced and another is underpriced by the same amount, the company is making two mistakes, even though there is no overall bias.

Where does noise come from? There is much evidence that irrelevant circumstances can affect judgments. In the case of criminal sentencing, for instance, a judge’s mood, fatigue and even the weather can all have modest but detectable effects on judicial decisions.

Another source of noise is that people can have different general tendencies. Judges often vary in the severity of the sentences they mete out: There are “hanging” judges and lenient ones.

A third source of noise is less intuitive, although it is usually the largest: People can have not only different general tendencies (say, whether they are harsh or lenient) but also different patterns of assessment (say, which types of cases they believe merit being harsh or lenient about). Underwriters differ in their views of what is risky, and doctors in their views of which ailments require treatment. We celebrate the uniqueness of individuals, but we tend to forget that, when we expect consistency, uniqueness becomes a liability.

Once you become aware of noise, you can look for ways to reduce it. For instance, independent judgments from a number of people can be averaged (a frequent practice in forecasting). Guidelines, such as those often used in medicine, can help professionals reach better and more uniform decisions. As studies of hiring practices have consistently shown, imposing structure and discipline in interviews and other forms of assessment tends to improve judgments of job candidates.

No noise-reduction techniques will be deployed, however, if we do not first recognize the existence of noise. Noise is too often neglected. But it is a serious issue that results in frequent error and rampant injustice. Organizations and institutions, public and private, will make better decisions if they take noise seriously.

“Brave Men” and “Emotional Women”: A Theory-Guided Literature Review on Gender Bias in Health Care and Gendered Norms towards Patients with Chronic Pain

From Feb 2018... “Brave Men” and “Emotional Women”: A Theory-Guided Literature Review on Gender Bias in Health Care and Gendered Norms towards Patients with Chronic Pain. Anke Samulowitz et al. Pain Research and Management, Volume 2018 |Article ID 6358624, Feb 2018. https://doi.org/10.1155/2018/6358624

Abstract

Background. Despite the large body of research on sex differences in pain, there is a lack of knowledge about the influence of gender in the patient-provider encounter. The purpose of this study was to review literature on gendered norms about men and women with pain and gender bias in the treatment of pain. The second aim was to analyze the results guided by the theoretical concepts of hegemonic masculinity and andronormativity.

Methods. A literature search of databases was conducted. A total of 77 articles met the inclusion criteria. The included articles were analyzed qualitatively, with an integrative approach.

Results. The included studies demonstrated a variety of gendered norms about men’s and women’s experience and expression of pain, their identity, lifestyle, and coping style. Gender bias in pain treatment was identified, as part of the patient-provider encounter and the professional’s treatment decisions. It was discussed how gendered norms are consolidated by hegemonic masculinity and andronormativity.

Conclusions. Awareness about gendered norms is important, both in research and clinical practice, in order to counteract gender bias in health care and to support health-care professionals in providing more equitable care that is more capable to meet the need of all patients, men and women.

5. Discussion

The purpose of this study was to review and condense literature on gendered norms about men and women with pain, gendered norms about how men and women with pain cope with their daily life, and gender bias in the treatment of pain. In the following, main findings are discussed and analyzed with theories related to the concepts andronormativity and hegemonic masculinity.

Among the main findings in this review was a distinct pattern of gendered norms described in pain literature, in line with hegemonic masculinity, that distinguished men’s and women’s perceptions, expressions, and coping with chronic pain. For instance, men were presented as being stoic, in control, and avoiding seeking health care [45, 46]. Women, on the other hand were presented as being more sensitive to pain and more willing to show and to report pain [62, 63], compared to men. These overall findings confirm a pattern of separation between men and women, not embedded in biological differences but gendered norms. The dichotomy between men and women has been described as a way to establish and maintain the gender order, allowing men’s dominance over women [33]. That women were described in comparison to men can also be seen as a proof for andronormativity in health care, stressing that men, and health problems more often present in men, tend to be considered as the norm, while women (and other social groups outside the norm) are seen as irregularities. Since men are the norm and perceived as being “normal,” women are compared to them. Although women have more pain than men [3, 7] and dominate most chronic pain diagnoses [3, 7], they are described in comparison to men, as being deviant from the norm, even when they are in majority.

Another main finding was the pattern of andronormativity in relation to certain pain diagnoses. There are conditions where pain is the only reported symptom. Those conditions are highly dominated by women and have been described as difficult to fit in to the traditional bioscientific medical system [69, 70]. They have low status in the medical hierarchy of diagnoses [35], and women with those diagnoses are often questioned as patients [69, 83]. The concept of andronormativity implies that men and masculinity dominate health care to such an extent that women and femininity become invisible. Our results showed that symptoms in women-dominated conditions that do not fit the masculine norm actually seem to be invisible. The definitions of these conditions in the reviewed studies have focused on the absence of medically provable signs, for example, “pain in the absence of diagnostic evidence” or “pain without organic pathology.” Accordingly, those conditions were not defined in their own terms but in terms of what they lack—in relation to the predominant medical norm. Interestingly, even women with those “medically unexplained” conditions have been treated as if their illness does not exist. Our results showed that those women have been described as “malingerers” or as “if the pain is all in her head” [49, 71]. An interesting finding worthy of future elaborations is that those pain conditions, which are predominantly suffered by women, are underexplored, and portrayed as a challenge for medicine [47, 70]. It would also be interesting to further investigate if the key for change lies in the dichotomous construction of gender, which can lead to different diagnoses given to men and women, despite equal needs or in the masculine stamp of bioscientific health care, which can lead to different approaches to high- and low-status diagnoses.

Another major finding is that women’s pain in the reviewed studies was psychologized [13, 72]. According to hegemonic masculinity, psychological strain is feminine coded and at the same time down-valued in comparison to somatic conditions [32]. Consequently, when their pain condition is psychologized by health-care providers, women can feel that their pain is down-valued or dismissed, which in turn can cause stress [82]. Stress cues can, in turn, lead health-care providers to take patients’ pain less serious [82], thus leading to a vicious circle. As long as stress and psychological strain are feminine coded, and a hierarchy between somatic and psychological findings exists in health care, there is a risk that not only the dichotomy between men’s and women’s pain, but also between somatic and psychological conditions is further consolidated.

Even men with chronic pain have to deal with hegemonic masculinity in health care. Physical strength is idealized in hegemonic masculinity, in opposition to weakness [33]. Chronic pain per se is a threat to idealized masculinities as pain generally goes along with loss of muscle strength. Our results indeed showed that physical strength was central for men’s gender identity, whereas weakness threatened it [54, 55], and that men with chronic pain risked to be perceived as more feminine than the typical man [50]. Imbedded in hegemonic masculinity is a competition for dominance among men, and the threat of losing masculinity is a threat of losing power [33]. Men in the reviewed studies showed different strategies, like denial and rejection, to deal with what could be described as a threat of losing masculinity ideals. An example is ignoring or questioning the diagnosis, or not following clinicians’ advice [48, 54]. Another interesting finding was that men according to the reviewed studies explained their pain with factors from outside, beyond their control [46, 57]. This may be a way for men to express that pain is not a part of them and their identity and could be understood as the attempt to keep the position as a masculine man by separating the feminine coded pain from the masculine man.

A recurrent finding in the studies reviewed was women’s struggle to try to handle pain and multiple demands from their surroundings simultaneously [75, 76]. Traditionally, as part of the gender order, women are responsible for their home and family and to take care of themselves. However, our results showed that an overload of responsibility for family, work, household, their pain, and their wellbeing seemed to be an obstacle for recovery for women with pain [49, 87]. Our results also showed that health-care providers considered it important that women learn to say “no” to demands from others [75]. Even if this may be thought as an attempt to lower women’s overload of responsibility, it can actually increase women’s responsibility [75]. This could be explained by hegemonic masculinity, where the subordinate part is expected to conform to the prevailing norm, making women responsible to solve their issue and also being responsible for the outcome. The consequences of hegemonic masculinity can increase the burden on women with chronic pain, as the reviewed studies showed.

In summary, our results confirmed a paradox, highlighted by Hoffmann and Tarzian [13]; compared to men, women have more pain, and it is more accepted for women to show pain, and more women are diagnosed with chronic pain syndromes. Yet, paradoxically, women’s pain reports are taken less seriously [13, 71, 78], their pain is discounted as being psychic or nonexistent [69, 70, 72], and their medication is less adequate than treatment given to men [2, 96]. This has been described as a paradox [13] but can be explained as an expression for hegemonic masculinity and andronormativity in health care.

5.1. The Relation between Gendered Norms and Gender Bias

Several researchers [2, 3] have emphasized the risk of gender bias in the treatment of pain; however, studies that demonstrated objectively measurable gender bias in medical treatment were less extensive and less consistent. Subjectivity in the assessment of pain makes pain experiences and pain treatment sensitive to gender norms [2, 12]. In addition, it is also reasonable to conclude that the subjectivity makes it difficult to prove malpractice related to gender. Nevertheless, when we searched for gender bias in pain, we found studies that showed that women received less adequate pain medication and more antidepressants compared to men [86, 98]. In addition, a pattern of parallels between gendered norms and gender bias could be demonstrated in the results. For example, gendered norms were expressed through presumptions such as “women are more emotional than men” [49, 71]. The psychologizing of women’s pain [13, 70] reflects this norm, and that antidepressants are more often described to women compared to men [22, 97] could be a consequence of it.

5.2. Consequences of Gendered Norms in Health Care

The notion of men and women as separate and different in manners and needs is problematic [106], as it can consolidate gendered norms, which in turn can lead to individual needs being overlooked [106]. Health is constituted within a wide range of gender-related experiences [106]. The patient-provider relation is one domain for constitution, reinforcement, or challenge of gendered norms, where andronormativity and hegemonic masculinity can cause health-care providers to treat men and women based on gendered norms rather than individual needs. For instance, gender norms like “men need to be physically strong” [43, 54, 58] can lead to the presumption that active leisure time is more important for men than for women, which in turn can lead health-care professionals to recommend men, but not women, to continue with sport activities despite their pain [54, 85]. Or, as another example, if women are seen as the primary care giver and responsible for family and household [49, 58, 71, 80], this can lead professionals to recommend women, but not men, to prioritize family above work and leisure time [22, 58]. Increased awareness of gendered norms and potential gender bias is a prerequisite to counter gender bias in health care [20]. There is a power imbalance between men and women, and many (though not all) gender biases are to women’s disadvantage [20]. However, both men and women are restricted by gendered expectations, and both men and women profit from more equitable care [3, 20].

5.3. Methodological Considerations

This review was theory-guided with a preunderstanding that gendered norms exist in health care, which has influenced the selection of our search terms. Our directed literature search might be criticized as it potentially excluded studies that did not find/report gender differences. However, the aim of this study was not to prove if gendered norms in health care exist, which earlier research already has shown [2, 3, 13], but to collect and analyze gendered norms and gender bias as described in pain literature and deepen the knowledge about them. Our results support the idea that there is hegemonic masculinity and andronormativity in health care, and several patterns of gendered norms and consequences thereof could be explained by hegemonic masculinity and andronormativity. It might be important to underline that these theoretical concepts were not chosen in advance but found applicable after the categorization and analysis of the reviewed studies.

Another concern addresses the large number of included studies, providing a risk for fragmentation and selective interpretation of their content. This was balanced by the coding in three distinct and clearly defined theoretical categories, which provided a tight framework for the selection of relevant material [39, 42]. All authors discussed and agreed also on all categories. The descriptive basis of the substantive categories allowed to capture different patterns. There might be other patterns to be found in the reviewed studies. However, our findings were consistent throughout the reviewed studies and provided new insights, which should be further examined in both qualitative and quantitative studies.

A common dilemma in gender research involves how to create awareness about stereotypes without confirming or reinforcing them [40]. The purpose of this study was to challenge stereotypes about men and women, not to emphasize the differences. Gender norms are not the only norms that influence treatment decisions and patient-provider relations in health care. For instance, presumptions on age, race, and educational level have an impact on pain and intersect with each other and with gender [3, 97, 102], which is an important field for further elaboration.

Across 48 nations we found age-related increases in self-esteem from late adolescence to middle adulthood and significant gender gaps, with males consistently reporting higher self-esteem than females

Bleidorn, W., Arslan, R. C., Denissen, J. J. A., Rentfrow, P. J., Gebauer, J. E., Potter, J., & Gosling, S. D. (2016). Age and gender differences in self-esteem—A cross-cultural window. Journal of Personality and Social Psychology, 111(3), 396–410, May 2021. https://doi.org/10.1037/pspp0000078

Research and theorizing on gender and age differences in self-esteem have played a prominent role in psychology over the past 20 years. However, virtually all empirical research has been undertaken in the United States or other Western industrialized countries, providing a narrow empirical base from which to draw conclusions and develop theory. To broaden the empirical base, the present research uses a large Internet sample (N = 985,937) to provide the first large-scale systematic cross-cultural examination of gender and age differences in self-esteem. Across 48 nations, and consistent with previous research, we found age-related increases in self-esteem from late adolescence to middle adulthood and significant gender gaps, with males consistently reporting higher self-esteem than females. Despite these broad cross-cultural similarities, the cultures differed significantly in the magnitude of gender, age, and Gender × Age effects on self-esteem. These differences were associated with cultural differences in socioeconomic, sociodemographic, gender-equality, and cultural value indicators. Discussion focuses on the theoretical implications of cross-cultural research on self-esteem.

Discussion

Two highly influential lines of past research have established that self-esteem is higher in men than in women (Kling et al., 1999) and that self-esteem increases from adolescence to middle adulthood (Orth & Robins, 2014). Yet, that prior research was overwhelmingly confined to Western cultures; this bias throws doubt on the generality of the patterns and potentially undermines attempts to understand the mechanisms driving gender and age differences in self-esteem. To begin to address this concern, we examined the cross-cultural generalizability of the gender and age trends in self-esteem across 48 nations. Specifically, we examined three questions concerning the cultural generalizability, cultural variability, and cultural correlates of gender, age, and Age  Gender effects on self-esteem. Consistent with previous research on Western samples, we found significant gender and age differences in self-esteem: Across all nations, men had higher levels of self-esteem than women did and both genders showed age-graded increases from late adolescence to middle adulthood. Both the shape and the average effect sizes for gender and age effects resembled previous findings and ranged between small to medium-sized effects (cf. Kling et al., 1999; Huang, 2010). The considerable degree of cross-cultural similarity has two major implications. First, it suggests that prior conclusions on gender and age differences in self-esteem are not some peculiarity of Western societies. Second, it might indicate that the normative gender and age differences in self-esteem are at least partly driven by universal mechanisms (Costa et al., 2001; Wood & Eagly, 2002). One such mechanism might be genetically based biological processes that transcend cultures and contexts. To date, only a few studies have examined biological sources, such as hormonal influences, of gender differences in self-esteem (Williams & Currie, 2000). Even fewer studies have examined potential biological explanations for age differences in self-esteem. This lack of research on the biological background of gender and age differences in self-esteem is surprising because global self-esteem shares many attributes with other broad personality characteristics for which biological explanations for gender and age differences, such as age-graded genetic influences, have been tested (e.g., Bleidorn, Kandler, Riemann, Angleitner, & Spinath, 2009; Kandler et al., 2010; for reviews see Bleidorn, Kandler, & Caspi, 2014; Briley & Tucker-Drob, 2014). The findings of the present research suggest that genetically based mechanisms might also play a role in the normative development of men’s and women’s self-esteem. Genetically informative studies and research on the biological pathways would be needed to shed light on the biological underpinnings of gender and age differences in self-esteem. An alternative explanation for the cross-cultural similarity would be that gender and age differences are largely influenced by universal sociocultural factors. For example, pancultural gender differences might result from universals in socially learned gender roles and stereotypes (Williams & Best, 1990; Wood & Eagly, 2002). In fact, several studies have shown that male attributes are positively correlated with self-esteem for both men and women, whereas the link between female attributes and self-esteem has been much weaker and less consistent (e.g., Gebauer, Wagner, Sedikides, & Neberich, 2013; Whitley, 1983; Wojciszke, Baryla, Parzuchowski, Szymkow, & Abele, 2011). In a similar vein, the majority of individuals in most cultures master relatively similar life tasks at roughly the same ages (e.g., graduation from school, one’s first job, parenthood). Such developmental turning points (Pickles & Rutter, 1991) can modify or redirect life trajectories by altering behavior, affect, cognition, or context and might be also relevant with regard to an individual’s self-esteem development (Orth & Robins, 2014). When these age-graded turning points are universal, they can produce the observed cross-cultural similarity in age differences in self-esteem. For example, during early and middle adulthood, individuals in many cultures increasingly engage in instrumental and social roles, such as professional, spouse, parent, or political party member. A successful mastery of new role demands and the socioemotional feedback associated with these social roles might convey a sense of self-worth and also lead to increases in self-esteem (e.g., Hogan & Roberts, 2004; Robins et al., 2002). For instance, a successful mastery of the challenges associated with the first job may boost young adults’ sense of mastery and consequently also lead to increased levels of self-esteem (Chung et al., 2014; Erol & Orth, 2011). Likewise, several studies have found that the transition to the first long-term romantic relationship is related to self-esteem development in young adults (Lehnart et al., 2010; Wagner, Becker, Lüdtke, & Trautwein, 2015). Despite the cross-cultural similarity in the overall pattern of gender and age differences, the 48 nations still differed significantly in the magnitude of the gender-specific trajectories. These cross-cultural differences in gender, age, and Age  Gender effects are inconsistent with strong universal explanations and suggest the relevance of culture-specific influences. In the present study, we adopted an exploratory perspective and examined the potential influences of a diverse set of 12 socioeconomic, sociodemographic, gender-equality, and cultural-value indicators. Overall, many of these cultural moderators did matter, albeit to a moderate degree (https://selfesteem.shinyapps.io/self_esteem). Specifically, gender differentiation was related to a nation’s GDP per capita, HDI, and mean age at marriage. Gender differentiation was also related to all Hofstede dimensions, except, perhaps surprisingly, masculinity. Overall, wealthy, developed, egalitarian, and individualistic nations were characterized by relatively larger gender differences in self-esteem. The above-described pattern is in line with previous crosscultural research on gender differences in Big Five personality traits. One potential explanation for the finding that the personality profiles of men and women tend to be less similar in more developed, prosperous, and egalitarian cultures was that different innate dispositional differences between men and women may have more space to develop in such cultures (Schmitt et al., 2008). An alternative explanation for this seemingly counterintuitive finding has been offered by Guimond et al. (2007). They proposed that cultural differences in the magnitude of gender differences in personality traits and other psychological constructs are partly the result of social comparison processes. Specifically, Guimond et al. (2007) predicted larger gender differences for cultures in which people are more likely to engage in between-gender social comparisons, because comparisons with other-gender individuals presumably induce self-stereotyping processes. In contrast, gender differences were supposed to be smaller in cultures in which people are more likely to engage in within-gender social comparisons because comparisons with same-gender individuals would reduce self-stereotyping processes. Guimond et al. compared samples from five different cultures with regard to their socialcomparison orientation and found that individuals from Western countries are more likely to engage in in between-gender social comparisons and, as a result, show larger gender differences than individuals from non-Western cultures. In the present study, we found particularly small gender differences in many Asian countries, such as Thailand or China, whereas gender differences tended to be generally larger in many Central and South American countries, such as Mexico or Chile (cf. Figure 2). Research on social comparison processes in these countries might help to further understand the role of within-gender versus betweengender social comparisons for the magnitude of gender differences in self-esteem. Another explanation of the larger gender differences in many Western societies concerns the cultural emphasis of girls’ and women’s physical appearance. Both males and females who feel physically attractive tend to have higher self-esteem (e.g., Feingold, 1994); yet numerous studies have shown that girls’ attitudes about their appearance become more negative during adolescence (Harter, 1993). This decline in girl’s perceived physical attractiveness is supposed to have particularly negative effects on selfesteem when cultural pressures regarding women’s physical appearance are high (Brumberg, 1997; Kling et al., 1999). Future research on cultural-beauty ideals and self-esteem would be needed to test this hypothesis in a cross-cultural research design. There were also significant cross-level interactions involving the age and Age  Gender effects on self-esteem. Specifically, for individualistic, prosperous, egalitarian, and developed nations with a lower adolescent birthrate and a later age at marriage, we found relatively smaller age effects on self-esteem for men but not for women (e.g., Norway). Moreover, we found more pronounced age effects on self-esteem for women from nations with greater gender equality and a longer history of women’s suffrage (e.g., Sweden or Finland). This finding implies that, in these nations, gender differences in self-esteem tend to become smaller with age. In contrast, even though the absolute gender gap is smaller in developing and less wealthy nations, the gender differences tend to become larger with age in these cultures. For example, in Australia—a nation with relatively high HDI and GDP scores—the absolute gender difference decreases from d  0.30 in adolescence to d  0.21 in middle adulthood. For Mexico—a nation with comparatively lower HDI and GDP scores—the absolute gender difference in self-esteem increases from d  0.24 in adolescence to d  0.35 (https://selfesteem.shinyapps.io/maps/). This pattern suggests that the gender-specific age trajectories of self-esteem are likely the result of distinct culture-specific, agegraded mechanisms, which are not necessarily related to the mechanisms that lead to the absolute gender differences in self-esteem. Consider, for example, the mechanisms that might underlie the effects of cultural differences in gender equality. Gender equality was unrelated to the absolute gender gap in self-esteem but positively correlated with steeper age effects on women’s self-esteem. In countries with less traditional gender roles and smaller genderbased gaps in economic participation, education, political empowerment, and health (e.g., Sweden, Norway, or Finland; cf. Table 1 and Figure 2), women are more likely to have access to status positions and instrumental roles, to experience a sense of mastery, and to receive appreciation and social support. As a consequence, women from countries with greater gender equality might show relatively stronger age-graded increases in self-esteem as they traverse early and middle adulthood. In summary, cultural differences in gender, age, and Age  Gender effects on self-esteem are systematically related to a broad set of socioeconomic, sociodemographic, gender-equality, and cultural value indicators. Specifically, individualistic, prosperous, egalitarian, developed nations with greater gender equality, lower adolescent birth rates and a later age at marriage are marked by larger gender gaps, which tend to decrease throughout early and middle adulthood. In contrast, collectivistic, poorer, developing nations with greater gender inequality, higher adolescent birth rates, and an earlier age at marriage are marked by smaller gender gaps, which tend to increase throughout early and middle adulthood. This pattern is likely the result of multiple macropsychological mechanisms that guide culture-specific self-esteem development in men and women. To shed more light on the nature and operation of these macropsychological mechanisms, longitudinal studies are needed that track self-esteem development over time in nonWestern societies.

Those who see themselves as less attractive might be willing to reject more attractive partners as a protective strategy

Harper, Kaitlyn, Fiona Stanley, Morgan Sidari, Anthony J. Lee, and Brendan P. Zietsch. 2021. “The Role of Accurate Self-assessments in Optimising Mate Choice.” PsyArXiv. March 23. doi:10.31234/osf.io/4qmuv

Abstract: Individuals are thought to seek the best possible romantic partner in exchange for their own desirability. We investigated the strategies that individuals use when choosing a partner, and whether these strategies optimise the quality of mutually interested partners (‘matches’). Further, we investigated whether these matching outcomes were affected by the accuracy of one’s self-perceived mate value. Participants (1501 total) took part in a speed dating experiment whereby they rated themselves and others on attractiveness variables and indicated their willingness to date each opposite sex partner they interacted with. We then calculated participants’ selectivity, minimum and maximum standards, accuracy, match quality, and match quantity. Individuals were somewhat accurate in their self-evaluations, and these self-evaluations guided individual’s minimum and maximum quality standards for a potential partner, leading to higher quality matches. These findings extend social exchange models by emphasising the adaptiveness of accurate self-evaluations in mating contexts.

 

Sex differences in personality scores on six scales: Many significant, but mostly small, differences

Sex differences in personality scores on six scales: Many significant, but mostly small, differences. Adrian Furnham & Luke Treglown. Current Psychology, Apr 10 2021. https://link.springer.com/article/10.1007/s12144-021-01675-x

Abstract: This study examined sex differences in domain and facet scores from six personality tests in various large adult samples. The aim was to document differences in large adult groups which might contribute new data to this highly contentious area. We reported on sex differences on the Myers-Briggs Type Indicator (MBTI); the Five Factor NEO-PI-R; the Hogan Personality Indicator (HPI); the Motives and Values Preferences Indicator (MVPI); the Hogan Development Survey (HDS) and the High Potential Trait Indicator (HPTI). Using multivariate ANOVAs we found that whilst there were many significant differences on these scores, which replicated other studies, the Cohen’s d statistic showed very few (3 out of 130) differences &gt;.50. Results from each test were compared and contrasted, particularly where they are measuring the same trait construct. Implications and limitations for researchers interested in assessment and selection are discussed.

Discussion

The results of this study can be interpreted in various different ways. A sex-difference maximiser would note that a cursory glance at the six tables shows that the vast majority of ANOVAs (over 80%) shows significant sex differences, many at the p &lt; .001 illustrating the fundamental point that there are many and important sex differences in personality, using a variety of measures and assessed at both the domain and facet level. On the other hand, the minimiser might take comfort in the effect size data (Cohen’s d) and note that there are very few large or even medium effect sizes, though this depends on how size is categorised.

Nearly all the hypotheses based on the previous literature were confirmed. Overall, the MBTI showed relatively small differences except in the Thinking-Feeling variable which has been the topic of much debate. It has been suggested (and refuted) that this factor is essentially measuring Neuroticism and hence the higher score for females which is consistent with the previous literature (Furnham, 2018),

The results from the NEO-PI-R confirmed some previous studies which showed males higher only on Conscientiousness but lower on Extraversion, Agreeableness, Openness and Neuroticism. The biggest domain differences were for three traits where females scored higher than males. The most unusual finding was the big difference on Openness (which was also shown in the HPTI trait of curiosity) where there is a limited literature and few speculations on sex differences. The smallest and fewest differences were on Consciousness and its facets. The facet analysis gave some indication of variability within domain but few where the differences went in the opposite direction. Two exceptions were the facets of assertiveness and excitement seeking in Extraversion where, as in many other studies males scored higher than females. Interestingly the highest d was for the Openness facet Feelings (d = .53) which reflects the finding in the MBTI. (Furnham, 1996).

The results of the HPI confirm previous studies with the biggest domain d’s being for Adjustment, Ambition and Curiosity with males scoring higher and Interpersonal Sensitivity with females scoring higher. Again, most of the facets scores went in the same direction though they did occasionally differ greatly in size: compare empathy and calmness in Adjustment.

The results of the replicated MVPI study showed two things: where there were significant differences the results went in the same direction, and that the biggest differences lay in male’s interest in power, business and science, values associated with entrepreneurship and work success (Furnham, 2018). Further, as in previous studies females scored higher in Altruism and Aesthetics.

The findings from the HDS show similar outcome in the two studies. When grouping the eleven traits into the recommended tri-partite system the results are clear: females tend to have scores on those traits moving away from (Cautious but not Reserved) and toward others (Dutiful not Diligent) while males score higher on traits in the moving against others category (especially Mischievous).

The final scale showed two of the six HPTI scales with relatively large differences: males score higher in Risk Approach and Ambiguity Acceptance which has been shown many times before. Although there was a sex difference on Competitiveness, the size of this was modest.

One interesting comparison could be between the scores of different tests which essentially (claimed to) measure the same construct. Thus, the sex difference d for Neuroticism in the NEO-PI-R was .35, Adjustment in the HPI was .30 and Adjustment in the HPTI was .14. Similarly, Conscientiousness in the NEO-PI-R was .12 and in the HPTI was .11, and Prudence .06. Equally the sex difference d in Agreeableness in the NEO-PI-R was .32 and Interpersonal Sensitivity in the HPI was .30. Therefore, the results seem to suggest similar sex differences on scales of different length and question measuring the same phenomenon. There were however exceptions: females were more Extraverted and Open on the NEO=PI-R, but less Sociable and Curious on the HPI.

One interesting issue concerns revisiting each question and facet to determine whether there was any inherent sex bias in the question wording and whether if these were removed the overall d would decline. This is not an issue of attempted to deny or reduce differences that exist but rather trying to reduce artefacts arising from question selection. Certainly, with changes in society, particularly with reference to sex and gender differences, questionnaire wording could cause both offense and differences in interpretation unless they are constantly updated.

Another issue to arise from this study is the great variability in the facet score items and labels that are essentially measuring the same dimension. Compare for instance the six Openness facets of the NEO-PI-R with six facets of the HPI. Given these labels it is expected that these two measures are relatively weakly correlated and measuring rather different factors.

Finally accepting that there are some real, biologically based, stable sex differences, as opposed to socialised gender differences, in personality traits the question arises as to why they occur. Results such as these cannot inform the nature-nurture debate, with (most) evolutionary psychologists offering a cohesive (and for some convincing) argument as to why there are replicable, consistent and cross-cultural findings. Minimizers who reject the “biology as destiny” approach attempt to explain all these differences in terms of primary and secondary socialisation (Buss, 1995). However, in a big review study Schmitt et al. (2017) concluded: “Social role theory appears inadequate for explaining some of the observed cultural variations in men’s and women’s personalities. Evolutionary theories regarding ecologically-evoked gender differences are described that may prove more useful in explaining global variation in human personality” (p45).

This study, like all, others has limitations. All participants were British adults taking part in a compulsory assessment centre. Though they might have been tempted by impression management there is no reason to suspect that there were sex differences in this behaviour. The reason why males outnumber females tended to reflect the profile of middle managers in those organisations which reflected all sectors, public and private. The sample was thus biased in terms of age, education and class and the question remains whether a more representative sample of people from a wider age range and social class background would have shown more or fewer sex differences. Furthermore, nearly all participants were from Europe and the effects of culture were thus not explored. It could be that sex differences are smaller in more Western, individualistic, democratic, egalitarian, and higher gender-parity cultural contexts than those from more traditional, developing countries.

It has been argued that personality changes over time and it may be that sex differences and similarities in personality are different for young, middle-aged and older participants (Roberts et al., 2001). Finally there is always the possibility that there are sex differences is self-report behaviours and biases, such that females exhibit more humility and males more hubris and that therefore some observed differences are more due to other factors and artefacts than actual personality differences.

81 % of mice display a preference for either the left or the right paw; In rats, 84 % of animals display a preference for either the left or the right paw; brain asymmetries are a basic characteristic of the rodent brain

Paw preferences in mice and rats: Meta-analysis. Martina Manns et al. Neuroscience & Biobehavioral Reviews, May 15 2021. https://doi.org/10.1016/j.neubiorev.2021.05.011

Highlights

• In mice, 81 % of animals display a preference for either the left or the right paw.

• In rats, 84 % of animals display a preference for either the left or the right paw.

• Rodents display individual- but not population-level lateralization for limb use.

• Brain asymmetries are a basic characteristic of the rodent brain.

Abstract: Mice and rats are among the most common animal model species in both basic and clinical neuroscience. Despite their ubiquity as model species, many clinically relevant brain-behaviour relationships in rodents are not well understood. In particular, data on hemispheric asymmetries, an important organizational principle in the vertebrate brain, are conflicting as existing studies are often statistically underpowered due to small sample sizes. Paw preference is one of the most frequently investigated forms of hemispheric asymmetries on the behavioural level. Here, we used meta-analysis to statistically integrated findings on paw preferences in rats and mice. For both species, results indicate significant hemispheric asymmetries on the individual level. In mice, 81 % of animals showed a preference for either the left or the right paw, while 84 % of rats show this preference. However, contrary to what has been reported in humans, population level asymmetries were not observed. These results are particularly significant as they point out that paying attention to potential individual hemispheric differences is important in both basic and clinical neuroscience.

Keywords: Animal modelClinical neuroscienceHandednessHemispheric asymmetriesLateralityRodentsTranslational neuroscience

From 2014... The Influence of the Digital Divide on Face Preferences in El Salvador: People without Internet Access Prefer More Feminine Men, More Masculine Women, and Women with Higher Adiposity

From 2014... Batres C, Perrett DI (2014) The Influence of the Digital Divide on Face Preferences in El Salvador: People without Internet Access Prefer More Feminine Men, More Masculine Women, and Women with Higher Adiposity. PLoS ONE 9(7): e100966. https://doi.org/10.1371/journal.pone.0100966

Abstract: Previous studies on face preferences have found that online and laboratory experiments yield similar results with samples from developed countries, where the majority of the population has internet access. No study has yet explored whether the same holds true in developing countries, where the majority of the population does not have internet access. This gap in the literature has become increasingly important given that several online studies are now using cross-country comparisons. We therefore sought to determine if an online sample is representative of the population in the developing country of El Salvador. In studies of Hispanic men and women aged 18–25, we tested facial masculinity and adiposity preferences by collecting data in person as well as online. Our results showed that there were no differences in preferences between people who reported having internet access, whether they were tested online or in person. This provides evidence that testing style does not bias preferences among the same population. On the other hand, our results showed multiple differences in preferences between people who reported having internet access and people who reported not having internet access. More specifically, we found that people without internet access preferred more feminine men, more masculine women, and women with higher adiposity than people with internet access. We also found that people without internet access had fewer resources (e.g. running water) than people with internet access, suggesting that harshness in the environment may be influencing face preferences. These findings suggest that online studies may provide a distorted perspective of the populations in developing countries.

Discussion

Our results showed that there were no differences in preferences between people from El Salvador who reported having internet access, whether they were tested online or in person. This provides evidence that testing style does not bias preferences among the same population. On the other hand, our results showed multiple differences in preferences between people from El Salvador who reported having internet access and people from El Salvador who reported not having internet access. This suggests that, unlike samples from studies conducted online with participants from developed countries (e.g. [15]), samples from studies conducted online with participants from developing countries may not be fully representative of the populations (e.g. [12], [11], [21]). Future research needs to take this into account when using online samples from countries where a substantial portion of the population does not have internet access. This applies not only to face preference research but to all studies that use online testing in developing countries (e.g. [29]).

Our data provide evidence that, even within a small country, sub-sectors of the population have different preferences. We found that adiposity preferences in female faces were higher among people without internet access than people with internet access. This finding is consistent with previous literature that has found that heavier figures are considered more attractive in poorer and rural areas [3], [4].

Contrary to our expectations, we found that masculinity in male faces was considered more attractive by people with internet access than by people without internet access. Past research has suggested that risks to health from disease [11] or violence [12] may be responsible for differing levels of masculinity preferences in male faces. Neither interpretation holds for face preferences within El Salvador since we found that participants without internet access prefer more feminine male faces even though health risks [22] and homicide rates [23] are both higher in areas of El Salvador where internet is less accessible. Further research is needed in order to determine what is driving these differing face preferences within sub-sections of the population.

One possibility is that media exposure is driving both sexual dimorphism and adiposity preferences. Several studies have found that the media promotes certain beauty ideals, such as masculinity in men, and femininity and low body weight in women [30], [31]. People who have internet access experience greater exposure to the media through online advertisements and websites and are therefore likely to be more exposed to faces with accentuated masculinity and femininity as well as female faces with lower adiposity.

We also found that participants with internet access were more likely to have a television in their home, which exposes them even further to the media through commercials, television shows, and movies. For example, starring movie roles are more likely to be played by women with low body mass indices [31]. Exposure to such beauty ideals has been found to impact behaviour and preferences. For instance, one study found that adolescent Fijian girls became more interested in weight loss after television was introduced in their town [32]. Thus, media exposure may explain our findings of preferences for higher masculinity in male faces and higher femininity and lower adiposity in female faces among people with internet access in El Salvador. Under the media exposure interpretation, however, it remains unclear why past research has found that online participants from developing countries prefer more masculine male faces than online participants from developed countries [11], since people from developing countries tend to have lower levels of media exposure than people from developed countries [33].

A second explanation for our findings is that the level of harshness in the environment may be influencing face preferences. Our data provide evidence that people without internet access face a harsher environment than people with internet access. For example, we found that people without internet access are less likely to have access to running water in their home than people with internet access. One study found that women prefer less masculine men and men prefer more masculine women for long-term relationships when they are asked to imagine themselves in harsh circumstances [20]. Therefore, increased levels of environmental harshness could explain our findings of preferences for masculine women and feminine men among people without internet access.

The environmental harshness explanation could also explain our adiposity findings. Past research suggests that BMI preferences may reflect differing optimal weights in different environments [4]. For instance, heavier women are better equipped to survive in periods of famine [5] and therefore may be found more attractive in environments with food shortages. Although BMI and weight were higher among people with internet access, preferences for adiposity were higher among people without internet access. This suggests that, although higher levels of weight are considered more attractive in the non-internet population, it may be harder to achieve high levels of weight in such a harsh environment.

Although the environmental harshness explanation is consistent with our findings, further research is needed in order to identify what forms of hardship are most influential on preferences. For instance, Lee and Zietsch [34] found that when women are primed with pathogen prevalence they prefer good-gene traits, such as ‘muscularity’, but when they are primed with resource scarcity they prefer good-dad traits, such as ‘nurturing’. In an environment like El Salvador, where both pathogen prevalence and resource scarcity are real threats, it remains to be determined which form of hardship is more influential on preferences. It may be possible that, among people with internet access in developing countries, pathogen prevalence is more influential since they face less resource scarcity. This would explain why past studies have found that masculinity preferences are negatively correlated with country-level health indices in online samples [11]. On the other hand, people without internet access face both pathogen prevalence as well as resource scarcity. Using Lee and Zietsch’s [34] findings, our studies provide some preliminary evidence that resource scarcity may be more influential than pathogen prevalence in environments with both threats since our non-internet sample preferred more feminine men. In order to confirm this preliminary analysis, more sensitive questions that measure resource scarcity would need to be used in future studies.

In addition to the differences in access to television and running water, we also found that people without internet access have been to other countries fewer times, have children earlier, are less educated, and are less likely to have been born in a hospital than people with internet access. These differences suggest that people with internet access have very different lifestyles from people without internet access, which provides further evidence of a digital divide [17], [18]. Our findings show that the digital divide does influence face preferences and this relationship needs to be taken into consideration in future experiments in order to accurately measure the preferences of people from developing countries.

One limitation from our experiment is that, unlike our in-person samples, our online sample was neither compensated nor supervised and participants might therefore be less motivated to take the experiment seriously. Past studies, however, have found that participants who are uncompensated and unsupervised yield results that are comparable in quality to participants who are compensated and supervised [35]. Our study was also limited in that our experiment consisted of only 5 trials per condition, it only used faces of white men and women, and our participants came from only one country. It would be beneficial to examine if any differences in face preferences arise from using faces of another ethnicity versus faces of own ethnicity. Additionally, although all Salvadorians fall under the ethnicity of Hispanic, there are differences within this ethnicity that may reflect cultural and genetic heritage and might influence preferences. It would therefore be beneficial for other studies to examine the influence of the digital divide within other developing countries. While it is clear from past studies that preferences for facial characteristics differ across populations (e.g. [11]), there are a number of factors that can contribute to these differences (e.g. health [15], violence [12], societal-level measures of development [21], income inequality [12], ecological conditions [36], media [32]). In order to gain a better understanding of these influences, more studies that compare sub-sectors of the same geographical population (e.g. [37], [36]) need to be undertaken.