What Is Problematic About Comparing Human Gender Difference With That Of Animals

• Periodical List
• Philos Trans R Soc Lond B Biol Sci
• v.371(1688); 2016 Feb 19
• PMC4785904

Philos Trans R Soc Lond B Biol Sci. 2016 February 19; 371(1688): 20150119.

Perils and pitfalls of reporting sex activity differences

Supplementary Materials

Supplementary Tabular array ane

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Supplementary Table two

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Supplementary Table three

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Information Availability Statement

The datasets supporting the figures have been uploaded as the electronic supplementary textile.

Abstract

The idea of sex differences in the brain both fascinates and inflames the public. As a outcome, the communication and public give-and-take of new findings is particularly vulnerable to logical leaps and pseudoscience. A new US National Institutes of Health policy to consider both sexes in near all preclinical research will increase the number of reported sex differences and thus the risk that research in this of import expanse will be misinterpreted and misrepresented. In this article, I consider means in which we might reduce that risk, for instance, by (i) employing statistical tests that reveal the extent to which sex activity explains variation, rather than whether or not the sexes 'differ', (ii) properly characterizing the frequency distributions of scores or dependent measures, which near always overlap, and (3) avoiding speculative functional or evolutionary explanations for sex activity-based variation, which usually invoke logical fallacies and perpetuate sex stereotypes. Ultimately, the cistron of sexual activity should be viewed as an imperfect, temporary proxy for yet-unknown factors, such as hormones or sex activity-linked genes, that explicate variation better than sexual practice. As scientists, nosotros should be interested in discovering and understanding the true sources of variation, which volition be more informative in the evolution of clinical treatments.

Keywords: gender differences, male person, female person, sex differences in the encephalon, U.s.a. National Institutes of Health policy

1. Introduction

Sex differences in the brain have fabricated headlines for more than a century. In 1912, James Crichton-Browne, a prominent neuropsychologist and collaborator of Darwin, explained in a New York Times commodity why 'women recollect quickly' and 'men are originators':

In woman, Sir James said, the posterior region of the brain receives a richer menstruum of arterial claret, in men the inductive region. The work of the ii regions of the brain is different. The posterior region is mainly sensory and concerned with seeing and hearing. The inductive region includes the speech centre, the higher inhibitory centres, which are concerned with will, and the clan centres, concerned with appetites and desires based upon internal sensations.

There is, Sir James thinks, a correspondence between the richer blood supply of the posterior region of the brain in women and their delicate powers of sensuous perception, rapidity of thought and emotional sensibility, and betwixt the richer blood supply of the inductive region in men and their greater originality on higher levels of intellectual work, their calmer judgment and their stronger volition [ane, p. 4].

Although we may find such revelations archaic and even a bit offensive, the same blazon of thinking remains prevalent today. News reports and information-based websites such every bit Wikipedia, WedMD and HowStuffWorks.com incorporate an alarming amount of pseudoscience. It is ordinarily asserted, for example, that women listen with both sides of the brain, whereas men utilize only the left side [2,3] and that women use white matter to think, whereas men utilize grey [iv,5]. Women allegedly have 10 times as much white affair as do men, whereas men have 6.5 times as much greyness matter equally do women ([half dozen,7], reviewed in [8]). Whereas women navigate using cerebral cortex, men use 'an entirely dissimilar area' that is 'not activated in women's brains' [6]. Such assertions, although inaccurate, are easy to find on the Internet and in the popular printing.

The misrepresentation of sex differences is likely to become fifty-fifty more commonplace. Partly because of increasing availability of imaging technologies, the percentage of periodical manufactures that refer to sex differences and the brain has more than doubled in the by two decades (figure i a). Over the same period, media reporting on the topic has risen by about fivefold (figure 1 b). These increases are already impressive, but the amount of research on sex differences is about to increase fifty-fifty further, far beyond what figure 1 could foretell. This year, the US National Institutes of Health (NIH) mandated the inclusion of both sexes in nigh research with animals, tissues or cells [9]. The new policy requires NIH-funded researchers to disaggregate data by sexual activity and, when possible, compare the sexes. The goal is to 'transform how science is done' [ten]. Research on sex differences is thus fix to expand from a small percentage of studies to nearly all studies funded past NIH. If this goal is achieved, the side furnishings will near certainly include a fresh onslaught of questionable interpretations and claims.

Interest in sexual practice differences in the brain has increased over the past 25 years. (a) The per centum of periodical articles that mention sex or gender differences and encephalon (Web of Scientific discipline) has approximately doubled. (b) The number of news articles about sex differences in the encephalon (Proquest) has increased approximately fivefold. Arrows betoken years during which a particular study or issue contributed substantially to an increment in news stories. For the methods and raw data, see the electronic supplementary material, table S1. (Online version in colour.)

In this article, I outline some traps that researchers face as they test for and report sexual practice differences. These pitfalls are largely related to the interpretation of statistical tests, choice of wording and the use of inference. I suggest beneath a number of strategies that may help researchers avoid common problems and therefore minimize misinterpretation and misrepresentation of their work.

2. Three fallacies of sex differences

Miscommunication of the nature and meaning of sex differences can be traced to many causes [11–14]. Here, I outline three problematic ways of thinking, or fallacies, that have impeded the communication of findings. First, we commonly nowadays our conclusions about sex activity differences equally the respond to a yes-or-no question when the real answer lies somewhere in betwixt 'yes' and 'no'. Second, nosotros often attempt to infer the behavioural or evolutionary function of a sex activity deviation in the brain without sufficient prove to practise so. Third, nosotros tend to assume that sexual practice differences are acquired by genetic or hormonal influences rather than by experience. At the root of all three of these points is a quaternary issue, which perhaps could be regarded as a fourth fallacy: the notion that sex acts as an contained variable that measurably affects other variables. Sex is merely a label; defining it in biological terms has proven tricky [15]. Sex is at best a proxy for the more than of import and interesting factors that covary with sex [16].

(a) Fallacy 1: with respect to any trait, the sexes are either fundamentally different or they are the same

Sexual practice has been called a basic biological variable that splits the population into two halves [17]; the categories of male person and female are regarded as rigidly discrete [18,19], forming 'taxa' [xiv]. When these two populations are compared, however, measures of most traits overlap extensively [14,xix–21]. The conceptualization and communication of that overlap are impeded by our natural urge to dichotomize [22] and by language choices that emphasize difference [12,23]. For example, if a statistical test returns a low p-value, we are likely to make statements such equally, 'females outperform males on the memory task' or 'women are more than susceptible than men to the side effects'. Taken literally, these statements imply that with respect to the trait measured, males and females constitute singled-out groups [24]. In nearly all cases, nonetheless, that interpretation is wildly wrong. Conversely, when the p-value is not low plenty to reject the null hypothesis of sameness, we often conclude that the sexes are the same even when sex could explain some important variation [25–28]. The problem here is that we are request a yes-or-no question when both 'yes' and 'no' are the wrong answer. To truly understand the nature of near sexual practice differences, which arguably are not actual 'differences', we need to enquire how much the sexes differ, not whether or not they do [25,26].

(b) Fallacy 2: the cause of a sexual practice departure in behaviour or ability can exist inferred from functional neuroanatomy

It is a longstanding tradition to invoke sex activity differences in neuroanatomy to explicate alleged sexual practice differences in behaviour, intellect or other traits [29]. Just as the New York Times printed in the early twentieth century that male-like patterns of blood menstruum allow more original thinking [1], in this century more white matter in women is said to confer greater language skills [xxx] and ability to multitask [seven]. The larger hippocampus of women is said to support meliorate retentiveness [31], language skills [32], learning skills [33] and processing of emotive data [34]. The junior parietal lobule, larger on the left in men and on the right in women [35], apparently underlies differences in math ability and sensitivity to crying babies [36]. Testosterone-induced lateralization of encephalon function is claimed to increase men's interest in machines [37], while oestradiol increases women's attention to emotions and communication [38]. Each of these anatomical or hormonal differences has been invoked to explain why men and women tend to enter different types of professions [39–41].

The above assertions are based on the following logic: (i) a construction (or hormone) we'll call 'X' differs between men and women; (two) 10 is related to a behaviour we'll call 'Y'; (3) men and women differ in Y; therefore, the sex difference in Ten causes the sex difference in Y. This statement is invalid considering information technology invokes the false cause fallacy–a sexual practice difference in Y cannot exist deduced to depend on X. In addition to being invalid, the argument is as well oft unsound in that rarely are all 3 bounds supported. Evidence that construction X plays a part in behaviour Y, for instance, is ordinarily scarce. Even in animate being models, in which lesions and other manipulations can be performed, the behavioural functions of sexually differentiated brain regions are, for the almost role, unclear [42]. Testify of a sex activity difference in behaviour Y is also sometimes lacking, and instead a stereotype is offered. Consider the following pop inference: (i) the hemispheres of the brain are more heavily interconnected in women than in men [43]; (ii) greater hemispheric interconnectedness allows amend multitasking; (3) women are ameliorate multitaskers than men, therefore the anatomical difference explains the difference in power [seven,44]. Start, the show that variation in interhemispheric connections really contributes to variation in human abilities is practically non-existent [45]. Second, studies of multitasking have shown no female person advantage [46,47]. The argument pervades popular culture nonetheless, probably because information technology appears to confirm stereotypes [8,11,48].

(c) Fallacy 3: sex differences in the brain must be preprogrammed and fixed

A third type of fallacious thinking, which pervades news stories and scholarly articles akin, is signalled by words such as 'hardwired', 'natural' and 'genetic'. These terms are about always used to argue that sex activity stereotypes are rooted in biology. They brand sexual practice differences sound predetermined and inevitable, untouched by experience or culture [8,11,23,49,l]. Readers are easily convinced, specially when the explanations appear to back up their own biases [eight,48]. Such arguments, however, ignore the exquisite plasticity of the brain; the furnishings of sex-linked genes and sex hormones on neuroanatomy are irreducibly entangled with the effects of sex-specific feel [23]. Suggesting otherwise leads to logical leaps known as the appeal to nature and deterministic fallacies—that sex-typical behaviour is natural, predetermined and out of our control. The cost of these fallacies is high: readers exposed to such arguments are more likely to endorse stereotypes and engage in stereotype-consistent behaviour (reviewed in [12,51,52]), and may feel powerless to change their ain trajectories [48,50].

In §§3 and iv, I will focus primarily on Fallacy i and how to avoid it. The remaining two fallacies are of import in the context of communicating findings in inquiry papers as well as press releases and are revisited in §v.

3. Pink hippocampus, blue hippocampus? Most are purple

Becker et al. [53] defined a sex departure as a dimorphism, in other words a trait that 'occurs in 2 forms, ane grade typical of males and the other typical of females.' (p. 1651). The trouble with such definitions is that, except for sex chromosomes, gonads and external ballocks [54], the two sexes rarely accept two distinct forms. The vast majority of sex differences in neuroanatomy and physiology are characterized by overlapping distributions. Variation that is attributable to sex can often require big sample sizes to notice. Information technology is almost never the example that the sexes can be distinguished by a single structure in the brain that is said to 'differ'. In other words, we typically cannot identify the sex of an individual by measuring whatsoever one matter in the encephalon; the majority of values autumn into a grey surface area [14,xix–21]. Conversely, values cannot be predicted accurately from the sex of an individual [21,54]. The overlap between the sexes is ordinarily non represented clearly by scientists and conflicts with public perception of sex differences in the brain [8,xi,49].

Figure two illustrates often-cited sex differences in humans. The graphs, which were made using the reported means and standard deviations (table S2), show the frequency distributions, or the number of individuals of each sex with any given measure or score. Annotation that Reis & Carothers [14] have shown that for many sex differences, actual information do not cluster according to sex equally they practise in figure ii, but rather fall onto a single continuum for both sexes.

Some of the almost-ofttimes cited sex differences in humans are characterized by extensive overlap (Δ). In each console, d represents Cohen'due south d and Δ represents the pct overlap. The graphs prove the frequency distributions, or the number of individuals of each sex (y-axis) with whatever given measure out or score (x-axis). (a) Distributions for homo acme [55] are shown for comparison. The effect size is large, simply men and women overlap in top by 32%. (b) Total brain volume is larger in men than in women [56]. (c) The volume of the hippocampus, corrected for full encephalon volume, has been reported to be larger in women than men [21,57]. (d) Intrahemispheric and (eastward) interhemispheric connectivity, measured via diffusion tensor imaging, varies slightly according to sexual practice [43]. The issue size plotted in (d) represents the average of 18 comparisons for which the values were college in men. (f) Serotonin synthesis has been reported to be college in women [58] and, (thousand) in a after report, higher in men [59]. (h) Pain thresholds are by and large reported to exist higher in men (data shown from [60]; see [61] for review). (i) The dosage of morphine required for analgesia may vary co-ordinate to sex simply the degree of overlap is high (information shown from [62]; see [63] for review). (j) The drug zolpidem, a popular slumber aid, is cleared by women more slowly than by men [64]. (k) The morning afterward taking zolpidem, women are more dumb than men during a driving task [65]. For the values used to make the plots, see the electronic supplementary material, table S2. Distributions were causeless normal in each case. All graphs were made using the interactive tool at www.sexdifference.org. Readers are encouraged to use this tool to assess overlap for sex differences that they find in the literature or in their own research.

Because most readers are familiar with the sex difference in human height, I have depicted that first [55], for comparison (figure ii a). This sex difference is relatively large, as is the difference in total brain book (figure 2 b) [56]. When encephalon volume is controlled, sex differences in individual brain regions are smaller or disappear completely [66]. One of the about often-cited sex differences in the brain is that of the hippocampus, which some authors have reported is larger in women than men [21]. A contempo meta-analysis showed no sex difference in this structure [67], and even when such a divergence has been detected [21,57] there is a skillful deal of overlap. In the dataset depicted in figure 2 c, hippocampal size is more than typical of the opposite sex, i.e. it is larger than average in men or smaller in women, in about a third of the population. Thus, despite a statistically pregnant sex departure (p < 0.0001) nosotros cannot say that the hippocampus occurs in ii forms.

The merits of two forms is usually made, even when the extent of overlap is quite large. In the paper on interhemispheric connectivity in humans cited in §2, Ingalhalikar et al. [43] concluded that at that place are 'fundamental differences' between male and female person brains. The authors did not report the degree of overlap, but the reported T statistics and degrees of freedom indicate that the sexes overlapped by almost 90% (figure 2 d,e; see too [68]). Nonetheless, the study was hailed by both scientists and the media every bit strong evidence that male and female person brains accept two distinct forms [thirteen,69]. News stories announced that 'men's brains become back to front, women's go side to side' [lxx] and that the structural differences are 'so profound that men and women might near be separate species' [71].

Sex differences are sometimes interpreted every bit evidence that, despite overlap, an entire sex is somehow deficient. For case, early on findings of a lower rate of serotonin synthesis in men (e.g. [58]) (effigy 2 f) have been used in the pop press to argue that a serotonin deficit makes men impulsive and 'stupid' [72]. This sort of interpretation of a sex difference, in other words that one sex exhibits a deficit, tin lead to singling out of one sex for interventions. The alleged serotonin arrears in men, for case, has been argued by educators to warrant specialized educational strategies for boys [33]. In 1997, a dissimilar written report [59] suggested that serotonin synthesis may actually be college in men (figure 2 yard). This finding eventually led to a reversal in the popular printing such that women became the abnormal sexual practice. In a book on women'due south mental wellness, Dr David Edelberg [73, p. 14] wrote, 'When doctors discovered the relationship betwixt low serotonin and emotional disorders, they started comparing the serotonin levels betwixt sexes and constitute that women but were not making enough'. As more clinically relevant biomarkers are discovered to vary co-ordinate to sexual practice, presenting and emphasizing overlap between the sexes should help foreclose the impression that an entire sex is singular.

The main goal of the new NIH policy [9] is to balance our approach to understanding diseases and clinical conditions, the aetiology of which may vary according to sexual activity [x]. An often-highlighted example of such a status is pain. Of the dozens of reported sexual practice differences in pain, two with among the largest sample sizes are shown in figure two. Figure two h shows lower pain thresholds for women than men—which is typical not only for pressure level [60], merely besides thermal, electric and other types of pain [61]. Sex differences in the response to analgesia, on the other mitt (figure 2 i), are characterized by greater overlap [62] and less understanding almost which sex exhibits the greater response. Some authors have reported that opioid analgesics are more than effective in women than men, some the other way around (reviewed in [63]). Although animate being research has suggested that mechanisms of morphine analgesia differs betwixt males and females [74], sex differences in morphine efficacy have been difficult to detect in humans—they may be masked by differences in side effects or pain thresholds [62,63,74].

Mayhap the most popular instance of a drug with differential effects in men and women is zolpidem, the sleep assistance in Ambien. Even subsequently decision-making for torso mass, the clearance rate of this drug is lower in women than in men [64] (effigy two j), which has clear consequences. The forenoon after taking zolpidem, for example, women deviated more than from a direct line while driving—in other words, they were more impaired (figure 2 one thousand) [65]. The U.Due south. Food and Drug Administration (FDA) recently issued new guidelines reducing the dosage for women [75], which was hailed past advocates of personalized medicine as a huge step in the right management. Cahill [76] pointed out that 'millions of women had been overdosing on Ambien'. That is almost certainly the example. Note, however, that a sizeable proportion of the men autumn into the female range for clearance charge per unit (figure 2 yard). If most of the women taking Ambien were overdosing, then nearly a 3rd of the men were doing the same. In their 2013 announcement [75], the FDA actually recommended lower doses for both sexes. The guidelines stated, 'These lower doses of zolpidem volition be effective in nigh women and many men' (p. 3; italics added). Despite the overlap acknowledged past the FDA, the alter in guidelines for zolpidem remains by far the virtually-cited example of the need for sex activity-specific medicine.

A statistically significant sexual activity difference does not necessarily indicate a meaningful separation between the sexes. Figure three shows hypothetical information for a fictional drug I will call 'Dimorphinil'. In this fictive sample of forty men and xl women, the sexual practice difference in clearance charge per unit is both meaning (p < 0.01) and of medium size (d = 0.lx). The effect size exceeds that for some existent drugs, for example, cyclosporine and nifedipine, for which clearance rate differs significantly between the sexes [77,78]. The low p-value and medium effect size for Dimorphinil suggest non-trivial, clinically relevant sex difference [79]. Yet, the percentage of males and females above and below the overall hateful is about the same—22 of the males and 18 of the females cleared Dimorphinil faster than the overall average and 18 of the males and 22 of the females cleared it more slowly. If nosotros were to recommend different dosages of Dimorphinil for men and women, just a scattering of patients would do good—those in the tails of the distributions, which consist mostly of ane sex. The majority of patients, for whom sex does not reliably predict clearance rate, could exist harmed by too much or besides little drug. Sex activity-based dosages, even in this instance, may be preferable to a one-size-fits-all approach, if just because benefiting a small minority of patients is nevertheless a do good. It is critical to remember, however, that when meaning sex activity differences exist, they usually signal that sexual practice explains some small portion of the variation, non that the sexes are 'different'. Treatments that are 'personalized' for each sex will do good anybody only when the upshot size is astronomical. Although some patients will certainly do good from sexual activity-specific medicine, information technology comes with a high cost tag: information technology over-emphasizes divergence and strengthens fake notions that men and women fall into dichotomous categories of patients.

Assay of a hypothetical dataset for 'Dimorphinil', a fictional drug. Normally distributed data were artificially generated for twoscore 'individuals' of each sex. (a) The values both higher up and beneath the population mean (grey dotted line) consist of xviii members of ane sex and 22 of the other. In other words, the numbers of higher up- and beneath-average individuals are nigh the aforementioned for each sex. (b) A Educatee's t-exam shows a pregnant sex difference (p < 0.01). (c) The effect is medium-sized (d = 0.60) but in that location is a high degree of overlap (Δ = 76%). For the methods and raw data, see the electronic supplementary material, tabular array S3.

Overlap between the sexes indicates that other factors, in addition to sex, contribute to variation in a trait. Because sex is itself not a mechanism [16] and cannot be absolutely defined in biological terms [15], it is at best a proxy for these other variables. Many of them are not yet known. Most sex differences, if they accept not already, will somewhen be completely explained by some other factor that covaries with sex. These explanatory factors will, I believe in every instance, contribute more to our understanding of mechanism than does the label 'sex'. Take, for example, a report that showed a male advantage in multitasking [46]. The results conflicted with the pop notion that women are better multitaskers than men [7]. The more interesting event, nonetheless, was that the sex difference was completely explained past a much larger sexual activity departure in video game experience. In other words, multitasking ability was actually predicted by video game experience, non sex. In this example, investigating the potentially explanatory correlates of sex activity was more informative and satisfying than merely reporting a sex difference. In the case of drug development, a better strategy than dividing patients by sex, or an of import next stride, would exist to notice and study the covariates that explain sex differences. For example, let the states imagine that unbeknownst to researchers, the sex divergence in Dimorphinil clearance rate (effigy 3) is explained past physical activity, which also depends on sex activity [80,81]. If we did not know well-nigh the outcome of activity on Dimorphinil clearance, we might tailor dosage according to sex instead—female athletes and male couch potatoes would receive the incorrect dose.

The list of known variables that can covary with sex is long [82], and includes some rather uninteresting, non-biological factors such every bit housing arrangements in beast facilities [83]. Perhaps for that reason, it is ordinarily argued that sex activity differences driven by obvious or uninteresting covariates, for example, body mass, are not 'true' sex activity differences [82]. If they are not acquired by biological factors that covary with sex, what, then, are true sexual activity differences? Those acquired by sexual activity hormones? Levels of sex steroids can overlap extensively, depending on the species and stage of development. Are true sex differences caused, so, past the sex-determining region of the Y chromosome? Some women have that cistron [84]. As nosotros skin abroad and discard each of the mechanisms that really do explicate sex differences, we are left merely with the 'essence' of male and female; in other words, slippery concepts that gender scholars identify as the basis of 'essentialist' thinking [45,85]. Essentialism is not useful to usa every bit neuroscientists [23,86]. In neuroscience, sex can be a predictor simply never a crusade [sixteen]. Sex differences are all caused by knowable factors that covary with sex—those factors are non likely to be divers by sex. Our chore is to find and empathize those factors, not simply to demonstrate that the sexes are different. The mechanisms underlying sex-based variation are incredibly complex, so for at present, using sex as a proxy for the more interesting variables will accept to suffice. Because sex is highly politicized and poorly communicated to the public, however, it is not a good stopping point.

iv. Is in that location a divergence? Both 'yeah' and 'no' are incorrect answers

When we compare the sexes, we carve up our sample into two categories. Thus, the very nature of the scientific question encourages the states to think dichotomously. To brand matters worse, the nearly usually used statistical tests encourage dichotomous thinking about the results [25]. Our decision to declare the sexes 'dissimilar' or the 'same' is usually based on whether a p-value is above or below 0.05. But p = 0.04 and p = 0.06 correspond essentially the same result and cannot lead logically to contrary conclusions. Further, no matter what our conclusion, we are almost certainly wrong. Every bit noted above, finding a statistically significant difference does non mean that the sexes are substantively 'different'—the differences are almost e'er characterized past of import overlap (figurestwo and ​ 3). Even a strikingly low p-value may non indicate a meaningful difference; if the sample size is large plenty, a statistically significant sex activity difference could be detected in any measure but owing to noise [26,27].

Conversely, a p-value above the threshold for a significant difference (ordinarily p > 0.05) does not indicate that the sexes are the same [25–27]. In other words, failure to reject the null does non give license to accept the null. In so doing, we would be accepting absence of prove equally evidence of absenteeism. Cumming has chosen this logical mistake the 'fallacy of the slippery slope of non-significance' [25]. The error is particularly mutual in psychology and neuroscience, fields that rely heavily on null hypothesis significance testing [27]. Hoekstra et al. [28] found that in the field of psychology, 60% of authors concluded 'no difference' when p > 0.05. If one'due south goal is to confirm that sex does not matter for the measurement at paw, the t-test would seem a rather poor choice to examination for sameness.

Rather than request a yes-or-no question near whether the sexes differ, information technology is more informative to quantify the extent to which, or how much, sex contributes to variation [25]. The p-value obtained from zip hypothesis significance tests, e.chiliad. t-tests, does not answer this question. Lower p-values do not bespeak larger effects. Measures of effect size, such as Cohen's d, are more useful (effigy two). When d is less than nearly 0.v, regardless of statistical significance, sex is unlikely to explain important variation and the finding should probably non be emphasized without good reason [79]. Fifty-fifty if no significant difference is detected, reporting the upshot size is helpful to determine side by side steps [23]. Estimates of conviction intervals [25,27] or Bayesian approaches [87] stand for other alternatives to zero hypothesis significance testing. Overlap or similarity between groups tin can be estimated [88,89]. The companion web page of this commodity, www.sexdifference.org, is an online tool that calculates effect size and percentage overlap from user-entered descriptive statistics. It can be used to visualize distributions of the user'southward own information or, as was washed in figure 2, those of published sexual activity differences.

Whether we are calculating p-values or effect sizes, to detect a sex activity difference we must compare the sexes directly. Disaggregation of data past sex, now mandated past NIH, does non involve an actual comparison. We tin can simply test for an issue of treatment in each sexual practice independently. When the p-value is below alpha for one sexual practice but non the other, nosotros typically claim a 'sexual activity-specific effect'. Such conclusions are problematic for many reasons. Equally critics of the NIH policy have pointed out [87,90], dividing a sample into subgroups lessens ability and therefore the ability to detect effects. In a famous illustration of this phenomenon, Sleight [91] recounted the analysis of data from the International Study of Infarct Survival, which showed a clear benefit of daily aspirin. When the population was divided by astrological sign, resulting in 12 separate subgroups, the beneficial outcome of aspirin was lost in the Libras and Geminis. Testing a hypothesis within each sexual activity incurs a similar risk that an outcome will exist detected in one sex just non the other, when in fact both sexes are responding.

The problem with conducting contained tests in males and females goes beyond the loss of statistical power. Such a design does not actually permit us to exam whether the consequence of treatment depends on sex. To reply that question, we must test for interactions between sexual practice and handling. Nonetheless, the practice of testing ii groups independently is quite common in neuroscience. In an analysis of articles in peak-ranking journals such as Nature Neuroscience and Neuron, Nieuwenhuis et al. [92] found that authors tested for an interaction in only half of the cases in which two experimental furnishings were compared. In the rest, the authors tested for effects in the two groups independently. When p < 0.05 for 1 grouping and p > 0.05 for the other, they concluded that the consequence of treatment depended on the group. This conclusion is only some other case of the slippery slope of non-significance [25]. Upon failing to reject the null for one grouping, the authors accepted the zippo—and worse, assorted the result with that of the other group. Simply when the p-values of two tests differ, the outcomes themselves cannot be said to differ [27,92,93].

Testing whether experimental effects differ between two groups requires a exam for interactions, for example, factorial analysis of variance (ANOVA). An reward of ANOVA is that the primary hypothesis can be tested using the entire sample of males and females together, thus avoiding the Libra/Gemini trouble described in a higher place [91]. Although power to detect an interaction is notoriously depression in ANOVA [94], a low-powered test is perhaps adequate in the context of developing sex-specific medical treatments because we are interested in detecting only robust, clinically relevant interactions. Note, however, that if we fail to detect an interaction, particularly with a low-powered exam, we cannot say that the sexes respond in the same way to treatment—in then doing we once once more slide downwardly the slippery slope [25].

5. Communicating sexual practice differences

What is the best fashion to plot a sex deviation? The most valuable representations of our data will accurately draw overlap. Plotting the distributions (figure ii; meet www.sexdifference.org) allows the reader to assess the consequence size. Other options to draw overlap include graphing confidence intervals using fault bars or 'true cat'southward eye pictures' [95]. Alternatively, plotting individual information points, for instance, in dot plots (figure 3), allows the reader to see exactly the extent of overlap as well equally the percentages of each sex in the tails of the distributions. Many readers, particularly those outside the field, may wait only at the figures; thus depicting overlap graphically likely pays off even more than than adjustments to linguistic communication in the paper.

One time the graphs are made and the paper accepted, some of the virtually of import piece of work is notwithstanding to be done. Publication of newsworthy results is more often than not accompanied by a press release, in nigh cases written past staff in the public relations department of the domicile establishment. This printing release, much more than the newspaper itself, sets the tone of media coverage and dictates the information contained therein. Even journalists who specialize in science writing may skip the journal article and read simply the press release [96]. Although scientists may arraign the media for misrepresenting and sensationalizing their findings [97–100], press releases oftentimes contain the aforementioned oversimplification, omission of information and misinterpretations every bit practice news stories [13,51,52,97,101]. The process of packaging our findings into sound bites naturally leads united states of america into the three traps outlined above in §2. Deviation is more pop than sameness [11,102], which may compel u.s.a. to downplay overlap and announce striking sex differences—thus invoking Fallacy 1.

In order to brand newly discovered sexual activity differences more meaningful to the public, researchers are prone to speculate about the functions of those differences—thus invoking Fallacy 2. In an analysis of a highly covered study on hemispheric connectivity (mentioned above; figure 2 d,e [43]), O'Connor & Joffe [thirteen] found that dubious claims in the news stories were actually present in the printing release. Some of the claims could be traced to the periodical article itself. Although the report contained no behavioural data, the authors listed a number of sex differences in domains such as retentiveness, social cognition and sensorimotor skills that their data might explain. The press release highlighted these domains and introduced new ones, such as multitasking. All of these were picked up past the pop media, which added even more alleged sex differences supposedly explained by the findings. The small sex effects on connectivity detected in the report (effigy two d,e) were said to explain sexual activity differences in emotional intelligence, intuition, athleticism, hunting, cleaning the house and countless other so-called gendered behaviours [xiii,71]. A typical headline stated, 'The hardwired difference betwixt male and female person brains could explain why men are 'better at map reading' [103].

By using the term 'hardwired', that headline besides invoked Fallacy 3: the idea that sex activity differences are predetermined and immutable. The event of predeterminism is particularly relevant to results from beast models, which are often extrapolated to humans more hastily than is warranted. Nosotros are told both by media and by researchers that because a sexual practice deviation appears in a non-human animal, it must exist genetic, shaped by evolution and free of sociocultural influence. Take, for example, a recent paper by Farmer et al. [104]. The authors showed that in mice, experiencing pain caused females to spend less time with males. By contrast, males in pain connected to pursue females. In their paper, the authors argued that the findings 'suggest that the well-known context sensitivity of the man female libido can exist explained past evolutionary rather than sociocultural factors.' (p. 5747; italics added). The press release [105], which led with 'Non this night honey…' proved irresistible; the report received worldwide coverage. The fact that information technology was conducted in mice, non humans, was sometimes lost, even so. Headlines appear, 'Women's depression sex drive due to biological reaction to pain' [106] and 'It's scientific discipline: why your headache excuse is really legit but his isn't' [107]. The coverage of this study shows clearly that animal studies are not immune to widespread media attention or potential over-interpretation.

Although the authors of a written report practise non typically write the press release, they are ofttimes quoted and may even exist given opportunities to edit. Thoughtful attention, particularly to how the work will be interpreted by the public, is of import at this stage. The press release should be regarded equally a 'point of no return'; once unleashed, misinformation evolves on its own and tin be difficult, if not incommunicable, to rein in [xiii,98]. Rather than offering questionable functional or evolutionary explanations for the results, it may be more effective to indicate out what the enquiry does not indicate. In a recent press release from Northwestern University [108,109], the senior author emphasized that research on sex differences in the encephalon 'is not about things such as who is amend at reading a map or why more men than women choose to enter certain professions'. Rather, the writer emphasized that it is 'about making biological science and medicine relevant to everyone, to both men and women'. The ensuing media coverage was both widespread and higher in quality than the usual. Clearly, close collaboration with the PR department tin can pay off. Authors may fifty-fifty want to take the atomic number 82 in communicating findings to the public; more than and more scientists utilize social media and blogs for this purpose [96,100]. Ultimately, although we all desire to share our findings widely and ponder what they hateful, the about constructive communications—those that raise public agreement—will stick to the facts and avoid speculations about evolutionary function or hardwiring. The topic of sex differences is too volatile and easily sensationalized to gamble doing otherwise.

vi. Future steps and an alternative ending

The inclusion of both sexes in biomedical research is a necessary and of import step forward. Comparing the sexes, and their responses to potential treatments, volition inform non only the development of inclusive medicine simply besides our understanding of mechanisms that covary with sexual activity [110]. The new NIH policy [nine] will advance these goals, just carries with it high risk of collateral damage. Every bit more and more sex differences are discovered, the number of misinterpretations will also increase. It would be best to be prepared, ideally by providing training to researchers and journalists. The NIH Office of Research for Women'south Health already offers helpful online courses that cover the importance of studying both sexes, the biological science of sexual differentiation and disorders that bear upon one sex disproportionately [82]. This preparation does non, however, cover how to recognize and avert contributing to pseudoscience. In fact, the training materials currently state that 'women take larger left cortical language receptors than men' (course two, lesson iv, p. 6) but the source cited [111] does not mention linguistic communication. According to the aforementioned course, men mount a 'fight or flight' response when faced with a crisis whereas women 'tend and befriend'; this departure is said to be caused past a sex activity difference in oxytocin. I of the cited sources does not mention sex differences [112]; some other states emphatically that the part of oxytocin in man behaviour is not well understood [113]. Certainly, if these sorts of misrepresentations can creep into NIH training materials, we can expect them to pop up practically anywhere— including in our own work [thirteen,52]. Training in the estimation and advice of sex differences should be a priority.

In this article, I have painted a rather grim film of beguiling headlines appearing in the news every 24-hour interval. Whether the new NIH guidelines actually increase the number of such headlines depends, of course, non only on the way in which results are communicated, but too on the extent to which the guidelines are followed. Depending on how stringently they are enforced, there could be a very dissimilar just equally disappointing issue. Research is expensive, and not all researchers are interested in sexual practice differences. When asked to increase sample sizes and perform additional analyses, a majority of researchers may be motivated to rule out sex differences as quickly as possible. In such cases, demonstrating that the sexes are the same becomes highly incentivized. Afterward a cursory t-test showing 'no difference', researchers may feel free to get dorsum to business equally usual. Thus, whereas dubious interpretations of positive findings threaten public scientific literacy, false negatives may plough out to be much more detrimental to the mission of the NIH. For every sex activity difference that makes headlines, numerous others may go undiscovered every bit they slip downward the slippery slope of not-significance and out of sight.

Supplementary Cloth

Supplementary Material

Supplementary Cloth

Acknowledgements

I am grateful to Evan Goode, who designed and implemented the interactive tool at sexdifference.org. I also thank Chris Goode, Kim Wallen and Catherine Woolley for helpful comments on the manuscript.

Data accessibility

The datasets supporting the figures accept been uploaded as the electronic supplementary material.

Competing interests

I have no competing interests.

Funding

My attempt devoted to writing this article was supported by Emory University.

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