% IMPORTANT: The following is UTF-8 encoded.  This means that in the presence
% of non-ASCII characters, it will not work with BibTeX 0.99 or older.
% Instead, you should use an up-to-date BibTeX implementation like “bibtex8” or
% “biber”.

@ARTICLE{Rippon:904414,
      author       = {Rippon, Gina and Eliot, Lise and Genon, Sarah and Joel,
                      Daphna},
      title        = {{H}ow hype and hyperbole distort the neuroscience of sex
                      differences},
      journal      = {PLoS biology},
      volume       = {19},
      number       = {5},
      issn         = {1544-9173},
      address      = {Lawrence, KS},
      publisher    = {PLoS},
      reportid     = {FZJ-2021-05984},
      pages        = {e3001253 -},
      year         = {2021},
      abstract     = {Sex/gender differences in the human brain attract attention
                      far beyond the neuroscience community. Given the interest of
                      nonspecialists, it is important that researchers studying
                      human female–male brain difference assume greater
                      responsibility for the accurate communication of their
                      findings.Research into female–male brain differences is
                      believed important for understanding sex/gender disparities
                      in neurological and mental health, in educational and
                      occupational achievement, and for informing diversity and
                      inclusion initiatives. (We use “sex/gender” to embrace
                      the difficulty of disentangling participants’
                      “sex”—biological attributes including genitalia,
                      sex-related chromosomes, and hormones—and
                      “gender”—psychological and social attributes
                      associated with males and females—as distinct variables in
                      human neuroscience.) Interest in the outcomes of brain
                      sex/gender difference research extends beyond the research
                      specialty itself, calling for attention to issues of
                      transparency and clarity in communicating such
                      findings.Concerned researchers have warned about the ease
                      with which new and existing datasets can be mined for
                      male–female group differences, often leading to reporting
                      bias and false positives or failures to report effect sizes
                      where differences have been found [1–3]. Likewise,
                      they’ve raised concerns about the misuse of sex/gender
                      brain findings in the public sphere, where the data have
                      been translated for popular communication in careless and
                      stereotypical ways [3,4]. Much less attention has been paid
                      to problems of misrepresentation arising from the narrative
                      and interpretive context in scientific articles themselves.
                      Here, we highlight the need for “impression management”
                      in research reports on brain sex/gender difference.A
                      recurrent problem in such studies is that the qualitative
                      terminology used to describe the results does not accurately
                      reflect the actual findings. Contemporary brain imaging
                      research employs datasets with hundreds or thousands of
                      measures, which are analyzed using multiple comparisons.
                      Frequently, statistically significant differences are found
                      in only a small fraction of possible contrasts. But this is
                      rarely made clear in the abstract and discussion section,
                      even if it is acknowledged in the results. For example, in a
                      study of brain connectivity networks, the abstract states
                      that sex differences were “prominent … at multiple
                      scales of analysis” despite only $2\%$ of the thousands of
                      comparisons showing small statistical differences [5]. Such
                      hyperbole can be compounded when there is unjustified
                      emphasis on marginally significant findings and/or findings
                      that did not actually survive correction for multiple
                      comparisons. For example, the title of another recent paper
                      referred to sex differences in “brain growth
                      trajectories” even though none of the 46 critical measures
                      showed significant sex-by-age differences after correcting
                      for multiple comparisons [6]. The discussion further focused
                      on sex/gender differences that had not survived appropriate
                      statistical corrections.The preference for positive results
                      in scientific publications is an acknowledged problem
                      [1,2,4], but is no excuse for glossing over the larger
                      context of any statistically significant findings. To ensure
                      an accurate reflection of all statistical comparisons,
                      journal editors and reviewers should require that these be
                      reported by indexing the number of (genuine) statistically
                      significant differences to the total number of comparisons
                      made or as a ratio of differences to similarities. This
                      should be included in the abstract, results, and discussion
                      sections to help readers gauge the true degree of
                      group-level differences. Verbal summaries of the findings
                      should use terms such as “many,” “strong,” etc. only
                      when justified by this numerical index.A second set of
                      problems emerges when sex/gender comparisons are conducted
                      by investigators naïve to the field or as an “add-on”
                      to the main objective of the study. Such researchers
                      commonly adopt an essentialist binary framework and an
                      evolutionary perspective that biases the analysis, design,
                      and interpretation of results. The underlying assumption is
                      that female–male differences are determined by biological
                      factors (i.e., “sex”), ignoring the myriad of
                      psychosocial influences (i.e., “gender”) that can affect
                      the brain and may not have been assayed as possible
                      covariates or considered when interpreting the results. For
                      example, a paper on “social brains” [7] interpreted some
                      limited male-female differences in correlations between
                      certain brain structures and social variables as evidence
                      “that human survival has been optimized toward
                      sex-specific strategies to successfully navigate the social
                      world (7, p. 9).” Considering the interest of such
                      research to nonexperts, journal editors and reviewers should
                      ensure authors acknowledge the full biopsychosocial
                      complexity of sex/gender and avoid the impression that there
                      is a single, well-established, and noncontroversial
                      interpretation of their findings.This leads us to the third
                      issue: the ease of deriving a post hoc rationalization for
                      discovery-based findings of sex/gender brain differences.
                      The core of this problem is a failure to acknowledge that
                      the link between structure and function in the human brain
                      is not well defined. Most mental processes engage many
                      overlapping neural structures and circuits, so researchers
                      have a wide range of choices in the behavioral
                      interpretation they apply to any sex/gender difference in
                      structure or connectivity. This makes it all too easy to
                      retroactively spin a speculative relationship to some gender
                      disparity around any differences detected in large-scale
                      human neuroimaging databases, such as a high-profile article
                      that interpreted modest connectome sex/gender differences as
                      supporting “co-ordinated action” by male brains versus
                      “communication” by female brains [8]. Although an
                      important solution for this issue is the preregistration of
                      research protocols, where post hoc analyses are regulated
                      and selective inference is detected [9], impression
                      management in the final communication of research findings
                      can remain a problem.Editorial policy and reviewer
                      guidelines commonly focus on methodological issues and pay
                      less attention to the responsible use of language in the
                      final text, even though the title and abstract are often the
                      sole source of a study’s take-home message for
                      nonspecialists.In the interests of both science and society,
                      neuroscientists need to think carefully about how they
                      present findings about brain differences between socially
                      segregated groups of healthy humans. They need to recognize
                      that any neurobiological comparison between such groups
                      raises the potential for stereotyping and stigmatization.
                      That means ensuring that research design and methodology
                      reflect current understanding of sex/gender. It also means
                      paying careful attention to the impression given by
                      selective narrative framing and inaccurate use of
                      quantitative descriptors. A failure to clarify the practical
                      significance of complex statistical findings or to
                      acknowledge the multifaceted biopsychosocial contributions
                      to sex/gender groupings gives undue weight to the relevance
                      of the findings. Given the real costs of entrenched
                      sex/gender disparities across society, neuroscientists have
                      a duty to prevent the spread of misinformation about the
                      neural basis of such differences.},
      cin          = {INM-7},
      ddc          = {610},
      cid          = {I:(DE-Juel1)INM-7-20090406},
      pnm          = {5251 - Multilevel Brain Organization and Variability
                      (POF4-525)},
      pid          = {G:(DE-HGF)POF4-5251},
      typ          = {PUB:(DE-HGF)16},
      pubmed       = {pmid:33970901},
      UT           = {WOS:000664233900002},
      doi          = {10.1371/journal.pbio.3001253},
      url          = {https://juser.fz-juelich.de/record/904414},
}