Rethinking sex-assigned-at-birth questions

Alpert, Ash B.; Ruddick, Roman; Manzano, Charlie

doi:10.1136/bmj.n1261

Cited by 18 publications

(11 citation statements)

References 8 publications

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“…The concept of gender identity originated in the 1960s in the United States of America (USA) ( 29 ), was refined in the 1990s through a postmodern philosophy called Queer Theory ( 30 ) and continues to evolve. Central to Queer Theory are the twin propositions that both sex and gender are socially constructed ( 31 , 32 ) and that gender is the more important of the two ( 3 , 33 ) 1 . Ideas informed by Queer Theory have spread from the USA to become influential in many other Western countries and beyond ( 30 ).…”

Section: The Concept Of Gender Identitymentioning

confidence: 99%

“…Advocacy to reduce the female data gap in medical and other research is ongoing ( 138 , 143 , 144 ). Yet, it is being suggested that collection of data on gender identity should be prioritized over sex ( 145 ) or that data on sex should not be collected at all ( 33 ). There have been reports of ethics committees rejecting research applications that include a sex question ( 146 ).…”

Section: What Are the Consequences Of These Language Changes?mentioning

confidence: 99%

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Effective Communication About Pregnancy, Birth, Lactation, Breastfeeding and Newborn Care: The Importance of Sexed Language

Gribble

Bewley

Bartick

et al. 2022

Front. Glob. Womens Health

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Section: The Concept Of Gender Identitymentioning

confidence: 99%

Section: What Are the Consequences Of These Language Changes?mentioning

confidence: 99%

Effective Communication About Pregnancy, Birth, Lactation, Breastfeeding and Newborn Care: The Importance of Sexed Language

Gribble

Bewley

Bartick

et al. 2022

Front. Glob. Womens Health

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“…[59][60][61][62] Some patients who are transgender have concerns over questions regarding sex assigned at birth because they force transgender people to adhere to categorizations that do not apply to them. 63,64 For example, a transgender woman…”

Section: Comprehensive Data Collectionmentioning

confidence: 99%

Gender- and Sexual Orientation– Based Inequities: Promoting Inclusion, Visibility, and Data Accuracy in Oncology

Alpert

Scout

Schabath

et al. 2022

American Society of Clinical Oncology Educational Book

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Sexual and gender minority (SGM) people, including agender, asexual, bisexual, gay, gender diverse, genderqueer, genderfluid, intersex, lesbian, nonbinary, pansexual, queer, and transgender people, comprise approximately 10% or more of the U.S. population. Thus, most oncologists see SGM patients whether they know it or not. SGM people experience stigma and structural discrimination that lead to cancer disparities. Because of the lack of systematic and comprehensive data collection, data regarding SGM cancer incidence, outcomes, and treatment responses are limited. Collection of data regarding sexual orientation, gender identity, transgender identity and/or experience, anatomy, and serum hormone concentrations in oncology settings would drastically increase collective knowledge about the impact of stigma and biologic markers on cancer outcomes. Increasing the safety of oncology settings for SGM people will require individual, institutional, and systems changes that will likely improve oncologic care for all patients.

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“…Sex obsession and sex confusion can lead to situations where false assumptions are made based on a patient's sex marker, particularly that all people with those designations have a particular body part, secondary sex characteristic, or hormone level (Alpert et al, 2021). It is very common for clinicians and researchers to assume that an "M" in the demographics section means not just a penis, but testosterone levels in a particular range, higher muscle mass, or a particular pelvic build.…”

Section: Lau Et Al (2020)mentioning

confidence: 99%

Sex Trouble: Common pitfalls in incorporating sex/gender in medical machine learning and how to avoid them

Albert,

Delano

2022

Preprint

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False assumptions about sex and gender are deeply embedded in the medical system, including that they are binary, static, and concordant. Machine learning researchers must understand the nature of these assumptions in order to avoid perpetuating them. In this perspectives piece, we identify three common mistakes that researchers make when dealing with sex/gender data: "sex confusion", the failure to identity what sex in a dataset does or doesn't mean; "sex obsession", the belief that sex, specifically sex assigned at birth, is the relevant variable for most applications; and "sex/gender slippage", the conflation of sex and gender even in contexts where only one or the other is known. We then discuss how these pitfalls show up in machine learning studies based on electronic health record data, which is commonly used for everything from retrospective analysis of patient outcomes to the development of algorithms to predict risk and administer care. Finally, we offer a series of recommendations about how machine learning researchers can produce both research and algorithms that more carefully engage with questions of sex/gender, better serving all patients, including transgender people.

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Rethinking sex-assigned-at-birth questions

Cited by 18 publications

References 8 publications

Effective Communication About Pregnancy, Birth, Lactation, Breastfeeding and Newborn Care: The Importance of Sexed Language

Effective Communication About Pregnancy, Birth, Lactation, Breastfeeding and Newborn Care: The Importance of Sexed Language

Gender- and Sexual Orientation– Based Inequities: Promoting Inclusion, Visibility, and Data Accuracy in Oncology

Sex Trouble: Common pitfalls in incorporating sex/gender in medical machine learning and how to avoid them

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