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Journal Article

Citation

Kidd KM, Sequeira GM, Rothenberger SD, Paglisotti T, Kristjansson A, Schweiberger K, Miller E, Coulter RWS. J. Am. Med. Inform. Assoc. 2022; 29(2): 249-256.

Copyright

(Copyright © 2022, American Medical Informatics Association, Publisher Elsevier Publishing)

DOI

10.1093/jamia/ocab137

PMID

34472616

PMCID

PMC8757306

Abstract

OBJECTIVE: Two-step questions to assess gender identity are recommended for optimizing care delivery for gender-diverse individuals. As gender identity fields are increasingly integrated into electronic health records, guidance is needed on how to analyze these data. The goal of this study was to assess potential approaches for analyzing 2-step gender identity questions and the impact of each on suicidal ideation.
MATERIALS AND METHODS: A regional Youth Risk Behavior Survey in one Northeastern school district used a 2-step question to assess gender identity. Three gender measurement strategies (GMSs) were used to operationalize gender identity, (1) combining all gender-diverse youth (GDY) into one category, (2) grouping GDY based on sex assigned at birth, and (3) categorizing GDY based on binary and nonbinary identities. Mixed-effects logistic regression was used to compare odds of suicidal ideation between gender identity categories for each GMS.
RESULTS: Of the 3010 participants, 8.3% were GDY. Subcategories of GDY had significantly higher odds (odds ratio range, 1.6-2.9) of suicidal ideation than cisgender girls regardless of GMS, while every category of GDY had significantly higher odds (odds ratio range, 2.1-5.0) of suicidal ideation than cisgender boys.
CONCLUSIONS: The field of clinical informatics has an opportunity to incorporate inclusive items like the 2-step gender identity question into electronic health records to optimize care and strengthen clinical research. Analysis of the 2-step gender identity question impacts study results and interpretation. Attention to how data about GDY are captured will support for more nuanced, tailored analyses that better reflect unique experiences within this population.


Language: en

Keywords

Humans; adolescent; Infant, Newborn; Female; Male; Schools; Adolescent; Odds Ratio; Suicidal Ideation; Gender Identity; gender identity; suicidal ideations; transgender persons; informatics; Transgender Persons

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