No Cover Image

Journal article 286 views

The Complexities of Categorizing Gender: A Hierarchical Clustering Analysis of Data from the First Australian Trans and Gender Diverse Sexual Health Survey

Denton Callander, Christy E. Newman, Martin Holt, Shoshana Rosenberg, Dustin T. Duncan, Mish Pony, Liadh Timmins Orcid Logo, Vincent Cornelisse, Liz Duck-Chong, Binhuan Wang, Teddy Cook

Transgender Health, Volume: 6, Issue: 2, Pages: 74 - 81

Swansea University Author: Liadh Timmins Orcid Logo

Full text not available from this repository: check for access using links below.

Check full text

DOI (Published version): 10.1089/trgh.2020.0050

Abstract

Purpose: This study used self-reported gender among trans and gender diverse people in Australia to identify and describe broad, overarching gender categories that encompass the expansive ways in which gender can be defined and expressed. Methods: Data were collected as part of the Australian Trans...

Full description

Published in: Transgender Health
ISSN: 2688-4887 2380-193X
Published: Mary Ann Liebert Inc 2021
Online Access: Check full text

URI: https://cronfa.swan.ac.uk/Record/cronfa64173
Tags: Add Tag
No Tags, Be the first to tag this record!
first_indexed 2023-09-26T10:06:13Z
last_indexed 2023-09-26T10:06:13Z
id cronfa64173
recordtype SURis
fullrecord <?xml version="1.0" encoding="utf-8"?><rfc1807 xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xmlns:xsd="http://www.w3.org/2001/XMLSchema"><bib-version>v2</bib-version><id>64173</id><entry>2023-08-30</entry><title>The Complexities of Categorizing Gender: A Hierarchical Clustering Analysis of Data from the First Australian Trans and Gender Diverse Sexual Health Survey</title><swanseaauthors><author><sid>7f227f6f0fc0400bae2893d252d2f5ec</sid><ORCID>0000-0001-7984-4748</ORCID><firstname>Liadh</firstname><surname>Timmins</surname><name>Liadh Timmins</name><active>true</active><ethesisStudent>false</ethesisStudent></author></swanseaauthors><date>2023-08-30</date><deptcode>HPS</deptcode><abstract>Purpose: This study used self-reported gender among trans and gender diverse people in Australia to identify and describe broad, overarching gender categories that encompass the expansive ways in which gender can be defined and expressed. Methods: Data were collected as part of the Australian Trans and Gender Diverse Sexual Health Survey hosted in October 2018. Participant self-identification with nonexclusive gender categories were analyzed using algorithm-based hierarchical clustering; factors associated with gender clusters were identified using logistic regression analyses. Results: Usable data were collected from 1613 trans and gender diverse people in Australia, of whom 71.0% used two or more labels to describe their gender. Three nonexclusive clusters were identified: (i) women/trans women, (ii) men/trans men, and (iii) nonbinary. In total, 33.8% of participants defined their gender in exclusively binary terms (i.e., men/women, trans men/trans women), 40.1% in nonbinary terms, and 26.0% in both binary and nonbinary terms. The following factors were associated with selecting nonbinary versus binary gender labels: presumed female gender at birth (adjusted odds ratio [aOR]=2.02, 95% confidence interval [CI]=1.60–2.54, p&lt;0.001), having a majority of sexual and/or gender minority friends (aOR=2.46, 95% CI=1.49–3.10, p&lt;0.001), and having spent more than half of one's life identifying as trans and/or gender diverse (aOR=1.75, 95% CI=1.37–2.23, p&lt;0.001). Conclusion: Trans and gender diverse people take up diverse and often multiple gender labels, which can be broadly categorized as binary and nonbinary. Systems of health care and research must be adapted to include nonbinary people while remaining amenable to further adaptation.</abstract><type>Journal Article</type><journal>Transgender Health</journal><volume>6</volume><journalNumber>2</journalNumber><paginationStart>74</paginationStart><paginationEnd>81</paginationEnd><publisher>Mary Ann Liebert Inc</publisher><placeOfPublication/><isbnPrint/><isbnElectronic/><issnPrint>2688-4887</issnPrint><issnElectronic>2380-193X</issnElectronic><keywords>Cluster analysis, gender identity, health informatics, nonbinary</keywords><publishedDay>16</publishedDay><publishedMonth>4</publishedMonth><publishedYear>2021</publishedYear><publishedDate>2021-04-16</publishedDate><doi>10.1089/trgh.2020.0050</doi><url>http://dx.doi.org/10.1089/trgh.2020.0050</url><notes/><college>COLLEGE NANME</college><department>Psychology</department><CollegeCode>COLLEGE CODE</CollegeCode><DepartmentCode>HPS</DepartmentCode><institution>Swansea University</institution><apcterm/><funders/><projectreference/><lastEdited>2023-09-26T11:07:58.2629435</lastEdited><Created>2023-08-30T13:06:54.6952312</Created><path><level id="1">Faculty of Medicine, Health and Life Sciences</level><level id="2">School of Psychology</level></path><authors><author><firstname>Denton</firstname><surname>Callander</surname><order>1</order></author><author><firstname>Christy E.</firstname><surname>Newman</surname><order>2</order></author><author><firstname>Martin</firstname><surname>Holt</surname><order>3</order></author><author><firstname>Shoshana</firstname><surname>Rosenberg</surname><order>4</order></author><author><firstname>Dustin T.</firstname><surname>Duncan</surname><order>5</order></author><author><firstname>Mish</firstname><surname>Pony</surname><order>6</order></author><author><firstname>Liadh</firstname><surname>Timmins</surname><orcid>0000-0001-7984-4748</orcid><order>7</order></author><author><firstname>Vincent</firstname><surname>Cornelisse</surname><order>8</order></author><author><firstname>Liz</firstname><surname>Duck-Chong</surname><order>9</order></author><author><firstname>Binhuan</firstname><surname>Wang</surname><order>10</order></author><author><firstname>Teddy</firstname><surname>Cook</surname><order>11</order></author></authors><documents/><OutputDurs/></rfc1807>
spelling v2 64173 2023-08-30 The Complexities of Categorizing Gender: A Hierarchical Clustering Analysis of Data from the First Australian Trans and Gender Diverse Sexual Health Survey 7f227f6f0fc0400bae2893d252d2f5ec 0000-0001-7984-4748 Liadh Timmins Liadh Timmins true false 2023-08-30 HPS Purpose: This study used self-reported gender among trans and gender diverse people in Australia to identify and describe broad, overarching gender categories that encompass the expansive ways in which gender can be defined and expressed. Methods: Data were collected as part of the Australian Trans and Gender Diverse Sexual Health Survey hosted in October 2018. Participant self-identification with nonexclusive gender categories were analyzed using algorithm-based hierarchical clustering; factors associated with gender clusters were identified using logistic regression analyses. Results: Usable data were collected from 1613 trans and gender diverse people in Australia, of whom 71.0% used two or more labels to describe their gender. Three nonexclusive clusters were identified: (i) women/trans women, (ii) men/trans men, and (iii) nonbinary. In total, 33.8% of participants defined their gender in exclusively binary terms (i.e., men/women, trans men/trans women), 40.1% in nonbinary terms, and 26.0% in both binary and nonbinary terms. The following factors were associated with selecting nonbinary versus binary gender labels: presumed female gender at birth (adjusted odds ratio [aOR]=2.02, 95% confidence interval [CI]=1.60–2.54, p<0.001), having a majority of sexual and/or gender minority friends (aOR=2.46, 95% CI=1.49–3.10, p<0.001), and having spent more than half of one's life identifying as trans and/or gender diverse (aOR=1.75, 95% CI=1.37–2.23, p<0.001). Conclusion: Trans and gender diverse people take up diverse and often multiple gender labels, which can be broadly categorized as binary and nonbinary. Systems of health care and research must be adapted to include nonbinary people while remaining amenable to further adaptation. Journal Article Transgender Health 6 2 74 81 Mary Ann Liebert Inc 2688-4887 2380-193X Cluster analysis, gender identity, health informatics, nonbinary 16 4 2021 2021-04-16 10.1089/trgh.2020.0050 http://dx.doi.org/10.1089/trgh.2020.0050 COLLEGE NANME Psychology COLLEGE CODE HPS Swansea University 2023-09-26T11:07:58.2629435 2023-08-30T13:06:54.6952312 Faculty of Medicine, Health and Life Sciences School of Psychology Denton Callander 1 Christy E. Newman 2 Martin Holt 3 Shoshana Rosenberg 4 Dustin T. Duncan 5 Mish Pony 6 Liadh Timmins 0000-0001-7984-4748 7 Vincent Cornelisse 8 Liz Duck-Chong 9 Binhuan Wang 10 Teddy Cook 11
title The Complexities of Categorizing Gender: A Hierarchical Clustering Analysis of Data from the First Australian Trans and Gender Diverse Sexual Health Survey
spellingShingle The Complexities of Categorizing Gender: A Hierarchical Clustering Analysis of Data from the First Australian Trans and Gender Diverse Sexual Health Survey
Liadh Timmins
title_short The Complexities of Categorizing Gender: A Hierarchical Clustering Analysis of Data from the First Australian Trans and Gender Diverse Sexual Health Survey
title_full The Complexities of Categorizing Gender: A Hierarchical Clustering Analysis of Data from the First Australian Trans and Gender Diverse Sexual Health Survey
title_fullStr The Complexities of Categorizing Gender: A Hierarchical Clustering Analysis of Data from the First Australian Trans and Gender Diverse Sexual Health Survey
title_full_unstemmed The Complexities of Categorizing Gender: A Hierarchical Clustering Analysis of Data from the First Australian Trans and Gender Diverse Sexual Health Survey
title_sort The Complexities of Categorizing Gender: A Hierarchical Clustering Analysis of Data from the First Australian Trans and Gender Diverse Sexual Health Survey
author_id_str_mv 7f227f6f0fc0400bae2893d252d2f5ec
author_id_fullname_str_mv 7f227f6f0fc0400bae2893d252d2f5ec_***_Liadh Timmins
author Liadh Timmins
author2 Denton Callander
Christy E. Newman
Martin Holt
Shoshana Rosenberg
Dustin T. Duncan
Mish Pony
Liadh Timmins
Vincent Cornelisse
Liz Duck-Chong
Binhuan Wang
Teddy Cook
format Journal article
container_title Transgender Health
container_volume 6
container_issue 2
container_start_page 74
publishDate 2021
institution Swansea University
issn 2688-4887
2380-193X
doi_str_mv 10.1089/trgh.2020.0050
publisher Mary Ann Liebert Inc
college_str Faculty of Medicine, Health and Life Sciences
hierarchytype
hierarchy_top_id facultyofmedicinehealthandlifesciences
hierarchy_top_title Faculty of Medicine, Health and Life Sciences
hierarchy_parent_id facultyofmedicinehealthandlifesciences
hierarchy_parent_title Faculty of Medicine, Health and Life Sciences
department_str School of Psychology{{{_:::_}}}Faculty of Medicine, Health and Life Sciences{{{_:::_}}}School of Psychology
url http://dx.doi.org/10.1089/trgh.2020.0050
document_store_str 0
active_str 0
description Purpose: This study used self-reported gender among trans and gender diverse people in Australia to identify and describe broad, overarching gender categories that encompass the expansive ways in which gender can be defined and expressed. Methods: Data were collected as part of the Australian Trans and Gender Diverse Sexual Health Survey hosted in October 2018. Participant self-identification with nonexclusive gender categories were analyzed using algorithm-based hierarchical clustering; factors associated with gender clusters were identified using logistic regression analyses. Results: Usable data were collected from 1613 trans and gender diverse people in Australia, of whom 71.0% used two or more labels to describe their gender. Three nonexclusive clusters were identified: (i) women/trans women, (ii) men/trans men, and (iii) nonbinary. In total, 33.8% of participants defined their gender in exclusively binary terms (i.e., men/women, trans men/trans women), 40.1% in nonbinary terms, and 26.0% in both binary and nonbinary terms. The following factors were associated with selecting nonbinary versus binary gender labels: presumed female gender at birth (adjusted odds ratio [aOR]=2.02, 95% confidence interval [CI]=1.60–2.54, p<0.001), having a majority of sexual and/or gender minority friends (aOR=2.46, 95% CI=1.49–3.10, p<0.001), and having spent more than half of one's life identifying as trans and/or gender diverse (aOR=1.75, 95% CI=1.37–2.23, p<0.001). Conclusion: Trans and gender diverse people take up diverse and often multiple gender labels, which can be broadly categorized as binary and nonbinary. Systems of health care and research must be adapted to include nonbinary people while remaining amenable to further adaptation.
published_date 2021-04-16T11:07:59Z
_version_ 1778094314143875072
score 11.016235

Similar Items