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To improve upon measures of sexual orientation and gender identity (SOGI) used in previous studies, we created and tested seven measures for inclusion in cancer research and refined them based on input from study participants. Between February and March 2024, cognitive interviews were conducted virtually with a purposive sample of 18 adults ≥50 years old. Equal numbers of participants identified as LGBTQ+ ( = 9) and cisgender heterosexual ( = 9). We chose older adults because-for the most part-participants in past studies on SOGI data acceptability have been younger than those typically recruited in cancer-related studies. Participants were selected for maximum diversity in age, race/ethnicity, U.S. geographic region, and political ideology. Descriptive themes and patterns for each measure were organized, evaluated, synthesized, and summarized. Most participants found six of seven tested measures easy to answer. Respondents were satisfied with being able to choose more than one response option for each item. Some terms, (e.g., response options "cisgender" and "non-binary" for gender identity measure) were new to some respondents. Revisions to measures were made based on respondent feedback. The breast/chest tissue item confused most respondents, so it was withdrawn. This study found that most tested SOGI measures were easy to understand, and the response options were appropriate. Refined measures can serve as a resource for investigators and clinicians to employ who wish to improve SOGI data collection.
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http://dx.doi.org/10.1177/23258292251362128 | DOI Listing |
Pediatr Ann
September 2025
Division of Gynecology, Boston Children's Hospital, Department of Surgery, Harvard Medical School.
Based on extensive evidence, gender-affirming care (GAC) is endorsed by numerous medical societies as the gold standard for supporting youth who are transgender and gender diverse (TGD). Unfortunately, there remain barriers to accessing GAC and an ongoing risk of gender identity-based mistreatment for youth who are TGD accessing all forms of health care. Gynecologic care is commonly accessed by youth who are TGD as part of medical gender affirmation, with needs ranging from hormone management, menstrual suppression, contraception counseling, and surgical consultation.
View Article and Find Full Text PDFArch Psychiatr Nurs
October 2025
Center for Innovation and Medical Education Research, Buddhist Tzu Chi Medical Foundation Hualien Tzu Chi Hospital, Hualien, Taiwan.
Background: Internalized sexual stigma is a significant psychological stressor contributing to depression among gay men. While resilience and positive sexual identity are known protective factors, their combined roles remain understudied in non-Western contexts, particularly in East Asian societies like Taiwan.
Purpose: This study investigated whether resilience mediates and positive sexual identity moderates the association between internalized stigma and depressive severity among Taiwanese gay men.
Appl Nurs Res
October 2025
Department of Nursing, Shandong Provincial Hospital Affiliated to Shandong First Medical University, Jinan, Shandong, China.
Aim: To develop the Male Nurse Identity Scale (MNIS) and further evaluate its validity and reliability.
Background: In a context where occupational gender stereotypes continue to influence the nursing profession, the male nurse population often experiences identity dilemmas. The Male Nurse Identity Scale (MNIS) focuses on measuring multidimensional identity; to our knowledge, no similar instrument exists.
JMIR Cancer
September 2025
Department of Health Outcomes and Biomedical Informatics, University of Florida, 1889 Museum Road, Suite 7000, Gainesville, FL, 32611, United States, 1 352 294-5969.
Background: Disparities in cancer burden between transgender and cisgender individuals remain an underexplored area of research.
Objective: This study aimed to examine the cumulative incidence and associated risk factors for cancer and precancerous conditions among transgender individuals compared with matched cisgender individuals.
Methods: We conducted a retrospective cohort study using patient-level electronic health record (EHR) data from the University of Florida Health Integrated Data Repository between 2012 and 2023.
PLOS Digit Health
September 2025
Department of Dermatology, Stanford University, Stanford, California, United States of America.
Large Language Models (LLMs) are increasingly deployed in clinical settings for tasks ranging from patient communication to decision support. While these models demonstrate race-based and binary gender biases, anti-LGBTQIA+ bias remains understudied despite documented healthcare disparities affecting these populations. In this work, we evaluated the potential of LLMs to propagate anti-LGBTQIA+ medical bias and misinformation.
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