Information and communication technology-based health interventions for transgender people: A scoping review

Wong, H.L.; Prankumar, Sujith Kumar; Cui, Jialiang; Tumwine, Christopher; Addo, Isaac Yeboah; Kan, Wan Sang; Noor, Muhammad Naveed

doi:10.1371/journal.pgph.0001054

Cited by 7 publications

(7 citation statements)

References 88 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…However, they show good rated competence regarding media use, which might be a good starting point to develop tele medical interventions to reduce barriers to health care. Yet, there is a lack of tele medical interventions for trans and gender diverse individuals [ 40 ] and validity of exciting interventions is limited [ 41 ]. Overall, information on health literacy as well as its impact on different health outcomes in the target sample remains understudied and should be further investigated.…”

Section: Discussionmentioning

confidence: 99%

Health literacy of trans and gender diverse individuals –a cross sectional survey in Germany

von der Warth,

Körner,

Farin-Glattacker

2024

BMC Public Health

View full text Add to dashboard Cite

Introduction To date, there has been little research on the general health literacy of trans and gender diverse individuals, even though previous research undermines the importance of good health literacy in this sample. The aim of the article is therefore to describe the general health literacy of trans and gender diverse individuals based on a German survey. Methods In September 2022, a survey study was conducted in which health literacy was recorded using HLS-EU-16. Data will be presented descriptively; gender differences will be explored using a Χ2- test and a univariate analysis of variance (ANOVA). Results Out of N = 223 participants, n = 129 individuals (57.8%) identified as non-binary; n = 49 (22.0%) identified themselves as male, while n = 45 (20.2%) identified as female. Mean age was 28.03 years. Overall, 26.4% of all the participants showed an inadequate health literacy, as proposed by the HLS-EU-16. In trend, health-related task related to media use were more often perceived as easy compared to the German general population. Conclusion Individuals, who identify as trans and gender diverse may have a general health literacy below average compared to the German general population. However, tasks related to media use were perceived as easy, which might be a good starting point for health literacy related interventions. Trial registration DRKS00026249, Date of registration: 15/03/2022.

show abstract

Section: Discussionmentioning

confidence: 99%

Health literacy of trans and gender diverse individuals –a cross sectional survey in Germany

von der Warth,

Körner,

Farin-Glattacker

2024

BMC Public Health

View full text Add to dashboard Cite

show abstract

“…Although such technology-delivered interventions should not be a replacement for medical interventions and certainly do not supplant the need for advocacy and policy reform to reduce treatment access barriers for TNB people, they may be an important step toward reducing gender dysphoria in TNB people living in high-stigma and low-resource areas, as these are often places where barriers to receiving gender dysphoria treatment are particularly pronounced [ 15 , 17 , 20 ]. In fact, the recognition of these treatment barriers has generated increased interest in technology-delivered interventions for promoting health of TNB people (eg, supportive SMS text messages that deliver TNB-affirming cognitive behavioral therapy [ 21 ]) because technology-delivered interventions can be used discretely, safely, and flexibly, overcoming many of the treatment barriers TNB people face [ 22 ]. However, most existing technology-delivered interventions developed for TNB populations target HIV risk [ 22 ].…”

Section: Introductionmentioning

confidence: 99%

“…In fact, the recognition of these treatment barriers has generated increased interest in technology-delivered interventions for promoting health of TNB people (eg, supportive SMS text messages that deliver TNB-affirming cognitive behavioral therapy [ 21 ]) because technology-delivered interventions can be used discretely, safely, and flexibly, overcoming many of the treatment barriers TNB people face [ 22 ]. However, most existing technology-delivered interventions developed for TNB populations target HIV risk [ 22 ]. Only 3 extant technology-delivered interventions target gender-affirming care [ 22 ], and none target gender dysphoria specifically.…”

Section: Introductionmentioning

confidence: 99%

“…However, most existing technology-delivered interventions developed for TNB populations target HIV risk [ 22 ]. Only 3 extant technology-delivered interventions target gender-affirming care [ 22 ], and none target gender dysphoria specifically.…”

Section: Introductionmentioning

confidence: 99%

“…Of the technology-delivered interventions currently available for TNB people [ 22 ], none leverage machine learning (ML; ie, the field of study that gives computers the ability to learn without being explicitly programmed) and natural language processing (NLP; ie, computer algorithms that understand patterns in human language) despite the use of these cutting-edge computational methods in technology-delivered interventions for other marginalized populations (eg, men who have sex with men [ 23 ]). A high-level introduction to ML and NLP is provided in the study by Goldberg et al [ 24 ].…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Models of Gender Dysphoria Using Social Media Data for Use in Technology-Delivered Interventions: Machine Learning and Natural Language Processing Validation Study

Cascalheira¹,

Flinn²,

Zhao³

et al. 2023

JMIR Form Res

View full text Add to dashboard Cite

Background The optimal treatment for gender dysphoria is medical intervention, but many transgender and nonbinary people face significant treatment barriers when seeking help for gender dysphoria. When untreated, gender dysphoria is associated with depression, anxiety, suicidality, and substance misuse. Technology-delivered interventions for transgender and nonbinary people can be used discretely, safely, and flexibly, thereby reducing treatment barriers and increasing access to psychological interventions to manage distress that accompanies gender dysphoria. Technology-delivered interventions are beginning to incorporate machine learning (ML) and natural language processing (NLP) to automate intervention components and tailor intervention content. A critical step in using ML and NLP in technology-delivered interventions is demonstrating how accurately these methods model clinical constructs. Objective This study aimed to determine the preliminary effectiveness of modeling gender dysphoria with ML and NLP, using transgender and nonbinary people’s social media data. Methods Overall, 6 ML models and 949 NLP-generated independent variables were used to model gender dysphoria from the text data of 1573 Reddit (Reddit Inc) posts created on transgender- and nonbinary-specific web-based forums. After developing a codebook grounded in clinical science, a research team of clinicians and students experienced in working with transgender and nonbinary clients used qualitative content analysis to determine whether gender dysphoria was present in each Reddit post (ie, the dependent variable). NLP (eg, n-grams, Linguistic Inquiry and Word Count, word embedding, sentiment, and transfer learning) was used to transform the linguistic content of each post into predictors for ML algorithms. A k-fold cross-validation was performed. Hyperparameters were tuned with random search. Feature selection was performed to demonstrate the relative importance of each NLP-generated independent variable in predicting gender dysphoria. Misclassified posts were analyzed to improve future modeling of gender dysphoria. Results Results indicated that a supervised ML algorithm (ie, optimized extreme gradient boosting [XGBoost]) modeled gender dysphoria with a high degree of accuracy (0.84), precision (0.83), and speed (1.23 seconds). Of the NLP-generated independent variables, Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition (DSM-5) clinical keywords (eg, dysphoria and disorder) were most predictive of gender dysphoria. Misclassifications of gender dysphoria were common in posts that expressed uncertainty, featured a stressful experience unrelated to gender dysphoria, were incorrectly coded, expressed insufficient linguistic markers of gender dysphoria, described past experiences of gender dysphoria, showed evidence of identity exploration, expressed aspects of human sexuality unrelated to gender dysphoria, described socially based gender dysphoria, expressed strong affective or cognitive reactions unrelated to gender dysphoria, or discussed body image. Conclusions Findings suggest that ML- and NLP-based models of gender dysphoria have significant potential to be integrated into technology-delivered interventions. The results contribute to the growing evidence on the importance of incorporating ML and NLP designs in clinical science, especially when studying marginalized populations.

show abstract

Technology-Based Interventions, with a Stepped Care Approach, for Reducing Sexual Risk Behaviors and Increasing PrEP Initiation Among Transgender and Gender Expansive Youth and Young Adults

Reback,

Cain,

Rusow

et al. 2024

AIDS Behav

View full text Add to dashboard Cite

Information and communication technology-based health interventions for transgender people: A scoping review

Abstract: Information and communication technology-based health interventions for transgender people: A scoping review. PLOS Glob Public Health 2(9): e0001054.

Cited by 7 publications

References 88 publications

Health literacy of trans and gender diverse individuals –a cross sectional survey in Germany

Health literacy of trans and gender diverse individuals –a cross sectional survey in Germany

Models of Gender Dysphoria Using Social Media Data for Use in Technology-Delivered Interventions: Machine Learning and Natural Language Processing Validation Study

Technology-Based Interventions, with a Stepped Care Approach, for Reducing Sexual Risk Behaviors and Increasing PrEP Initiation Among Transgender and Gender Expansive Youth and Young Adults

Contact Info

Product

Resources

About