Search Articles

View query in Help articles search

Search Results (1 to 10 of 153 Results)

Download search results: END BibTex RIS


Capture-Recapture Among Men Who Have Sex With Men and Among Female Sex Workers in 11 Towns in Uganda

Capture-Recapture Among Men Who Have Sex With Men and Among Female Sex Workers in 11 Towns in Uganda

IntroductionBackgroundKey populations such as female sex workers (FSWs) and men who have sex with men (MSM) are disproportionately affected by the HIV epidemic [1,2].

Kevin Apodaca, Reena Hemendra Doshi, Moses Ogwal, Herbert Kiyingi, George Aluzimbi, Geofrey Musinguzi, Ibrahim Lutalo, Evelyn Akello, Wolfgang Hladik

JMIR Public Health Surveill 2019;5(2):e12316

Opportunities for Enhanced Strategic Use of Surveys, Medical Records, and Program Data for HIV Surveillance of Key Populations: Scoping Review

Opportunities for Enhanced Strategic Use of Surveys, Medical Records, and Program Data for HIV Surveillance of Key Populations: Scoping Review

See Figure 1.Disaggregation of HIV surveillance indicators [2] for the five key populations recognized by WHO (men who have sex with men [MSM], people in prisons and other closed settings, people who inject drugs, sex workers, and transgender people [3]) is

Sharon Stucker Weir, Stefan D Baral, Jessie K Edwards, Sabrina Zadrozny, James Hargreaves, Jinkou Zhao, Keith Sabin

JMIR Public Health Surveill 2018;4(2):e28

Informing HIV Prevention Programs for Adolescent Girls and Young Women: A Modified Approach to Programmatic Mapping and Key Population Size Estimation

Informing HIV Prevention Programs for Adolescent Girls and Young Women: A Modified Approach to Programmatic Mapping and Key Population Size Estimation

to reach women who engage in other types of sexual partnerships that may also be associated with increased risk of HIV acquisition—namely, condomless sex in the context of transactional sex and casual sex [14].

Eve Cheuk, Shajy Isac, Helgar Musyoki, Michael Pickles, Parinita Bhattacharjee, Peter Gichangi, Robert Lorway, Sharmistha Mishra, James Blanchard, Marissa Becker

JMIR Public Health Surveill 2019;5(2):e11196

Using Computer Simulations for Investigating a Sex Education Intervention: An Exploratory Study

Using Computer Simulations for Investigating a Sex Education Intervention: An Exploratory Study

However, people continue to engage in risky sexual behaviors, such as having condomless sex [4] and using condoms incorrectly [5,6].

Anastasia Eleftheriou, Seth Bullock, Cynthia A Graham, Roger Ingham

JMIR Serious Games 2017;5(2):e9

Sexual Desire, Mood, Attachment Style, Impulsivity, and Self-Esteem as Predictive Factors for Addictive Cybersex

Sexual Desire, Mood, Attachment Style, Impulsivity, and Self-Esteem as Predictive Factors for Addictive Cybersex

The dependent variable was the CIUS score, and the independent variables were the SDI score, the SDHS score, the ECR-R subscales, the UPPS-P subscales, the SISE, sex, and sexual orientation.

Nektaria Varfi, Stephane Rothen, Katarzyna Jasiowka, Thibault Lepers, Francesco Bianchi-Demicheli, Yasser Khazaal

JMIR Ment Health 2019;6(1):e9978

Intragroup Stigma Among Men Who Have Sex with Men: Data Extraction from Craigslist Ads in 11 Cities in the United States

Intragroup Stigma Among Men Who Have Sex with Men: Data Extraction from Craigslist Ads in 11 Cities in the United States

Online sex-seeking has become increasingly popular [19,20]; an estimated 40% of MSM in the United States have used the Internet to look for a sex partner [21-25].

Tamar Goldenberg, Dhrutika Vansia, Rob Stephenson

JMIR Public Health Surveill 2016;2(1):e4

Novel Approaches for Estimating Female Sex Worker Population Size in Conflict-Affected South Sudan

Novel Approaches for Estimating Female Sex Worker Population Size in Conflict-Affected South Sudan

The relative stability allowed increased commerce and the apparent increase in the number of female sex workers (FSW) [4]. Little data exist on sex workers in South Sudan.

Alfred Geoffrey Okiria, Alex Bolo, Victoria Achut, Golda Ceasar Arkangelo, Acaga Taban Ismail Michael, Joel Sua Katoro, Jennifer Wesson, Steve Gutreuter, Lee Hundley, Avi Hakim

JMIR Public Health Surveill 2019;5(1):e11576

An Environmental Scan of Sex and Gender in Electronic Health Records: Analysis of Public Information Sources

An Environmental Scan of Sex and Gender in Electronic Health Records: Analysis of Public Information Sources

For sex, there are 11 unique data element names from 13 code systems and 16 value sets (Textbox 3). GSSO has also defined 3 sex subtypes as biological sex, anatomic sex, and genotypic sex.

Francis Lau, Marcy Antonio, Kelly Davison, Roz Queen, Katie Bryski

J Med Internet Res 2020;22(11):e20050