This catalog record includes detailed variable-level descriptions, enabling data discovery and comparison. The data are not archived at ICPSR. Users should consult the data owners (via the Roper Center for Public Opinion Research) directly for details on obtaining the data. This collection includes variable-level metadata of the 2017 Discrimination in the United States Survey, a survey from Harvard T.H. Chan School of Public Health/Robert Wood Johnson Foundation/National Public Radio conducted by Social Science Research Solutions (SSRS). Topics covered in this survey include:Belief in discrimination against racial/ethnic minoritiesDiscrimination against men/womenDiscrimination against lesbian/gay/bisexual peopleDiscrimination against transgender peopleBiggest problem with discrimination against lesbian/gay/bisexual/transgender/queer (LGBTQ) peopleLive on tribal landsLocal/tribal government Discrimination based on raceDiscrimination based on genderDiscrimination based on being part of the LGBTQ communityReasons for avoiding seeking health careExperiences with discriminationDiscrimination resulting in fewer employment opportunitiesDiscrimination resulting in unequal payDiscrimination resulting in fewer chances for quality educationEncouraged to/discouraged from applying to collegePredominant groups living in respondent's areaNot feeling/being welcomed in neighborhood due to raceNot feeling/being welcomed in neighborhood due to being part of LGBTQ communityConsidered moving to another area because of discriminationComparing respondent's area to othersPolice using unnecessary force based on race/ethnicityAvoiding activities to avoid discrimination from policeExperiences caused by racial discriminationExperiences caused by gender discriminationExperiences caused by discrimination against LGBTQ communityLocal police force does/does not reflect racial/ethnic background of communityContacted by political representatives about voting/supporting causeRegistered to voteVote in 2016 presidential electionPhysical health statusMental health statusDisabilityChronic illnessVeterans AdministrationIndian Health ServicesSeeking health careInsurance coverageThe data and documentation files for this survey are available through the Roper Center for Public Opinion Research [Roper #31114655]. Frequencies and summary statistics for the 235 variables from this survey are available through the ICPSR social science variable database and can be accessed from the Variables tab.

Although South Africa is the global epicenter of the HIV epidemic, the uptake of HIV testing and treatment among young people remains low. Concerns about confidentiality impede the utilization of HIV prevention services, which signals the need for discrete HIV prevention measures that leverage youth-friendly platforms. This paper describes the process of developing a youth-friendly internet-enabled HIV risk calculator in collaboration with young people, including young key populations aged between 18 and 24 years old. Using qualitative research, we conducted an exploratory study with 40 young people including young key population (lesbian, gay, bisexual, transgender (LGBT) individuals, men who have sex with men (MSM), and female sex workers). Eligible participants were young people aged between 18–24 years old and living in Soweto. Data was collected through two peer group discussions with young people aged 18–24 years, a once-off group discussion with the [Name of clinic removed for confidentiality] adolescent community advisory board members and once off face-to-face in-depth interviews with young key population groups: LGBT individuals, MSM, and female sex workers. LGBT individuals are identified as key populations because they face increased vulnerability to HIV/AIDS and other health risks due to societal stigma, discrimination, and obstacles in accessing healthcare and support services. The measures used to collect data included a socio-demographic questionnaire, a questionnaire on mobile phone usage, an HIV and STI risk assessment questionnaire, and a semi-structured interview guide. Framework analysis was used to analyse qualitative data through a qualitative data analysis software called NVivo. Descriptive statistics were summarized using SPSS for participant socio-demographics and mobile phone usage. Of the 40 enrolled participants, 58% were male, the median age was 20 (interquartile range 19–22.75), and 86% had access to the internet. Participants’ recommendations were considered in developing the HIV risk calculator. They indicated a preference for an easy-to-use, interactive, real-time assessment offering discrete and private means to self-assess HIV risk. In addition to providing feedback on the language and wording of the risk assessment tool, participants recommended creating a colorful, interactive and informational app. A collaborative and user-driven process is crucial for designing and developing HIV prevention tools for targeted groups. Participants emphasized that privacy, confidentiality, and ease of use contribute to the acceptability and willingness to use internet-enabled HIV prevention methods.