Social Media as a Risk Tool for HIV Prevention Needs

NCT06566417 | Completed DMC

• 2 other identifiers: 2023P0016251R21MH132436-01A1
• Study Type: observational
• Target: 400
• Locations: 1 country
• Sites: 1

Brief Summary

The impact of effective HIV prevention tools is limited because many people do not know that they are at risk for HIV acquisition, despite the availability of various risk assessment scores and criteria. This proposal aims to use a novel data science approach to assessing HIV prevention needs among 400 young women in Kisumu, Kenya- namely, topic modeling and network analysis of text and/or social media messages (e.g., WhatsApp, Instagram, Twitter). The study will involve in-depth assessment of relevant ethical and logistical factors to ensure appropriate and optimized use of a sentiment analysis tool for implementation in routine clinical care.

Conditions

HIV Prevention; HIV Preexposure Prophylaxis

Keywords

HIV prevention; HIV Pre-exposure prophylaxis; Sentiment analysis

Outcome Measures

Primary Outcomes (2)

• Association of artificial intelligence measure datasets with the VOICE risk score

  Analysts will examine 6 months of SMS/social media message content from each of the 400 study participants using three computational linguistic methods: 1) sentiment, valence, and arousal analysis; 2) topic modeling; 3) simple textual counts. Analysts will also perform network analysis with up to 20 contacts from each participant to understand how often and with which parties the participant communicates most frequently. These networks will be examined temporally to see if any of the connections have grown or weakened over time. From these analyses, the investigators will generate multiple measure datasets to compare with the VOICE risk score (i.e., a combined assessment of HIV risk based on age, marital status, sexual partner support, sexual partner sexual behavior, and alcohol use), as assessed in the study participants at the time of SMS/social media data collection.

  6 months

• Association of artificial intelligence measure datasets with the Wand risk score

  The investigators will compare the above-noted measure datasets with the Wand risk score (i.e., a combined assessment of HIV risk based on age, marital status, age at sexual debut, number of sexual partners, use of injectable contraception, and history of sexually transmitted infections), as assessed in the study participants at the time of SMS/social media data collection.

  One day

Secondary Outcomes (1)

• Association of artificial intelligence measure datasets with HIV test results

  One day

Eligibility Criteria

• Age: 18 Years - 24 Years
• Sex: female
• Healthy Volunteers: Yes
• Age Groups: Adult (18-64)
• Sampling Method: Non-Probability Sample

Study Population

Research assistants will recruit young Kenyan women (ages 18-24), attending one of four clinics for any health services. Smart phone ownership and use of SMS, WhatsApp, or other social media is required.

You may qualify if:

• Identifying as a young woman (age 18-24 years)
• Attending clinic for any health services, including PrEP and HIV testing
• Smart phone ownership
• Ability to understand Kiswahili, DhoLuo, and/or English
• Use of SMS, WhatsApp, and/or other types of social media

You may not qualify if:

• Inability to provide informed consent (e.g., intoxication, developmental delay)

Sponsors & Collaborators

• Massachusetts General Hospital: lead
• Kenya Medical Research Institute: collaborator
• KEMRI-Wellcome Trust Collaborative Research Program: collaborator
• North Carolina State University: collaborator
• National Institute of Mental Health (NIMH): collaborator

Study Sites (1)

KEMRI

Kisumu, Kenya

Location

Study Officials

• Jessica Haberer, MD, MS

  Massachusetts General Hospital

  PRINCIPAL INVESTIGATOR

Study Design

• Study Type: observational
• Observational Model: COHORT
• Time Perspective: PROSPECTIVE
• Sponsor Type: OTHER
• Responsible Party: PRINCIPAL INVESTIGATOR
• PI Title: Professor of Medicine, Director of Research

Study Record Dates

• First Submitted: July 30, 2024
• First Posted: August 22, 2024
• Study Start: February 1, 2024
• Primary Completion: May 15, 2025
• Study Completion: July 20, 2025
• Last Updated: November 12, 2025

Record last verified: 2025-11

Data Sharing

• IPD Sharing: Will share
• Shared Documents: STUDY PROTOCOL, SAP, ICF
• Time Frame: We will make this data available after publishing our findings.
• Access Criteria: We will post a de-identified dataset to the Harvard Dataverse, a datasharing platform.

Locations

KE (1)