Social Media as a Risk Tool for HIV Prevention Needs (SMaaRT)

August 26, 2026 updated by: Jessica Haberer, MD, Massachusetts General Hospital

Use of Sentiment Analysis and Social Media to Understand HIV Prevention Needs Among Young Women in Kenya

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.

Study Overview

Status

Status

Indicates the current recruitment status or the expanded access status.
Completed

Conditions

Conditions

The disease, disorder, syndrome, illness, or injury that is being studied. On ClinicalTrials.gov, conditions may also include other health-related issues, such as lifespan, quality of life, and health risks.

Detailed Description

In the Social Media as a Risk Tool (SMaaRT) Study, the investigators hypothesize that topic modeling of SMS/social media data combined with network analysis among young women in Kenya will correlate well with existing HIV risk scales and ultimately yield a better understanding of HIV prevention needs. The investigators propose the following aims:

  1. Explore ethical factors that may influence analysis of SMS and social media messages. Research assistants will conduct individual qualitative interviews with up to 32 young women (16 who would and 16 who would not provide SMS/social media data, stratified among four clinic sites) and one focus group of five Kenyan bioethicists. Questions will explore ethical concerns from individual and bystander (e.g., contacts involved in SMS/social media) perspectives and differences in ethical issues by type of social media (e.g., conversations vs posts). Follow-up interviews will be conducted with the women who provide SMS and/or social media data (in Aim 2).
  2. Conduct topic modeling and network analysis of SMS and social media messages to predict HIV prevention needs among young women in Kenya. Working with four clinical sites in Kisumu, study staff will ask approximately 400 women (ages 18-24) seeking HIV testing, PrEP, and other health services to download six months of SMS/social media messages (e.g., WhatsApp, Instagram, Twitter) as a one-time procedure. For those providing data, research assistants will assess social networks engaged via SMS/social media (e.g., anonymously labeled as peers, sexual partners), administer multiple HIV risk assessments (e.g., VOICE, Wand risk scores), and obtain HIV test results. Data analysts will use automated structural topic modelling to determine "topics" (word clusters) and assess for association with other risk assessments (primary outcome) and HIV test results (exploratory outcome), and will also evaluate the impact of social networks, SMS/social media type, data volume, and language type on outcomes. Data collection and analysis will conform to Aim 1 findings.
  3. Assess practical factors that may influence use of a sentiment analysis tool in routine care. In a needs assessment based on Implementation Mapping, research assistants will conduct four focus groups with five staff per clinic and two focus groups with five young women each to explore staffing best suited to implement a sentiment analysis tool and how it could be best integrated into routine care. The investigators will also assess available resources to determine optimal efficiency in developing a preliminary implementation strategy.

Study Type

Study Type

Describes the nature of a clinical study. Study types include interventional studies (also called clinical trials), observational studies (including patient registries), and expanded access.
Observational

Enrollment (Actual)

Enrollment

The number of participants in a clinical study. The "anticipated" enrollment is the target number of participants that the researchers need for the study.
400

Contacts and Locations

This section provides the contact details for those conducting the study, and information on where this study is being conducted.

Study Contact

Study Contact

The name and contact information for the person who can answer enrollment questions for a clinical study. Each location where the study is being conducted may also have a specific contact, who may be better able to answer those questions.

Study Locations

  • Kenya
      • Kisumu, Kenya
        • KEMRI

Participation Criteria

Researchers look for people who fit a certain description, called eligibility criteria. Some examples of these criteria are a person's general health condition or prior treatments.

Eligibility Criteria

Eligibility Criteria

The key requirements that people who want to participate in a clinical study must meet or the characteristics they must have. Eligibility criteria consist of both inclusion criteria (which are required for a person to participate in the study) and exclusion criteria (which prevent a person from participating). Types of eligibility criteria include whether a study accepts healthy volunteers, has age or age group requirements, or is limited by sex.

Ages Eligible for Study

  • Adult

Accepts Healthy Volunteers

Yes

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.

Description

Inclusion Criteria:

  • 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

Exclusion Criteria:

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

Study Plan

This section provides details of the study plan, including how the study is designed and what the study is measuring.

How is the study designed?

Design Details

What is the study measuring?

Primary Outcome Measures

Primary Outcome Measures

In a clinical study's protocol, the planned outcome measure that is the most important for evaluating the effect of an intervention/treatment. Most clinical studies have one primary outcome measure, but some have more than one.
Outcome Measure
Measure Description
Time Frame
Association of Artificial Intelligence Measure Datasets With the Wand Risk Score
Time Frame: 6 months of data given at one time

The investigators will compare the above-noted measure datasets with the Wand risk score as assessed in the study participants at the time of SMS/social media data collection.

The Wand risk score is an empirically validated HIV prediction tool designed to estimate the probability of HIV acquisition in women. It calculates a total score (max 50 pts): age <20 years (11 pts), 20-24 years (10 pts), 25-29 years (6 pts), 30+ years (0 pts); marital status of single/not cohabitating (13 pts), married/cohabitating (0 pts); # sexual partners in last 3 months of 3 or more (5 pts), <3 (0 pts); age at sexual debut of <16 years (3 pts), 16+ years (0 pts); parity (# of births) of 0-1 births (10 pts), 2 births (8 pts), 3+ births (0 pts); ever diagnosed with an STI as yes (4 pts), no (0 pts); and use of injectable contraception as yes (4 pts), no (0 pts). A higher score denotes a higher HIV risk. The total possible range is 0-50.
6 months of data given at one time
Association of Artificial Intelligence Measure Datasets With the VOICE Risk Score
Time Frame: 6 months

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.

The VOICE risk score (modified to not use biological markers) is a measure of behavioral and demographic factors to determine HIV risk: <25 y/o (2 pts), unmarried or not living with a partner (2 pts), primary partner has other partners (2 pts), partner does not provide financial support (1 pt), alcohol use in the last 3 months (1 pt). A higher score denotes a greater HIV risk. The total possible range is 0-8.
6 months

Secondary Outcome Measures

Secondary Outcome Measures

In a clinical study's protocol, a planned outcome measure that is not as important as the primary outcome measure for evaluating the effect of an intervention but is still of interest. Most clinical studies have more than one secondary outcome measure.
Outcome Measure
Measure Description
Time Frame
Association of artificial intelligence measure datasets with HIV test results
Time Frame: One day
The investigators will compare the above-noted measure datasets with the HIV test results obtained from the study participants at the time of data collection.
One day

Collaborators and Investigators

This is where you will find people and organizations involved with this study.

Sponsor

Sponsor

The organization or person who initiates the study and who has authority and control over the study.
Massachusetts General Hospital

Collaborators

Collaborators

An organization other than the sponsor that provides support for a clinical study. This support may include activities related to funding, design, implementation, data analysis, or reporting.
National Institute of Mental Health (NIMH)
KEMRI-Wellcome Trust Collaborative Research Program
Kenya Medical Research Institute
North Carolina State University

Investigators

Investigators

A researcher involved in a clinical study. Related terms include site principal investigator, site sub-investigator, study chair, study director, and study principal investigator.
  • Principal Investigator: Jessica Haberer, MD, MS, Massachusetts General Hospital

Study record dates

These dates track the progress of study record and summary results submissions to ClinicalTrials.gov. Study records and reported results are reviewed by the National Library of Medicine (NLM) to make sure they meet specific quality control standards before being posted on the public website.

Study Major Dates

Study Start (Actual)

Study Start

The actual date on which the first participant was enrolled in a clinical study. The "anticipated" study start date is the date that the researchers think will be the study start date.
February 1, 2024

Primary Completion (Actual)

Primary Completion

The date on which the last participant in a clinical study was examined or received an intervention to collect final data for the primary outcome measure. Whether the clinical study ended according to the protocol or was terminated does not affect this date. For clinical studies with more than one primary outcome measure with different completion dates, this term refers to the date on which data collection is completed for all the primary outcome measures. The "anticipated" primary completion date is the date that the researchers think will be the primary completion date for the study.
May 15, 2025

Study Completion (Actual)

Study Completion

The date on which the last participant in a clinical study was examined or received an intervention/treatment to collect final data for the primary outcome measures, secondary outcome measures, and adverse events (that is, the last participant's last visit). The "anticipated" study completion date is the date that the researchers think will be the study completion date.
July 20, 2025

Study Registration Dates

First Submitted

First Submitted

The date on which the study sponsor or investigator first submitted a study record to ClinicalTrials.gov. There is typically a delay of a few days between the first submitted date and the record's availability on ClinicalTrials.gov (the first posted date).
July 30, 2024

First Submitted That Met QC Criteria

First Submitted That Met QC Criteria

The date on which the study sponsor or investigator first submits a study record that is consistent with National Library of Medicine (NLM) quality control (QC) review criteria. The sponsor or investigator may need to revise and submit a study record one or more times before NLM's QC review criteria are met. It is the responsibility of the sponsor or investigator to ensure that the study record is consistent with the NLM QC review criteria.
August 19, 2024

First Posted (Actual)

First Posted

The date on which the study record was first available on ClinicalTrials.gov after National Library of Medicine (NLM) quality control (QC) review has concluded. There is typically a delay of a few days between the date the study sponsor or investigator submitted the study record and the first posted date.
August 22, 2024

Study Record Updates

Last Update Posted (Actual)

Last Update Posted

The most recent date on which changes to a study record were made available on ClinicalTrials.gov. There may be a delay between when the changes were submitted to ClinicalTrials.gov by the study's sponsor or investigator (the last update submitted date) and the last update posted date.
August 31, 2026

Last Update Submitted That Met QC Criteria

Last Update Submitted That Met QC Criteria

The most recent date on which the study sponsor or investigator submitted changes to a study record that are consistent with National Library of Medicine (NLM) quality control (QC) review criteria. It is the responsibility of the sponsor or investigator to ensure that the study record is consistent with the NLM QC review criteria.
August 26, 2026

Last Verified

Last Verified

The most recent date on which the study sponsor or investigator confirmed the information about a clinical study on ClinicalTrials.gov as accurate and current. If a study with a recruitment status of recruiting; not yet recruiting; or active, not recruiting has not been confirmed within the past 2 years, the study's recruitment status is shown as unknown.
August 1, 2026

More Information

Terms related to this study

Keywords

Additional Relevant MeSH Terms

Other Study ID Numbers

Other Study ID Numbers

Identifiers or ID numbers other than the NCT number that are assigned to a clinical study by the study's sponsor, funders, or others. These numbers may include unique identifiers from other trial registries and National Institutes of Health grant numbers.
  • 2023P001625
  • 1R21MH132436-01A1 (U.S. NIH Grant/Contract)

Plan for Individual participant data (IPD)

Plan to Share Individual Participant Data (IPD)?

YES

IPD Plan Description

This project will release and share final de-identified research data and materials from NIH-supported research for use by other researchers in a timely manner. Due to the sensitive nature of the SMS/social media messages, that data will be deleted at the conclusion of the study.

IPD Sharing Time Frame

We will make this data available after publishing our findings.

IPD Sharing Access Criteria

We will post a de-identified dataset to the Harvard Dataverse, a datasharing platform.

IPD Sharing Supporting Information Type

  • STUDY_PROTOCOL
  • SAP
  • ICF

Drug and device information, study documents

Studies a U.S. FDA-regulated drug product

No

Studies a U.S. FDA-regulated device product

No

This information was retrieved directly from the website clinicaltrials.gov without any changes. If you have any requests to change, remove or update your study details, please contact register@clinicaltrials.gov. As soon as a change is implemented on clinicaltrials.gov, this will be updated automatically on our website as well.

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