# Skin cancer on social media: Analyzing current communications, modeling diffusion potential, and developing innovative prevention-focused messages

> **NIH NIH R01** · TRUSTEES OF INDIANA UNIVERSITY · 2024 · $542,724

## Abstract

Project Abstract
Exposure to ultraviolet (UV) light between the ages of 15-20 years is the most important etiological factor in skin
cancer, yet adolescents and young adults (AYAs) this age are more likely to engage in health-compromising
behaviors like indoor and outdoor tanning without skin protection. As an intervention modality, social media (SM)
represents an opportunity to reach AYAs, who are among the most active Facebook, Instagram, and Twitter
users. Recent research suggests SM may also be a rich hub for proliferation of skin cancer misinformation; yet
the characteristics and diffusion patterns of this misinformation and risk/prevention communication across
platforms are unknown. Characterizing the skin cancer communication landscape and creating effective
risk/prevention posts, with an “understanding of which messages will resonate with specific groups” (The
Surgeon General’s Call to Action to Prevent Skin Cancer), could enable targeted prevention methods for AYAs.
Our long-term goal is to reduce health-compromising behaviors (e.g., indoor tanning, sunscreen nonuse) among
at-risk AYAs, who are vulnerable to developing skin cancer. This proposal’s main objective is to: 1) characterize
the SM landscape regarding skin cancer-related posts; and 2) develop/test messages for skin cancer prevention
among AYAs that are clear, specific, consistent, and scientifically up to date. With a robust multidisciplinary team,
we will accomplish this objective via three specific aims—AIM 1: Characterize skin cancer-related communication
across three popular SM platforms. AIM 2: Build a predictive, explainable health communication model to
determine the diffusion potential of skin cancer-related messages. AIM 3: Develop/pilot test sun-protection and
indoor tanning-related messages for AYAs for future implementation and evaluation. In AIM 1 we will use content
analyses to assess the skin cancer communication/misinformation landscapes on Facebook, Instagram, and
Twitter, describing message features, source characteristics, posters/users, and social networks, and identifying
network characteristics and diffusion patterns of skin cancer misinformation (exploratory). In AIM 2 we will apply
machine learning methods to characterize message features; develop/evaluate a predictive model of a message
diffusion potential using large-scale training data; apply the model to predict a set of online diffusion metrics for
a given message; and assess its ability to reach skin cancer prevention-relevant populations. In AIM 3 we will
engage two stakeholder segments in iterative rounds of message development/testing: 1) cancer organization
staff (who post on their SM accounts); and 2) intended recipients of these messages: five sub-groups of AYAs
aged 15-20 years—White boys/men, White girls/women, and White, Black, and Hispanic gay and bisexual
boys/men. The research is innovative because of its focus on posts across three SM platforms and the Multilevel
Model of Meme Diffusio...

## Key facts

- **NIH application ID:** 10881117
- **Project number:** 1R01CA279679-01A1
- **Recipient organization:** TRUSTEES OF INDIANA UNIVERSITY
- **Principal Investigator:** Eric Richard Walsh-Buhi
- **Activity code:** R01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2024
- **Award amount:** $542,724
- **Award type:** 1
- **Project period:** 2024-09-03 → 2025-08-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10881117

## Citation

> US National Institutes of Health, RePORTER application 10881117, Skin cancer on social media: Analyzing current communications, modeling diffusion potential, and developing innovative prevention-focused messages (1R01CA279679-01A1). Retrieved via AI Analytics 2026-05-26 from https://api.ai-analytics.org/grant/nih/10881117. Licensed CC0.

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