Evidence map›Paper›PMID 37662553›Full record

ArticleAJPM focus2023

A Social Media-Based Public Health Campaign to Reduce Indoor Tanning in High-Risk Populations.

Isabella de Vere Hunt, Zhuo Ran Cai, Vanessa Nava, Natnaelle E Admassu, Stephanie Bousheri, Tiffani Johnson, Anna Tomz, Jessica Thompson, Lucy Zhang, Sherry Pagoto and 3 more

Abstract read
In one paragraph

Article in AJPM focus, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

3 citing papers in PubMed.

  1. Article
  2. Article
  3. Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

13 authors.

Isabella de Vere HuntProgram for Clinical Research and Technology, Stanford University, Stanford, California.
Zhuo Ran CaiProgram for Clinical Research and Technology, Stanford University, Stanford, California.
Vanessa NavaProgram for Clinical Research and Technology, Stanford University, Stanford, California.
Natnaelle E AdmassuMemorial Sloan Kettering Cancer Center, New York, New York.
Stephanie BousheriProgram for Clinical Research and Technology, Stanford University, Stanford, California.
Tiffani JohnsonProgram for Clinical Research and Technology, Stanford University, Stanford, California.
Anna TomzProgram for Clinical Research and Technology, Stanford University, Stanford, California.
Jessica ThompsonProgram for Clinical Research and Technology, Stanford University, Stanford, California.
Lucy ZhangProgram for Clinical Research and Technology, Stanford University, Stanford, California.
Sherry PagotoDepartment of Allied Health Sciences, University of Connecticut, Mansfield, Connecticut.
Mackenzie R WehnerDepartment of Health Services Research, The University of Texas MD Anderson Cancer Center, Houston, Texas.
Maya B MathurQuantitative Sciences Unit, Department of Pediatrics, Stanford University, Stanford, California.
Eleni LinosProgram for Clinical Research and Technology, Stanford University, Stanford, California.

Funding

X-RAY CRYSTALLOGRAPHYP30CA008748 · NCI · SLOAN-KETTERING INSTITUTE FOR CANCER RES · PI Nicholas D Socci · 1985 to 2026
$347.4M
Translational Oncology Research Program (Project-005)P30CA124435 · NCI · STANFORD UNIVERSITY · PI Melinda L. Telli · 2007 to 2026
$71.4M
Patient Oriented Research in Vulnerable Populations with Skin DiseaseK24AR075060 · NIAMS · STANFORD UNIVERSITY · PI Eleni Linos · 2019 to 2026
$1.6M
Skin Cancer Risks and Risk Prediction in Patients with Actinic KeratosisK08CA263298 · NCI · UNIVERSITY OF TX MD ANDERSON CAN CTR · PI Mackenzie Rachel Wehner · 2022 to 2026
$1.3M
Novel digital tools for home-based monitoring of skin diseaseR01AR082109 · NIAMS · STANFORD UNIVERSITY · PI Eleni Linos · 2023 to 2026
$629k
NCI NIH HHS K08 CA263298NCI NIH HHS P30 CA008748NCI NIH HHS P30 CA124435NIAMS NIH HHS K24 AR075060NIAMS NIH HHS R01 AR082109
6 · The paper itself

Abstract

Introduction: Indoor tanning beds cause more than 450,000 new skin cancers each year, yet their use remains common, with a global indoor tanning prevalence of 10.4%. Social media provides an opportunity for cost-effective, targeted public health messaging. We sought to direct Instagram users at high risk of indoor tanning to accurate health information about the risks of indoor tanning and to reduce indoor tanning bed use. Methods: We disseminated a public health campaign on Instagram on April 6-27, 2022 with 34 video and still-image advertisements. We had 2 target audiences at high risk of indoor tanning: women aged 18-30 years in Kentucky, Nebraska, Ohio, or Tennessee interested in indoor tanning and men aged 18-45 years in California interested in indoor tanning. To evaluate the impact of the campaign, we tracked online metrics, including website visits, and conducted an interrupted time-series analysis of foot traffic data in our target states for all tanning salons documented on SafeGraph from January 1, 2018 to 3 months after the campaign. Results: Our indoor tanning health information advertisements appeared on Instagram feeds 9.1 million times, reaching 1.06 million individuals. We received 7,004 views of our indoor tanning health information landing page (Average Time on Page of 56 seconds). We did not identify a significant impact on foot traffic data on tanning salons. Conclusions: We show the successful use of social media advertising to direct high-risk groups to online health information about indoor tanning. Future research quantifying tanning visits before and after indoor tanning interventions is needed to guide future public health efforts.

Indexed as

cancer preventionhealth communicationPublic healthskin cancersocial media

Identifiers

PMID37662553
PMCPMC10465716

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.