Evidence map›Paper›PMID 25103820›Full record

ArticleCancer epidemiology, biomarkers & prevention : a publication of the American Association for Cancer Research, cosponsored by the American Society of Preventive Oncology2014

Cancer prevention and control interventions using social media: user-generated approaches.

David N Cavallo, Wen-Ying Sylvia Chou, Amy McQueen, Amelie Ramirez, William T Riley

Abstract read
In one paragraph

Article in Cancer epidemiology, biomarkers & prevention : a publication of the American Association for Cancer Research, cosponsored by the American Society of Preventive Oncology, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 24 papers, 4 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
24citing papers in PubMed, 4 pooled it
–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

24 citing papers in PubMed, 4 syntheses or guidelines pooled it.

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  17. Community Engagement for Identifying Cancer Education Needs in Puerto Rico.Journal of cancer education : the official journal of the American Association for Cancer Education · 2018
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  20. Social Media and Mobile Technology for Cancer Prevention and Treatment.American Society of Clinical Oncology educational book. American Society of Clinical Oncology. Annual Meeting · 2017
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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

5 authors.

David N CavalloCenter for Cancer Prevention and Control Research, University of California Los Angeles, Los Angeles, California. dncavallo@ucla.edu.
Wen-Ying Sylvia ChouDivision of Cancer Control and Population Sciences, National Cancer Institute, Bethesda, Maryland.
Amy McQueenWashington University School of Medicine, St. Louis, Missouri.
Amelie RamirezInstitute for Health Promotion Research, Cancer Therapy and Research Center, University of Texas Health Science Center, San Antonio, Texas.
William T RileyDivision of Cancer Control and Population Sciences, National Cancer Institute, Bethesda, Maryland.

Funding

TISSUE CULTURE---COREP30CA054174 · NCI · UNIVERSITY OF TEXAS HLTH SCIENCE CENTER · PI Lei Zheng · 1991 to 2026
$59.1M
UCLA Career Development Program in Cancer Prevention and Control ResearchR25CA087949 · NCI · UNIVERSITY OF CALIFORNIA LOS ANGELES · PI BASTANI, ROSHAN · 2000 to 2014
$6.8M
Training ProgramU54CA153511 · NCI · UNIVERSITY OF TEXAS HLTH SCIENCE CENTER · PI RAMIREZ, AMELIE G · 2010 to 2015
$6.2M
NCI NIH HHS P30 CA054174NCI NIH HHS P30CA054174NCI NIH HHS R25 CA087949NCI NIH HHS R25 CA87949NCI NIH HHS U54 CA153511
6 · The paper itself

Abstract

Social media are now used by a majority of American internet users. Social media platforms encourage participants to share information with their online social connections and exchange user-generated content. Significant numbers of people are already using social media to share health-related information. As such, social media provide an opportunity for "user-generated" cancer control and prevention interventions that employ users' behavior, knowledge, and existing social networks for the creation and dissemination of interventions. These interventions also enable novel data collection techniques and research designs that will allow investigators to examine real-time behavioral responses to interventions. Emerging social media-based interventions for modifying cancer-related behaviors have been applied to such domains as tobacco use, diet, physical activity, and sexual practices, and several examples are discussed for illustration purposes. Despite some promising early findings, challenges including inadequate user engagement, privacy concerns, and lack of internet access among some groups need to be addressed in future research. Recommendations for advancing the field include stronger partnerships with commercial technology companies, utilization of rapid and adaptive designs to identify successful strategies for user engagement, rigorous and iterative efficacy testing of these strategies, and inclusive methods for intervention dissemination.

Indexed as

Social MediaFemaleHumansMaleNeoplasms

Identifiers

PMID25103820
PMCPMC4154981

What OpenQuestion holds

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LicenceTDM
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.