Evidence map›Paper›PMID 31067411›Full record

ArticleJDR clinical and translational research2020

Social Media Research Strategy to Understand Clinician and Public Perception of Health Care Messages.

J Huber, T Woods, A Fushi, M T Duong, A S Eidelman, A R Zalal, O Urquhart, E Colangelo, S Quinn, A Carrasco-Labra

Abstract read
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In one paragraph

Article in JDR clinical and translational research, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
8citing papers in PubMed, 1 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

8 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Article
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  6. Review
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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

10 authors.

J HuberCenter for Evidence-Based Dentistry, Science Institute, American Dental Association, Chicago, IL, USA.
T WoodsCenter for Evidence-Based Dentistry, Science Institute, American Dental Association, Chicago, IL, USA.
A FushiCollege of Dental Medicine, Midwestern University, Downers Grove, IL, USA.
M T DuongThe Center for Advanced Oral Health, Arizona School of Dentistry & Oral Health, Mesa, AZ, USA.
A S EidelmanSchool of Dental Medicine, Tufts University, Boston, MA, USA.
A R ZalalSchool of Dentistry, University of North Carolina, Chapel Hill, NC, USA.
O UrquhartCenter for Evidence-Based Dentistry, Science Institute, American Dental Association, Chicago, IL, USA.ORCID 0000-0003-0517-1266
E ColangeloCenter for Evidence-Based Dentistry, Science Institute, American Dental Association, Chicago, IL, USA.
S QuinnAmerican Dental Association, Chicago, IL, USA.
A Carrasco-LabraCenter for Evidence-Based Dentistry, Science Institute, American Dental Association, Chicago, IL, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

introductionDespite the potential of social media to influence public health and generate insights, the process of monitoring and analyzing the dissemination of health care messages on social media has been described as difficult and in need of improvement.

objectivesThe objective of this study was to describe and demonstrate a reproducible methodology for cataloging and analyzing health care-related social media comments and provide insight into how clinicians and members of the general public respond to health care messaging on social media.

methodsWe collected social media comments related to the American Dental Association's 2016 "Evidence-Based Clinical Practice Guideline for the Use of Pit-and-Fissure Sealants" between April 10, 2017, and October 31, 2017, from Facebook, Twitter, LinkedIn, Reddit, and online message boards for the

resultsWe collected 671 comments. Among our findings, Facebook (472 of 671) was the most popular platform among commentators; almost half of all comments (335 of 671) aligned with the recommendations of the 2016 American Dental Association sealants guideline; clinicians were more likely than the general public to like a comment that suggested an improvement to the guideline; and >75% of comments (521 of 671) were supported by anecdotal evidence.

conclusionAs the prevalence of anecdotes on social media suggests, the likelihood of falsehoods spreading on social media is high. Insights gleaned from the methodology described in this research could help combat the spread of such misinformation by providing disseminators of health care messaging with insight into their target audiences. Armed with this knowledge, disseminators can craft health care messages that more effectively engage clinicians and the general public. KNOWLEDGE TRANSFER STATEMENT: The methodology used in this research provides a reproducible strategy for tracking social media engagement with health care messages. Engagement results can assist future delivery of health care messages to key stakeholders and ensure better implementation and adoption of these communications.

Indexed as

Social MediaDelivery of Health CareNew YorkPublic HealthResearch DesignUnited Statesdata miningdental informaticsinformation disseminationpit and fissure sealantspractice guidelines as topicstakeholder participation

Identifiers

PMID31067411
PMCPMC6918023

What OpenQuestion holds

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LicenceCC BY-NC
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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.