Evidence map›Paper›PMID 27330669›Full record

ArticleThe western journal of emergency medicine2016

Survey of Individual and Institutional Risk Associated with the Use of Social Media.

Manish Garg, David A Pearson, Michael C Bond, Michael Runyon, M Tyson Pillow, Laura Hopson, Robert R Cooney, Jay Khadpe, Jason T Nomura, Pholaphat C Inboriboon

Abstract read
In one paragraph

Article in The western journal of emergency medicine, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
6citing 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

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

  1. Pooled it
  2. Article
  3. Article
  4. Article
  5. Article
  6. Assessing the use of social media in physician assistant education.International journal of medical education · 2019
    Article
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.

Manish GargTemple University Hospital, Department of Emergency Medicine, Philadelphia, Pennsylvania.
David A PearsonCarolinas Medical Center, Department of Emergency Medicine, Charlotte, North Carolina.
Michael C BondUniversity of Maryland School of Medicine, Department of Emergency Medicine, Baltimore, Maryland.
Michael RunyonCarolinas Medical Center, Department of Emergency Medicine, Charlotte, North Carolina.
M Tyson PillowBaylor College of Medicine, Department of Emergency Medicine, Houston, Texas.
Laura HopsonUniversity of Michigan, Department of Emergency Medicine, Ann Arbor, Michigan.
Robert R CooneyConemaugh Memorial Medical Center, Department of Emergency Medicine, Johnstown, Pennsylvania.
Jay KhadpeSUNY Downstate Medical Center, Department of Emergency Medicine, Brooklyn, New York.
Jason T NomuraChristiana Care Health System, Department of Emergency Medicine, Newark, Delaware.
Pholaphat C InboriboonUniversity of Missouri-Kansas City, Department of Emergency Medicine, Kansas City, Missouri.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

introductionResidents and faculty in emergency medicine (EM) residency programs might be unaware of the professional and legal risks associated with the use of social media (SM). The objective of this study was to identify and characterize the types and reported incidence of unprofessional SM behavior by EM residents, faculty, and nurses and the concomitant personal and institutional risks.

methodsThis multi-site study used an 18-question survey tool that was distributed electronically to the leaders of multiple EM residency programs, members of the Council of Emergency Medicine Residency Directors (CORD), and the residents of 14 EM programs during the study period May to June 2013.

resultsWe received 1,314 responses: 772 from residents and 542 from faculty. Both groups reported encountering high-risk-to-professionalism events (HRTPE) related to SM use by residents and non-resident providers (NRPs), i.e., faculty members and nurses. Residents reported posting of one of the following by a resident peer or nursing colleague: identifiable patient information (26%); or a radiograph, clinical picture or other image (52%). Residents reported posting of images of intoxicated colleagues (84%), inappropriate photographs (66%), and inappropriate posts (73%). Program directors (PDs) reported posting one of the following by NRPs and residents respectively: identifiable patient information (46% and 45%); a radiograph, clinical picture or other image (63% and 58%). PDs reported that NRPs and residents posted images of intoxicated colleagues (64% and 57%), inappropriate photographs (63% and 57%), or inappropriate posts (76% and 67%). The directors also reported that they were aware of or issued reprimands or terminations at least once a year (30% NRPs and 22% residents). Residents were more likely to post photos of their resident peers or nursing colleagues in an intoxicated state than were NRPs (p=0.0004). NRPs were more likely to post inappropriate content (p=0.04) and identifiable patient information (p=0.0004) than were residents.

conclusionEM residents and faculty members cause and encounter HRTPE frequently while using SM; these events present significant risks to the individuals responsible and their associated institution. Awareness of these risks should prompt responsible SM use and consideration of CORD's Social Media Task Force recommendations.

Indexed as

Faculty, MedicalInternship and ResidencyAdultEmergency MedicineEmployee DisciplineFemaleHumansInterprofessional RelationsMalePhysician ExecutivesPrivacyProfessional CompetenceProfessional MisconductSocial MediaUnited States

Identifiers

PMID27330669
PMCPMC4899068

What OpenQuestion holds

Textmetadata
LicenceCC BY
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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.