Evidence map›Paper›PMID 33983129›Full record

ArticleJMIR medical education2021

Analysis of Cyberincivility in Posts by Health Professions Students: Descriptive Twitter Data Mining Study.

Jennie C De Gagne, Eunji Cho, Sandra S Yamane, Haesu Jin, Jeehae D Nam, Dukyoo Jung

Abstract read
In one paragraph

Article in JMIR medical education, 2021. 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. Educational data mining in medical education: A five-level approach.Journal of education and health promotion · 2025
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  2. Article
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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

6 authors.

Jennie C De Gagne *School of Nursing, Duke University, Durham, NC, United States.ORCID https://orcid.org/0000-0001-9814-5942
Eunji Cho *School of Nursing, Vanderbilt University, Nashville, TN, United States.ORCID https://orcid.org/0000-0002-2540-1535
Sandra S Yamane *Department of Nursing, Catawba College, Salisbury, NC, United States.ORCID https://orcid.org/0000-0002-8873-9269
Haesu Jin *Division of Hematologic Malignancies and Cellular Therapy, Duke University Medical Center, Durham, NC, United States.ORCID https://orcid.org/0000-0002-1368-0127
Jeehae D Nam *Global Health Institute, Duke University, Durham, NC, United States.ORCID https://orcid.org/0000-0003-2128-6127
Dukyoo Jung *College of Nursing, Ewha Womans University, Seoul, Republic of Korea.ORCID https://orcid.org/0000-0002-0087-765X

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundHealth professions students use social media to communicate with other students and health professionals, discuss career plans or coursework, and share the results of research projects or new information. These platforms allow students to share thoughts and perceptions that are not disclosed in formal education settings. Twitter provides an excellent window through which health professions educators can observe students' sociocultural and learning needs. However, despite its merits, cyberincivility on Twitter among health professions students has been reported. Cyber means using electronic technologies, and incivility is a general term for bad manners. As such, cyberincivility refers to any act of disrespectful, insensitive, or disruptive behavior in an electronic environment.

objectiveThis study aims to describe the characteristics and instances of cyberincivility posted on Twitter by self-identified health professions students. A further objective of the study is to analyze the prevalence of tweets perceived as inappropriate or potentially objectionable while describing patterns and differences in the instances of cyberincivility posted by those users.

methodsWe used a cross-sectional descriptive Twitter data mining method to collect quantitative and qualitative data from August 2019 to February 2020. The sample was taken from users who self-identified as health professions students (eg, medicine, nursing, dental, pharmacy, physician assistant, and physical therapy) in their user description. Data management and analysis were performed with a combination of SAS 9.4 for descriptive and inferential statistics, including logistic regression, and NVivo 12 for descriptive patterns of textual data.

resultsWe analyzed 20 of the most recent tweets for each account (N=12,820). A total of 639 user accounts were analyzed for quantitative analysis, including 280 (43.8%) medicine students and 329 (51.5%) nursing students in 22 countries: the United States (287/639, 44.9%), the United Kingdom (197/639, 30.8%), unknown countries (104/639, 16.3%), and 19 other countries (51/639, 8.0%). Of the 639 accounts, 193 (30.2%) were coded as having instances of cyberincivility. Of these, 61.7% (119/193), 32.6% (63/193), and 5.7% (11/193) belonged to students in nursing, medicine, and other disciplines, respectively. Among 502 instances of cyberincivility identified from 641 qualitative analysis samples, the largest categories were profanity and product promotion. Several aggressive or biased comments toward other users, politicians, or certain groups of people were also found.

conclusionsCyberincivility is a multifaceted phenomenon that must be considered in its complexity if health professions students are to embrace a culture of mutual respect and collaboration. Students' perceptions and reports of their Twitter experiences offer insights into behavior on the web and the evolving role of cyberspace, and potentially problematic posts provide opportunities for teaching digital professionalism. Our study indicates that there is a continued need to provide students with guidance and training regarding the importance of maintaining a professional persona on the web.

Indexed as

cyberincivilitydigital professionalismhealth professions studentssocial mediasocial networking sitesTwitter

Identifiers

PMID33983129
PMCPMC8160798

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LicenceCC BY
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Registered trials

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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.