Evidence map›Paper›PMID 30724738›Full record

ArticleJMIR public health and surveillance2019

Differences in Emotional and Pain-Related Language in Tweets About Dentists and Medical Doctors: Text Analysis of Twitter Content.

Jan-Are K Johnsen, Trude B Eggesvik, Thea H Rørvik, Miriam W Hanssen, Rolf Wynn, Per Egil Kummervold

Open access · goldAbstract read
In one paragraph

Article in JMIR public health and surveillance, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed
2.6field-weighted citation impact, top 11% of its field
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, 18 citations in OpenAlex.

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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 at 2 institutions in 1 country.

Jan-Are K JohnsenDepartment of Clinical Dentistry, Faculty of Health Sciences, UiT The Arctic University of Norway, Tromsø, Norway.ORCID http://orcid.org/0000-0001-6976-6192
Trude B EggesvikDepartment of Clinical Dentistry, Faculty of Health Sciences, UiT The Arctic University of Norway, Tromsø, Norway.ORCID http://orcid.org/0000-0002-5997-3638
Thea H RørvikDepartment of Clinical Dentistry, Faculty of Health Sciences, UiT The Arctic University of Norway, Tromsø, Norway.ORCID http://orcid.org/0000-0002-3692-3929
Miriam W HanssenDepartment of Clinical Dentistry, Faculty of Health Sciences, UiT The Arctic University of Norway, Tromsø, Norway.ORCID http://orcid.org/0000-0002-7385-1223
Rolf WynnDepartment of Clinical Medicine, Faculty of Health Sciences, UiT The Arctic University of Norway, Tromsø, Norway.ORCID http://orcid.org/0000-0002-2254-3343
Per Egil KummervoldNorut Northern Research Institute, Tromsø, Norway.ORCID http://orcid.org/0000-0003-1007-0945
UiT The Arctic University of Norway · NONorthern Research Institute · NO

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundSocial media provides people with easy ways to communicate their attitudes and feelings to a wide audience. Many people, unfortunately, have negative associations and feelings about dental treatment due to former painful experiences. Previous research indicates that there might be a pervasive and negative occupational stereotype related to dentists and that this stereotype is expressed in many different venues, including movies and literature.

objectiveThis study investigates the language used in relation to dentists and medical doctors on the social media platform Twitter. The purpose is to compare the professions in terms of the use of emotional and pain-related words, which might underlie and reflect the pervasive negative stereotype identified in relation to dentists. We hypothesized that (A) tweets about dentists will have more negative emotion-related words than those about medical doctors and (B) pain-related words occur more frequently in tweets about dentists than in those about medical doctors.

methodsTwitter content ("tweets") about dentists and medical doctors was collected using the Twitter application program interface 140Dev over a 4-week period in 2015, scanning the search terms "dentist" and "doctor". Word content of the selected tweets was analyzed using Linguistic Inquiry and Word Count software. The research hypotheses were investigated using nonparametric Wilcoxon-Mann-Whitney tests.

resultsOver 2.3 million tweets were collected in total, of which about one-third contained the word "dentist" and about two-thirds contained the word "doctor." Hypothesis A was supported since a higher proportion of negative words was used in tweets about dentists than in those about medical doctors (z=-10.47; P<.001). Similarly, tests showed a difference in the proportions of anger words (z=-12.54; P<.001), anxiety words (z=-6.96; P<.001), and sadness words (z=-9.58; P<.001), with higher proportions of these words in tweets about dentists than in those about doctors. Also, Hypothesis B was supported since a higher proportion of pain-related words was used in tweets about dentists than in those about doctors (z=-8.02; P<.001).

conclusionsThe results from this study suggest that stereotypes regarding dentists and dental treatment are spread through social media such as Twitter and that social media also might represent an avenue for improving messaging and disseminating more positive attitudes toward dentists and dental treatment.

Indexed as

dental anxietydental public healthdentistryinternetoccupational stereotypeprofessional rolepsychologysocial mediaTwitter

Identifiers

PMID30724738
PMCPMC6381402
OpenAlexW2899164584

What OpenQuestion holds

Textmetadata
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.