Evidence map›Paper›PMID 33292857›Full record

ArticleBMC rheumatology2020

Web-based information on the treatment of the mouth in systemic sclerosis.

Ismail Abdouh, Stephen Porter, Stefano Fedele, Nadia Elgendy, Richeal Ni Riordain

Abstract read
In one paragraph

Article in BMC rheumatology, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.

0numbers the graph read from it
0cells of the map it votes in
11citing 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

11 citing papers in PubMed.

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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.

Ismail AbdouhOral Medicine, UCL Eastman Dental Institute, University Street, London, WC1E 6DE, UK. ismail.abdouh.12@ucl.ac.uk.ORCID http://orcid.org/0000-0003-2606-3918
Stephen PorterOral Medicine, UCL Eastman Dental Institute, University Street, London, WC1E 6DE, UK.
Stefano FedeleOral Medicine, UCL Eastman Dental Institute, University Street, London, WC1E 6DE, UK.
Nadia ElgendyFaculty of Dentistry, King Abdulaziz University, Jeddah, Saudi Arabia.
Richeal Ni RiordainOral Medicine, UCL Eastman Dental Institute, University Street, London, WC1E 6DE, UK.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundTo categorise the content and assess the quality and readability of the web-based information regarding treatment of the mouth in systemic sclerosis.

methodsAn online search using three different search terms regarding the treatment of the mouth in SSc was undertaken using the Google search engine. The first 100 websites from each search were selected for analysis. Data recorded included DISCERN instrument scores along with the Journal of the American Medical Association (JAMA) benchmarks and the presence of the Health on the Net seal (HON). Flesch Reading Ease Scores, Flesch-Kincaid Grade Level, the Simplified Measure of Gobbledygook Index and Coleman-Liau index were calculated to assess readability.

resultsFifty seven of the first websites remained for analysis after applying appropriate exclusion criteria. The mean overall DISCERN score was 2.37 (±1.01). Only 4 websites (7%) achieved all four JAMA benchmarks. Only 12 websites (21.1%) displayed the HON seal. The reading level was found to be difficult to very difficult among the majority of websites.

conclusionThe overall quality of the available online information concerning the treatment of the mouth of systemic sclerosis is questionable and requires a high level of reading skill. Further efforts should be directed toward establishing higher quality, reliable online information sources on the treatment of oral disease relevant to patients with systemic sclerosis.

Indexed as

Online informationPatient educationSystemic sclerosis

Identifiers

PMID33292857
PMCPMC7684884

What OpenQuestion holds

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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.