Evidence map›Paper›PMID 36799471›Full record

ArticleHand (New York, N.Y.)2024

YouTube as a Source of Patient Information for Cubital Tunnel Syndrome: An Analysis of Video Reliability, Quality, and Content.

Christopher J Lama, Davis A Hartnett, Joseph C Donnelly, Daniel S Yang, Lindsay R Kosinski, Julia A Katarincic, Joseph A Gil

Abstract read
In one paragraph

Article in Hand (New York, N.Y.), 2024. 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. Article
  2. Article
  3. 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

7 authors.

Christopher J LamaThe Warren Alpert Medical School of Brown University, Providence, RI, USA.ORCID 0000-0002-9484-9181
Davis A HartnettThe Warren Alpert Medical School of Brown University, Providence, RI, USA.
Joseph C DonnellyThe Warren Alpert Medical School of Brown University, Providence, RI, USA.
Daniel S YangThe Warren Alpert Medical School of Brown University, Providence, RI, USA.
Lindsay R KosinskiThe Warren Alpert Medical School of Brown University, Providence, RI, USA.
Julia A KatarincicThe Warren Alpert Medical School of Brown University, Providence, RI, USA.
Joseph A GilThe Warren Alpert Medical School of Brown University, Providence, RI, USA.ORCID 0000-0002-0117-1026

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThis study seeks to examine the reliability, quality, and content of YouTube videos on cubital tunnel syndrome, on which there is presently a paucity of information.

methodsThe top 50 unique YouTube videos by relevance resulting from the Boolean search term "cubital tunnel + cubital tunnel syndrome" were identified, with video properties for analysis including source, upload date, duration, views, and comments. Content was assessed using the

resultsThe average video saw 72 108 ± 199 362 views, with videos produced by allied (nonphysician) health professionals demonstrating the highest mean views (111 789 ± 294 471 views). Videos demonstrated low mean

conclusionsYouTube is a source of highly accessible information on cubital tunnel syndrome, although the average video presents generally poor and inadequate information. Directing patients toward higher quality video resources can be a meaningful component of patient education.

Indexed as

Cubital Tunnel SyndromeSocial MediaVideo RecordingConsumer Health InformationHumansInformation DisseminationPatient Education as TopicReproducibility of Resultsanatomybasic sciencecubital tunnel syndromediagnosishandnervenerve compressionnerve injury

Identifiers

PMID36799471
PMCPMC11342704

What OpenQuestion holds

Textmetadata
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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.