Evidence map›Paper›PMID 42865283›Full record

ArticleJournal of Korean medical science2026

Publishing Quality Statistics Videos on YouTube: Analysis of Sources and Publishing Formats.

Aizhan Oralbek, Olena Zimba, Ainur B Qumar, Nurlan Aukenov, Ramazan Azim Okyay, Burhan Fatih Kocyigit

Abstract read
In one paragraph

Article in Journal of Korean medical science, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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.

Aizhan OralbekDepartment of Social Health Insurance and Public Health, South Kazakhstan Medical Academy, Shymkent, Kazakhstan.ORCID https://orcid.org/0009-0003-2616-4660
Olena ZimbaDepartment of Rheumatology, Immunology and Internal Medicine, University Hospital in Kraków, Kraków, Poland.ORCID https://orcid.org/0000-0002-4188-8486
Ainur B QumarDepartment of Health Policy and Management, Asfendiyarov Kazakh National Medical University, Almaty, Kazakhstan.ORCID https://orcid.org/0000-0003-0457-7205
Nurlan AukenovSouth Kazakhstan Medical Academy, Shymkent, Kazakhstan.ORCID https://orcid.org/0000-0002-3163-2997
Ramazan Azim OkyayDepartment of Public Health, University of Health Sciences, Adana Faculty of Medicine, Adana, Türkiye.ORCID https://orcid.org/0000-0001-8767-2771
Burhan Fatih KocyigitDepartment of Physical Medicine and Rehabilitation, University of Health Sciences, Adana City Research and Training Hospital, Adana, Türkiye. bfk2701@hotmail.com.ORCID https://orcid.org/0000-0002-6065-8002

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThis study aims to assess the content quality, presentation characteristics, and viewer engagement of YouTube videos on statistics, and to compare video quality categories based on fundamental video parameters, interaction metrics, presentation formats, and content sources.

methodsYouTube videos were searched for on November 17, 2025, using the search terms "statistical analysis," "data analysis," "statistics," and "statistical methods." The top 50 most relevant videos for each search term were assessed; after applying exclusion criteria, 114 videos were reviewed. The Global Quality Scale was used to measure video quality, and reliability was determined using a modified DISCERN tool. Videos were divided into low-, intermediate-, and high-quality categories. Engagement metrics and presentation methods were compared among quality groups.

resultsEighty-seven (76.3%) of the videos were categorized as high quality. Statistically significant differences were observed among video quality groups in daily views, likes, and comments (

conclusionA substantial proportion of YouTube videos on statistics were rated high quality, and significant differences were observed in engagement metrics across quality groups. The quality distribution varied by video source and presentation format. These findings emphasize the need for educators and content developers to integrate accurate statistical content with engaging presentation formats to improve the educational value of YouTube videos.

Indexed as

PublishingSocial MediaVideo RecordingHumansData AnalysisOnline Social NetworkingSocial MediaStatisticsYouTube

Identifiers

PMID42865283
PMCPMC13659105

What OpenQuestion holds

Textmetadata
Read underepoch 390

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.