Evidence map›Paper›PMID 39463531›Full record

ArticleCureus2024

Quality Assessment of YouTube Videos As Information Source for Breast Self-Examination.

Mohammed S Bu Bshait, Abdullah Almaqhawi

Abstract read
In one paragraph

Article in Cureus, 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
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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

2 authors.

Mohammed S Bu BshaitDepartment of Surgery, King Faisal University, Al Ahsa, SAU.
Abdullah AlmaqhawiDepartment of Family and Community Medicine, King Faisal University, Al Ahsa, SAU.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Introduction Breast self-examination (BSE) is essential for early detection of breast cancer to lower the disease's morbidity and death rate. Education about the proper application reinforces its effectiveness. YouTube is an emerging modality for education distribution. Thus, we aimed to evaluate the quality and reliability of BSE videos on YouTube. Materials and methods A web search of YouTube was conducted using the term "breast self-examination". The first 50 relevant videos found through this search were compiled and evaluated. Video reliability was evaluated by applying benchmark criteria from the Journal of the American Medical Association (JAMA). The educational quality of the videos was evaluated using the Global Quality Score (GQS) and the guidelines' comprehensiveness score for BSE-specific instructions. Results The mean number of views was 311,625.9. Medical sources were the most common upload sources, which were found in 60% of the analyzed videos (30 videos), while examination demonstration was the most common type of video content (33 videos, 66%), followed by examination information (15 videos, 30%). However, a significant association was found between videos containing both examination information and demonstration and better educational quality. Regarding video reliability, 34% of videos (17 videos) scored 0, and only 2% (one video) scored four. According to the GQS, only 8% (four videos) were of excellent quality, while the majority (20 videos, 40%) were of suboptimal quality. Based on the BSE comprehensiveness score, the mean score was seven out of nine. Conclusions Videos containing examination information and demonstrations showed the best educational quality. Although most of the YouTube videos of BSE showed a high comprehensiveness score for BSE-specific instructions, their JAMA reliability and GQS scores were poor.

Indexed as

breast cancerbreast examinationeducationvideoyoutube

Identifiers

PMID39463531
PMCPMC11512166

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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.