ArticleHeliyon2022
Assessing the accuracy and quality of YouTube videos on early pregnancy loss.
Article in Heliyon, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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.
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.
Who cites it
5 citing papers in PubMed, 12 citations in OpenAlex.
- Quality of TikTok videos on sudden cardiac death varies by video characteristics and health information accuracy.Scientific reports · 2026Article
- Quality Analysis of YouTube and Facebook Videos for Glaucoma Treatment Options.Clinical ophthalmology (Auckland, N.Z.) · 2026Article
- #GenderAffirmingHormoneTherapy and Health Information on TikTok: Thematic Content Analysis.JMIR infodemiology · 2025Article
- Social media as health educator: An assessment of the understandability and accuracy of tiktok content about contraception.Contraception and reproductive medicine · 2024Article
- An innovative state-of-the-art health storytelling technique for better management of type 2 diabetes.Frontiers in public health · 2023Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Objective: To assess the accuracy and quality of YouTube videos pertaining to early pregnancy loss for use as a patient education tool. Methods: A cross-sectional study was conducted via YouTube search using the keywords "miscarriage," "spontaneous abortion," "pregnancy loss," and "pregnancy failure." The first 20 results for each keyword search, sorted by both relevance and view count, were compiled into a list. Descriptive characteristics, including the numbers of views, likes, dislikes, video length, and duration of upload were collected. All videos were independently evaluated by two physician researchers using two unique assessment tools. The Currency, Relevance, Authority, Accuracy, and Purpose (CRAAP) test was used to measure the reliability of video content. The Miscarriage-Specific Question Score (MSQS) criterion was used to objectively assess video content specific to miscarriage. Inter-rater agreement was analyzed via kappa coefficient and Pearson correlation. Results: 160 videos were screened, among which 74 videos were included for analysis. The mean CRAAP score was 8.3 out of a total possible score of 15, demonstrating good quality sources, though not of academic level. Mean MSQS score was 8.1 out of a total possible score of 24, demonstrating "fair" accuracy and comprehensiveness. Pearson correlations were 0.87 and 0.86 for CRAAP and MSQS total scores, respectively, demonstrating excellent inter-rater reliability. Conclusion: YouTube videos related to early pregnancy loss span a wide range of quality, accuracy, and purpose. While some videos provide effective content, mean rater scores demonstrate that YouTube is not a reliable source for patient education on early pregnancy loss.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
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.