ArticleInternational nursing review2026
YouTube Communication of the International Council of Nurses: A Topic Modeling Analysis Using Latent Dirichlet Allocation.
Article in International nursing review, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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
0 citing papers in PubMed.
No citing paper in PubMed yet.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
aimThis study aims to analyze the YouTube videos of the International Council of Nurses using text mining and Latent Dirichlet Allocation to provide thematic insights that can strengthen the organization's digital communication strategies and support its institutional objectives.
backgroundSince 2015, the International Council of Nurses has used its YouTube channel to create global awareness about the nursing profession and to strengthen nurses' influence on health policies.
methodsA total of 193 videos with English subtitles, published on the International Council of Nurses YouTube channel between June 2015 and September 2024, were analyzed. Texts were pre-processed through normalization, lemmatization, and stopword removal. Latent Dirichlet Allocation was used for topic modeling, and Python-based natural language processing tools were applied for analysis and visualization.
resultsThe channel has more than 6000 subscribers. The highest number of videos was published in 2020, while the lowest number was published in 2017. The most frequently used words were "nurse," "health," and "care." As a result of the analysis, ten main themes were identified, encompassing topics such as leadership, international organizations, crisis management, resource management, professional solidarity, and education.
conclusionAudience engagement appears to be shaped not only by the format of the content but also by temporal and global circumstances.The digital communication of the International Council of Nurses is thematically strong; however, its visibility should be enhanced through more effective presentation and engagement-focused content. IMPLICATIONS FOR NURSING AND HEALTH POLICY: The International Council of Nurses should continue its digital presence on YouTube to enhance nursing's visibility and impact on policy. The strategic use of digital communication tools can increase the profession's societal impact.
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.