ArticleJournal of clinical and experimental dentistry2024
Looking at the dark side: A bibliometric study on uncited and poorly cited articles in orthodontic research.
Article in Journal of clinical and experimental dentistry, 2024. 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
6 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Background: Many studies have analysed the bibliometric characteristics of highly cited articles in dentistry, and orthodontics. However, scant attention has been paid to articles with low citation rates. The aim of this study is to identify author- and article-specific factors that may be associated with a low citation rate at least 6 years after publication. Material and Methods: In June 2023, a cross-sectional study was conducted on articles published between 2009 and 2018 in eight orthodontic journals indexed in the Journal Citation Report. The study recorded author- and article-specific variables for articles that received zero citations and those that received between one and three citations. Descriptive statistics were used to describe the articles and journals included in the study. Pearson's correlation analysis was used to test the correlation between a journal's impact factor and the number of low-cited articles for the individual journals. The articles' related topics were further analysed using VOSviewer 1.6.6 software. Results: The electronic search identified 11,257 published items. After applying the inclusion and exclusion criteria, 216 uncited and 683 poorly cited articles were included in the final assessment. The Australasian Orthodontic Journal had the highest number of uncited and poorly cited articles, followed by Seminars in Orthodontics. A high negative correlation was found between the journal impact factor and the normalized number of uncited and poorly cited articles. The majority of uncited articles were expert opinions (28.24%), case reports (21.76%), and narrative reviews (21.30%). The most frequent topics were legislation, litigation, and ethics, followed by marketing and management. Most of the poorly cited articles were observational (29.43%) or translational studies (26.21%), and case reports (22.55%). The most prevalent topic in this cohort was eruption problems. Conclusions: The impact factor of a journal is linked to the number of published articles that receive a low citation rate. Orthodontics has a higher prevalence of such articles compared to other branches of medicine. Topics such as litigation, legislation, ethics, and marketing tend to receive low citation rates. Uncited articles often consist of expert opinions or narrative reviews. Case reports are a common study design in both uncited and poorly cited articles.
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.