BACKGROUND: Despite the increasing recognition of the importance of research in undergraduate dental education, limited studies have explored the nature of undergraduate research activities in dental schools in the Middle East region. This study aimed to evaluate the research experience of final year dental students from three dental schools in the Middle East.
METHODS: A descriptive, cross-sectional study was conducted among final-year dental students from three institutions, namely Jordan University of Science and Technology, University of Sharjah (UAE), and Oman Dental College. Participants were asked about the nature and scope of their research projects, the processes involved in the research, and their perceived benefits of engaging in research.
RESULTS: A total of 369 respondents completed the questionnaire.  Cross-sectional studies represented the most common research type  (50.4%), with public health (29.3%) and dental education (27.9%) being the predominant domains. More than half of research proposals were developed via discussions with instructors (55.0%), and literature reviews primarily utilized PubMed (70.2%) and Google Scholar (68.5%). Regarding statistical analysis, it was usually carried out with instructor\'s assistance (45.2%) or using specialized software (45.5%). The students typically concluded their projects with a manuscript (58.4%), finding the discussion section most challenging to write (42.0%). The research activity was considered highly beneficial, especially in terms of teamwork and communication skills, as well as data interpretation skills, with 74.1% of students reporting a positive impact on their research perspectives.
CONCLUSIONS: The research experience was generally positive among surveyed dental students. However, there is a need for more diversity in research domains, especially in qualitative studies, greater focus on guiding students in research activities s, especially in manuscript writing and publication. The outcomes of this study could provide valuable insights for dental schools seeking to improve their undergraduate research activities.

Adequate and transparent reporting is necessary for critically appraising published research, yet ample evidence suggests that the design, conduct, analysis, interpretation, and reporting of oral health research could be greatly improved. Accordingly, the Task Force on Design and Analysis in Oral Health Research, statisticians and trialists from academia and industry, identified the minimum information needed to report and evaluate observational studies and clinical trials in oral health: the OHStat guidelines. Drafts were circulated to the editors of 85 oral health journals and to Task Force members and sponsors and discussed at a December 2020 workshop attended by 49 researchers. The guidelines were subsequently revised by the Task Force writing group. The guidelines draw heavily from the Consolidated Standards for Reporting Trials (CONSORT), Strengthening the Reporting of Observational Studies in Epidemiology, and CONSORT harms guidelines, and incorporate the SAMPL guidelines for reporting statistics, the CLIP principles for documenting images, and the GRADE indicating the quality of evidence. The guidelines also recommend reporting estimates in clinically meaningful units using confidence intervals, rather than relying on P values. In addition, OHStat introduces seven new guidelines that concern the text itself, such as checking the congruence between abstract and text, structuring the discussion, and listing conclusions to make them more specific. OHStat does not replace other reporting guidelines; it incorporates those most relevant to dental research into a single document. Manuscripts using the OHStat guidelines will provide more information specific to oral health research.

OBJECTIVE: To evaluate where orthodontic research papers are published and to explore potential relationships between the journal of publication and the characteristics of the research study and authorship.
METHODS: An online literature search of seven research databases was undertaken to identify orthodontic articles published in English language over a 12-month period (1 January-31 December 2022) (last search: 12 June 2023). Data extracted included journal, article, and author characteristics. Journal legitimacy was assessed using a ternary classification scheme including available blacklists and whitelists, cross-checking of indexing claims and history of sending unsolicited emails. The level of evidence (LOE) of all included studies was assessed using a modified Oxford LOE classification scale. Univariable and multivariable ordinal logistic regression analyses were performed to examine possible associations between the level of evidence, journal discipline, and authorship characteristics.
RESULTS: A total of 753 studies, published by 246 unique journal titles, were included and further assessed. Nearly two-thirds of orthodontic papers were published in non-orthodontic journals (62.8%) and over half (55.6%) of the articles were published in open-access policy journals. About a fifth of the articles (21.2%) were published either in presumed predatory journals or in journals of uncertain legitimacy. Journal discipline was significantly associated with the level of evidence. Higher-quality orthodontic studies were more likely published in established orthodontic journals (likelihood ratio test P < .001).
CONCLUSIONS: The identification and classification of predatory journals are challenging due to their covert nature.
CONCLUSIONS: The majority of orthodontic articles were published in non-orthodontic journals. In addition, approximately one in five orthodontic studies were published in presumed predatory journals or in journals of uncertain legitimacy. Studies with higher levels of evidence were more likely to be published in established orthodontic journals.

Artificial intelligence is much in the news. One issue is whether it might be a useful tool for dental research. This paper provides ad overview of AI and explores its usefulness in some simple history of dentistry topics, including potential dangers.

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BACKGROUND: The published literature represents the fundamental basis of any academic specialty, including orthodontics. Orthodontic research outputs provide useful insight into clinical and research priorities, which can help inform future research efforts and resource outputs. In recent years, the need for more patient-reported outcomes in orthodontic research has been highlighted.
OBJECTIVE: To identify the most common reported research subjects in orthodontics between 2013-23; (2) identify the main outcomes and types of study design associated with this research, including study design related to patient-reported outcomes; and (3) identify trends in this research activity based upon these findings.
METHODS: A literature search was performed in a single electronic database (Scopus) to return all indexed publications with relevance to orthodontics published from 2013 to 2023. The 50 most-cited publications per year were then identified. Publication characteristics were extracted using a data collection sheet. Descriptive statistics including frequency distributions were calculated.
RESULTS: A total of 14 397 publications were identified. Publications on orthodontic bonding made up 7.02% of all output, followed by materials (5.88%) and tooth movement (5.42%). Subsequent analysis of the most-cited publications per year revealed the most frequently published subjects were aligners (12.5%), orthodontic tooth movement (9.45%), and digital workflow (9.09%), and the most common study designs were in vitro (19.09%) and retrospective observational studies (15.45%). The most common outcome type was morphological features of malocclusion (26.9%). Conversely, patient-focused measures were only reported in 12.7% of studies.
CONCLUSIONS: Orthodontic research outputs are dynamic but do show consistent research interest in certain subjects. There is a predilection for the reporting of clinician-focused outcomes; whilst these have some value, more efforts should be focused on conducting rigorous and robust studies that include patient-reported outcomes.

This study assessed the features of the 100 most-cited papers on diabetes mellitus (DM) in dentistry using bibliometric measures. A search of the most cited papers on DM using journals included in the category \"Dentistry, Oral Surgery and Medicine\" in the Web of Science database up to January 2023 was performed. The complete bibliographic records of the selected papers were exported in plain text or Research Information Systems (RIS) file format. The following bibliometric indicators were collected: title, year, authors, number of citations, mean number of citations, institution, country, continent, study design, journal, impact factor, and keywords. Graphical bibliometric networks were created using the VOSviewer software. The number of citations for the 100 most-cited papers in DM research ranged from 111 to 566. Six papers each had more than 400 citations. Most were observational studies (n = 50) from the United States (USA) (n = 23) and were published in the Journal of Periodontology (30%; n=30). Robert Genco was the most cited author and contributed the most to the top 100 articles (3,653 citations; n = 13). The VOSviewer map of co-authorship showed the existence of clusters in research collaboration. The most prolific institutions were the Universities of Buffalo and Michigan (n = 6 each). \"Diabetes mellitus\" was the most frequent keyword, with 31 occurrences. In conclusion, the most cited studies that investigated the relationship between dentistry and DM were in periodontology. Observational studies, primarily from the USA, have been the most cited thus far.

BACKGROUND: The aim of this study was to understand the trends regarding the use of artificial intelligence in dentistry through a bibliometric review.
METHODS: The authors performed a literature search on Web of Science. They collected the following data: articles-number and density of citations, year, key words, language, document type, study design, and theme (main objective, diagnostic method, and specialties); journals-impact factor; authors-country, continent, and institution. The authors used Visualization of Similarities Viewer software (Leiden University) to analyze the data and Spearman test for correlation analysis.
RESULTS: After selection, 1,478 articles were included. The number of citations ranged from 0 through 327. The articles were published from 1984 through 2024. Most articles were characterized as proof of concept (979). Definition and classification of structures and diseases was the most common theme (550 articles). There was an emphasis on radiology (333 articles) and radiographic-based diagnostic methods (715 articles). China was the country with the most articles (251), and Asia was the continent with the most articles (871). The Charité-University of Medicine Berlin was the institution with the most articles (42), and the author with the most articles was Schwendicke (53).
CONCLUSIONS: Artificial intelligence is an important clinical tool to facilitate diagnosis and provide automation in various processes.

BACKGROUND: Generative artificial intelligence (GenAI) Large-language models such as ChatGPT have become increasingly popular in various fields. However, the impact of ChatGPT on dental research writing has yet to be quantified. This study aimed to assess ChatGPT\'s usage in dental research writing and discuss potential advantages and challenges.
METHODS: Using a bibliometric design, we performed a keyword analysis of specific \'signaling words\' indicative of ChatGPT use in the titles/abstracts of 299,695 dental research abstracts indexed PubMed 2018-2024. Statistical comparisons using normalized ratios per 10,000 dental publications compared changes in word frequency before and after the ChatGPT release on November 30, 2022.
RESULTS: Before ChatGPT\'s release, the frequency of abstracts with signaling words was 47.1 per 10,000 papers. After the release, this increased to 224.2 per 10,000 papers, an increase of 177.2 per 10,000 papers (p = 0.014, 95 % CI 53.5-300.7). The word \'delve\' showed the most significant usage increase (increased ratio=17.0).
CONCLUSIONS: This study is among the first to systematically assess the use of GenAI, specifically ChatGPT, in dental research. We found evidence of the use and growth of ChatGPT in dental research publications. This trend indicates the widespread adoption of GenAI-assisted writing in scientific communication, consistent with other scientific fields. While GenAI can potentially increase productivity and inclusivity, it raises concerns such as bias, inaccuracy, and distortion of academic incentives. Therefore, our findings support the need for clear AI guidelines and standards for academic publishing to ensure responsible use and maintain scientific integrity.