Enhancing the quality of reporting of orthodontic clinical research

Danchen Qin, Hong He, Yu-Kang Tu, Fang Hua

Research output: Contribution to journalArticlepeer-review

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Abstract

Research reports need to provide complete, accurate, and transparent information to allow readers to easily understand and critically assess the study results. Poor reporting makes studies unable to be synthesized in systematic reviews, fail to inform clinical practice, and compromise evidence-based clinical decision making. Evidence suggested the reporting quality of orthodontic clinical studies was poor, which caused a large amount of avoidable research waste. Reporting guidelines (RGs) are developed to guide and standardize the reporting of specific study types and improve their reporting quality. This article introduces the commonly used RGs in orthodontic clinical studies and illustrates the relationship between the existing RGs and their extensions. The majority of extensions are those to the CONSORT and PRISMA guidelines. The EQUATOR Network is an online library of RGs and education resources, and authors can use it to find appropriate RGs. Although a large number of RGs and extensions have been published, involving various study types, the reporting quality of orthodontic clinical studies still needs to be improved. Active strategies to strengthen the implementation of RGs are necessary to fill the gaps between RG publication and the quality improvement of studies. Other issues including selective reporting and spin, structure format of abstracts, and artificial intelligence in reporting are also discussed. Language models such as ChatGPT have largely changed scientific research and reporting in the era of artificial intelligence. Authors are strongly recommended to always be transparent in reporting and responsible for the content of their studies.
Original languageEnglish
Pages (from-to)2-9
JournalSeminars in Orthodontics
Volume30
Issue number1
Early online date26 Jan 2024
DOIs
Publication statusPublished - 1 Feb 2024

Keywords

  • Scientific writing
  • Reporting guideline
  • Editorial policy
  • Research waste
  • Artificial intelligence

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