https://scholars.lib.ntu.edu.tw/handle/123456789/642285
標題: | Enhancing the quality of reporting of orthodontic clinical research | 作者: | Qin, Danchen He, Hong YU-KANG TU Hua, Fang |
關鍵字: | Artificial intelligence | Editorial policy | Reporting guideline | Research waste | Scientific writing | 公開日期: | 1-二月-2024 | 出版社: | ELSEVIER | 卷: | 30 | 期: | 1 | 起(迄)頁: | 2-9 | 來源出版物: | Seminars in Orthodontics | 摘要: | 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. |
URI: | https://scholars.lib.ntu.edu.tw/handle/123456789/642285 | ISSN: | 10738746 | DOI: | 10.1053/j.sodo.2024.01.010 |
顯示於: | 健康數據拓析統計研究所 |
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