从数据角度识别护理科技稿件中学术不端行为的方法与应对策略  

Strategies and coping methods for identifying academic misconduct articles in nursing technology journals from a data perspective

作　　者：王玉静 曹作华 WANG Yujing;CAO Zuohua(Chinese Nursing Journals Publishing House Co.,Ltd.,100035,Beijing,China)

机构地区：[1]《中华护理杂志》社有限责任公司,北京100035

出　　处：《编辑学报》2025年第1期65-69,共5页Acta Editologica

摘　　要：数据作为护理类科技期刊论文中的重要组成部分,反映了研究成果的真实性与准确性。本文针对护理类期刊论文特点,从数据的前后一致性、合理性、统计学方法的规律性探讨了识别学术不端稿件的方法,提出编辑和审稿专家应严谨假设、小心求证,从知、信、行角度强化数据审查行为,期刊编辑部也应加强对数据的规范化管理和作者的诚信教育,旨在帮助护理类科技期刊编辑了解并识别数据造假的稿件,充分发挥科技期刊防范学术不端的“守门员”作用,杜绝学术不端稿件刊出,助力健康学术生态圈建设,从而营造良好的学术生态环境。Data,a pivotal element in nursing technology journal articles,serves as a testament to the authenticity and precision of research findings.This paper delves into methods for detecting academic misconduct in nursing journal submissions,focusing on data consistency,rationality,and statistical regularities.It advocates for editors and reviewers to adopt a rigorous stance in their assumptions and conduct meticulous verification,while enhancing data review practices grounded in knowledge,belief,and practice.Furthermore,it underscores the importance of journals strengthening standardized data management and integrity education for authors.By utilizing these identification methods and response strategies,nursing science and technology journal editors can effectively discern and address articles involving data fraud.In doing so,they can fulfill their role as“gatekeepers”in preventing academic misconduct in science and technology journals,thereby averting the publication of such articles,fostering a healthy academic ecosystem,and nurturing a positive academic environment.

关 键 词：学术不端 护理科技期刊 数据 应对方法 

分 类 号：R47[医药卫生—护理学] G232[医药卫生—临床医学]