- \n
- A new quantitative algorithm aims to identify \u201cdeserving contributors\u201d and determine the order of authorship on clinical study manuscripts.<\/li>\n
- The tool uses attributes from the ICMJE authorship criteria and Good Publication Practice 3 guidelines.<\/li>\n<\/ul>\n
\n![\"\"](\"https:\/\/i0.wp.com\/thepublicationplan.com\/wp-content\/uploads\/2022\/04\/iStock-1195871692.jpg?resize=591%2C591&ssl=1\")
<\/p>\nThe International Committee of Medical Journal Editors (ICMJE) criteria<\/a> and Good Publication Practice (GPP) 3 guidelines<\/a> are widely used to support the authorship decision-making process. But how can sponsors ensure all contributors to clinical trial manuscripts are appropriately credited whilst sticking to these guidelines? Authorship algorithms, like that recently announced by ISMPP<\/a>, are hoped to provide a quantitative method of identifying who qualifies as an author for pharmaceutical industry-sponsored research.<\/p>\n
\n
\u201c\u2026with the ever-expanding field of clinical research publications and evolving transparency and ethical requirements, there are often deficiencies or limitations in putting [ICMJE and GPP3] guidelines into practice.\u201d<\/em><\/p>\n<\/blockquote>\n
Dr Sam T. Mathew<\/a> et al have developed a new quantitative authorship decision support tool<\/a> using attributes of clinical trial publications based on the ICMJE\u2019s four criteria of authorship and the GPP3 guidelines. Overall, 26 attributes were identified, including study concept\/design, data acquisition\/analysis\/interpretation, content development\/review, and accountability. Contributors are ranked for each attribute on a Likert scale (0\u20135) or dichotomous scale (yes=1, no=0) in an easy-to-use algorithm in Microsoft Excel.<\/p>\n
The tool identifies substantial contributors and orders them using the following rules:<\/p>\n
- \n
- Contributors with a minimum score of 78\/120 (65%) qualify for authorship (the threshold can be amended by users if necessary).<\/li>\n
- First author is the person with the highest overall score, followed by the others in order of their score (the tool has provisions to resolve any ties in scores).<\/li>\n
- Senior author has the maximum score for study design or concept, content, and accountability.<\/li>\n
- Corresponding author has the maximum score for content development and accountability.<\/li>\n<\/ul>\n
The creators hope that their algorithm will help reduce author inflation and ensure authorship is appropriately assigned by quantifying contributions to all parts of the clinical study. Dr Mathew and colleagues plan to further develop the tool as a web-based system, and we look forward to seeing how this and other algorithms will be implemented in publication development moving forward.<\/p>\n
\u2014\u2014\u2014\u2014\u2014\u2014\u2014\u2014\u2014\u2014\u2014\u2014\u2014\u2014\u2014\u2014\u2014\u2013<\/p>\n
![\"\"](\"https:\/\/i0.wp.com\/thepublicationplan.com\/wp-content\/uploads\/2021\/08\/Byline_Rachel-Hubbard.png?resize=618%2C75&ssl=1\")
<\/a><\/p>\n