Development and Validation of Authorship Order Score (AOS) for Scientific Publication

Masud, Nazish; Masuadi, Emad; Moukaddem, Afaf; Omair, Aamir; Mohamud, Mohamud; Dubayee, Mohammad Al; Althubaiti, Alaa; Alnamshan, Mohammad Khabti; Bawazeer, Manal; AlJasser, Mohammed I.

doi:10.1016/j.hpe.2020.04.006

Cited by 4 publications

(5 citation statements)

References 24 publications

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“…The Authorship Order Score, proposed by Masud et al [13], ■ The tool is updated with contributors and scores till the approval of submission draft. ■ The updated tool is now used for deciding contributing authors, order of authors and non-contributing authors.…”

Section: Discussionmentioning

confidence: 99%

Development of a decision-support tool to quantify authorship contributions in clinical trial publications

Mathew¹,

Razack²,

Viswanathan³

2022

Sci Ed

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Purpose: This study aimed to develop a decision-support tool to quantitatively determine authorship in clinical trial publications.Methods: The tool was developed in three phases: consolidation of authorship recommendations from the Good Publication Practice (GPP) and International Committee of Medical Journal Editors (ICMJE) guidelines, identifying and scoring attributes using a 5-point Likert scale or a dichotomous scale, and soliciting feedback from editors and researchers.Results: The authorship criteria stipulated by the ICMJE and GPP recommendations were categorized into 2 Modules. Criterion 1 and the related GPP recommendations formed Module 1 (sub-criteria: contribution to design, data generation, and interpretation), while Module 2 was based on criteria 2 to 4 and the related GPP recommendations (sub-criteria: contribution to manuscript preparation and approval). The two modules with relevant sub-criteria were then differentiated into attributes (n = 17 in Module 1, n = 12 in Module 2). An individual contributor can be scored for each sub-criterion by summing the related attribute values; the sum of sub-criteria scores constituted the module score (Module 1 score: 70 [contribution to conception or design of the study, 20; data acquisition, 7; data analysis, 27; interpretation of data, 16]; Module 2 score: 50 [content development, 27; content review, 18; accountability, 5]). The concept was integrated into Microsoft Excel with adequate formulae and macros. A threshold of 50% for each sub-criterion and each module, with an overall score of 65%, is predefined as qualifying for authorship.Conclusion: This authorship decision-support tool would be helpful for clinical trial sponsors to assess and provide authorship to deserving contributors.

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Section: Discussionmentioning

confidence: 99%

Development of a decision-support tool to quantify authorship contributions in clinical trial publications

Mathew¹,

Razack²,

Viswanathan³

2022

Sci Ed

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“…A five-level ordinal rating 10 for the pre-2013 ICMJEc, seven criteria, four-level index, 27 harmonic authorship credits, fractional authorship credit based on the order of authorship, 28 a percentage-based Author Contribution Index, 12 an AHP model to increase the accountability of co-authors in collaborative research, 18 and a 13 criteria Authorship Order Score have been described. 11 Masud's work primarily applies to the determination of authorship order and did not include the criterion of accountability.…”

Section: Discussionmentioning

confidence: 99%

“…The objective of this paper is to decrease the abuses of authorship by developing a numeric index to improve the documentation of authorship claims because the four International Committee of Medical Journal Editors (ICMJE) criteria 8 are binary, not quantified, and several criteria have combined rather than individual components. There have been several suggestions to quantify authorship [9][10][11][12] but none have surveyed the opinion of medical editors, the acknowledged experts on authorship. Also, many of the previous works [9][10][11] did not incorporate all four of the authorship criteria proposed by the ICMJE.…”

Section: Introductionmentioning

confidence: 99%

“…There have been several suggestions to quantify authorship [9][10][11][12] but none have surveyed the opinion of medical editors, the acknowledged experts on authorship. Also, many of the previous works [9][10][11] did not incorporate all four of the authorship criteria proposed by the ICMJE. This study used a cross-sectional survey of medical editors to rank the relative importance of the tetrad ICMJE criteria and applied the median responses to objectively calibrate an Analytic Hierarchy Process (AHP).…”

Section: Introductionmentioning

confidence: 99%

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A Survey-Weighted Analytic Hierarchy Process to Quantify Authorship

Ing¹

2021

AMEP

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Background: Authorship is a pinnacle activity in academic medicine that often involves collaboration and a mentor-mentee relationship. The International Committee of Medical Journal Editors criteria for authorship (ICMJEc) are intended to prevent abuses of authorship and are used by more than 5500 medical journals. However, the binary ICMJEc have not yet been quantified. Aim: To develop a numeric scoring rubric for the ICMJEc to corroborate the authenticity of authorship claims. Methods: The four ICMJEc were separated into the nine authorship components of conception, design, data acquisition, data analysis, interpretation of data, draft, revision, final approval and accountability. In spring 2021, members of an international association of medical editors rated the importance of each authorship component using an 11-point Likert scale ranging from 0 (no importance) to 10 (most important). The median component scores were used to calibrate the pairwise comparisons in an analytic hierarchy process (AHP). The AHP priority weights were multiplied against a four-level perceived effort/ capability grade to calculate an authorship score. Results: Sixty-six decision-making medical editors completed the survey. The components had the median scores/AHP weights: conception 7.5/5.3%; design 8/8.9%; data acquisition 7/3.6%; data analysis 7/3.6%; interpretation of data 8/8.9%; draft 8/8.9%; revision 8/8.9%; final approval 9/20.1%; and accountability 10/31.8%, with Kruskal-Wallis Chi 2 = 65.11, p < 0.001. Conclusion:The editors rated accountability as the most important component of authorship, followed by the final approval of the manuscript; data acquisition had the lowest median importance score for authorship. The scoring rubric (https://tinyurl.com/eyu86y96) transforms the binary tetrad ICMJEc into 9 quantifiable components of authorship, providing a transparent method to objectively assess authorship contributions, determine authorship order and potentially decrease the abuse of authorship. If desired, individual journals can survey their editorial boards and use the AHP method to derive customized weightings for an ICMJEc-based authorship index.

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“…Based on weights from previous studies for authors' contributions [ 21 , 22 ], the contributions are as follows: Study design, concept, objectives, methods, writing, literature review, data analysis, interpretation and proofreading: Qandeel, M.S. Data collection: Qandeel, M.S., Riyad, N., Aryan, H., Ajaj, O., Alkhatib, H., and Hamdan, Y.…”

mentioning

confidence: 99%

Analyzing the queuing theory at the emergency department at King Hussein cancer center

Qandeel

Al-Qudah²,

Nayfeh³

et al. 2023

BMC Emerg Med

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Objectives This study was conducted in 2022 at King Hussein Cancer Center (KHCC) to analyze the queuing theory approach at the Emergency Department (ED) to estimate patients’ wait times and predict the accuracy of the queuing theory approach. Methods According to the statistics, the peak months were July and August, with peak hours from 10 a.m. until 6 p.m. The study sample was a week in July 2022, during the peak days and hours. This study measured patients’ wait times at these three stations: the health informatics desk, triage room, and emergency bed area. Results The average number of patients in line at the health informatics desk was not more than 3, and the waiting time was between 1 and 4 min. Since patients were receiving the service immediately in the triage room, there was no waiting time or line because the nurse’s role ended after taking the vital signs and rating the patient’s disease acuity. Using equations of queuing theory and other relativistic equations in the emergency bed area gave different results. The queuing theory approach showed that the average residence time in the system was between 4 and 10 min. Conclusions Conversely, relativistic equations (ratios of served patients and departed patients and other related variables) demonstrated that the average residence time was between 21 and 36 min.

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Development and Validation of Authorship Order Score (AOS) for Scientific Publication

Cited by 4 publications

References 24 publications

Development of a decision-support tool to quantify authorship contributions in clinical trial publications

Development of a decision-support tool to quantify authorship contributions in clinical trial publications

A Survey-Weighted Analytic Hierarchy Process to Quantify Authorship

Analyzing the queuing theory at the emergency department at King Hussein cancer center

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