Opinion: Authors overestimate their contribution to scientific work, demonstrating a strong bias

Is something rotten in the state of Denmark? Cross-national evidence for widespread involvement but not systematic use of questionable research practices across all fields of research

Questionable research practices (QRP) are believed to be widespread, but empirical assessments are generally restricted to a few types of practices. Furthermore, conceptual confusion is rife with use and prevalence of QRPs often being confused as the same quantity. We present the hitherto most comprehensive study examining QRPs across scholarly fields and knowledge production modes. We survey perception, use, prevalence and predictors of QRPs among 3,402 researchers in Denmark and 1,307 in the UK, USA, Croatia and Austria. Results reveal remarkably similar response patterns among Danish and international respondents (τ = 0.85). Self-reported use indicates whether respondents have used a QRP in recent publications. 9 out of 10 respondents admitted using at least one QRP. Median use is three out of nine QRP items. Self-reported prevalence reflects the frequency of use. On average, prevalence rates were roughly three times lower compared to self-reported use. Findings indicated that the perceived social acceptability of QRPs influenced self-report patterns. Results suggest that most researchers use different types of QRPs within a restricted time period. The prevalence estimates, however, do not suggest outright systematic use of specific QRPs. Perceived pressure was the strongest systemic predictor for prevalence. Conversely, more local attention to research cultures and academic age was negatively related to prevalence. Finally, the personality traits conscientiousness and, to a lesser degree, agreeableness were also inversely associated with self-reported prevalence. Findings suggest that explanations for engagement with QRPs are not only attributable to systemic factors, as hitherto suggested, but a complicated mixture of experience, systemic and individual factors, and motivated reasoning.

The CalculAuthor: determining authorship using a simple-to-use, fair, objective, and transparent process

Authorship determination on a research article remains a largely subjective process. Existing guidelines on authorship taxonomy lack objectivity and are more useful in determining who deserves authorship rather than determining the order of authors. To promote best practices in authorship taxonomy, we developed an authorship rubric that provides a fair, objective, and transparent means of crediting authorship. We christened this tool the "CalculAuthor". The following steps are to be undertaken to create a scoring system based on the requirements of the projects: determining creditable criteria, assigning credit weightages, deciding levels of contribution, determining each author's contribution, calculating authorship scores and ranking. These must be performed by or in close collaboration with the primary investigator (PI), with conflicts being resolved at the PI's discretion. All team members should be informed about the authorship determination process early in the project and their agreement regarding its use must be obtained. While the CalculAuthor was developed to be used in medical research, its customizability enables it to be employed in any field of academia. We recommend that the CalculAuthor be piloted within institutions before its mainstream adoption, and any institution-specific factors should be considered to make the process more efficient and suitable.

The COVID19-NMR Consortium: A Public Report on the Impact of this New Global Collaboration

The outbreak of COVID-19 in December 2019 required the formation of international consortia for a coordinated scientific effort to understand and combat the virus. In this Viewpoint Article, we discuss how the NMR community has gathered to investigate the genome and proteome of SARS-CoV-2 and tested them for binding to low-molecular-weight binders. External factors including extended lockdowns due to the global pandemic character of the viral infection triggered the transition from locally focused collaborative research conducted within individual research groups to digital exchange formats for immediate discussion of unpublished results and data analysis, sample sharing, and coordinated research between more than 50 groups from 18 countries simultaneously. We discuss key lessons that might pertain after the end of the pandemic and challenges that we need to address.

A Survey-Weighted Analytic Hierarchy Process to Quantify Authorship

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 Chi² = 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.