Objective: No published methods for research integrity review include both statistical techniques applied to groups of randomised trials and individual assessment of papers. We propose a method based on practical experience of investigating data integrity across the collected papers of one author or author-group.
Study design and setting: We report our approach to investigating the collected papers of an author or author-group suspected of academic misconduct.
Results: In the investigation of the work of one author or author-group, we recommend a systematic search for the work of the involved author(s) in PubMed, Google Scholar and the RetractionWatch database, as well as a search of trial registries for unpublished clinical trials. Summary information from studies should be tabulated to assess consistency between study registration, execution, and publication. Each paper should be investigated for unfeasible features of the governance, methodology, execution, results, and reporting of the study. Pairwise comparison of baseline and outcome tables between papers may reveal data duplication or unfeasibly large differences between baseline characteristics in similar studies. Assessment of baseline characteristics from multiple randomised trials using Carlisle's method can determine whether the data are consistent with a properly executed randomisation process, as can checking whether reported baseline characteristics follow expected patterns for random variables such as Benford's Law. If serious concerns are raised, a more thorough investigation should be performed by journals, publishers, and institutions.
Conclusion: These methods provide a systematic and reproducible way to assess the collected work of one author or group of authors.
Keywords: academic misconduct; data integrity; methods; randomization; research integrity; systematic review.
Copyright © 2024. Published by Elsevier Inc.