Academic criteria for promotion and tenure in biomedical sciences faculties: cross sectional analysis of international sample of universities

Rice, Danielle B; Raffoul, Hana; Ioannidis, John P. A.; Moher, David

doi:10.1136/bmj.m2081

Cited by 165 publications

(152 citation statements)

References 21 publications

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“…Moreover, university-based studies satisfying thesis and graduation requirements can contribute to waste if not rigorously conducted and reported (Nieminen et al 2007). Finally, incentives in the funding and academic environment should be aligned with these desirable improvements in research practices (Rice et al 2020).…”

Section: Discussionmentioning

confidence: 99%

Dental Research Waste in Design, Analysis, and Reporting: A Scoping Review

et al. 2020

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Research waste is highly prevalent across biomedical investigations. We aimed to assess the evidence on the extent of research waste in dental research. We performed a scoping review of empirical evaluations of dental studies assessing the prevalence and impact of limitations in design, conduct, analysis, and reporting of research. PubMed was searched using specific terms to retrieve studies dealing with design, conduct, analysis, and reporting of studies in dentistry, with no year or language restrictions. Of the 1,807 publications identified from the search and from manual searches, 71 were included in this review. The topic and article selection was based on the expert opinion of the authors. The existing evidence suggests that, although there are improvements over time, substantial deficiencies in all areas (design, conduct, analysis, reporting) were prevalent in dental research publications. Waste in research is a multifaceted problem without a simple solution. However, an appreciation of optimal research design and execution is a prerequisite and should be underpinned by policies that include appropriate training in research methods and properly aligned incentives.

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Section: Discussionmentioning

confidence: 99%

Dental Research Waste in Design, Analysis, and Reporting: A Scoping Review

et al. 2020

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“…38 Academic institutions should make data sharing an explicit criterion for promotion and tenure. 39 All trial sponsors, including industry, should pledge to share data rapidly through one of the existing platforms (eg, Infectious Diseases Data Observatory). Requests for data after trial completion and publication are associated with poor retrieval rates in meta-analyses.…”

Section: Sharing Datamentioning

confidence: 99%

“…Sponsors’ transparency and data sharing practices should be periodically monitored and publicly reported 38. Academic institutions should make data sharing an explicit criterion for promotion and tenure 39. All trial sponsors, including industry, should pledge to share data rapidly through one of the existing platforms (eg, Infectious Diseases Data Observatory).…”

Section: Areas For Improvementmentioning

confidence: 99%

Producing and using timely comparative evidence on drugs: lessons from clinical trials for covid-19

Naci

Kesselheim

Røttingen

et al. 2020

BMJ

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Since the early days of the novel coronavirus outbreak, a record number of studies have been launched to test several repurposed and new medicines as potential treatments for covid-19. 1 An analysis by the news organisation STAT identified over 1000 clinical trials registered on ClinicalTrials.gov between January and June 2020. 2 This is a testament to the research and clinical community's commitment to identify effective treatments for covid-19. However, the large volume of studies may paradoxically limit the generation of robust evidence and complicate the formulation of trustworthy guidance and decisions related to drug use if the current research is duplicative and redundant or produces conflicting data. 3-5 Indeed, the multiplicity of research on candidate therapeutics for covid-19 has exposed important flaws and failures in the current evidence ecosystem. 6 7 Crucially, these limitations also affect the full spectrum of research on new health technologies. 8 9 Users of evidence across the healthcare system (patients, clinicians, health technology assessment bodies, guideline developers, payers) need timely data on how different treatments compare with each other in terms of their benefits and harms-their comparative effectiveness. Producing comparative evidence and ensuring its rapid translation into trustworthy guidance requires extensive coordination and collaboration between the researchers conducting clinical trials, those conducting comparative effectiveness assessments, and those producing guidance. 8 9 The experience of covid-19 highlights the difficulties in making comparative assessments and suggests areas for improvement.

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“…More broadly, academic institutions need to recognize data sharing and input to patient-level datasets as an important contribution to the research enterprise and endorse these, for example, in promotion and tenure criteria. 8 Finally, resources for data sharing need to be built into grants and institutional research infrastructure to make them feasible and sustainable.…”

mentioning

confidence: 99%