Tracing Long-Term Outcomes of Basic Research Using Citation Networks

The development of the national tuberculosis research priority in Indonesia: A comprehensive mixed-method approach

Ranked second in global tuberculosis (TB) incidence, Indonesia has developed a National Strategy for TB Prevention and Control 2020-2024 to accelerate the TB elimination program. Research and innovation are key pillars to support the program and need to be prioritised. This study aimed to develop updated national TB research priorities in Indonesia. This study was a mixed-methods study consisting of an open survey, a published literature survey, and Delphi survey. The open survey invited all related TB stakeholders to answer (a) the main barriers of the TB program and (b) the need for studies to support TB elimination. The published literature survey retrieved scientific articles published in national and international journals between 2015 and 2020 to identify gaps between published research and the current national strategy for TB control. The online survey and literature survey informed a panel of TB experts in a two-phase Delphi Survey to select the top 10 priority research topics. We identified 322 articles and analysed 1143 open survey responses. Through two-phases Delphi surveys, top ten research categories were listed: early TB detection; diagnosis and treatment of DR-TB; contact investigation; case detection and treatment of child TB; TB preventive therapy; government policy; laboratory for drug-sensitive- and drug-resistant-TB diagnosis; treatment adherence; diagnostic tool development; and community empowerment. This study also found the gap between stakeholders' interests and the importance of translating research into policy and practice. TB research priorities have been identified through the involvement of various stakeholders. The combination of an online survey, a published literature survey, and a Delphi survey was a rigorous methodology and was fit to build a systematic consensus about the priority of TB research.

Understanding the funding characteristics of research impact: A proof-of-concept study linking REF 2014 impact case studies with Researchfish grant agreements

BACKGROUND

All parts of the research community have an interest in understanding research impact whether that is around the pathways to impact, processes around impact, methods for measurement, describing impact and so on. This proof of concept study explored the relationship between research funding and research impact using the case studies submitted to the UK Research Excellence Framework (REF) exercise in 2014 as a proxy for impact.

METHODS

The paper describes an approach to link the REF impact case studies with the underpinning research grants present in the Researchfish dataset, primarily using the publications captured in both datasets. Where possible the methodology utilised unique identifiers such as Digital Object Identifiers and PubMed ID's, and where this was not possible the funding information within each publication was used.

RESULTS

Through this automated approach 21% of the non-redacted case studies could be linked to a specific research grant. Additional qualitative analysis was then done for unlinked REF impact case studies, which involved reading the document to identify additional information to make the linkage. This approach was taken on 100 REF impact case studies selected at random and resulted in only seven having no identifiable research grants funding associated. The linked research grants were analysed to identify characteristics that are more frequently associated with these grants, than non-linked ones.

CONCLUSIONS

This analysis did point to some interesting observations such as the grant funding linked to REF impact case studies are more likely to be longer, higher financial value, have more publications and be more collaborative (amongst other characteristics). These findings should be used with caution at present and not be over interpreted, this is due to the sample size for this proof of concept study and some potential limitations on the data which were not addressed at this stage.