Delphi survey on the most promising areas and methods to improve systematic reviews' production and updating.
Automation tools
Evidence syntesis
Prioritization
Journal
Systematic reviews
ISSN: 2046-4053
Titre abrégé: Syst Rev
Pays: England
ID NLM: 101580575
Informations de publication
Date de publication:
28 03 2023
28 03 2023
Historique:
received:
08
09
2022
accepted:
20
03
2023
medline:
29
3
2023
entrez:
27
3
2023
pubmed:
28
3
2023
Statut:
epublish
Résumé
Systematic reviews (SRs) are invaluable evidence syntheses, widely used in biomedicine and other scientific areas. Tremendous resources are being spent on the production and updating of SRs. There is a continuous need to automatize the process and use the workforce and resources to make it faster and more efficient. Information gathered by previous EVBRES research was used to construct a questionnaire for round 1 which was partly quantitative, partly qualitative. Fifty five experienced SR authors were invited to participate in a Delphi study (DS) designed to identify the most promising areas and methods to improve the efficient production and updating of SRs. Topic questions focused on which areas of SRs are most time/effort/resource intensive and should be prioritized in further research. Data were analysed using NVivo 12 plus, Microsoft Excel 2013 and SPSS. Thematic analysis findings were used on the topics on which agreement was not reached in round 1 in order to prepare the questionnaire for round 2. Sixty percent (33/55) of the invited participants completed round 1; 44% (24/55) completed round 2. Participants reported average of 13.3 years of experience in conducting SRs (SD 6.8). More than two thirds of the respondents agreed/strongly agreed the following topics should be prioritized: extracting data, literature searching, screening abstracts, obtaining and screening full texts, updating SRs, finding previous SRs, translating non-English studies, synthesizing data, project management, writing the protocol, constructing the search strategy and critically appraising. Participants have not considered following areas as priority: snowballing, GRADE-ing, writing SR, deduplication, formulating SR question, performing meta-analysis. Data extraction was prioritized by the majority of participants as an area that needs more research/methods development. Quality of available language translating tools has dramatically increased over the years (Google translate, DeepL). The promising new tool for snowballing emerged (Citation Chaser). Automation cannot substitute human judgement where complex decisions are needed (GRADE-ing). Study protocol was registered at https://osf.io/bp2hu/ .
Sections du résumé
BACKGROUND
Systematic reviews (SRs) are invaluable evidence syntheses, widely used in biomedicine and other scientific areas. Tremendous resources are being spent on the production and updating of SRs. There is a continuous need to automatize the process and use the workforce and resources to make it faster and more efficient.
METHODS
Information gathered by previous EVBRES research was used to construct a questionnaire for round 1 which was partly quantitative, partly qualitative. Fifty five experienced SR authors were invited to participate in a Delphi study (DS) designed to identify the most promising areas and methods to improve the efficient production and updating of SRs. Topic questions focused on which areas of SRs are most time/effort/resource intensive and should be prioritized in further research. Data were analysed using NVivo 12 plus, Microsoft Excel 2013 and SPSS. Thematic analysis findings were used on the topics on which agreement was not reached in round 1 in order to prepare the questionnaire for round 2.
RESULTS
Sixty percent (33/55) of the invited participants completed round 1; 44% (24/55) completed round 2. Participants reported average of 13.3 years of experience in conducting SRs (SD 6.8). More than two thirds of the respondents agreed/strongly agreed the following topics should be prioritized: extracting data, literature searching, screening abstracts, obtaining and screening full texts, updating SRs, finding previous SRs, translating non-English studies, synthesizing data, project management, writing the protocol, constructing the search strategy and critically appraising. Participants have not considered following areas as priority: snowballing, GRADE-ing, writing SR, deduplication, formulating SR question, performing meta-analysis.
CONCLUSIONS
Data extraction was prioritized by the majority of participants as an area that needs more research/methods development. Quality of available language translating tools has dramatically increased over the years (Google translate, DeepL). The promising new tool for snowballing emerged (Citation Chaser). Automation cannot substitute human judgement where complex decisions are needed (GRADE-ing).
TRIAL REGISTRATION
Study protocol was registered at https://osf.io/bp2hu/ .
Identifiants
pubmed: 36973729
doi: 10.1186/s13643-023-02223-3
pii: 10.1186/s13643-023-02223-3
pmc: PMC10042663
doi:
Types de publication
Meta-Analysis
Journal Article
Research Support, Non-U.S. Gov't
Langues
eng
Sous-ensembles de citation
IM
Pagination
56Informations de copyright
© 2023. The Author(s).
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