Digital evidence synthesis tools (DEST) for climate and health: survey |
Introductory questions
Dear Participants,
Thank you for taking the time to complete the below survey containing several questions regarding the development, use and evaluation of digital evidence synthesis tools (DESTs), and specifically those developed and used in the climate & health domain. The survey should take approximately 10-12 minutes to complete.
Digital evidence synthesis tools (DESTs) are tools that have been developed to automate one or several tasks of an evidence synthesis project such as a systematic review or systematic map. We understand automation in a broad sense that includes complex machine learning tasks, but also more trivial ones such as automatically populating database fields with manually extracted data (Tsafnat et al. 2014).
With this survey we aim to get an overview of the various DEST developments, practices and user experiences, which will inform further workshops in the research project. To meet the objectives of this study, in these workshops we will discuss and analyse in depth the main barriers and facilitators to wider uptake of evidence synthesis tools for climate and health, helping us map the needs for DEST use that is currently unmet.
The DESTs-CH research team
(Dr Pauline Scheelbeek, Prof James Thomas, Prof Jan Minx, Dr Max Callaghan, Dr Ashrita Saran, Prof Julian Elliott, Dr Christopher Trisos, Dr Patrick O'driscoll, Dr Melissa Bond, Dr Alison O’Mara Eves and Ms Genevieve Hadida)
Thank you for taking the time to complete the below survey containing several questions regarding the development, use and evaluation of digital evidence synthesis tools (DESTs), and specifically those developed and used in the climate & health domain. The survey should take approximately 10-12 minutes to complete.
Digital evidence synthesis tools (DESTs) are tools that have been developed to automate one or several tasks of an evidence synthesis project such as a systematic review or systematic map. We understand automation in a broad sense that includes complex machine learning tasks, but also more trivial ones such as automatically populating database fields with manually extracted data (Tsafnat et al. 2014).
With this survey we aim to get an overview of the various DEST developments, practices and user experiences, which will inform further workshops in the research project. To meet the objectives of this study, in these workshops we will discuss and analyse in depth the main barriers and facilitators to wider uptake of evidence synthesis tools for climate and health, helping us map the needs for DEST use that is currently unmet.
The DESTs-CH research team
(Dr Pauline Scheelbeek, Prof James Thomas, Prof Jan Minx, Dr Max Callaghan, Dr Ashrita Saran, Prof Julian Elliott, Dr Christopher Trisos, Dr Patrick O'driscoll, Dr Melissa Bond, Dr Alison O’Mara Eves and Ms Genevieve Hadida)