GALENOS

The GALENOS crowd has been formed to support GALENOS evidence synthesis activities (e.g., screening of records) and to increase opportunities for people to be involved in mental health research. With the support of crowd members, GALENOS can ensure ongoing and rigorous updates across multiple living systematic reviews (LSRs). Previous, and ongoing, successful examples of crowdsourcing tasks such as screening and data extraction include the Cochrane Crowd and the MHCOVID crowd (Salanti et al., 2022).

Crowd members will receive training on systematic review methodology and training specific to the systematic review which they are working on. They will receive certificates upon completing the training and will be rewarded for their time and contributions made to the project. The incentives may slightly differ across reviews depending on the number of records that need to be screened and extracted. Incentives include certificates of acknowledgement, being listed in manuscript acknowledgement sections and co-authorship. We plan to report on how best to involve crowd members in evidence synthesis projects.

If you’re interested in being a crowd member and have experience in health research and evidence synthesis, we would love to hear from you. We are looking for people who want to become part of a global community researching important topics within anxiety, depression and psychosis research. You can join the Cochrane Crowd (https://crowd.cochrane.org/) to screen titles and abstracts or submit your interest to screen full texts and support data extraction by completing the form on this page. We look forward to hearing from you! If you have any questions, please email us via our contact us page.

The GALENOS team want to hear from you!

What are the research questions within anxiety, depression and psychosis that you want answered? The team want to hear from researchers, clinicians and people with lived experience from all around the world via this short survey.

How To Get Involved

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Have you previously screened records for a systematic review?

Have you previously extracted data from records for a systematic review?

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Please click 'submit' to submit your form and we will be in touch with you, thank you.