Search

Background: Involving consumers in systematic reviews can make them more valuable and help achieve goals around transparency. Systematic reviews are technically complex and training can be needed to enable consumers to engage with them fully. The Cochrane Common Mental Disorders group sought to engage people with lived experience of mental health problems in the Voice of Experience College, three workshops introducing them to systematic review methods and to opportunities to contribute as Cochrane consumers. We aimed to collectively evaluate the College from the perspective of both facilitators and consumers, to critically reflect on the experience, and to identify how the College could be sustained and spread to other review groups. Methods: This study was a longitudinal qualitative and collaborative evaluation, structured around normalisation process theory. Both facilitators and consumers were involved in not only providing their perspectives but also reflecting on these together to identify key learning points. Results: The workshops were positively evaluated as being engaging and supportive, largely due to the relational skills of the facilitators, and their willingness to engage in joint or two‐way learning. The College suffered from a lack of clarity over the role of consumers after the College itself, with a need for greater communication to check assumptions and clarify expectations. This was not achieved due to pandemic disruptions, which nevertheless demonstrated that resources for involvement were not prioritised as core business during this period. Conclusions: Soft skills around communication and support are crucial to effective consumer engagement. Sustaining involvement requires sustained communication and opportunities to reflect together on opportunities and challenges. This requires committed resources to ensure involvement activity is prioritised. This is critical as negative experiences later in the involvement journey can undermine originally positive experiences if contributors are unclear as to what their involvement can lead to. Open discussions about this are necessary to avoid conflicting assumptions. The spread of the approach to other review groups could be achieved by flexibly adapting to group‐specific resources and settings, but maintaining a core focus on collaborative relationships as the key mechanism of engagement. Patient and Public Contribution: Public contributors were collaborators throughout the evaluation process and have co‐authored the paper. [ABSTRACT FROM AUTHOR]

Background: Relapse and recurrence of depression are common, contributing to the overall burden of depression globally. Accurate prediction of relapse or recurrence while patients are well would allow the identification of high-risk individuals and may effectively guide the allocation of interventions to prevent relapse and recurrence.Aims: To review prognostic models developed to predict the risk of relapse, recurrence, sustained remission, or recovery in adults with remitted major depressive disorder.Method: We searched the Cochrane Library (current issue); Ovid MEDLINE (1946 onwards); Ovid Embase (1980 onwards); Ovid PsycINFO (1806 onwards); and Web of Science (1900 onwards) up to May 2021. We included development and external validation studies of multivariable prognostic models. We assessed risk of bias of included studies using the Prediction model risk of bias assessment tool (PROBAST).Results: We identified 12 eligible prognostic model studies (11 unique prognostic models): 8 model development-only studies, 3 model development and external validation studies and 1 external validation-only study. Multiple estimates of performance measures were not available and meta-analysis was therefore not necessary. Eleven out of the 12 included studies were assessed as being at high overall risk of bias and none examined clinical utility.Conclusions: Due to high risk of bias of the included studies, poor predictive performance and limited external validation of the models identified, presently available clinical prediction models for relapse and recurrence of depression are not yet sufficiently developed for deploying in clinical settings. There is a need for improved prognosis research in this clinical area and future studies should conform to best practice methodological and reporting guidelines. [ABSTRACT FROM AUTHOR]