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Objectives: The objective of the study was to develop a classification of methods used to personalize participative interventions in randomized controlled trials (RCTs)., Study Design and Setting: We conducted a systematic review including protocols of RCTs assessing participative interventions in PubMed and ClinicalTrials.gov between June 2018 and May 2019. Data extraction was performed by two independent reviewers. We developed a precise classification of methods used to personalize interventions. Then, protocols were reviewed to determine whether personalization was sufficiently described to enable replication., Results: We included 109 protocols. The classification used four components and 13 subcomponents accounting for decision points (when interventions were personalized), tailoring variables (on what interventions were personalized), decision rules (how and by whom interventions were personalized), and nature of the subsequent tailoring (what was personalized in the interventions). In 95% of protocols, at least one component or subcomponent of our classification was not adequately reported to enable the replication of the intervention. Components the least well described were tailoring variables (72% of protocols insufficiently described) and the nature of the subsequent tailoring (46% of protocols)., Conclusion: This study provides the first detailed classification of methods used to personalize interventions. This is required to transparently implement personalization and improve reporting in RCTs., (Copyright © 2021 Elsevier Inc. All rights reserved.)

Objectives: Our aim was to determine the coverage of randomized controlled trials (RCTs) by the Consolidated Standards of Reporting Trial (CONSORT) Statement and its extensions and to evaluate the potential workload for authors to adhere to the guidelines., Study Design and Setting: We identified CONSORT extensions from the CONSORT Web site. We randomly selected a sample of 1,000 RCTs indexed in PubMed in 2016 and recorded whether they were covered by CONSORT extensions for specific study designs or interventions. We evaluated the potential workload for authors by counting the number of documents and pages they have to consult to have a full understanding of the guidelines., Results: We identified 14 extensions. Only one extension was updated concurrently with the main CONSORT in 2010, three were updated after 2-7 years, and three are still based on CONSORT 2001. Overall, 81% of RCTs are covered by relevant CONSORT guidelines; missing extensions for specific study designs were under development at the time of the search (Nov 2018). However, 6 of 10 extensions covered <2% of the trials. A median [Q1-Q3] of 4 [4-5] documents and 67 [57-78] pages should be consulted., Conclusion: Most RCTs indexed in PubMed are covered by the CONSORT Statement and extensions, but the potential workload for authors could be high., (Copyright © 2019 Elsevier Inc. All rights reserved.)

Objectives: New forms of research involving collective intelligence (CI) of diverse individuals mobilized through crowdsourcing is successfully emerging in various fields. This scoping review aimed to describe these methods across different fields and propose a framework for implementation., Study Design and Setting: We searched seven electronic databases for reports describing projects that had mobilized CI with crowdsourcing. We used content analysis to develop themes and categories of the methods., Results: We identified 145 reports. CI was mobilized to generate ideas, conduct evaluations, solve problems, and create intellectual outputs. Most projects (n = 110, 76%) were open to the public without restrictions on participants' expertise. Participants contributed to projects by independent contribution (i.e., no interaction with other participants) (n = 50, 34%), collaboration (n = 41, 28%), competitions (n = 33, 23%), and playing games (n = 16, 11%). In total, 61% of articles (n = 89) reported methods to evaluate participants' contribution and decision-making process: 43% used an independent panel of experts and 18% involved end users. We identified challenges in implementation and sustainability of CI and proposed solutions., Conclusion: New research methods based on CI through crowdsourcing could transform clinical research. This framework facilitates the implementation of these methods., (Copyright © 2019 The Authors. Published by Elsevier Inc. All rights reserved.)