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© 2019 Elsevier. This manuscript version is made available under the CC-BY-NC-ND 4.0 license http://creativecommons.org/licenses/by-nc-nd/4.0/ Objectives The objective of the study was to identify factors affecting the use of the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) statement, specifically authors’ attitudes toward and experiences with it. Study Design and Setting An online survey was distributed to authors of observational studies recruited via social media, personal network snowballing, and mass mailings using targeted search strategies. Data on demographics, awareness, motivators, and usage were collected in conjunction with a modified Unified Theory of Acceptance and Use of Technology (UTAUT) scale on which confirmatory factor analysis (CFA) was performed. Results One thousand fifteen participants completed the survey. Of these, 185 (18.2%) indicated they had never heard of STROBE nor used it previously, 195 (19.2%) had heard of it but never used it, and 635 (62.6%) had used it. Journals promoting STROBE were both key motivators and awareness mechanisms; peers and educational workshops were also important influencing factors to a lesser degree. The internal consistency of the modified UTAUT scale was strong (Cronbach's alpha = 0.94). CFA supported a four-factor model with 23 questions. Conclusion The endorsement of STROBE by journals is key to authors’ awareness and use of the guideline. We tested and validated our scale which can guide future research on reporting guidelines. The authors would like to acknowledge the Methods in Research on Research (MiRoR) network for their support and guidance. The authors would also like to thank Dr. Michail Kovanis for assistance gathering author emails and Ms. Alice Biggane for her assistance with the recruitment strategy.

International audience; Objective: Identify the current practice for recruitment prediction and monitoring within clinical trials.Study Design and Setting: Chief investigators (CIs) were surveyed to identify data sources and adjustments made to support recruitment prediction. Statisticians were surveyed to determine methods and adjustments used when predicting and monitoring recruitment. Participants were identified from the National Institute for Health Research recently funded studies, the UK Clinical Research Collaboration registered Clinical Trial Units network or by the European Clinical Research Infrastructure Network.Results: A total of 51 CIs (UK = 32, ECRIN = 19) and 104 statisticians (UK = 51, ECRIN = 53) were contacted. Response rates varied (CIs UK = 53% ECRIN = 32%; statisticians UK = 98% ECRIN = 36%).Multiple data sources are used to support recruitment rates, most commonly audit data from multiple sites. Variation in individual site recruitment rates are frequently incorporated, but staggered site openings were featured more commonly among UK respondents. Simple prediction methods are preferred to rarely used statistical models. Lack of familiarity with statistical methods are barriers to their use with evidence needed to justify the time required to support their implementation.Conclusion: Simplistic methods will continue as the mainstay of prediction; however, generation of evidence supporting the benefits of complex statistical models should promote their implementations. Multiple data sources to support recruitment prediction are being used, and further work on the quality of these data is needed. Pressure to be optimistic about recruitment rates for the trial to be attractive to funders was felt by a sizable minority. (C) 2020 The Authors. Published by Elsevier Inc.