Objective: Patient recruitment in clinical trials is challenging with failure to recruit to time and target sample size common. This may be caused by unanticipated problems or by overestimation of the recruitment rate. This study is a systematic review of statistical models to predict recruitment at the design stage of clinical trials.Study Design and Setting: The Online Resource for Recruitment research in Clinical triAls database was searched to identify articles published between 2008 and 2016. Articles published before 2008 were identified from a relevant systematic review. Google search was used to find potential methods in gray literature.Results: Thirteen eligible articles were identified of which, 11 focused on stochastic approaches, one on deterministic models, and one included both stochastic and deterministic methods. Models varied considerably in the factors included and in their complexity. Key aspects included their ability to condition on time; whether they used average or center-specific recruitment rates; and assumptions around center initiation rates. Lack of flexibility of some models restricts their implementation.Conclusion: Deterministic models require specification of few parameters but are likely unrealistic although easy to implement. Increasingly, stochastic models require greater parameter specification, which, along with greater complexity may be a barrier to their implementation.

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 5 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.

ObjectivesTo analyse the total number of newspaper articles citing the four leading general medical journals and to describe national citation patterns.DesignQuantitative content analysis.Setting/sampleFull text of 22 general newspapers in 14 countries over the period 2008–2015, collected from LexisNexis. The 14 countries have been categorised into four regions: the USA, the UK, Western World (European countries other than the UK, and Australia, New Zealand and Canada) and Rest of the World (other countries).Main outcome measurePress citations of four medical journals (two American: NEJM and JAMA; and two British: The Lancet and The BMJ) in 22 newspapers.ResultsBritish and American newspapers cited some of the four analysed medical journals about three times a week in 2008–2015 (weekly mean 3.2 and 2.7 citations, respectively); the newspapers from other Western countries did so about once a week (weekly mean 1.1), and those from the Rest of the World cited them about once a month (monthly mean 1.1). The New York Times cited above all other newspapers (weekly mean 4.7). The analysis showed the existence of three national citation patterns in the daily press: American newspapers cited mostly American journals (70.0% of citations), British newspapers cited mostly British journals (86.5%) and the rest of the analysed press cited more British journals than American ones. The Lancet was the most cited journal in the press of almost all Western countries outside the USA and the UK. Multivariate correspondence analysis confirmed the national patterns and showed that over 85% of the citation data variability is retained in just one single new variable: the national dimension.ConclusionBritish and American newspapers are the ones that cite the four analysed medical journals more often, showing a domestic preference for their respective national journals; non-British and non-American newspapers show a common international citation pattern.

Background and Purpose-There is a lack of agreement regarding measuring the effects of stroke treatment in clinical trials, which often relies on the dichotomized value of 1 outcome scale. Alternative analyses consist mainly of 2 strategies: use all the information from an ordinal scale and combine information from several outcome scales in a single estimate. Methods-We reanalyzed 3 outcome scales that assessed patient recovery (modified Rankin Scale, National Institutes of Health Stroke Scale, and Barthel Index). With data collected from the 1652 patients in the Citicoline pooling data analysis, we used 2 standard techniques of exploratory multivariate analysis to analyze the distances among ranks and to isolate the common and the unique information provided by each of the 3 scales. Results-The different scale values correspond to gradually different patient status, confirming that information is lost when a scale is collapsed to just 2 values, whether recovered or not. The scales shared 90.7% (95% CI, 84.5-96.9) of their information, with no individual scale contributing unique information. Conclusions-Salient stroke outcome information is lost when an ordinal scale is collapsed into fewer categories. In contrast, the full scales provide a comprehensive patient outcome estimate. Furthermore, in the context of stroke clinical trials, those scales are highly correlated, providing the rationale to pool them into a single estimate. These insights may be used to optimize the analysis of stroke trials to increase study power to detect efficacious interventions. (Stroke. 2010;41:e143-e150.)