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- Data for: Authors of randomized controlled trials from high-ranking journals in the field of anesthesiology are not willing to share raw dataRaw data set of a study in which we analyzed whether high-impact anesthesiology journals indicate their willingness to share raw data.
- Data for: Network meta-analysis of diagnostic test accuracy studies allowing for multiple tests at multiple thresholdsThis dataset provides diagnostic test accuracy data of 13 studies assessing cognitive screening tests for the diagnosis of dementia and cognitive impairment in stroke-survivors. The screening tests of interest were Mini Mental State Examination at thresholds of <25 and <27, and Montreal Cognitive Assessment (MoCA) at thresholds of <22 and <26.
- Data for: Appraisal of 91 Practice Guidelines in the Philippines Using AGREE II Results of the appraisal of 91 CPGs in the Philippines
- Data for: Bias in diagnostic accuracy studies by forcing a dichotomous disease classification from reference standards: The case of expert panels.Scripts of the simulations run to generate the data used in the manuscript.
- Data for: Sample size calculations are poorly conducted and reported in many randomised trials of hip and knee osteoarthritis: results of a systematic reviewData extraction on 2-arm randomised trials of hip and/or knee osteoarthritis published in 2016 including study characteristics, methods used to calculate the sample size, and the reporting, justification of components used in the sample size calculation and details of an attempt to replicate the sample size calculation using the reported information.
- Data for: Reliable Change Index of WHODAS 2.0 in patients with mental health disorders: results of applying Classical Test Theory and Rasch modelsData from instrument used at the MS
- Data for: SMOOTH: Self-Management Open Online Trials in Health An Analysis of Existing Online Trials Appendix-1 ORCHID search strategy Appendix-2 Glossary Appendix 3 Table of included and Excluded studies Self-Management Open Online Trials in Health (SMOOTH) What can we learn from existing trials? BACKGROUND The use of online clinical trials is growing, but there remains little practical guidance on their conduct and it is sometimes challenging for researchers to adapt the conventions used in face-to-face trials and maintain the validity of the work. Online trials of self-management may indicate how an intervention will be used in daily practice as the online environment can mirror the self-management of care increasingly expected. The Online Randomized Controlled Trials of Health Information Database (ORCHID) contains health trials undertaken using the internet which were systematically sought and cataloged. This ORCHID analysis provides insight into the current state of online clinical trials. AIM To systematically explore existing self-recruited online randomized trials of self-management interventions and analyze the trials to assess their strengths and weaknesses, the quality of reporting and the involvement of participants in the research process. METHODS ORCHID was used as a sampling frame to identify a subset of self-recruited looking at self-management interventions. These were appraised to explore the qualities of self-recruited online randomized trials and to evaluate the usefulness of online trials for obtaining trustworthy answers to questions about health self-management and citizen research involvement. RESULTS The sample included (n=41) online trials published from 2002-2015. Trial quality was critically appraised as High (n=9), Medium-high (n=15), Medium (n=17), and low as (n=1). Descriptive settings in (N=23/41) trials provided insufficient information to be replicable and did not report piloting or testing platforms before the trial launch. Reporting of patient and public involvement was more common than in face-to-face trials, however reporting, replicability, and methods used in online randomized trials of self-recruited self-management interventions were sub-optimal and dissemination strategies were sparse and reported in only (n=1) trial. CONCLUSIONS The information gained in this study catalogs the state of online trials of self-management in the early 21st century and provides insights for online trials development as early as the protocol planning stage.
- Data for: Efforts to Retrieve Individual Participant Datasets for Use in a Meta-Analysis Result in Moderate Data Sharing but Many Datasets Remain MissingResults from each study.
- Data for: Redundant meta-analyses are common in genetic epidemiologyData for: Redundant meta-analyses are common in genetic epidemiology
- Data for: Latency to enrol, attrition and intervention effect estimation: Meta-epidemiological study of four randomised behaviour change trials Data from four (published) web-based intervention trials used here to test methodological hypotheses
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