Bmc Med Res Methodol
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Bmc Med Res Methodol · May 2014
Comparative StudyEfficient clinical evaluation of guideline quality: development and testing of a new tool.
Evaluating the methodological quality of clinical practice guidelines is essential before deciding which ones which could best inform policy or practice. One current method of evaluating clinical guideline quality is the research-focused AGREE II instrument. This uses 23 questions scored 1-7, arranged in six domains, which requires at least two independent testers, and uses a formulaic weighted domain scoring system. Following feedback from time-poor clinicians, policy-makers and managers that this instrument did not suit clinical need, we developed and tested a simpler, shorter, binary scored instrument (the iCAHE Guideline Quality Checklist) designed for single users. ⋯ The iCAHE Guideline Quality Checklist has promising psychometric properties and clinical utility.
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Systematic Reviews (SRs) of experimental animal studies are not yet common practice, but awareness of the merits of conducting such SRs is steadily increasing. As animal intervention studies differ from randomized clinical trials (RCT) in many aspects, the methodology for SRs of clinical trials needs to be adapted and optimized for animal intervention studies. The Cochrane Collaboration developed a Risk of Bias (RoB) tool to establish consistency and avoid discrepancies in assessing the methodological quality of RCTs. A similar initiative is warranted in the field of animal experimentation. ⋯ SYRCLE's RoB tool is an adapted version of the Cochrane RoB tool. Widespread adoption and implementation of this tool will facilitate and improve critical appraisal of evidence from animal studies. This may subsequently enhance the efficiency of translating animal research into clinical practice and increase awareness of the necessity of improving the methodological quality of animal studies.
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Bmc Med Res Methodol · Jan 2014
Meta AnalysisAn overview of the statistical methods reported by studies using the Canadian community health survey.
The Canadian Community Health Survey (CCHS) is a cross-sectional survey that has collected information on health determinants, health status and the utilization of the health system in Canada since 2001. Several hundred articles have been written utilizing the CCHS dataset. Previous analyses of statistical methods utilized in the literature have focused on a particular journal or set of journals to understand the statistical literacy required for understanding the published research. In this study, we describe the statistical methods referenced in the published literature utilizing the CCHS dataset(s). ⋯ Our study shows a diverse set of analysis methods being referenced in the CCHS literature, however, the literature heavily relies on only a subset of all possible statistical tools. This information can be used in identifying gaps in statistical methods that could be applied to future analysis of public health surveys, insight into training and educational programs, and also identifies the level of statistical literacy needed to understand the published literature.
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Bmc Med Res Methodol · Jan 2014
ReviewExternal validation of multivariable prediction models: a systematic review of methodological conduct and reporting.
Before considering whether to use a multivariable (diagnostic or prognostic) prediction model, it is essential that its performance be evaluated in data that were not used to develop the model (referred to as external validation). We critically appraised the methodological conduct and reporting of external validation studies of multivariable prediction models. ⋯ The vast majority of studies describing some form of external validation of a multivariable prediction model were poorly reported with key details frequently not presented. The validation studies were characterised by poor design, inappropriate handling and acknowledgement of missing data and one of the most key performance measures of prediction models i.e. calibration often omitted from the publication. It may therefore not be surprising that an overwhelming majority of developed prediction models are not used in practice, when there is a dearth of well-conducted and clearly reported (external validation) studies describing their performance on independent participant data.
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Bmc Med Res Methodol · Jan 2014
Thresholds for statistical and clinical significance in systematic reviews with meta-analytic methods.
Thresholds for statistical significance when assessing meta-analysis results are being insufficiently demonstrated by traditional 95% confidence intervals and P-values. Assessment of intervention effects in systematic reviews with meta-analysis deserves greater rigour. ⋯ If followed, the proposed eight-step procedure will increase the validity of assessments of intervention effects in systematic reviews of randomised clinical trials.