Bmc Med Res Methodol
-
Bmc Med Res Methodol · Jan 2006
Reviewer agreement trends from four years of electronic submissions of conference abstract.
The purpose of this study was to determine the inter-rater agreement between reviewers on the quality of abstract submissions to an annual national scientific meeting (Canadian Association of Emergency Physicians; CAEP) to identify factors associated with low agreement. ⋯ The correlation between reviewers' total scores suggests general recognition of "high quality" and "low quality" abstracts. Criteria based on the presence/absence of objective methodological parameters (i.e., blinding in a controlled clinical trial) resulted in higher inter-rater agreement than the more subjective and opinion-based criteria. In future abstract competitions, defining criteria more objectively so that reviewers can base their responses on empirical evidence may lead to increased consistency of scoring and, presumably, increased fairness to submitters.
-
Bmc Med Res Methodol · Jan 2006
Room for improvement? A survey of the methods used in systematic reviews of adverse effects.
Although the methods for conducting systematic reviews of efficacy are well established, there is much less guidance on how systematic reviews of adverse effects should be performed. ⋯ There is an obvious need to improve the methodology and reporting of systematic reviews of adverse effects. The methodology around identification and quality assessment of primary data is the main concern.
-
Bmc Med Res Methodol · Jan 2006
Does a "Level I Evidence" rating imply high quality of reporting in orthopaedic randomised controlled trials?
The Levels of Evidence Rating System is widely believed to categorize studies by quality, with Level I studies representing the highest quality evidence. We aimed to determine the reporting quality of Randomised Controlled Trials (RCTs) published in the most frequently cited general orthopaedic journals. ⋯ Our findings suggest that readers should not assume that 1) studies labelled as Level I have high reporting quality and 2) Level I studies have better reporting quality than Level II studies. One should address methodological safeguards individually.
-
Bmc Med Res Methodol · Jan 2006
Protocol of the COSMIN study: COnsensus-based Standards for the selection of health Measurement INstruments.
Choosing an adequate measurement instrument depends on the proposed use of the instrument, the concept to be measured, the measurement properties (e.g. internal consistency, reproducibility, content and construct validity, responsiveness, and interpretability), the requirements, the burden for subjects, and costs of the available instruments. As far as measurement properties are concerned, there are no sufficiently specific standards for the evaluation of measurement properties of instruments to measure health status, and also no explicit criteria for what constitutes good measurement properties. In this paper we describe the protocol for the COSMIN study, the objective of which is to develop a checklist that contains COnsensus-based Standards for the selection of health Measurement INstruments, including explicit criteria for satisfying these standards. We will focus on evaluative health related patient-reported outcomes (HR-PROs), i.e. patient-reported health measurement instruments used in a longitudinal design as an outcome measure, excluding health care related PROs, such as satisfaction with care or adherence. The COSMIN standards will be made available in the form of an easily applicable checklist. ⋯ Since the study will mainly be anonymous, problems that are commonly encountered in face-to-face group meetings, such as the dominance of certain persons in the communication process, will be avoided. By performing a Delphi study and involving many experts, the likelihood that the checklist will have sufficient credibility to be accepted and implemented will increase.
-
Bmc Med Res Methodol · Jan 2006
Comparative StudyBeyond logistic regression: structural equations modelling for binary variables and its application to investigating unobserved confounders.
Structural equation modelling (SEM) has been increasingly used in medical statistics for solving a system of related regression equations. However, a great obstacle for its wider use has been its difficulty in handling categorical variables within the framework of generalised linear models. ⋯ The analysis of binary data can be greatly enhanced by Yule's transformation of odds ratios into estimated correlation matrix that can be further analysed by SEM. The interpretation of results is aided by expressing them as odds ratios which are the most frequently used measure of effect in medical statistics.