Blog Posts
‘Cohort’ vs. ‘Case-Control’ diagnostic test accuracy study designs and their impact on accuracy estimates
Not all diagnostic accuracy studies are created equal. The diagnostic test accuracy sub-designs of ‘Cohort’ and ‘Case-control’ have significant impact on the diagnostic accuracy estimates. Here’s how to avoid overestimating the accuracy of diagnostic tests in clinical practice. Cohort vs. Case-Control Diagnostic Accuracy Study Designs The diagnostic accuracy cohort study is the ‘traditional’ study […] →Read more
Implementation Science Terminology (but simple)
Implementation science helps bridge the gap between research and clinical practice. It focuses on how to get people (or places) to adopt an intervention, practice, or innovation. Unfortunately, complex jargon makes the field daunting and at times challenging for newcomers. Recognizing this challenge, Geoffrey M. Curran developed a teaching tool that simplifies the core concepts […] →Read more
Understanding Receiver Operating Curves and the AUC: A Guide for Clinicians
For clinicians, understanding the diagnostic accuracy of the tests we order is vital. Often, test results are continuous, necessitating a dichotomous categorization into ‘disease present’ or ‘disease absent’. This decision hinges on setting an appropriate cut-off value at which we call the test a ‘positive’ result. The Receiver Operating Characteristic (ROC) curve is a fundamental […] →Read more
What is a scoping review and how is it different than a systematic review?
A scoping review uses a systematic search strategy to gives a broad overview of a field of research or topic. Unlike systematic reviews with (or without) meta-analysis (SRMA), which are driven by a specific, well-defined research question typically structured around a Population, Intervention, Comparator, and Outcome (PICO) framework, scoping reviews are designed to identify gaps […] →Read more
What is Knowledge Translation and why is it core to performing impactful research?
In the realm of medical research, the concept of knowledge translation (KT) is pivotal, yet often undervalued. At its core, KT is the process of transforming research findings into actionable practices. It’s about ensuring that the valuable insights gleaned from research reach and are utilized by those who need them most, such as clinicians, patients, […] →Read more
What is a P-value? (and what a P-value is NOT!)
In the realm of medical research and statistical analysis, the P-value stands as one of the most frequently cited yet often misunderstood concepts. In practice, it (incorrectly) is reduced by some clinicians as a binary classifier of a ‘significant’ or ‘not significant’ results. In reality, it’s a probability value that tells us how likely it […] →Read more