Understanding contextual factors is important for healthcare workers as these factors significantly influence patient outcomes. Learn what they are, and why they are important, in this blog for beginners to the topic.
In this blog you will be able to understand the basic concepts about composite endpoints, their limitations and benefits, as well as an approach to how to interpret them.
What are the differences between a systematic review and a meta-analysis? Here are some tips to help you understand these two different yet related types of study.
When you bring studies together in a meta-analysis, one of the things you need to consider is the variability in your studies – this is called heterogeneity. This blog presents the three types of heterogeneity, considers the different types of outcome data, and delves a little more into dealing with the variations.
Is this study valid? Can I trust this study’s methods and design? Can I apply the results of this study to other contexts? Learn more about internal and external validity in research to help you answer these questions when you next look at a paper.
Rapid reviews are often driven by requests for timely evidence for decision-making purposes. This blog is a brief introduction to the topic.
A living systematic review is a type of review which is continually updated, incorporating relevant new evidence as it becomes available.
This blog summarizes the concepts of cluster randomization, and the logistical and statistical considerations while designing a cluster randomized controlled trial.
What is a non-inferiority trial and how do patient, drug, and study design characteristics influence decisions of the non-inferiority threshold and clinical decisions.
This blog summarizes the concepts of Expertise-based randomized controlled trials with a focus on the advantages and challenges associated with this type of study.
This is the third in a three-part blog which will look at a few aspects of the topic in more detail like the cost-effectiveness plane, discount rates, and other key elements in health economic evaluation.
The CONSORT statement aims at comprehensive and complete reporting of randomized controlled trials. This blog introduces you to the statement and why it is an important tool in the research world.
What is data dredging, how does it affect the p-value and what is its impact on the world around us?
Conducting successful research requires choosing the appropriate study design. This article describes the most common types of designs conducted by researchers.
What are adverse events? Why is the recording and reporting of adverse events necessary?
The PROGRESS acronym is designed to remind researchers, and others, to consider the factors which may affect health opportunities and outcomes.
Participants in clinical trials may exit the study prior to having their results collated; in this case, what do we do with their results?
Learn about the different types of sampling methods, examples of their uses, and potential sampling errors to avoid when conducting research.
A brief introduction and tips for students embarking on a rapid review, when they should be used, and their advantages and limitations.
Vaccine trials have to go through a rigorous testing process before being released for use. This topic is particularly relevant as vaccine developers aim to deliver a SARS-CoV2 vaccine to the population in record time.
This blog introduces you to crossover trials with a clear explanation and example, together with some advantages and limitations of this study design.
Yousif examines the HIP ATTACK trial, appraises the primary composite endpoint, verifies the assessment and then thinks of ways to interpret the result.
This blog provides an introduction to critically appraising diagnostic studies. Find out what questions are important to ask as you go through a paper.
This blog is an introduction to Research Priority Setting (RSP), also providing useful resources to understand how RSP exercises are carried out.
In the last of a series of three blogs about Thematic analysis (TA), Dolly Sud describes the six phases of TA and provides further reading and conclusions.
In the second of a series of three blogs about Thematic analysis (TA), Dolly Sud describes the 3 schools of TA and discusses some study design recommendations.
In the first of a series of three blogs about Thematic analysis, Dolly Sud introduces us to the topic and explains what a ‘theme’ is.
The GRADE-CERQual approach is a transparent method of assessing the confidence of evidence from reviews of qualitative research. This blog from Dolly Sud introduces this type of assessment and provides useful further reading and resources.
This blog provides a detailed explanation of a dyad (something that consists of two elements or parts) and how this is used within the context of healthcare research.
This blog is a critical appraisal of the following pilot study: Intraexaminer comparison of applied kinesiology manual muscle testing of varying durations.
A well-designed cohort study can provide powerful results. This blog introduces prospective and retrospective cohort studies, discussing the advantages, disadvantages and use of these type of study designs.
Randomized controlled trials (RCTs) can be subject to different kinds of bias. Read about different sources of bias in this blog and how much the magnitude of effect can be changed by the presence of bias.
The growth in implementation science and research represents a growing recognition that successful dissemination and implementation is an essential part of evidence-based practice.
Heidi Gardner is part of a team of researchers working on the PRioRiTy II project, a research project aiming to identify the most important things that we currently don’t know about things that affect whether people stay involved in trial. Read more about the project here and then have your say in identifying the top 10 questions about trial retention that still need answering.
Blinding is a common element used in rigorously designed trials. Most people are familiar with the general concept but what is its purpose and what is the best way to perform it? This blog by Neelam Khan explores both of these questions and discusses ways to tackle situations where blinding cannot be done.
In this blog, Julie Duncan Millar, PhD Student and Physiotherapist, reflects on the difficulties of comparing and sharing upper limb rehabilitation trial data and proposes a condensed toolkit of measures recommended for researchers to use in future trials.
Saul Crandon provides an overview of Case-control and Cohort studies: what are they, how are they different, and what are the pros and cons you need to consider in each study design.
In this blog, Leonardo provides 5 interpretations that you should consider when you read or hear about a reported association in observational studies.
This blog provides a detailed overview of the Delphi Technique, a method of congregating expert opinion through a series of iterative questionnaires, with a goal of coming to a group consensus. It covers what it is, the process involved, pros and cons and when you would consider using it.
This blog provides an introduction to sample size and power; what it is, why it’s important to consider when designing a study, and how to carry out a power calculation.
A pilot study is a small scale preliminary study conducted in order to evaluate feasibility of the key steps in a future, full-scale project. Pilot studies can teach researchers about any amendments they will need to make to the design of the future study, in order to minimise waste of time and resources.
This blog is a Portuguese translation of the blog ‘Meta-analysis: what, why and how’. Thanks to Cochrane Brazil for the translation.
This blog takes a detailed look at the issue of attrition bias (bias that can arise when participants drop out of a study). It also describes measures that can be taken by researchers to minimize this bias (including different types of statistical analyses).
Beware dodgy research (particularly when it’s pharmaceutical-funded)! This blog shines a spotlight on some of the appalling ‘tricks’ that researchers and sponsors can (and do!) play to help them get the results they want from their trials. From fiddling with the study design, to fiddling with the data analysis and ‘spinning’ results…
This blog provides a basic overview of: 1) what a meta-analysis is; 2) why they’re considered the ‘gold standard’ of evidence; and 3) how a meta-analysis is carried out.
This blog explains what allocation concealment is & why it’s important, in terms of preventing researchers from (intentionally or otherwise) influencing which participants are assigned to a given intervention group.
Let’s figure out how the epidemiologists determine the diagnostic thresholds by studying the cases of anemia and type II diabetes.
When dealing with a difficult question, we tend to seek the answer for a simpler one, that seems to be relevant. However, a seductive trap awaits us here. Come with me, I’ll show you the world of surrogate endpoints.
Outcome switching is a major problem in clinical trial reporting that distorts the evidence doctors and patients use to make real-world clinical decisions. Numerous prevalence studies have already shown this to be an extremely common problem, even in top medical journals. However the CEBM Outcome Monitoring Project (COMPare) has taken a new approach: writing to journals to correct the record on individual trials, in the hope that individual accountability and open data sharing will help solve this important problem. Our main question was: how will the journals respond? This blog tells the story of COMPare so far.
Patients, carers and members of the public offer a unique perspective in health and social care research, adding to the expertise of the research team. Improving healthcare services will only be possible by involving the people accessing those services.
Randomised Controlled Trials (RCTs) are central to evidence-based healthcare; but they themselves are riddled with inefficiency. Trial Forge aims to change that.
In this post you are going to figure out how to interpret the evaluation of diagnostic tests through sensitivity and specificity.
Deevia takes a look at ‘effect modification’ and ‘confounding’ and explains the differences.
YouTube video series by Dr. Aaron Carroll called Healthcare Triage, where his motto is, “To the Research!”
Danny Minkow looks into how the COMET initative is working to developing and apply an agreed-upon set of outcomes measures in medical research. Why is it needed?
Advancing techniques and mechanization in every field has led to newer computer or written questionnaires in the field of medicine.
One often is confused whether to rely on these questionnaires or carry out oral history taking which has been prevalent for ages?
here’s an insight to it through various researches…
Surrogate endpoints are like a double edged sword. Even though they do have some benefits on some occasions, they can easily mislead doctors into withdrawing the wrong conclusions. It is, therefore, important to use them with caution.
Terms such as significant, hypothesis testing, and p-value are usually found in research papers, here is a review explaining them.
In search of a book with simple, comprehensible definitions and examples of clinical evidence? Do you want to take the first step in understanding common terms in clinical evidence as well as commonly used methods and their pitfalls? This review will inform you if this is the book you’re looking for.
Is this your first contact with evidence-based healthcare? This course is a perfect start…
What happens when you have a test result? Do you believe it, can you act on it? It all depends where you are. Check out this discussion of post-test probabilities and how they help in the interpretation of test results.
An introduction to the role of statistical power in the search for evidence.
Observational research is an important method in evidence-based medicine, especially when it is performed to support or assess effectiveness results from randomized controlled trials. An unwanted (but not always observable) confounder in observational research is confounding by indication and should be eliminated from the research design when possible for the results to be meaningful. Let’s find out what this confounder is!
Because of the increase in health care costs and the limited available resource costs, economic evaluation becomes more important in daily practice. What do we have to know for an economic evaluation?
Another 20 minute tutorial from Tim.
Anna reminds us of the value of observational evidence in low income countries.
Ben has made an entertaining YouTube video explaining what an RCT is.
Want to find out how to evaluate a randomised controlled trial? This is the perfect resource for you, brought to you by CASP Tools.
There’s a lot of evidence out there of varying quality. This slideshow looks at the uses of grading medical evidence, and how it can be done.
A meta-epidemiological study published in the BMJ last month has found that smaller trials consistently report larger effect sizes.
This is a tutorial that looks at the statistical basis of randomised controlled trials, the theory behind meta-analyses and how to read a meta-analysis
CASPin provide many tools to help you systematically read evidence and this specific tool will help you make sense of any case control study and assess its validity in a quick and easy way.
A website providing a detailed guide to the steps researchers have to take before, during and after a clinical study.
The BMJ has on its website a series of articles on how to read papers, including clear explanations of the statistics commonly used and common pitfalls found in studies.
Bias is often an issue within clinical research, and we take many measures to avoid it. However, these measures are often neglected in preclinical animal studies, which give us the results upon which clinical trial study designs are based.
The EBM Pyramid shows the various levels of information available in evidence-based medicine.
Download this form if you would like help reading and making sense of qualitative research.
PowerPoint by Dr Amanda Burls, on randomized controlled trials and meta-analysis, described through four real-life examples.
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