Our library of evidence-based nursing resources features links to a range of resources that can help student nurses get to grips with various aspects of evidence-based practice. This page is continually updated, so do let us know if you know of resources that are missing.
If you’d like to blog for Students 4 Best Evidence, but are feeling unsure where to start, have a look at this list of suggested blog topics.
Here are 34 key concepts that are crucial to understand to be able to critically appraise the claims that people make about treatments. And here are lots of resources that explain each key concept. Students, we need your help reviewing them!
Our library features links to a range of resources that can help you get to grips with various aspects of evidence-based healthcare. From statistics tutorials to guidance on how to critically appraise a paper. This page is continually updated, so do let us know if you know of resources that are missing.
Keep up to date with the latest Cochrane evidence by following our sister blog, Evidently Cochrane. Evidently Cochrane posts weekly blogs, which usually feature new or updated Cochrane reviews on a health topic. It is for everyone interested in finding and using the best quality evidence to inform decisions about health.
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, Sasha Lawson-Frost explores what moral values underpin or justify the practice of Evidence-Based Medicine, specifically in response to a recent article which stated “the policy side of evidence-based medicine is basically a form of rule utilitarianism”.
In this blog, Leonardo provides 5 interpretations that you should consider when you read or hear about a reported association in observational studies.
This is the nineteenth blog in a series of 36 blogs explaining 36 key concepts we need to be able to understand to think critically about treatment claims.
People in treatment comparisons who are not followed up to the end of the study may have worse outcomes than those who are followed up. For example, they may have dropped out because the treatment was not working or because of side effects. If those people are excluded, the findings of the study may be misleading.
Is evidence-based medicine a fairy tale? With this in mind, Foo Wee brings her personal experience into a review of the evidence available for analgesic treatment of G6PD deficient children. This blog won 2nd prize in the recent Cochrane Malaysia blog writing competition.
In this blog, Kamal Pandit discusses the findings of three recent Cochrane reviews which assessed the effectiveness of treatments for Coronary heart disease (CHD). He adds personal experience to provide context to treatment of a condition which is the single leading cause of death globally (WHO 2014).
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 is the eighteenth blog in a series of 36 blogs explaining 36 key concepts we need to be able to understand to think critically about treatment claims.
If an outcome is measured differently in two comparison groups, differences in that outcome may be due to how the outcome was measured rather than because of the treatment received by people in each group. For example, if outcome assessors believe that a particular treatment works and they know which patients have received that treatment, they ma y be more likely to observe better outcomes in those who have received the treatment. One way of preventing this is to keep outcome assessors unaware (“blind”) of which people have been allocated to which treatment. This is less important for “objective” outcomes like death than for “subjective” outcomes like pain.
In this blog, Saul Crandon provides the key points to consider, advantages, disadvantages, and further details regarding intercalated degrees.
Tarang Sharma was lead-author of a recent article entitled “The Yusuf-Peto method was not a robust method for meta-analyses of rare events data from antidepressant trials”. In this blog, Tarang gives more details about meta-analysis methods of rare events and sparse data, and why these can lead to misleading results.
This blog, written by Leonard Goh, was the winner of Cochrane Malaysia and Penang Medical College’s recent evidence-based medicine blog writing competition. Leonard has written an insightful and informative piece to answer the question: ‘Evidence-based health practice: a fairytale or reality’.
Cochrane Malaysia and Penang Medical College, with the support of Students 4 Best Evidence (S4BE) recently ran an evidence-based medicine blog writing competition for undergraduate and postgraduate students of health in Malaysia.
This is the seventeenth blog in a series of 34 blogs explaining 34 key concepts we need to be able to understand to think critically about treatment claims.
People in a treatment group may experience improvements (for example, less pain) because they believe they are receiving a better treatment, even if the treatment is not actually better (this is called a placebo effect), or because they behave differently (due to knowing which treatment they received, compared to how they otherwise would have behaved). If individuals know that they are receiving (they are not “blinded” to) a treatment that they believe is better, some or all of the apparent effects of the treatment may be due either to a placebo effect or because the recipients behaved differently.
This is the sixteenth blog in a series of 34 blogs explaining 34 key concepts we need to be able to understand to think critically about treatment claims.
Apart from the treatments being compared, people in the treatment comparison groups should otherwise receive similar care. If, for example, people in one group receive more attention and care than people in the comparison group, differences in outcomes could be due to differences in the amount of attention each group received rather than due to the treatments that are being compared. One way of preventing this is to keep providers unaware (“blind”) of which people have been allocated to which treatment.