Posted on March 8, 2017
Our student bloggers are welcome to blog about any topic or issue related to evidence-based healthcare that interests them. However, if you’re thinking of blogging for Students 4 Best Evidence, and are unsure where to start, below are a list of suggested topics you might like to choose from.
- What is the difference between absolute & relative risk?
- What is attrition bias?
- What is detection bias?
- What is performance bias?
- What is an “economic analysis”?
- What does “no evidence of effect”/”evidence of no effect” mean and how do they differ?
- Prioritisation – how are research topics prioritised?
- How might patients be involved in prioritising research? (An example is the James Lind Alliance)
- Distinction between systematic reviews & meta-analysis
- What is heterogeneity and what is the I2 statistic?
- Blinding – what is it? What is effective blinding? What is not?
- What databases are there? PubMed, EMBASE, LILACS, CENTRAL
- What is confounding?
- What is confounding by indication?
- What are outcomes? What are “relevant outcomes”? What are “surrogate outcomes”?
- What is a “composite outcome”? Why are they reported? What is the significance?
- What are “cut-off points”?
- How do patients values and beliefs get taken into account when practising evidence-based healthcare?
- What is “shared-decision making”?
- What is “unwarranted variation in practice”?
- What is a “ROC” curve (receiver operator characteristics)?
- What is a guideline?
- How is evidence incorporated into guidelines?
- What is the Cochrane Collaboration?
- Who was Archie Cochrane?
- What is a “post hoc analysis”? How do we interpret these results?
- What is “data dredging” or a “fishing trip”?
- What is statistical power and how do you calculate it?
- What is a prospective cohort study?
- What is a retrospective cohort study?
- What is “preference-sensitive care”?
- What does “fixed effects model” mean?
- What does “random effects model” mean?
- What is the difference between descriptive and inferential statistics?
- What is the difference between standard deviation and standard error (and how are they related)?
- What is an “as treated” analysis?
- What is a “per protocol” analysis?
- What do trialists do about participants who are “lost to follow-up”?
- What is a cross-over trial?
- What is a “carry over effect”?
- What are ‘adverse events’ and why is it so important that they are recorded and reported in studies?
Issues and debates within evidence-based healthcare
- The seamier side of academia; lying, cheating and occasionally stealing. Retractions (withdrawals) of journal articles are increasing (more than the publication rate of articles is increasing). Moreover, misconduct accounts for the majority of retracted scientific publications. But how do some researchers get away with malpractice for so long and what is being done to tackle the issue? (See retractionwatch.com – a website keeping track of the authors who have had the highest number of retractions (e.g. for falsifying data)).
- What evidence-based healthcare currently is vs. what it should be (in an ideal, but not necessarily unrealistic, world).
- Communicating risk: how figures can be (mis)used and the difference between absolute and relative risk. (Have a look at understandinguncertainty.org from which the following is taken: “A good example to start with is ‘bacon sandwiches’. A major report estimated that there was a 20% increased risk of bowel cancer if you ate 50g of processed meat every day – that’s a large bacon sandwich. This was reported in the Sun with the headline: “Careless pork costs lives!“. This is a relative risk, and can sound quite frightening. But for an average person, the chance of getting bowel cancer at some point in their life is around 5%. A 20% relative increase on this translates to a lifetime risk of 6%, or an increase of 1% in absolute risk, which now does not sound so bad”).
- The role (and responsibility of!) the media for disseminating research to policy-makers, practitioners and patients.
- The perverse incentives (publication, funding, promotion) in academia to produce positive results.
- Patients and the public tend to have unrealistic expectations about interventions, overestimating the benefits and underestimating potential harms. This may be contributing to the problem of overdiagnosis and overtreatment. (See http://bit.ly/1rvoOkj)
- ‘The medicalization of normal?’ Allen Francis, the chair of DSM-IV has been vocal concerns about over-diagnosis in psychiatry. Are we witnessing the medicalization of ‘ordinary’ issues? And what are the implications – stigma; exposure to potentially harmful (unnecessary) medications; misallocation of resources etc.
- “Making people sick in the pursuit of medicine”. The problems and harms associated with over-treatment (from over-detection, to over-diagnosis, to over-treatment).
- Poor health literacy among the general population and the implications of this (see http://bit.ly/29lU0Ny)
Health in the media series
We’re also looking for students to start up our ‘health in the media’ series again, looking at the claims made in the media about various interventions and evaluating whether these claims are true to the evidence.
Reviews of resources
We’re also looking for students to write short, informal reviews of learning resources, giving feedback on how useful they find them. You can find more information here.
Evidently Cochrane, our sister blogging website, are also looking for bloggers and have a list of suggested blog topics on their website.