Description:
Structure of your blog entry:
You can structure your blog entry however you see fit, hoever you should include the following information:
Introduction:
You should briefly describe the purpose and aims of the study you are describing. Remember your audience is GPs and pharmacists. You shouldn’t need to give long explanations of common medical conditions. Remember that the marks are awarded for your description and critical analysis of the research.
Description of methods:
Think carefully about including the most important details in the methods, because you will not be able to include all the details. You should include details of the the experimental protocol, but do not forgot to mention what was measured (and how) and what the primary end point of the study was (or which value was compared between groups.). As your critical analysis is largely dependent on the methods, it is important to make clear how the experiment was conducted.
Description of results:
It is important to discuss the most important results quantitatively and to consider the most important information to include in a short summary. Don’t be tempted to write too much about statistical significance, without commenting on the size of the effect measured. Many papers will include lots of measurements, you need to consider which are the most important, as you won’t have room to discuss them all.
Critical analysis:
This is probably the most difficult section (and consequently, where the most marks are available). Essentially, you should aim to consider the work critically, rather than simply accepting the authors’ conclusion. You can approach this task by asking questions such as: Were the methods (and endpoints) appropriate? What do the results mean? Is the authors’ interpretation of the results supported by the data?
You should try to judge each paper on its own merits. If a paper set out to test the hypothesis that ‘dogs enjoy eating bones’ it’s not really fair to criticise it for not asking whether cats like eating bones. Proposing an extension to a study (however interesting) is not critical analysis. You may wish, briefly, to discuss the implications of the research which is again interesting but is not critical analysis.
Try to keep your critical analysis specific rather than general for example, rather than automatically saying ‘the experiment would have been better if the sample size had been bigger’ consider whether this is really the case. In very may experiments it is true, but it requires some justification. Experimenters don’t usually pick a sample size (n number) out of thin air, they will perform calculations to work out the sample size they need. A trial that is bigger than it needs to be costs more money and may have ethical implications relating to unnecessary experimentation on volunteers or animals. A comment along the lines of ‘the authors don’t state how they calculated their sample size’ or ‘the authors calculated their sample size but were not able to recruit enough volunteers’ is a much more useful indication that something is wrong.
It is important to comment on bias e.g. ‘there were more people with hypertension in the control group than the test group’ and to think carefully about critical analysis of the measurements and endpoints used in the trial. Many studies will claim that drug x reduces cardiovascular risk, when in fact they have only measured the effect of drug x on blood pressure, not on cardiovascular events. If a trial uses the ‘Penson depression score’ as its endpoint, you need to question what this score is? What does it mean? Has it been validated in other trials? What are its strengths and weaknesses?. Some experiments don’t seem to have a clear hypothesis and don’t state the primary endpoint in the methods. This is often the case with trials involving mental health where the patients will be assessed for severity of symptoms using 4 or 5 different scales before and after an intervention. You should be asking if it is necessary to use so many scales , or whether the authors were ‘hedging their bets’ and hoping they would see a significant difference in at least one of the measurements.
It is also interesting to comment on the way in which numerical data are treated. For example, Some trials of antihypertensives set out arbitrary categories for BP (ie normal<140/90
These are by no means the only things you can comment on, but hopefully they give some food for thought.
In order to write a blog entry about a piece of research, you should know the paper ‘inside-out’ and understand it. My strong advice would be to try to write the blog entry without the paper in front of you. You will obviously need to check figures and details, but this approach should help you to avoid any allegations of academic misconduct, for which the sanctions are very serious. University advice regarding academic misconduct and plagarism can be found here: https://www.ljmu.ac.uk/studysupport/81924.htm