Over on the Bad Science blog there is a great article on research conducted by journalists and the conclusions derived. An issue that we will become more important with the increased prevalence of access to data on the web.
The author, Ben Goldacre, uses the example of an article in the Telegraph that links the rise in anti-depressant prescriptions to the recession. Which postulates that the 43% increase in the number of prescriptions for the SSRI class of antidepressants is/was caused, in part, by the recession. Anyone who has taken a traditional research course in college and poke in holes in this claim. From the very basic understanding that correlation <> causation. Ben goes on to debunk the claim:
…Well. Firstly, this rise in scripts for antidepressants isn’t a new phenomenon. In 2009 the BMJ published a paper titled “Explaining the rise in antidepressant prescribing”, which looks at the period from 1993 to 2005. In the 5 year period from 2000 to 2005 – the boom before the bust these journalists are writing about – antidepressant prescribing also increased, by 36%. This isn’t very different to 43%, so it feels unlikely that the present increase in prescriptions is due to the recession.
That’s not the only problem here. It turns out that the number of prescriptions for an SSRI drug is a rubbish way of measuring how many people are being treated for depression: not just because people get prescribed SSRIs for all kinds of other things, like anxiety, PTSD, hot flushes, and more; and not just because doctors have moved away from older types of antidepressants, so would be prescribing more of the newer SSRI drugs even if the number of people with depression had stayed the same.
Excitingly, it’s a bit more complicated than that. A 2006 paper from the British Journal of General Practice looked at prescribing and diagnosis rates in Scotland. Overall, again, the number of prescriptions for antidepressants increased from 1.5 million in 1996 to 2.8.million in 2001 (that is, it almost doubled)…
As Ben points out, there are too many variables to correlate the rise in prescriptions to the recession. Having a background in academia these types of articles frustrate me. You can essentially correlate any increase/decrease during this time-frame to the recession.
Now the conclusion in the Telegraph article conclusion is logical and makes a great headline. Anyone reading that article will come away probably thinking “… yeah that makes sense”. When in reality the reason behind the increase is more in line with the above or simply that the sales teams for SSRIs deserve a raise.
Whatever the case, it highlights that point that data ethics is just as important as ethics in journalism, in fact they are one in the same. Professional and academic researchers go to great lengths to support conclusions in their research, not to mention the peer review processes in place to get published. Open data and ease of publication, while a necessity, opens the door for irresponsible data journalism and damages it’s credibility.
Data Journalism + Ethics
Over on the Bad Science blog there is a great article on research conducted by journalists and the conclusions derived. An issue that we will become more important with the increased prevalence of access to data on the web.
The author, Ben Goldacre, uses the example of an article in the Telegraph that links the rise in anti-depressant prescriptions to the recession. Which postulates that the 43% increase in the number of prescriptions for the SSRI class of antidepressants is/was caused, in part, by the recession. Anyone who has taken a traditional research course in college and poke in holes in this claim. From the very basic understanding that correlation <> causation. Ben goes on to debunk the claim:
As Ben points out, there are too many variables to correlate the rise in prescriptions to the recession. Having a background in academia these types of articles frustrate me. You can essentially correlate any increase/decrease during this time-frame to the recession.
Now the conclusion in the Telegraph article conclusion is logical and makes a great headline. Anyone reading that article will come away probably thinking “… yeah that makes sense”. When in reality the reason behind the increase is more in line with the above or simply that the sales teams for SSRIs deserve a raise.
Whatever the case, it highlights that point that data ethics is just as important as ethics in journalism, in fact they are one in the same. Professional and academic researchers go to great lengths to support conclusions in their research, not to mention the peer review processes in place to get published. Open data and ease of publication, while a necessity, opens the door for irresponsible data journalism and damages it’s credibility.