Header picture by Ken Teegardin
Trying to make sense of nonsense
Tag Archives: science
June 19, 2013Posted by on
There are a lot of scary things to face when doing a PhD: supervisor’s ideas of ‘normal’ working hours, reviewers whose sole aim in life is to reject as many papers as possible, or the experimental equipment that only works when the right amount of blu-tack is in the right place and you karate chop the on-button. But possibly the scariest of all is the journalist.
This is why sense about science has set up their Standing up for Science media workshop: a one day workshop, specifically for early career scientist that gives a bit of insight into how science gets translated into news. It’s a great workshop that combines a session of scientists talking about successful (and less successful) experiences with journalists, with a session of journalists talking about what they actually do during their busy days. But most of all, it gets us early career scientists away from our lab benches for a day to talk about why we think it is so scary in the first place.
Most of us grad students (and scientists in general) are funded by public money, so it is a reasonable expectation that we try to feed our results back to the public. That’s easier said than done though. As scientists, we spend a lot of time getting the right results, and even more so, getting them just right on paper. Even though a scientific article might be only 3,000 words, it has to represents years of blood, sweat and tears.
So it might be understandable that we can be a bit hesitant when we have to hand this over to a journalist not familiar with our particular brand of science. We’ll just have to stand by while they condense it into a catchy headline and accompanying article that is often shorter than any summary we could write ourselves. Everyone knows someone for whom this has gone horribly wrong. Stories are abound about how a basic science paper on cells in a petri dish ended up promising to have found the cure-all pill for cancer, or how bacon is apparently responsible for doubling our (already 100%) risk of death.
It’s great to hear from experienced people like Dr Deirde Hollingsworth and Prof Stephen Keevil that talking to media gets easier after a while, and that the mess-ups are rarely remembered by anyone but yourself. Even talking to a news outlet with a reputation like Fox News can be a good experience, according to Dr Emily So who talked to them live on air after the Fukushima earthquake and tsunami.
In the Q&A session afterwards, Dr Hollingsworth advises us not be afraid of silence (unless you’re The Doctor, in which case you’re right to be afraid). It’s up to the journalist to ask questions, and if you try to fill the void you might end up saying things you didn’t intend to.
The journalist session is equally enlightening. Jason Palmer (BBC), Richard Van Noorden (Nature) and Jane Symons (former health editor at the Sun) assure us they’re not out to get us: they want to get the science right as much as we do. However, they do have a product to sell and a deadline to make (not to mention a mythical sleepy granny to keep awake), so it would be helpful to them if we do pick up the phone when they call. If we don’t, they might go for someone even less qualified to answer their question.
Helpfully, sense about science has provided a booklet with some easy tips (and even a checklist) on talking to the media. Sense about science are organising the Standing up for Science workshop again in September (London) and in November (Glasgow).
March 1, 2013Posted by on
We read about statistics every day: be it the predicted winner of a football league, the association between the weather and mortality, or a newly discovered link between an inanimate object and cancer. Statistics are everywhere. And perhaps even more so this year, as 2013 has been hailed as the International Year of Statistics. Despite all this attention for numbers, we generally don’t know a lot about the people hiding behind their computers churning them out. With media attention for people like Nate Silver and Hans Rosling, some are now able to name at least one statistician, but, stepping it up a level, could you name a female statistician?
Statistics is definitely not the only branch of STEM subjects suffering from a lack of distinguished women. Just take a look at the list of Nobel Prize winners (44 out of 839 Laureates), fellows of the Royal Society (currently 5%), or scientists on television. This is not due to a lack of women in statistics, there are many. So with this being the year of statistics, I thought it might be the perfect timing to highlight some of the women who work(ed) in statistics.
Dr Janet Lane-Claypon: epidemiologic pioneer
Dr Janet made quite a few important contributions to epidemiology by using and improving its use of statistics. Born in 1877 in Lincolnshire, she moved to London to study physiology at the London School of Medicine for Women (today part of UCL). She spent a few years there collecting an impressive list of titles: a BSc, DSc and MD, making her one of the first, irrespective of gender, Doctor-doctor’s.
All very exciting of course, but what has she got to do with statistics? Her run-in with statistics started in 1912, when she published a Report to the Local Government Board upon the Available Data in Regard to the Value of Boiled Milk as a Food for Infants and Young Animals. It’s an impressive report (available at the British Library, in case you’d like to leaf through it on a rainy Saturday afternoon), and the first of its kind. In it, Lane-Claypon compares the weights of infants fed on breast and cows’ milk, to find whether the type of milk had an effect on how fast babies grew. To answer this question, she used, for the very first time, a retrospective cohort study, description of confounding, and the t-test.
Before she started she study, Dr Janet realised she would need a large number of healthy babies who had been fed cows’ milk and a similar number of babies on breast milk. More importantly, she realised that in order to compare the two groups, she would need the babies to be “as far as possible” from the same social environments. She ended up travelling to Berlin, where babies from the working classes regularly attended Infant Consultations where their diet and weight was registered, resulting in the perfect dataset to answer her question.
This visit resulted in data on just over 500 infants making up the first retrospective cohort study (many others would follow, but not till some 30 years later), which was ready to be analysed. However, although all babies came from working class parents, Dr Janet realised that their social environments could still be slightly different, leading to different rates of weight gain between the groups. She explains:
“It does not, however, necessarily follow that the difference of food has been the causative factor, and it becomes necessary to ask whether there can be any other factor at work which is producing the difference found. The social class of the children seemed a possible factor, and it was considered advisable to investigate the possible significance of any difference which existed between the social conditions of the homes.”
Dr Janet compared the wages from the fathers of the infants, for the first time taking confounding into account, and found that they looked the same for the two groups. Still not satisfied whether the difference she had found between breast and cows’ milk fed children was real, she decided to use a new complicated technique that had been published 4 years earlier, but hadn’t been used in epidemiology up till then: Student’s t-test. Chances are that you’ve heard about this test, as it is now one of the most commonly used tests in any branch of science. Although it was developed to monitor the quality of stout by W.S. Gosset, Janet Lane-Claypon was the first to use it in medical statistics.
Dr Janet’s pioneering didn’t stop there. She went on to conduct the first ever case-control study in 1926, which possibly used the first ever questionnaire to gather health data (so think about her next time you see a pop-up window/email asking if you’ve got a few minutes to spare) on the causes of breast cancer. Her results were used by two other famous statisticians: Nathan Mantel and William Haenszel. They developed the Mantel-Haenszel test to adjust results for confounding. Her findings included most of the currently recognised risk factors for breast cancer. Dr Janet continued to work till 1929, when she had to retire at 52 due to the silly reason that married women weren’t allowed to work in the civil service.
Some further reading on Dr Janet:
Lane-Claypon JE. Report to the Local Government Board upon the Available Data in Regard to the Value of Boiled Milk as a Food for Infants and Young Animals. 1912
Lane-Claypon JE. A Further Report on Cancer of the Breast with Special Reference to its Associated Antecedent Conditions. Reports on Public Health and Medical Subjects. 1926
Winkelstein W. Vignettes of the history of epidemiology: Three firsts by Janet Elizabeth Lane-Claypon. American Journal of Epidemiology 2004;160(2)97
Winkelstein W. Janet Elizabeth Lane-Claypon: a forgotten epidemiologic pioneer. Epidemiology 2006;17(6)705
Have yourself a merry epi-Christmas: gift ideas for epidemiologists (and possibly a few statisticians)
December 17, 2012Posted by on
With only a couple of days left until presents are expected to magically appear under trees, here are a few (affordable) suggestions for gifts for that special epidemiologist in your life.
Naturally, you could get him/her a John Snow mug (though beware true coffee/tea addicts: the mug is a bit on the small side), Florence Nightingale, or a brain-eating amoeba, or perhaps a cuddly, but evil Poisson distribution (oh, it promises to be discreet, but as soon as you say something negative it bails on you). There’s even some stuff if you want to be more traditional and go with jewellery: a π necklace for instance, or a necklace spelling out ‘I am star stuff’ in amino acids (the shop is closed at the moment unfortunately). And best of all, there’s the Sciencegrrl calendar – and tote bag, badges and memory sticks – which is pretty awesome and features epidemiology girl Soozaphone as April.
But hey, if you’re anything like me, you’re planning to spend the entire Christmas break reading on your parents’ couch, so here are my favourite three 2012 books vaguely related to epidemiology:
3. Ben Goldacre: Bad Pharma
A good book on an important topic, that happens to partially coincide with my PhD, so I’m probably a bit biased. It’s not a book to read in one go, if only because your blood will boil, and as the trials on blood pressure drugs are a bit dodgy, that might not be a good thing.
The title of the book might be a tad bit misleading though as Big Pharma isn’t inherently bad, we (regulators, academics, governments, patient groups, the public) just let them get away with it. Google, Amazon and Starbucks are ‘morally wrong’ in trying to pay the least possible amount of tax, but we don’t put the sole blame on them. The same principle goes for Big Pharma: we let them do it. Let’s change that.
So why only third place? Well, there happened to be two even more awesome books vaguely related to epidemiology published this year (that, and I can’t figure out the braille joke on the cover, which has been bugging me for weeks).
2. Jon Ronson: The Psychopath Test
A mystery package from Sweden arrives in an academic’s pigeonhole in London. There is no return address. Inside the package is a book of which every other page is blank, the pages with words on them have words cut out, and it is written by a ‘Joe K’. Intrigue follows: many academics all over the world, in distant corners such as Tibet and Iran, have received the exact same package. The London academic decides to enlist Jon Ronson to find out what’s going on and a journey into the madness industry follows.
The book might be a particularly good read with DSM-5 coming up in 2013. Psychology Today has a nice overview of everything that might be wrong with this new edition of the ‘bible of mental health disorders’ (calling it that for one). Perhaps everything will be all right and the new DSM will just create more psychiatric atheism among those wielding the power to diagnose, but with normal behaviour such as grieving longer than two weeks being classed as a mental disorder,
1. David Quammen: Spillover
“If you look at the world from the point of view of a hungry virus, or even a bacterium – we offer a magnificent feeding ground with all our billions of human bodies, where, in the very recent past, there were only half as many people. In some 25 or 27 years, we have doubled in number. A marvellous target for any organism that can adapt itself to invading us.” William H. McNeill – historian
I’ve grown up in a part of the world that was hit by epidemics almost every other year, or so it seemed at the time. It was horrible. Going to school every morning and not knowing who would be victimised next. Luckily, they weren’t epidemics affecting humans, but livestock. We had classical swine fever in 1997/98, foot-and-mouth disease in 2001, and blue tongue in 2006/07. During those epidemics, the farms of my school friends would be hit one by one. They had to stand by as professionals came in to kill off thousands of animals which they loved and were their families’ only source of income. Later that same day it would all be repeated on the TV during the eight o’clock news, and the next day the trucks would pull up at their neighbours’. It was hard. And it became even harder after 2007, when it turned out that one of those epidemics, Q-fever, was affecting humans.
When we think about where the Next Big One might come from, a rural village in the Netherlands doesn’t tend to be high on the list. Nevertheless, it features in ‘Spillover’ as one of the places where a spillover, the transmission of an infectious disease from animal to human, happened recently. The Dutch story might not be as thrilling as capturing bats potentially infected with a deadly virus (Marburg), tailing gorillas who could be the host of the elusive Ebola virus or tracking down stories on the origins of SARS, HIV and Nipah. The latter, though relatively unknown, caused an outbreak in Malaysia when it spread from fruit bats, via pigs to humans. A million pigs had to be killed. “There’s no easy way to kill a million pigs,” notes Dr Hume Field, one of the experts followed by David Quammen in the book. Later he corrects himself: It was in fact 1.1 million pigs. The difference might seem like just a rounding error, he tells Quammen, but if you ever had to kill an “extra” hundred thousand pigs and dispose of their bodies in bulldozed pits, you’d remember the difference as significant.
Spillover is, without doubt, the most intriguing book I’ve read all year.
*But perfectly timed for my birthday in January 😉
August 21, 2012Posted by on
Well, thank you all for reading the first part – I got more visitors than I normally get in a month! Hope you like the second half as much as the first! Any comments/other tips are of course very welcome.
Step 3: Submission and waiting
Before you submit, you should make some final checks, for which most journals supply a handy checklist (sometimes you don’t run in to these until you actually register to their submission system, so have a look around there early on). Are you complying with the relevant reporting guidelines? Do you have all necessary forms, such as conflict of interest statements, and the perfect abstract and cover letter (those are two things an editor is sure to look at) to convince the journal your article is worth reviewing? Right then: hit those buttons and submit.
And now the wait starts. If you don’t hear from the journal within the next couple of days, your paper has probably been sent out for review, which is good, but could take weeks, if not months. Luckily, there are things you can do to slightly speed this process up, such as suggesting potential reviewers in your cover letter (if the journal doesn’t provide that option in their submission system). Even though the journal might have published lots of similar studies, it is always helpful to make some recommendations.
Step 4: Results!
Unless your are submitting to the journal of universal rejection, you can never be sure what the outcome of a submission is going to be. There are three possible outcomes: you’re paper gets rejected, the editor wants you to revise your paper, or your paper is accepted without changes (it’s theoretically possible, I’ve been told). In case of rejection, you can either appeal the decision or move on to the next journal.
Personally, I have never appealed, but it is possible to do so when you feel you’ve been unfairly rejected. Maybe the reviewers didn’t display any knowledge of the topic area (you’d be surprised how many reviewers accept to review paper on topics they have no or little expertise on), or the decision of the editor doesn’t seem to add up with the opinions of the reviewers. It happens. One thing to keep in mind is that an appeal can take a long time: if the editor appears to have made the wrong call, associate editors will have to make a decision, which can be fairly quick. However, if the reviewers were in the wrong, the editor will have to assert their incompetence, and find new reviewers. It might be faster to submit to a different journal (which might be preferable in the case of looming grant application deadlines).
The third option, revision, comes in two flavours: minor and major. Although the first one gives you a better chance of eventual acceptance, it’s still not sure you’re going to get in. The vestiges of published, peer-review science are guarded well, or that is the intended function of peer-review at least. Major revisions will require re-analysis, new tests or experiments, rewrites or explanations of unexplained concepts: the list is endless really.
Step 5: Responding to reviewers’ comments
One thing to take into account when responding to reviewers’ comments is that is not personal, and that reviewers rarely agree. A large meta-analysis  actually found that peer reviewers only agree about 1 in 3 times (or even less if you focus on the larger studies with smaller confidence intervals). However, the editor would like to see your study published (that’s what is paying
his their salary) and the reviewers’ comments are meant to be constructive, so it’s important to stay in character and be polite when you answer.
This might seem like pointing out the obvious, but under the guise of anonymity, some reviewers tend to lose composure. Although you might be tempted to give in and give such reviewers a piece of your mind, it will be the editor who will read your response first, so it’s better to hold your guns. Some reviewers might have a vested interest in whether or not your paper gets published: they work in your field, so they will have an opinion on whether what you’re doing is correct and line with their work. Other peculiar behaviour might happen when someone remarks you only cited one single paper by the distinguished Dr Scientist. Maybe you could also cite these other eight (barely relevant) papers by the honourable Dr Scientist, who you’re not supposed to guess is the actual reviewer?
Working through comments can get very frustrating. Here’s a beautiful pair of comments I got back from some reviewers (both on the same paper):
- Reviewer #1: “The analysis and purpose of the study is confusing. The quality of the data is likely suspect.”
- Reviewer #2: “I found the paper to be well written, the analysis rigorous and well conceived and the conclusions supported by the data and analysis.”
And this was just the start of both reviews, the disagreements between both reviewers got worse with every paragraph they dealt with. As mentioned before, these inconsistencies between reviewers are common, which is why it is an editor making the final decision, rather than the reviewers battling it out amongst themselves. Working through them can be become a bit tedious to say the least.
The final part of responding to reviewers’ comments (and you have to respond to all of them), is writing the rebuttal or revision letter. I like to start by thanking the editor for giving me the opportunity to revise and respond to the comments. That will take up one page, which I structure a bit like my cover letter (department-headed paper and all). Then I start the actual rebuttal:
“We thank the reviewers for their comments on our paper. We have changed our paper accordingly and addressed all the comments as listed below:”
[Short summary of major changes]
[Copy and paste comments from reviewers and write a short response to each of them for instance:]
1. In figure 1, the authors have not included in which units the y-axis is labelled.
We thank the reviewer for noticing this omission. We have now correctly labelled our y-axis in rate per 100 person-years.
(the colour helps to distinguish between reviewer’s and my words)
It might take a few pages to get through all of them, but it makes it easier for the editor to see what I did and why I did it – hopefully shortening my waiting time a bit. Then it’s time to resubmit the whole thing again. If the comments were only minor, it’s usually the editor who will make the final decision. If there were any major comments, the paper is likely to go back to the initial reviewers and you’ll have to wait a bit longer.
Alternative ways to get published
Writing papers isn’t the only way to get your name out there: give blogging a go! Or offer to write a book review (free books!), write science news articles (a good way to keep on top of what is happening in your field, and to practice those abstract writing skills) or enter a science writing competition. (I’m obviously not entirely subjective here). Significance is always on the look out for new bloggers, so why not try them if you’re tempted?
So every journal on your list rejected your paper? Why not try the Journal of Negative Results in Biomedicine, the All Results Journal, the Journal of Pharmaceutical Negative Results or even the Journal of Articles in Support of the Null Hypothesis?
And now go read some author guidelines! They’re likely to be shorter than this post.
Resources & Reference:
1. Bornmann L, Mutz R, Daniel H-D (2010) A Reliability-Generalization Study of Journal Peer Reviews: A Multilevel Meta-Analysis of Inter-Rater Reliability and Its Determinants. PLoS ONE 5(12): e14331. doi:10.1371/journal.pone.0014331
Twitter hashtags: #PhDchat / #ECRchat / #acwri <- useful to ask questions and find other good resources. If you don’t use Twitter, no worries: PhD-chat has an off-twitter wiki, and ECR (early career researcher) chat has a blog.
August 20, 2012Posted by on
With only 3 papers with my name on it, I’m definitely not an expert when it comes to getting papers published. However, those 3 papers (and one that’s waiting in some reviewers’ inboxes right now) have been rejected a total number of 12 times, giving me at least some experience in preparing and submitting them. Maybe that’s why I got invited to give a talk on publishing papers at the student skills workshop at the ICPE – the International Conference on Pharmacoepidemiology and Risk Management. Or it might have been that when a publisher dropped out last minute, and the organisers (one of whom I happen to share a supervisor with) really needed someone who had already booked their tickets to Barcelona.
Either way, I’ve got a presentation to prepare for, and in doing so, I’ve found that actually I have developed a bit of a five-step system when it comes to preparing papers. Even more so: when talking with other students and staff around my department, I’ve found some interesting tips and thoughts on how to get published. I felt it might be worth it to actually write all of this up in a blog (and get some last minute considerations to add to my talk?), as a reference to build on, so here we go:
Step 1: Selecting a journal
I’ll start at the point where you’ve done all your analyses and have pretty good idea what you want your paper to be about. Maybe you’re working on that first draft, or you’re already on version 17.3, but at some point you’ll have to start considering what journal to submit to. As my first supervisor told me when my very first paper was rejected by JAMA: “If the first journal you submit your paper to accepts it, you didn’t aim high enough”.
And there you immediately have your first problem: what constitutes aiming high? Impact factors are one determinant of ‘high’, though we all know now that using those in any decision making will only prove you are statistically illiterate. Rather, you could aim at submitting to one of the general medicine journals, such as the New England Journal of Medicine, JAMA, the Lancet or BMJ. All of those boast large regular reader counts and even larger rejection rates.
The scopes of these journals are wide, but they will only consider the studies that will keep their impact factors up, so it might be good to consider some more specialist journals as well. You might not reach as many researchers, but you are more likely to reach the right ones. To find out which are best for your research, go over the papers your citing: there are bound to be some relevant journals there. Or ask an expert; you’re collaborators (if you have any) will probably be able to make some suggestions.
These can ideas can then form a list of potential journals to submit to. Being rejected becomes a lot less painful if you’ve your plan B at the ready. Final considerations will depend on your funder (should the journal be open access?) and funding (yes, it costs money to be published).
Step 2: Formatting and editing
However much I’d like it, there is no getting out of formatting or weeding through formatting guidelines (at least not until you’re senior enough to have someone do it for you), but there are some little things that can make it easier. One of these is Wordle, which creates a ‘word cloud’ highlighting the words you’ve used most often. The first time I copied a paper of mine in there (luckily just before I meant to send it to my supervisors), one word stood out like a sore thumb: However. Without really noticing it, I had started using the word in every other sentence in the discussion. Apart from highlighting unnecessary repetitions, it’s also a very nice tool for identifying key words in your paper: if the right ones don’t come up, you’re probably using to many different terms to describe one phenomenon.
Also important: use a reference manager (I like Zotero – it’s free and integrates with Firefox/Chrome, so you can you use it on any computer without needing to bring the most recent database file with you). Different programs will have different (dis)advantages, so shop around a bit before you decide upon one, there are a lot of options out there.
Another tip is to read your paper aloud. After taking six years of Latin, I’ve really come to love subordinate clauses and the dactylic hexameter. Unfortunately, they don’t work so well for academic writing, and reading sections aloud really helps in locating the overly complicated sentences I can come up when left to myself for too long (enter joke about ablative absolutes). It works even better when you leave your paper for a few days or even weeks, and then come back to it. Instead of reading what you think is there, you’ll suddenly be able to see what it is actually there.
When you finally come round to sending it to your co-authors make sure you give them enough time. Or even better: decide on a revision plan. How many times will each co-author see the paper, and in which order will you send it round? It can be hugely ineffective to send it to everyone at the same time, as you will end up with lots of similar or contradictory comments. Of course this will get more difficult with increasing numbers of co-authors, but it is important to keep at least the PI and supervisors involved.
One last formatting tip: LaTeX. It’s amazing. Like reference managers format your references, LaTeX can format your entire paper. It will take a bit coding (unless you opt for a program like LyX – thank you @JStreetley), but it will be worth it. One downside: the resulting text will be in PDF, making it harder for some reviewers to write comments or make changes.
Naturally, publishing involves a lot of waiting. So as my post is already past the 1,000 word mark, I’ll leave you to wait for part 2 (submitting & final checks, results!, and responding to reviewers’ comments) tomorrow.
April 11, 2012Posted by on
Today, a copy of the thesis of a friend of mine from the Netherlands dropped through my mailbox. If you, like me, are from the Netherlands, that sentence will contain nothing out of the ordinary. People from Britain however, will be in awe at the apparent size of my mailbox, if it can muster up the capacity to have an entire thesis pushed through it.
It was one of the first things my now supervisor told me when I met her to discuss my potential PhD project: the thesis. Did I realise how much work it was going to be? Especially compared to Dutch theses? I’d always secretly dreamt about one day writing a book, so working on a magnum opus on three years of my own research seemed like it might be right up my alley. And anyway, I’d read a couple of (Dutch) theses and they seemed entirely within reach. Even if the British version was to be twice as big (which I was sure was an overestimation, a worst case scenario), it still would be attainable. The world of academia is full of PhDs, how hard could it really be?
As you might guess at this point, I was slightly baffled, to say the least, when I first encountered the doorstop that is a thesis in this part of the world. Now, a year and a half later, when I seem to have accepted what I’ve let myself in for, my friend’s thesis reminded me of what I could have gotten away with, so to say. And it got me thinking.
What should a thesis contain? How big should it be? I’ve heard many stories from PhD hopefuls and PhD completees over the last year and there seems to be a huge variation in theses. Not only between countries (I’ve only seen theses from the UK and the Netherlands), but also between universities, and even between different departments within the same university.
According to Wikipedia, a dissertation or thesis is a document submitted in support of candidature for an academic degree or professional qualification presenting the author’s research and findings. That description allows for many interpretations, which I am sure there are.
The most important difference between the two theses in the picture above is their aim. While the thesis is an aim in its own worth in the world of UK universities, it is merely a tangible summary of the work you’ve accomplished in the Netherlands. Publishing your results is deemed more important, and the thesis functions as a binder of those studies, with a short general introduction and discussion to hold the whole thing together (the Dutch thesis pictured about is actually rather bulky as it contains five papers, rather than the standard three). Whether you’ve passed your examination depends more on your thesis defence and publication record than what you’ve actually put in your little paperback.
Meanwhile, in the UK you can pass your viva and become a doctor of philosophy without even a single publication, as long as you’ve done the works on your thesis. Writing the thesis, almost as much as doing the necessary research, becomes a rite of passage.
I’m sure there are many more varieties out there of the written account of completing a doctoral degree. A whole world of theses. So what do they look like? Do they look like the playful Dutch paperbacks, or are more them in the serious looking UK corner? And what do they contain? Published papers? Extensive accounts of every single piece of research? Every single graph and table ever produced? And maybe the most important question: what should be in them? I hope to hear from you in the comments!