July 21, 2012

Best-practice guidelines for science reporting

These are from the UK Science Media Centre, part of its submission to the Leveson Inquiry

  • State the source of the story – e.g. interview, conference, journal article, a survey from a charity or trade body, etc. – ideally with enough information for readers to look it up or a web link.
  •  Specify the size and nature of the study – e.g. who/what were the subjects, how long did it last, what was tested or was it an observation? If space, mention the major limitations.
  • When reporting a link between two things, indicate whether or not there is evidence that one causes the other.
  • Give a sense of the stage of the research – e.g. cells in a laboratory or trials in humans – and a realistic time-frame for any new treatment or technology.
  •  On health risks, include the absolute risk whenever it is available in the press release or the research paper – i.e. if ’cupcakes double cancer risk’ state the outright risk of that cancer, with and without cupcakes.
  •  Especially on a story with public health implications, try to frame a new finding in the context of other evidence – e.g. does it reinforce or conflict with previous studies? If it attracts serious scientific concerns, they should not be ignored.
  •  If space, quote both the researchers themselves and external sources with appropriate expertise. Be wary of scientists and press releases over-claiming for studies.
  • Distinguish between findings and interpretation or extrapolation; don’t suggest health advice if none has been offered.
  •  Remember patients: don’t call something a ’cure’ that is not a cure.
  • Headlines should not mislead the reader about a story’s contents and quotation marks should not be used to dress up overstatement

This blog would be a lot less interesting (except to rugby fans) if the media followed these guidelines.  I think the second-last item is the only one that hasn’t been the basis for one or more posts.     (via)

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Thomas Lumley (@tslumley) is Professor of Biostatistics at the University of Auckland. His research interests include semiparametric models, survey sampling, statistical computing, foundations of statistics, and whatever methodological problems his medical collaborators come up with. He also blogs at Biased and Inefficient See all posts by Thomas Lumley »