Every journalist covering medical and other types of scientific research should read this thought-provoking open-access article recently published in PNAS: “Crisis or self-correction: Rethinking media narrative about the well-being of science.”
This piece by Kathleen Hall Jamieson of the Annenberg School for Communication at the University of Pennsylvania is one of the best articles I’ve read about how to think about the big picture in our coverage of medicine and science and the public perception of media narratives about science. It’s one of those rare, important writings whose entire purpose is to examine the nuance that’s missing – yet essential – in the majority of science and medicine coverage. Continue reading
Surveillance is the process or system for tracking cases of risk factors, medical conditions, disease cases, adverse events, etc.
It is often used to track incidence of a disease, such as keeping up with where measles cases are during an outbreak or where remaining polio cases are in the attempt to eradication the disease. It’s also used to track prevalence, such as the total number of women living with breast cancer, or adverse events, such as tracking hospital-acquired infections or possible side effects from vaccines or drugs that the FDA has already licensed. Continue reading
The second season of 13 Reasons Why, a controversial teen drama TV show, premiered May 18 on Netflix. Throughout its first season, loosely based on the award-winning book by Jay Asher, the show dealt in great detail with the suicide of a high school student, including its precursors and its aftermath. Now, the show has already drawn criticism for a rape scene this season. Continue reading
We are well into the age of Big Data, in which researchers may use databases or another dataset with data from tens of thousands or even millions of individuals.
These massive datasets have many advantages, such as the ability to narrow down a specific population through inclusion or exclusion criteria, having adequate participation to achieve statistical power, being able to analyze and compare subgroups based on demographics or other differences and the ability to get diverse, representative populations. Continue reading
Looking for p-hacking or other statistical red flags is challenging, particularly for journalists who don’t have training in statistics or medical research design or access to the complete data sets a researcher may be using. But that doesn’t mean you can’t learn a few tips on how to scrutinize studies that analyze huge datasets. In fact, three statistical editors of JAMA Surgery — Amy H. Kaji, M.D., Ph.D.; Alfred W. Rademaker, Ph.D.; and Terry Hyslop, Ph.D. — recently penned an editorial aimed at researchers that journalists can benefit from as well. Continue reading