Researchers warn that the influx of research papers leveraging easily processed public health data may lead to misleading health claims. A recent study in PLoS Biology analyzed over 300 publications using the US National Health and Nutrition Examination Survey data. It found that many papers followed a formulaic template, oversimplifying complex health issues by drawing unsubstantiated connections between single variables and multifactorial conditions. The authors highlight issues such as statistical flaws and data cherry-picking, suggesting a need for systematic evaluations to address these emerging problems.
Imagine you're trying to pass an exam that has a particular pass rate, and you add as many questions as you want. You see which ones you got right, and you remove the ones that you got wrong. That's basically what they're doing.
We have a sudden explosion in publication rates [of papers] that are extremely formulaic that could easily have been generated by large language models.
We need these systematic evaluations to get some way to gauge the extent of the problem.
The papers all seemed to follow a similar template, associating one variable... with a complex disorder... ignoring the fact that these conditions have many contributing factors.
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