
“It’s vital that we safeguard research integrity”: study suggests rise in misleading health research articles linked to AI tools
17 July
A sharp rise in potentially misleading health research articles could be due to the use of artificial intelligence tools, a new study co-authored by a Health and Care Research Wales Senior Research Leader suggests.
Professor Reyer Zwiggelaar, from the Department of Computer Science at Aberystwyth University, co-authored the findings published in PLOS Biology with colleague Charlie Harrison.
The team worked with researchers from the University of Surrey and analysed 341 studies published over the past decade that used the US National Health and Nutrition Examination Survey (NHANES), a survey which publishes health, nutrition and behaviour data from people across the United States.
The investigation found that of those 341 studies many followed an almost identical structure: isolating one variable, testing its association with a health condition, and publishing the result, often without accounting for confounding factors or correcting for multiple comparisons.
This approach is easy to automate and increases the risk of false positives, misleading conclusions and failing to meet basic standards of scientific rigour.
The findings also showed that there was a selective use of data from NHANES, known as “data dredging”, with many studies only analysing narrow timeframes or specific subgroups without clear justification.
This practice can lead to cherry-picked results that appear statistically significant but lack real-world relevance.
Researchers also noted that 190 papers had been published based on the dataset in just nine months - compared to just four papers in 2014.
Professor Zwiggelaar said: “We’re seeing a troubling surge in AI-assisted papers that prioritise quantity over quality. These studies often adopt a formulaic and simple methodology and ignore statistical best practices.
“This leads to oversimplified conclusions and increases the risk of false discoveries. Our findings raise serious concerns about the misuse of AI in scientific publishing.”
“Vital that we safeguard research integrity”
The study also notes that AI tools are being used as? “paper mills” – organisations that mass-produce academic papers for profit.
These companies can rapidly generate manuscripts by plugging variables into pre-written templates, often with minimal human oversight or scientific justification.
The authors propose guidelines for researchers, data custodians, publishers, and peer reviewers to improve statistical practices, ensure transparency and guard against unethical publication practices.
Professor Zwiggelaar added: “As research using large datasets and AI tools becomes more common, it is vital that we safeguard research integrity.
“These measures are not just safeguards – they are essential steps toward preserving the credibility and value of scientific discovery in the age of big data.”
Co-author Charlie Harrison said that while “AI can be a powerful tool” it could, when misused, “undermine scientific integrity”.
He said: “This isn’t just an academic issue - when flawed research enters the literature, it can mislead clinicians, confuse policymakers, and ultimately harm public trust in science.”
Professor Zwiggelaar will be chairing the parallel session, What does AI and data mean for research?, at the 2025 Health and Care Research Wales conference, 'Today’s research; tomorrow’s care: celebrating 10 years of impact' - register now.
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