A new study reveals that the true risks of developing long COVID may be exaggerated due to flawed research. Scientists from the U.S., U.K., and Denmark say that the “overly broad case definitions and a striking absence of control groups” in studies of long COVID have led to a distortion of risk.

Their paper, published Monday in BMJ Evidence Based Medicine, states that the consequences of this faulty research has led to “increased societal anxiety and healthcare spending, a failure to diagnose other treatable conditions misdiagnosed as COVID, and diversion of funds and attention from those who truly suffer from chronic conditions secondary to COVID-19.”

According to the New York Post, the study says that none of the working definitions of long COVID provided by health organizations, such as the Centers for Disease Control and Prevention, the World Health Organization, and the U.K. National Institute for Health and Care Excellence, required a “causal link” between the virus and a range of symptoms.

“Ultimately, biomedicine must seek to aid all people who are suffering. In order to do so, the best scientific methods and analysis must be applied,” wrote the study authors. “Inappropriate definitions and flawed methods do not serve those whom medicine seeks to help.”

The researchers pointed out that some of the symptoms COVID-19 infection include shortness of breath following pneumonia and post-ICU syndrome, typical consequences of health conditions present in intensive care that persist after discharge. But the experts said that these symptoms may be caused by many upper respiratory viruses. The researchers suggested that the term “long COVID” be replaced with more specific terms to describe the long-term effects more accurately.

According to the study authors, in the early days of the pandemic, when testing wasn’t as widespread, studies used  a non-representative sample of COVID patients because they included fewer patients with mild symptoms. The researchers said that control groups need to be included in studies of long COVID and should be properly matched in patients based on factors such as age, sex, geography, and socioeconomic status, as well as underlying health conditions and health behaviors, says the Post.

“Improving standards of evidence generation is the ideal method to take long COVID seriously, improve outcomes, and avoid the risks of misdiagnosis and inappropriate treatment,” they wrote. “Future research should include properly matched control groups, sufficient follow-up time after infection and internationally established diagnostic or inclusion and exclusion criteria.”