Texas A&M Researchers Develop Tool to Help Early Career Veterinarians Evaluate Research Quality

Veterinarians have limited time to read research, yet many spend valuable hours sorting through studies that don’t directly address their clinical questions.

That struggle, shared across the profession, prompted Texas A&M researchers and a global team to develop the Quality and Uncertainty Indicator Tool (QUIT) — a simple, 10‑question triage tool that helps early-career veterinarians quickly decide whether to keep reading or set aside a research paper.

“QUIT gets its name from its purpose: to help readers quit reading a study with too many shortcomings. It can save time that might be spent going down rabbit holes that aren’t the best choices for them,” said Laura Rey, an instructional assistant professor at the Texas A&M College of Veterinary Medicine & Biomedical Sciences (VMBS) and one of the project’s authors. Rey was joined in developing the resource by Molly Crews, also a VMBS instructional assistant professor and a member of the Evidence‑Based Veterinary Medicine Association (EBVMA).  

Rey also helped shape the website and the audio series that accompanies the free tool.

“Our ambition is for every veterinarian to be able to apply the 10 straightforward questions,” said Dr. Sheila Keay, EBVMA president. “There’s no other tool out there like this.”

Simple Questions Spot Concerns in Complex Studies

QUIT is built as a one‑page flowchart that guides readers through 10 plain‑language, yes‑or‑no questions, organized the same way a research paper is laid out — from the abstract and introduction to the methods, results, and discussion.

Website users can click “yes” or “no” on each question, which generates a traffic‑light summary that helps users quickly evaluate a paper — yellow cautions flag areas that may need a closer look, while red stop signs point to more serious concerns.

One of QUIT’s first questions asks whether a study addresses a clinically relevant problem: did the authors measure outcomes that matter in practice — such as pain, appetite, or sleep — or focus only on obscure physiological markers? If not, even a strong study may be set aside.

The tool also helps beginners in assessing a study’s risk of bias in the methods section, which can feel overwhelming, through four guiding questions. One simply asks whether researchers calculated how many samples (animals, people, or data points) they needed before beginning the study.

“People often jump straight to judging the sample size, but calculating it can be brutal for complex studies,” Keay said. “What matters is simply asking, ‘Was it done?’ Most veterinary studies don’t report their sample‑size calculations at all.”

Another question encourages readers to compare what researchers said they would measure with what they actually reported in the results.

“If researchers strongly believe a treatment is effective, they might test three outcomes. If only one shows a benefit and the other two don’t, do they report just the favorable one?” Keay said. “Authors should always explain why certain outcomes weren’t reported. When they don’t, it becomes an important source of potential bias.”

Turning Shared Frustration into Practical Tools

The inspiration for QUIT stemmed from the EBVMA’s Website Committee’s empathy for veterinarians who are scrambling to keep up with increasingly complex literature. Many of them have few systematic reviews to guide their decisions. That need brought together a 17-member volunteer group of EBVMA Board members and invited experts from diverse veterinary backgrounds to design the tool.

Their first instinct was to help readers confirm when a study was trustworthy. But they quickly realized veterinarians would get stuck on questions that required deeper knowledge of bias and study design. So, they flipped the idea: instead of ruling a study in, QUIT would focus on a short set of questions to rule one out. 

“That nuance mattered. You can’t escape the fact that assessing risk of bias still requires skill and training— there’s no shortcut for that,” Keay said. “But if clinicians can quickly set aside papers with obvious problems, they’re already far ahead of the game.”

As the team worked to make the tool accessible for non‑experts, they refined the questions through an estimated 30 rounds of revisions before landing on language that early-career practitioners could answer comfortably.

To make the content easier to absorb without heavy reading, the team also developed the Evidence Anxiety Series, a set of short audio recordings covering six topics.

The team is now testing QUIT as a teaching resource for practitioners and educators.

Next, the team plans to validate the tool by comparing how students and experts trained in risk‑of‑bias assessment use QUIT to evaluate the same studies.

“Ultimately, we want to advocate for research synthesis,” Keay said. “This tool is just a starting point and an interim measure — something to help veterinarians begin talking about uncertainty and how to navigate it.”