Is it a study or not? Decision tree helps
Researchers requested help
When researchers told the Cornell University IRB in a survey how difficult it was to determine whether a study should be submitted for IRB review, the IRB office created a tool that would make it easier for researchers to make the correct choice.
The tool, an interactive decision tree, was created before the Notice of Proposed Rulemaking (NPRM) on the Common Rule was published in September.
When studies involve minimal risk, the decision on whether a study can be exempt from IRB review or needs expedited review can be unclear, notes Amita Verma, MS, MBA, director of the Office of Research Integrity and Assurance at Cornell University in Ithaca, NY.
“The criterion of no more than minimal risk is somewhat subjective,” Verma says. “So if you’re doing an interview or questionnaire, depending on the nature of the questions or the population or the context, the study could be expedited or exempt, or even need full IRB review.”
The turning point came in 2013 when an IRB satisfaction survey found that researchers were not happy with how minimal risk research was handled, Verma says.
“They expressed frustration that they did not always know which form to fill out and what to expect in terms of the review procedures or timelines,” she explains.
“Often, they did not realize that their research that involved human data or projects was not considered research under the IRB rules,” Verma adds. “So we decided to create two tools that they could use themselves rather than talking to us every time they had questions about their project.”
One of the decision trees helps researchers determine if their project is considered research. The goal is to make it easier for investigators to decide whether their study should be submitted for exempt, expedited, or full IRB review — particularly for types of research that are in a gray area.
For example, oral history often falls into gray areas of human subjects research: “Certain portions of that work does not need IRB review,” Verma says. “If I’m doing oral history and I’m not making generalizable conclusions, then I don’t need an application to the IRB.”
The same can be true with classroom projects, she adds.
“Students are interested in learning statistical techniques and not really figuring out a research question,” Verma explains. “We tell people if the intent is not to publish the data as generalizable knowledge, then you don’t need an IRB application, and we’ve made that clear in the decision tree.”
For instance, one question asks, “Is the project an oral history, ethnographic, or journalistic piece?”
The “yes” answer states, “Does the project involve stories that will or may draw broad conclusions about the population, cultures, and practices — even if no research hypothesis is being tested or validated?”
Also, investigators routinely might turn in an exemption request for studies using secondary data even when this might not be necessary, she adds.
“There are certain types of secondary data that can be exempted, and certain types cannot be,” Verma says. “Those differences are described in the regulations, but they are not always clear to researchers.”
The IRB created a second decision tree specifically to address secondary or existing data, documents, or biological specimens.
The first question on this decision tree is “Are the data/specimens about or from individuals who are or may be still living?”
A “yes” answer takes the researcher down a path requiring an application to the IRB office and written notice of approval or notice of exemption before research can begin.
For convenience, the decision tree is available in a PDF format as a chart and also in an online version in which each answer can lead to a different question. “We wanted to make sure people had multiple ways to make use of the tools and arrive at the right initial determination,” Verma says.
Part of the decision tree’s creation included getting extensive feedback from researchers and IRB members. The feedback period lasted a couple of months and led to many changes to simplify the language, introduce more logical branches, and develop an interactive format, Verma says.
Once the decision tree was reviewed, it stayed in a beta mode for a while.
“We continued to get feedback and to tweak it,” Verma says. “It’s now up on our website, and several of our peer institutions have told us that they intend to borrow it, modify it for their IRB, and publish it.”
The Cornell IRB office is beginning to advertise the tolls and track usage.
The NPRM has also suggested that investigators will be able to use a tool to determine whether a study is exempt from IRB review.
If NPRM is finalized as it was published in September, then the decision trees will need to be revised because some categories of exemptions will change, she says.
“With the NPRM, a lot of research that is currently exempt will be excused from the definition of research, and the exemption criteria will be different than it currently is because certain types of experiments will be exempt from review,” Verma says. “But at least we have a framework, and if all we have to change are some questions, we can do that.”
When researchers told the Cornell University IRB in a survey how difficult it was to determine whether a study should be submitted for IRB review, the IRB office created a tool that would make it easier for researchers to make the correct choice.
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