A University of California, San Diego, research team hopes to craft ethical best practices for research studies involving participants' personal data, including confidential healthcare information.
The Connected and Open Research Ethics (CORE) project, funded by the university and the Robert Wood Johnson Foundation, will build a Web resource to help Institutional Review Boards (IRBs) and others create ethically sound research using mHealth data collected via mobile apps, devices, sensors and social media platforms, according to an announcement.
"There are an estimated 6,000 IRBs out there, and they all will need to think about how the existing regulations apply to 21st century research tools and methods," Camille Nebeker, assistant professor in UC San Diego School of Medicine's Department of Family Medicine and Public Health, said in the announcement.
Nebeker, who serves as the principal investigator, adds that "IRBs frequently lack the expertise or resources necessary for making informed decisions about studies ... so researchers are engaging independently with them--which means they're often duplicating efforts."
The focus on social responsibility within mHealth research is necessary as tech innovation is happening quickly and no ethical standards have yet to be developed for evaluating study benefits and risks.
"It will also provide consistency, accuracy and convenience for researchers, and an opportunity to share what we've learned," Nebeker said.
Ignorance on privacy protection for data is cited as a big reason mHealth apps are not delivering on expected benefits. Data standards can help eliminate ambiguity and boost integration of data streams, as FierceMobileHealthcare has reported.
In addition, privacy issues relating to sharing and security of personal data could impede robust growth expected in connected healthcare devices and fitness tools. Juniper predicts there will be 13 million users subscribing to mHealth tools within the next five years, and development of standards could actually propel the use and revenue expectation further than expected.
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