The data collected from mobile mental health apps has promising benefit toward the field of mental health. The risks are usually limited to breach of confidentiality and investigators mitigate those risks by implementing processes to protect access to the data. In studies involving algorithms and personalized medicine, the risks increase. So, how do IRBs determine when risks outweigh the benefits? Read more
PRIM&R is generally very pleased with the breadth and aims of the framework. The framework’s third objective, which emphasizes integrity, accountability, and social responsibility in the conduct of science, demonstrates NIH’s clear commitment to the idea that good science is responsible science. Read more
data-rich networked information technologies are unique in that they represent people’s lives and activities, bridge multiple dimensions of a person’s life, and are often collected, aggregated, exchanged, and mined without them knowing. We call this data “pervasive data,” and the increased scale, scope, speed, and depth of pervasive data available to researchers require that we confront the ethical frameworks that guide such research activities. Read more
