It would be amazing to use this data in a study. I&#x27;m all for observing and analyzing unsuspecting people - that&#x27;s the only reasonable way you can avoid the effect of people changing their behavior when they know they&#x27;re being studied. I think that the biggest issue here is not with scaling, or even with finding a reliable subset of the data - it&#x27;s with fitting such experiment into formal and ethical framework of science. Some of the issues I see:<p>- Scientists generally <i>design</i> their studies, trying to amplify the visibility of studied phenomenon while filtering out as much noise as possible. Here you&#x27;d have an experiment that&#x27;s not designed. My guess is that it&#x27;s something most researchers are not used to nowadays.<p>- It may be hard to reuse this technique. The first team to run this study may have some results that we could trust, but as soon as they publish and everyone knows that apps are now used to study people, users will change behavior.<p>- It creates a whole <i>battlefield</i> of interest. It suddenly is in the interest of scientists and their research institutions to promote commercial apps. It&#x27;s also in the interest of the app vendors to enter into agreements with researchers, because getting an interesting result will become a huge marketing opportunity. And so there will be pressure to find &quot;proper&quot; results.<p>&gt; <i>I&#x27;ve also ran some unscientific analysis that confirmed my biases. Major one: when I consume less calories then I burn my weight goes down, and vice versa. ;-)</i><p>I think you should publish :).