In our research in digital phenotyping, I’ve long advocated for the importance of collecting raw data from smartphones and wearables instead of using pre-packaged proprietary data summaries available through Google’s and Apple’s software development kits (SDKs). There are many reasons for this. First, it is important to use the same algorithms for users of both Android and iOS phones. Second, these algorithms have often not been validated, which leads to challenges in reproducibility. Third, these algorithms change over time, which can invalidate even within-person comparisons (let alone comparisons across persons) over time. The topic of this post deals with this last issue. One would assume that downloading data for the same period twice should return the same data. After all, nothing about the behavior has changed for the historical data, it just happened to be downloaded at two different points in time. In the experiment below, we discover that when downloading data for a specific time period at two different points in time, we get strikingly different data sets.
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