I do wonder about the negative aspect of data streams from ‘worried well’ quantified selfers masking health outcome subtleties when analysing aggregated tracking data. This also leads to a consequent increase in costs for holding the quantified self derived non-essential data on top of an already burgeoning expansion in health data storage and analytical tool usage. And not forgetting a concomitant increase in the data analysis capabilities required of healthcare professionals at all levels. We need a way to pre-filter the irrelevant from the significant – in effect automating much of what a doctor does in normal practice but on a hugely enlarged scale and for a broader set of potential data sources.
All true. Beyond the identification of ‘real’ data and pre-filtering of irrelevance (although should we really be discounting ‘worried well’ searches overall?), for me motivation remains the missing link in the potential of quantifying the self to improve health outcomes. The intrinsic/extrinsic dichotomy between an internalised desire and an externalised means of recording it masks the reason an action is triggered.
Are readings tracked because the user is involved in the recording of data, or because they are changing their health behaviour? Does the action become a supplement to or a surrogate for change?
Finally: this paradigm still considers the tracking of health behaviour within the context of a manual intervention; when the quantification of the data that streams from our bodies is fully automated, this mechanism of motive transmission will be fully subsumed and — ironically — it may be at this point that we truly own it as a consequence of our not being diverted from the change in behaviour it is trying to affect by the act of our measuring it.