Understanding the Complexity of Health and Wellness Longitudinal Data

The human brain is the most complex thing in the known universe and by extension health data is extremely complicated. Conventional statistics are often based around a reductionistic scientific philosophy that will inherently struggle to capture this complexity. In contrast this talk will pull from my peer-reviewed studies on using repeated measures data and strategies from the non-linear dynamical systems academic tradition to embrace and understand the complexity of health data. The punchline is that you need to consider both long-term trends as well as short term fluctuations in longitudinal data. This will be illustrated through the 8 Bit Cortex app my start up has developed, which is using health and wellness data at both the individual and group level to evaluate burnout risk. This talk will be targeted to an intermediate level of expertise (assume some knowledge of statistics and data science) and while this approach can generalize to many types of data, it will focus on health data.