Abstract
Text data is highly information-rich and accessing this information would greatly benefit applied health researchers and decision makers. Text data can be viewed as both qualitative and quantitative data by the researcher. When both the quality and the quantity of the data can be informative, a rigorous mixed methods approach is necessary to make best use of available analysis techniques to yield high quality inferences. In this analytic essay, a sketch of a suggested mixed methods content analysis method is provided, combining the rich interpretive power of close readings of text data by researchers with the robust quantitative modelling via machine learning. This mixed methods content analysis method appears promising for applied health research.
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