Harnessing smartphone and environmental data to explore the impact of temperature on real-time mental wellbeing

Background Smartphone-based ecological momentary assessments (EMAs) offer a unique opportunity to actively engage and involve the public in scientific research and study the impact of environment on mental wellbeing. Objective tracking of environmental exposures is not easily achieved with commonly used portable devices, however linkage with external datasets can enhance geotagged EMA data with detailed environmental information. Methods We illustrate a novel approach matching geotagged EMA assessments from the Urban Mind study with ambient temperature, air pollution, and green space exposure data. We applied a case-time series design, self-matched analytic methods (distributed lag non-linear models) and a multistep approach to missing data to analyse associations between ambient temperature and momentary wellbeing, calculated using self-reported contemporaneous levels of positive (5 items) and negative affect (five items). Results 7088 assessments from 266 participants over 14 days were successfully matched to ambient environmental data. We found little evidence that daily maximum temperatures are associated with momentary mental wellbeing, nor for effect modification by air pollution or green space exposure. Conclusions This study illustrates the value of this methodology for allowing researchers to answer a broader range of questions in climate change, environment and human health.