Temporal influences in movement and exercise (TIME) study
In TIME study, we developed a mobile and smartwatch application to gather information on factors that might influence physical activity, sedentary behavior, and sleep patterns in young adults. The app gathers information on health behaviors using ecological momentary assessment, smartwatch-based microEMA, and passive sensors on phone and the smartwatch. Note: This is a work in progress with an ongoing data collection. If you are interested in participating, please visit TIMEStudy webpage.
By measuring different variables, microEMA might provide a comprehensive picture of the individual’s behaviors, states, and experiences in close time-intervals. The variables measured include positive and negative affect, social context, demands, and reactive processes influencing behavior change and maintenance. below is the snapshot of 6-day data from one such participant answering microEMA questions for > 6 months.
With microEMA in TIME study, we could observe diverse diurnal rhythms of different behaviors, states, and contexts of interest including positive and negative affect, social context, and intention to engage in healthy behaviors (such as physical activity, less sedentary time, and improved diet).
We also find preliminary evidence of how similar the response patterns to common behavioral constructs are when using microEMA (or uEMA) and the standard phone-based EMA.
Note: More results will be updated as we make progress.
Android, Android Wear, Python, R, Firebase Cloud, Discovery Cluster
Prof. Genevieve Dunton (Univ. Southern California), Shirlene Wang (PhD Student, Univ. Southern California), Qu Tang (PhD Student, Northeastern University), Binod Thapa-Chhetry (PhD Student Northeastern University), Jixin Li (PhD Student, Northeastern University)
This work is supported by national institutes of Health NIH/NCI U01HL146327. The content is solely the responsibility of the authors and does not necessarily represent the official views of the NIH.