Context-Aware Delivery of Ecological Momentary Assessment.

Clicks: 246
ID: 15994
2019
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Abstract
Ecological Momentary Assessment (EMA) is an in-the-moment data collection method which avoids retrospective biases and maximizes ecological validity. A challenge in designing EMA systems is finding a time to ask EMA questions that increases participant engagement and improves the quality of data collection. In this work, we introduce SEP-EMA, a machine learning-based method for providing transition-based context-aware EMA prompt timings. We compare our proposed technique with traditional timebased prompting with for 19 individuals living in smart homes. Results reveal that SEP-EMA increased participant response rate by 7.19% compared to time-based prompting. Our findings suggest that prompting during activity transitions makes the EMA process more usable and effective by increasing EMA response rates and mitigating loss of data due to low response rates.
Reference Key
aminikhanghahi2019contextawareieee Use this key to autocite in the manuscript while using SciMatic Manuscript Manager or Thesis Manager
Authors Aminikhanghahi, Samaneh;Schmitter-Edgecombe, Maureen;Cook, Diane J;
Journal ieee journal of biomedical and health informatics
Year 2019
DOI
10.1109/JBHI.2019.2937116
URL
Keywords Keywords not found

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