μEMA: Microinteraction-based Ecological Momentary Assessment (EMA) Using a Smartwatch.

Area of Science:

• Ubiquitous computing
• Behavioral science
• Human-computer interaction

Background:

• Ecological Momentary Assessment (EMA) collects real-time data on behaviors and states.
• Traditional EMA uses mobile devices, but can suffer from recall bias and lower compliance.
• There is a need for less intrusive and more efficient EMA methods.

Purpose of the Study:

• To introduce and evaluate a microinteraction-based EMA (μEMA) method using smartwatches.
• To compare the compliance, completion rates, and user experience of μEMA with phone-based EMA.
• To assess the potential of μEMA for high-density data collection in ubiquitous computing.

Main Methods:

• A between-subjects pilot study comparing μEMA on smartwatches (n=19) with phone-based EMA (n=14) over 4 weeks.
• Data collection involved prompted questions delivered via mobile devices.
• User compliance, completion rates, and perceived intrusiveness were measured.

Main Results:

• μEMA demonstrated significantly higher compliance, completion rates, and first prompt response rates.
• Despite an eightfold increase in interruptions, μEMA was perceived as less distracting than phone-based EMA.
• Smartwatch-based μEMA allows for a higher temporal density of data collection.

Conclusions:

• μEMA on smartwatches is a viable and effective alternative to traditional phone-based EMA.
• This method enhances data collection efficiency and user adherence.
• μEMA holds promise for advancing research in ubiquitous computing and behavioral studies.