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Accepted for/Published in: JMIR Formative Research

Date Submitted: Aug 9, 2021
Date Accepted: Dec 17, 2021

The final, peer-reviewed published version of this preprint can be found here:

Intensive Longitudinal Data Collection Using Microinteraction Ecological Momentary Assessment: Pilot and Preliminary Results

Ponnada A, Wang S, Chu D, Do B, Dunton G, Intille S

Intensive Longitudinal Data Collection Using Microinteraction Ecological Momentary Assessment: Pilot and Preliminary Results

JMIR Form Res 2022;6(2):e32772

DOI: 10.2196/32772

PMID: 35138253

PMCID: 8867293

Intensive Longitudinal Data Collection using Microinteraction Ecological Momentary Assessment (μEMA): Pilot and Preliminary Results

  • Aditya Ponnada; 
  • Shirlene Wang; 
  • Daniel Chu; 
  • Bridgette Do; 
  • Genevieve Dunton; 
  • Stephen Intille

ABSTRACT

Background:

Ecological momentary assessment (EMA) uses mobile technology to enable in-situ self-report data collection on behaviors and states. In a typical EMA study, participants are prompted several times a day to answer sets of multiple-choice questions. While the repeated nature of EMA reduces recall bias, it may induce participation burden. There is a need to explore complementary approaches to collecting in-situ self-report data that are less burdensome, yet provide comprehensive information on an individual’s behaviors and states. One new approach, microinteraction ecological momentary assessment (μEMA), restricts EMA items to single, cognitively simple questions answered on a smartwatch with single-tap answers; i.e., EMA is limited to only those answerable with a quick, glanceable microinteraction. However, the viability of using μEMA to capture behaviors and states in a large-scale intensive longitudinal data collection (ILD) study has not yet been demonstrated.

Objective:

This paper describes 1) the μEMA protocol currently used in the Temporal Influences on Movement and Exercise (TIME) Study conducted with young adults, 2) the interface of the μEMA app to gather self-report responses on a smartwatch, 3) qualitative feedback from participants following a pilot study of the μEMA app, 4) changes made to the main TIME study μEMA protocol and app based on the pilot feedback, and 5) preliminary μEMA results from a subset of active participants in the TIME Study.

Methods:

The TIME Study involves data collection on behaviors and states using passive sensors on smartwatches and smartphones along with intensive phone-based EMA, four-day hourly EMA bursts every two weeks among 250 people. Every day, participants also answer a nightly EMA survey. On non-EMA burst days, participants answer μEMA questions on the smartwatch assessing momentary states such as physical activity, sedentary behavior, and affect. At the end of the study, participants take part in a semi-structured interview to describe their experience with EMA and μEMA. A pilot study was used to test and refine the μEMA protocol for the main study.

Results:

Changes made to the μEMA study protocol based on pilot feedback included adjustments to the single-question selection method and watch vibrotactile prompting. We also added sensor-triggered questions for physical activity and sedentary behavior. As of June 2021, 81 participants completed at least six months of data collection in the main study. For 662,397 μEMA questions delivered, the compliance rate was 67.61% (SD = 24.36) and completion rate was 79.03% (SD = 22.19).

Conclusions:

This study provides opportunities to explore a novel approach for collecting temporally dense intensive longitudinal self-report data in a sustainable manner. Data suggest that μEMA may be valuable for understanding behaviors and states at the individual level, thus possibly supporting future longitudinal interventions that require within-day, temporally dense self-report in the real world. Clinical Trial: Not applicable


 Citation

Please cite as:

Ponnada A, Wang S, Chu D, Do B, Dunton G, Intille S

Intensive Longitudinal Data Collection Using Microinteraction Ecological Momentary Assessment: Pilot and Preliminary Results

JMIR Form Res 2022;6(2):e32772

DOI: 10.2196/32772

PMID: 35138253

PMCID: 8867293

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