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

2021 ◽  
Author(s):  
Aditya Ponnada ◽  
Shirlene Wang ◽  
Daniel Chu ◽  
Bridgette Do ◽  
Genevieve Dunton ◽  
...  
Keyword(s):  
Data Collection ◽  
Ecological Momentary Assessment ◽  
Self Report ◽  
Time Study ◽  
Longitudinal Data Collection ◽  
Report Data ◽  
Self Report Data ◽  
Ecological Momentary ◽  
Study Participants ◽  
Momentary Assessment

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. CLINICALTRIAL Not applicable

Ecological Momentary Assessment

2014 ◽  
Author(s):  
Saul Shiffman
Keyword(s):  
Substance Use ◽  
Ecological Momentary Assessment ◽  
Self Report ◽  
Use Patterns ◽  
Valid Data ◽  
Report Data ◽  
Self Report Data ◽  
Ecological Momentary ◽  
Ema Data ◽  
Momentary Assessment

Ecological momentary assessment (EMA) is a method for collecting data in real time and in real-world settings in order to avoid retrospective biases, collect ecologically valid data, and study behavioral processes over time. EMA is particularly suited for studying substance use because use is episodic and related to contextual factors like mood, setting, and cues. This chapter addresses the application of EMA to substance use research, describing important elements of EMA design and analysis and illustrating them with examples from substance use research. It discusses and reviews data on methodological issues such as compliance and reactivity and covers considerations in designing EMA studies of substance use. Data on the associations between EMA data on substance use and more traditional self-report data are reviewed. EMA methods reveal substance use patterns not captured by questionnaires or retrospective data and hold promise for substance use research and treatment.

Why Ecological Momentary Assessment Surveys Go Incomplete?: When It Happens and How It Impacts Data

2020 ◽  
Author(s):  
Yu-Hsiang Wu ◽  
Jingjing Xu ◽  
Elizabeth Stangl ◽  
Shareka Pentony ◽  
Dhruv Vyas ◽  
...  
Keyword(s):  
Real Time ◽  
Self Report ◽  
Data Logging ◽  
Time Data ◽  
Real Time Data ◽  
Report Data ◽  
Self Report Data ◽  
Ecological Momentary ◽  
The Impact ◽  
Momentary Assessment

Abstract Background Ecological momentary assessment (EMA) often requires respondents to complete surveys in the moment to report real-time experiences. Because EMA may seem disruptive or intrusive, respondents may not complete surveys as directed in certain circumstances. Purpose This article aims to determine the effect of environmental characteristics on the likelihood of instances where respondents do not complete EMA surveys (referred to as survey incompletion), and to estimate the impact of survey incompletion on EMA self-report data. Research Design An observational study. Study Sample Ten adults hearing aid (HA) users. Data Collection and Analysis Experienced, bilateral HA users were recruited and fit with study HAs. The study HAs were equipped with real-time data loggers, an algorithm that logged the data generated by HAs (e.g., overall sound level, environment classification, and feature status including microphone mode and amount of gain reduction). The study HAs were also connected via Bluetooth to a smartphone app, which collected the real-time data logging data as well as presented the participants with EMA surveys about their listening environments and experiences. The participants were sent out to wear the HAs and complete surveys for 1 week. Real-time data logging was triggered when participants completed surveys and when participants ignored or snoozed surveys. Data logging data were used to estimate the effect of environmental characteristics on the likelihood of survey incompletion, and to predict participants' responses to survey questions in the instances of survey incompletion. Results Across the 10 participants, 715 surveys were completed and survey incompletion occurred 228 times. Mixed effects logistic regression models indicated that survey incompletion was more likely to happen in the environments that were less quiet and contained more speech, noise, and machine sounds, and in the environments wherein directional microphones and noise reduction algorithms were enabled. The results of survey response prediction further indicated that the participants could have reported more challenging environments and more listening difficulty in the instances of survey incompletion. However, the difference in the distribution of survey responses between the observed responses and the combined observed and predicted responses was small. Conclusion The present study indicates that EMA survey incompletion occurs systematically. Although survey incompletion could bias EMA self-report data, the impact is likely to be small.

scholarly journals Trait-like nocturnal sleep behavior identified by combining wearable, phone-use, and self-report data

2021 ◽  
Vol 4 (1) ◽  
Author(s):  
Stijn A. A. Massar ◽  
Xin Yu Chua ◽  
Chun Siong Soon ◽  
Alyssa S. C. Ng ◽  
Ju Lynn Ong ◽  
...  
Keyword(s):  
Self Report ◽  
Sleep Behavior ◽  
Wake Time ◽  
Time Estimates ◽  
Time In Bed ◽  
Sleep Measurement ◽  
Report Data ◽  
Self Report Data ◽  
Ecological Momentary ◽  
Momentary Assessment

AbstractUsing polysomnography over multiple weeks to characterize an individual’s habitual sleep behavior while accurate, is difficult to upscale. As an alternative, we integrated sleep measurements from a consumer sleep-tracker, smartphone-based ecological momentary assessment, and user-phone interactions in 198 participants for 2 months. User retention averaged >80% for all three modalities. Agreement in bed and wake time estimates across modalities was high (rho = 0.81–0.92) and were adrift of one another for an average of 4 min, providing redundant sleep measurement. On the ~23% of nights where discrepancies between modalities exceeded 1 h, k-means clustering revealed three patterns, each consistently expressed within a given individual. The three corresponding groups that emerged differed systematically in age, sleep timing, time in bed, and peri-sleep phone usage. Hence, contrary to being problematic, discrepant data across measurement modalities facilitated the identification of stable interindividual differences in sleep behavior, underscoring its utility to characterizing population sleep and peri-sleep behavior.

Using Personal Cell Phones for Ecological Momentary Assessment

2013 ◽  
Vol 18 (1) ◽  
pp. 3-11 ◽  
Author(s):  
Emmanuel Kuntsche ◽  
Florian Labhart
Keyword(s):  
Data Collection ◽  
Ecological Momentary Assessment ◽  
Communication Systems ◽  
Cell Phones ◽  
Personal Digital Assistants ◽  
Natural Environments ◽  
Mobility Patterns ◽  
Standard Data ◽  
Ecological Momentary ◽  
Momentary Assessment

Ecological Momentary Assessment (EMA) is a way of collecting data in people’s natural environments in real time and has become very popular in social and health sciences. The emergence of personal digital assistants has led to more complex and sophisticated EMA protocols but has also highlighted some important drawbacks. Modern cell phones combine the functionalities of advanced communication systems with those of a handheld computer and offer various additional features to capture and record sound, pictures, locations, and movements. Moreover, most people own a cell phone, are familiar with the different functions, and always carry it with them. This paper describes ways in which cell phones have been used for data collection purposes in the field of social sciences. This includes automated data capture techniques, for example, geolocation for the study of mobility patterns and the use of external sensors for remote health-monitoring research. The paper also describes cell phones as efficient and user-friendly tools for prompt manual data collection, that is, by asking participants to produce or to provide data. This can either be done by means of dedicated applications or by simply using the web browser. We conclude that cell phones offer a variety of advantages and have a great deal of potential for innovative research designs, suggesting they will be among the standard data collection devices for EMA in the coming years.

scholarly journals Combining ecological momentary assessment, wrist-based eating detection, and dietary assessment to characterize dietary lapse: A multi-method study protocol

2021 ◽  
Vol 7 ◽  
pp. 205520762098821
Author(s):  
Stephanie P Goldstein ◽  
Adam Hoover ◽  
E Whitney Evans ◽  
J Graham Thomas
Keyword(s):  
Weight Loss ◽  
Eating Behavior ◽  
Ecological Momentary Assessment ◽  
Structured Interview ◽  
Self Report ◽  
Significant Weight Loss ◽  
Clinically Significant ◽  
Ecological Momentary ◽  
Momentary Assessment ◽  
Lapse Behavior

Objectives Behavioral obesity treatment (BOT) produces clinically significant weight loss and health benefits for many individuals with overweight/obesity. Yet, many individuals in BOT do not achieve clinically significant weight loss and/or experience weight regain. Lapses (i.e., eating that deviates from the BOT prescribed diet) could explain poor outcomes, but the behavior is understudied because it can be difficult to assess. We propose to study lapses using a multi-method approach, which allows us to identify objectively-measured characteristics of lapse behavior (e.g., eating rate, duration), examine the association between lapse and weight change, and estimate nutrition composition of lapse. Method We are recruiting participants (n = 40) with overweight/obesity to enroll in a 24-week BOT. Participants complete biweekly 7-day ecological momentary assessment (EMA) to self-report on eating behavior, including dietary lapses. Participants continuously wear the wrist-worn ActiGraph Link to characterize eating behavior. Participants complete 24-hour dietary recalls via structured interview at 6-week intervals to measure the composition of all food and beverages consumed. Results While data collection for this trial is still ongoing, we present data from three pilot participants who completed EMA and wore the ActiGraph to illustrate the feasibility, benefits, and challenges of this work. Conclusion This protocol will be the first multi-method study of dietary lapses in BOT. Upon completion, this will be one of the largest published studies of passive eating detection and EMA-reported lapse. The integration of EMA and passive sensing to characterize eating provides contextually rich data that will ultimately inform a nuanced understanding of lapse behavior and enable novel interventions. Trial registration: Registered clinical trial NCT03739151; URL: https://clinicaltrials.gov/ct2/show/NCT03739151

Cross-Study, Cross-Method Associations Between Negative Urgency and Internalizing Symptoms

Assessment ◽  
2021 ◽  
pp. 107319112098388
Author(s):  
Kevin M. King ◽  
Max A. Halvorson ◽  
Kevin S. Kuehn ◽  
Madison C. Feil ◽  
Liliana J. Lengua
Keyword(s):  
Depressive Symptoms ◽  
Ecological Momentary Assessment ◽  
Internalizing Symptoms ◽  
Negative Emotions ◽  
Anxiety Symptoms ◽  
Negative Emotionality ◽  
Self Report ◽  
Negative Urgency ◽  
Ecological Momentary ◽  
Momentary Assessment

There is a small body of research that has connected individual differences in negative urgency, the tendency to report rash actions in response to negative emotions, with self-report depressive and anxiety symptoms. Despite the conceptual overlap of negative urgency with negative emotionality, the tendency to experience frequent and intense negative emotions, even fewer studies have examined whether the association of negative urgency with internalizing symptoms hold when controlling for negative emotionality. In the current study, we estimated the bivariate association between negative urgency and internalizing symptoms, tested whether they remained significant after partialling out negative emotionality, and tested whether these effects generalized to real-time experiences of negative emotions. We used data from five independent samples of high school and college students, assessed with global self-report ( n = 1,297) and ecological momentary assessment ( n = 195). Results indicated that in global self-report data, negative urgency was moderately and positively associated with depressive and anxiety symptoms, and the partial association with depressive symptoms (but not anxiety symptoms) controlling for negative emotionality remained significant and moderate in magnitude. This pattern was replicated in ecological momentary assessment data. Negative urgency may convey risk for depressive symptoms, independent of the effects of negative emotionality.

scholarly journals Awake Bruxism – Definition Through Self-report and Through Ecological Momentary Assessment

2021 ◽  
Author(s):  
Alona Emodi-Perlman ◽  
Daniele Manfrendini ◽  
Tamar Shalev-Antsel ◽  
Ilanit Yevdayev ◽  
Pessia Frideman-Rubin ◽  
...  
Keyword(s):  
Ecological Momentary Assessment ◽  
Single Point ◽  
Smartphone Application ◽  
Self Report ◽  
Teeth Grinding ◽  
Teeth Clenching ◽  
The Status ◽  
Ecological Momentary ◽  
Awake Bruxism ◽  
Momentary Assessment

Diagnosis of Awake Bruxism (AB) is problematic due to the inability to use continuous recordings during daytime activities. Recently, a new semi-instrumental approach was suggested, viz., an Ecological Momentary Assessment (EMA), with the use of a smartphone application. With the application subjects are requested to report, at least 12 times per day, the status of their masticatory muscle activity (relaxed muscles, jaw bracing without tooth contact, teeth contact, teeth clenching or teeth grinding). The aim of the present study was to compare the EMA to the assessment of AB as defined by a single point self-report. The most frequent condition recorded by the EMA was relaxed muscles (ca. 60%) and the least frequent one - Teeth grinding (0.6 %). The relaxed muscle condition also showed the lowest coefficient of variance over a 7day period of report. Additionally, only the relaxed muscles and the Jaw bracing conditions presented an acceptable ability to discriminate between AB positive and AB negative subjects, as defined by single point self-report questions. The combination between self-report and EMA may have a potential to promote our ability to diagnose AB. We suggest to re-consider the conditions of Teeth contact and Teeth grinding while using EMA to evaluate AB.

scholarly journals Methodology Used in Ecological Momentary Assessment Studies About Sedentary Behavior in Children, Adolescents, and Adults: Systematic Review Using the Checklist for Reporting Ecological Momentary Assessment Studies (Preprint)

2018 ◽  
Author(s):  
Catiana Leila Possamai Romanzini ◽  
Marcelo Romanzini ◽  
Mariana Biagi Batista ◽  
Cynthia Correa Lopes Barbosa ◽  
Gabriela Blasquez Shigaki ◽  
...  
Keyword(s):  
Sedentary Behavior ◽  
Ecological Momentary Assessment ◽  
Web Of Science ◽  
Review Literature ◽  
Self Report ◽  
Accelerometer Data ◽  
Adolescents And Adults ◽  
Ecological Momentary ◽  
Momentary Assessment

BACKGROUND The use of ecological momentary assessment (EMA) to measure sedentary behavior (SB) in children, adolescents, and adults can increase the understanding of the role of the context of SB in health outcomes. OBJECTIVE The aim of this study was to systematically review literature to describe EMA methodology used in studies on SB in youth and adults, verify how many studies adhere to the Methods aspect of the Checklist for Reporting EMA Studies (CREMAS), and detail measures used to assess SB and this associated context. METHODS A systematic literature review was conducted in the PubMed, Scopus, Web of Science, PsycINFO, Cumulative Index to Nursing and Allied Health Literature (CINAHL), and SPORTDiscus databases, covering the entire period of existence of the databases until January 2018. RESULTS This review presented information about the characteristics and methodology used in 21 articles that utilized EMA to measure SB in youth and adults. There were more studies conducted among youth compared with adults, and studies of youth included more waves and more participants (n=696) than studies with adults (n=97). Most studies (85.7%) adhered to the Methods aspect of the CREMAS. The main criteria used to measure SB in EMA were self-report (81%) with only 19% measuring SB using objective methods (eg, accelerometer). The main equipment to collect objective SB was the ActiGraph, and the cutoff point to define SB was <100 counts/min. Studies most commonly used a 15-min window to compare EMA and accelerometer data. CONCLUSIONS The majority of studies in this review met minimum CREMAS criteria for studies conducted with EMA. Most studies measured SB with EMA self-report (n=17; 81.0%), and a few studies also used objective methods (n=4; 19%). The standardization of the 15-min window criteria to compare EMA and accelerometer data would lead to a comparison between these and new studies. New studies using EMA with mobile phones should be conducted as they can be considered an attractive method for capturing information about the specific context of SB activities of young people and adults in real time or very close to it.

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