Evidence map›Paper›PMID 28298264›Full record

ArticleJournal of medical Internet research2017

Ecological Momentary Assessment in Behavioral Research: Addressing Technological and Human Participant Challenges.

Lora E Burke, Saul Shiffman, Edvin Music, Mindi A Styn, Andrea Kriska, Asim Smailagic, Daniel Siewiorek, Linda J Ewing, Eileen Chasens, Brian French and 4 more

Abstract read
In one paragraph

Article in Journal of medical Internet research, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 159 papers, 7 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
159citing papers in PubMed, 7 pooled it
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

159 citing papers in PubMed, 7 syntheses or guidelines pooled it.

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  14. Day-level shifts in social contexts during youth cannabis use treatment.Journal of consulting and clinical psychology · 2021
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99 more citing papers are in PubMed but not listed here.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

14 authors.

Lora E BurkeDepartment of Health & Community Systems, University of Pittsburgh School of Nursing, Pittsburgh, PA, United States.ORCID 0000-0003-2434-9867
Saul ShiffmanUniversity of Pittsburgh School of Medicine, Pittsburgh, PA, United States.ORCID 0000-0002-9639-490X
Edvin MusicDepartment of Health & Community Systems, University of Pittsburgh School of Nursing, Pittsburgh, PA, United States.ORCID 0000-0002-6248-3015
Mindi A StynDepartment of Health & Community Systems, University of Pittsburgh School of Nursing, Pittsburgh, PA, United States.ORCID 0000-0002-1923-7695
Andrea KriskaDepartment of Epidemiology, University of Pittsburgh Graduate School of Public Health, Pittsburgh, PA, United States.ORCID 0000-0002-3522-0869
Asim SmailagicInstitute for Complex Engineered Systems, Carnegie Mellon University, Pittsburgh, PA, United States.ORCID 0000-0001-8524-997X
Daniel SiewiorekHuman Computer Interaction Institute, Carnegie Mellon University, Pittsburgh, PA, United States.ORCID 0000-0001-6644-3929
Linda J EwingUniversity of Pittsburgh School of Medicine, Pittsburgh, PA, United States.ORCID 0000-0003-2558-4121
Eileen ChasensDepartment of Health & Community Systems, University of Pittsburgh School of Nursing, Pittsburgh, PA, United States.ORCID 0000-0002-7233-1269
Brian FrenchDepartment of Epidemiology and Biostatistics, University of Georgia College of Public Health, Athens, GA, United States.ORCID 0000-0002-6173-5321
Juliet MancinoUniversity of Pittsburgh School of Medicine, Pittsburgh, PA, United States.ORCID 0000-0002-7617-8521
Dara MendezDepartment of Epidemiology, University of Pittsburgh Graduate School of Public Health, Pittsburgh, PA, United States.ORCID 0000-0003-3999-1991
Patrick StrolloUniversity of Pittsburgh School of Medicine, Pittsburgh, PA, United States.ORCID 0000-0002-2065-9641
Stephen L RathbunDepartment of Epidemiology and Biostatistics, University of Georgia College of Public Health, Athens, GA, United States.ORCID 0000-0002-4704-5316

Funding

Real Time Data Collection with Adaptive Sampling and Innovative TechnologiesR01HL107370 · NHLBI · UNIVERSITY OF PITTSBURGH AT PITTSBURGH · PI BURKE, LORA EMILIE, RATHBUN, STEPHEN L · 2011 to 2015
$3.0M
NHLBI NIH HHS R01 HL107370
6 · The paper itself

Abstract

backgroundEcological momentary assessment (EMA) assesses individuals' current experiences, behaviors, and moods as they occur in real time and in their natural environment. EMA studies, particularly those of longer duration, are complex and require an infrastructure to support the data flow and monitoring of EMA completion.

objectiveOur objective is to provide a practical guide to developing and implementing an EMA study, with a focus on the methods and logistics of conducting such a study.

methodsThe EMPOWER study was a 12-month study that used EMA to examine the triggers of lapses and relapse following intentional weight loss. We report on several studies that informed the implementation of the EMPOWER study: (1) a series of pilot studies, (2) the EMPOWER study's infrastructure, (3) training of study participants in use of smartphones and the EMA protocol and, (4) strategies used to enhance adherence to completing EMA surveys.

resultsThe study enrolled 151 adults and had 87.4% (132/151) retention rate at 12 months. Our learning experiences in the development of the infrastructure to support EMA assessments for the 12-month study spanned several topic areas. Included were the optimal frequency of EMA prompts to maximize data collection without overburdening participants; the timing and scheduling of EMA prompts; technological lessons to support a longitudinal study, such as proper communication between the Android smartphone, the Web server, and the database server; and use of a phone that provided access to the system's functionality for EMA data collection to avoid loss of data and minimize the impact of loss of network connectivity. These were especially important in a 1-year study with participants who might travel. It also protected the data collection from any server-side failure. Regular monitoring of participants' response to EMA prompts was critical, so we built in incentives to enhance completion of EMA surveys. During the first 6 months of the 12-month study interval, adherence to completing EMA surveys was high, with 88.3% (66,978/75,888) completion of random assessments and around 90% (23,411/25,929 and 23,343/26,010) completion of time-contingent assessments, despite the duration of EMA data collection and challenges with implementation.

conclusionsThis work informed us of the necessary preliminary steps to plan and prepare a longitudinal study using smartphone technology and the critical elements to ensure participant engagement in the potentially burdensome protocol, which spanned 12 months. While this was a technology-supported and -programmed study, it required close oversight to ensure all elements were functioning correctly, particularly once human participants became involved.

Indexed as

Ecological Momentary AssessmentAdultBehavioral ResearchFemaleHumansMaleSmartphoneWeight Reduction Programsadherenceeating behaviorecological momentary assessmentobesityrelapsesmartphone

Identifiers

PMID28298264
PMCPMC5371716

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.