mHealth technology for ecological momentary assessment in physical activity research: a systematic review
Open accessAbstract
Objective: To systematically review the publications on ecological momentary assessment (EMA) relating to physical activity (PA) behavior in order to classify the methodologies, and to identify the main mHealth technology-based tools and procedures that have been applied during the first 10 years since the emergence of smartphones. As a result of this review, we want to ask if there is enough evidence to propose the use of the term “mEMA” (mobile-based EMA). Design: A systematic review according to PRISMA Statement (PROSPERO registration: CRD42018088136). Method: Four databases (PsycINFO, CINALH, Medline and Web of Science Core Collection) were searched electronically from 2008 to February 2018. Results: A total of 76 studies from 297 potential articles on the use of EMA and PA were included in this review. It was found that 71% of studies specifically used “EMA” for assessing PA behaviors but the rest used other terminology that also adjusted to the inclusion criteria. Just over half (51.3%) of studies (39) used mHealth technology, mainly smartphones, for collecting EMA data. The majority (79.5%) of these studies (31 out of 39) were published during the last 4 years. On the other hand, 58.8% of studies that only used paper-and-pencil were published during the first 3 years of the 10-year period analyzed. An accelerometer was the main built-in sensor used for collecting PA behavior by means of mHealth (69%). Most of the studies were carried out on young-adult samples, with only three studies in older adults. Women were included in 60% of studies, and healthy people in 82%. The studies lasted between 1 and 7 days in 57.9%, and between three and seven assessments per day were carried out in 37%. The most popular topics evaluated together with PA were psychological state and social and environmental context. Conclusions: We have classified the EMA methodologies used for assessing PA behaviors. A total of 71% of studies used the term “EMA” and 51.3% used mHealth technology. Accelerometers have been the main built-in sensor used for collecting PA. The change of trend in the use of tools for EMA in PA coincides with the technological advances of the last decade due to the emergence of smartphones and mHealth technology. There is enough evidence to use the term mEMA when mHealth technology is being used for monitoring real-time lifestyle behaviors in natural situations. We define mEMA as the use of mobile computing and communication technologies for the EMA of health and lifestyle behaviors. It is clear that the use of mHealth is increasing, but there is still a lot to be gained from taking advantage of all the capabilities of this technology in order to apply EMA to PA behavior. Thus, mEMA methodology can help in the monitoring of healthy lifestyles under both subjective and objective perspectives. The tendency for future research should be the automatic recognition of the PA of the user without interrupting their behavior. The ecological information could be completed with voice messages, image captures or brief text selections on the touch screen made in real time, all managed through smartphone apps. This methodology could be extended when EMA combined with mHealth are used to evaluate other lifestyle behaviors.
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Wearables can measure long-term data in the naturalistic environment of study participants, allowing for ecological momentary assessments.
“Wearables can measure long-term data in the naturalistic environment of study participants, allowing for ecologic momentary assessments [10,11].”
From The impact of wearable technologies in health research: scoping review (2022) · cites this paper as [11]
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- Zapata-Lamana R Lalanza JF Losilla JM Capdevila L Methodology of ecological momentary assessment (EMA) in physical activity research: a systematic review PROSPERO 2018 CRD42018088136 https://www.crd.york.ac.uk/prospero/display_record.php?ID=CRD42018088136 PMC7103204 32257648
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“31 Ongoing developments in PA assessment research since the last 2011 Compendium update include additional focus on multiple behaviors (i.e., PA and sedentary behaviors) 32,33 using self-report, 34 mHealth technologies, 35 and device-based measures, such as accelerometers.”
BackgroundThe impact of wearable technologies in health research: scoping review
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Free Technical Solutions for Ecological Momentary Assessments - Searching GitHub plus Google
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- Authors
- Zapata-Lamana, R., Lalanza, J. F., Losilla, J.-M., Parrado, E., & Capdevila, L.
- Affiliations
- Escuela de Educación, Universidad de Concepción, Los Ángeles, Chile
- Universitat Autònoma de Barcelona (ES)
- Department of Psychobiology and Methodology of Health Science, Universitat Autónoma de Barcelona, Bellaterra, Spain
- Department of Basic Psychology, Universitat Autónoma de Barcelona, Bellaterra, Spain
- Venue
- PeerJ
- Publisher
- PeerJ
- Published
- 2020-03-26
- Volume
- 8
- Pages
- e8848
- ISSN
- 2167-8359 (ISSN-L)
- PMC
- PMC7103204
- OpenAlex
- W3013987354
- Cited by
- 61
- References
- 123
- Citations by year
- 2026: 7 · 2025: 11 · 2024: 17 · 2023: 10 · 2022: 8 · 2021: 7 · 2018: 1
- FWCI
- 1.20
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Locations
- PeerJ (publishedVersion, cc-by)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- Dipòsit Digital de Documents de la UAB (Universitat Autònoma de Barcelona) (submittedVersion, cc-by)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
- NORA - Norwegian Open Research Archives (submittedVersion, other-oa)
- Funders
- Spanish Government (DEP2015-68538-C2-1-R and PGC2018-100675-B-I00)
- Universidad de Concepción
- Topics
- Health Sciences › Health Professions › General Health Professions › Mobile Health and mHealth Applications
- Health Sciences › Medicine › Physiology › Physical Activity and Health
- Social Sciences › Psychology › Experimental and Cognitive Psychology › Mental Health Research Topics
- Keywords
- ecological momentary assessment, physical activity, smartphones, accelerometer, embedded sensors, psychological state, young adults, older adults, healthy adults
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
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