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      mHealth technology for ecological momentary assessment in physical activity research: a systematic review

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          Abstract

          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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          Most cited references99

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          Limits to the measurement of habitual physical activity by questionnaires.

          Despite extensive use over 40 years, physical activity questionnaires still show limited reliability and validity. Measurements have value in indicating conditions where an increase in physical activity would be beneficial and in monitoring changes in population activity. However, attempts at detailed interpretation in terms of exercise dosage and the extent of resulting health benefits seem premature. Such usage may become possible through the development of standardised instruments that will record the low intensity activities typical of sedentary societies, and will ascribe consistent biological meaning to terms such as light, moderate, and heavy exercise.
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            Ecological Momentary Assessment (Ema) in Behavioral Medicine

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              Exercise and mental health.

              There is a growing body of literature that recognizes the positive effects of exercise on mood states such as anxiety, stress and depression, through physiological and biochemical mechanisms, including endorphins, mitochondria, mammalian target of rapamycin, neurotransmitters and the hypothalamic-pituitary-adrenal axis, and via the thermogenic hypothesis. In addition, psychological mechanisms influence the effects of exercise on mood states, as suggested by both the distraction hypothesis and the self-efficacy hypothesis. Exercise has also been shown to reduce inflammation via several different processes (inflammation, cytokines, toll-like receptors, adipose tissue and via the vagal tone), which can contribute to better health outcomes in people suffering from mood disorders.
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                Author and article information

                Contributors
                Journal
                PeerJ
                PeerJ
                PeerJ
                PeerJ
                PeerJ
                PeerJ Inc. (San Diego, USA )
                2167-8359
                26 March 2020
                2020
                : 8
                : e8848
                Affiliations
                [1 ]Escuela de Educación, Universidad de Concepción , Los Ángeles, Chile
                [2 ]Department of Basic Psychology, Universitat Autónoma de Barcelona , Bellaterra, Spain
                [3 ]Department of Psychobiology and Methodology of Health Science, Universitat Autónoma de Barcelona , Bellaterra, Spain
                [4 ]Sport Research Institute UAB, Universitat Autònoma de Barcelona , Bellaterra, Spain
                Article
                8848
                10.7717/peerj.8848
                7103204
                32257648
                8dd423b5-7308-46a3-a41a-bbdd7e4b33cf
                © 2020 Zapata-Lamana et al.

                This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, reproduction and adaptation in any medium and for any purpose provided that it is properly attributed. For attribution, the original author(s), title, publication source (PeerJ) and either DOI or URL of the article must be cited.

                History
                : 16 October 2019
                : 3 March 2020
                Funding
                Funded by: Spanish Government
                Award ID: DEP2015-68538-C2-1-R and PGC2018-100675-B-I00
                Funded by: Universidad de Concepción (Chile)
                This study was supported by the grants DEP2015-68538-C2-1-R and PGC2018-100675-B-I00 from The Spanish Government. Rafael Zapata-Lamana is supported by a scholarship from the Universidad de Concepción (Chile). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
                Categories
                Kinesiology
                Psychiatry and Psychology
                Human-Computer Interaction

                mhealth,ema,ecological momentary assessment,physical activity,health,lifestyle,smartphones,mobile devices,systematic review,ehealth

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