824-P: Ecological Momentary Assessment of Diabetes Self-Management: A Systematic Review of Methods and Procedures

Diabetes ◽  
2019 ◽  
Vol 68 (Supplement 1) ◽  
pp. 824-P
Author(s):  
SOOHYUN NAM ◽  
ROBIN WHITTEMORE ◽  
DAVID VLAHOV ◽  
GENEVIEVE DUNTON
Keyword(s):  
Systematic Review ◽  
Ecological Momentary Assessment ◽  
Self Management ◽  
Ecological Momentary ◽  
Momentary Assessment

scholarly journals A Systematic Review of Ecological Momentary Assessment of Diet: Implications and Perspectives for Nutritional Epidemiology

Nutrients ◽  
2019 ◽  
Vol 11 (11) ◽  
pp. 2696 ◽  
Author(s):  
Andrea Maugeri ◽  
Martina Barchitta
Keyword(s):  
Systematic Review ◽  
Ecological Momentary Assessment ◽  
Eating Behaviors ◽  
Dietary Habits ◽  
Contextual Information ◽  
Dietary Assessment ◽  
Nutritional Epidemiology ◽  
Future Research ◽  
Ecological Momentary ◽  
Momentary Assessment

The ecological momentary assessment (EMA) of eating behaviors represents an innovative, detailed and valid approach to capture the complexity of food intake and to overcome limitations of traditional dietary assessment methods. Moreover, EMA studies might generate a large variety of data (e.g., dietary, behavioral, physical, sociopsychological, and contextual information), thereby enabling to examine concurrent exposures and events. Due to the increasing number of studies in this field of research, here we systematically reviewed EMA methods for the assessment of dietary intake in epidemiological studies, and discussed implications and perspectives for future research. Our study summarized several protocols and platforms that may be applied to assess diet in terms of eating frequency, choices, and habits. Nearly 38% of studies used an event-contingent strategy by asking participants to report foods and beverages consumed in real-time at each eating occasion. Instead, approximately 55% of studies used a signal-contingent prompting approach that notified the participants to record their dietary consumption. The remaining studies used a combination of event- and signal-contingent protocols to compare their accuracy or to improve the assessment of dietary data. Although both approaches might improve the accuracy and ecological validity of dietary assessment—also reducing the burden for participants—some limitations should nevertheless be considered. Despite these limitations, our systematic review pointed out that EMA can be applied in various fields of nutritional epidemiology, from the identification of determinants of dietary habits in healthy people to the management of patients with eating or metabolic disorders. However, more efforts should be encouraged to improve the validity and the reliability of EMA and to provide further technological innovations for public health research and interventions.

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

PeerJ ◽  
2020 ◽  
Vol 8 ◽  
pp. e8848 ◽  
Author(s):  
Rafael Zapata-Lamana ◽  
Jaume F. Lalanza ◽  
Josep-Maria Losilla ◽  
Eva Parrado ◽  
Lluis Capdevila
Keyword(s):  
Physical Activity ◽  
Systematic Review ◽  
Real Time ◽  
Ecological Momentary Assessment ◽  
Psychological State ◽  
Future Research ◽  
Lifestyle Behaviors ◽  
Mhealth Technology ◽  
Ecological Momentary ◽  
Momentary Assessment

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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