Devices and EMA — a Match Made in Heaven

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Childhood Obesity News mentioned a meta-study designed to assess the usefulness of EMA (Ecological Momentary Assessment) in evaluating PA (physical activity). It spoke of eligibility criteria: validity, reliability, objectivity, norms, and standardization. PA can be tracked by gadgets that use mechanical and electronic means to monitor physical activity via many different parameters such as “direct and indirect calorimetry, maximum oxygen consumption/VO2max, doubly-labeled water consumption, or energy expenditure.”

When it comes to behavior, questionnaires depend either on self-reporting that is performed by the patient, or on secondhand narration that originates with professionals or other staff members who relate their direct observations of the patient. In either case the reporting is subjective, because it depends on impressions formed in the mind of an individual, whether that individual is the patient or someone whose job it is to take notes.

For the researcher who wants the most complete and accurate picture of subjects’ behavior, many caveats and nuances are involved. For instance, it would seem straightforward enough to accept that devices track activity most accurately. To relegate this important task to self-reporting seems unwise. But the authors make this counter-intuitive point:

Furthermore, as objective methods do not differentiate between periods of inactivity and periods when the device is not being worn, subjective methods are preferred for measuring sedentary behavior.

For this and other reasons, EMA and wearable devices are seen as a match made in heaven — capable, when they team up, of wringing almost every drop of information from any situation. The idea of using mobile phones to administer EMA protocols has been around for years.

The introduction to a 2010 study set forth the problems:

Children often experience difficulties remembering the intensity and duration of activities after 24 h or more has passed since the behavior… Also, when used alone, accelerometers and pedometers are unable to measure mood during or the context of activities, which may be the important factors that influence behavior.

The report offered exhaustively detailed explanations of every aspect of the study, and was very optimistic about the prospects of overcoming limitations via “technology-enabled real-time self-report assessment strategies.” That optimism has been proven to be justified. A few years later, a meta-study with very strict criteria published its results:

This systematic review examines current use of mobile health technologies in the prevention or treatment of pediatric obesity to catalogue the types of technologies utilized and the impact of mHealth to improve obesity-related outcomes in youth.

The section titled “Usability” is extensive and lavishly footnoted. For instance:

Studies described the best placement and accuracy of mobile device(s) to record PA and dietary intake (22, 34, 35, 37, 47), ways to lessen user burden (43) and which non-intrusive and practical devices (34, 37, 47) will actually be carried and used by participants (15, 22).

The authors go on to speak of incentives, social connections, privacy and sharing issues, competition, user-friendly formats, motivational techniques, language, positive feedback, costs, software and hardware compatibilities, and many other factors that need to be taken into consideration.

Your responses and feedback are welcome!

Source: “Using Ecological Momentary Assessment to Evaluate Current Physical Activity,” NIH.com, 07/14/14
Source: “Investigating children’s physical activity and sedentary behavior using ecological momentary assessment with mobile phones,” Wiley.com, June 2011
Source: “Prevention and treatment of pediatric obesity using mobile and wireless technologies: a systematic review,” NIH.gov, 01/12/15
Photo credit: NYC Media Lab on Visualhunt/CC BY-SA

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