However, detailed self-monitoring is labor-intensive and compliance levels by
users of such forms are low [5].
The rapidly developing field of ecological momentary
assessment (EMA) can help reduce the challenges of selfmonitoring.
EMA is a method increasingly used by behavioral
researchers for the collection of self-report data
on people’s experiences as they go about their everyday
activities [6, 7]. Frequent instantaneous reports of behavioral
phenomena have been shown to minimize recall bias
and more faithfully represent the true natural history of
transitory states [8]. In addition, distributing smaller
amounts of data collection throughout the day instead of
larger amounts at rigid times or locations may decrease
participant burden. Electronic forms of EMA have also
shown higher compliance than paper diaries [9].
The promise of mobile technologies in health interventions
is represented in part by Ecological Momentary
Intervention (EMI) [10]. EMI borrows implicitly from
EMA, but also explicitly includes intervention as a focus.
EMI is “just in time” prompting for a behavior change
based upon a set of predefined conditions. For example, a
computer can be programmed to monitor for changes in
everyday activities. Based on the values measured, it can
also proactively present tailored information that may lead
to health-related behavior changes [11].
The ubiquity of mobile phones combined with their
increasing computational and network communication
capabilities present an obvious opportunity for EMI applications.
First, the always-carried and always-on nature of
mobile phones means that users can self-monitor in situ at
their convenience throughout the day. Second, the increased
processing power of mobile phones allows for more
sophisticated assessment and intervention applications.
Third, network capabilities allow for data to be remotely
processed on a server. These characteristics of mobile
phones satisfy the requirements of EMI.
As the technology for context-aware applications continues
to be developed, pilot studies are needed to lay the
groundwork for assessing usability and feasibility. For these
reasons, the usability and feasibility of mobile phones as a
tool for monitoring eating and exercise behavior in real
time were investigated. Real-time data capture allows for
real-time data analysis and interventions—the basis of EMI.
Through four phases, the researchers iteratively designed,
developed, and evaluated Patient-Centered Assessment &
Counseling Mobile Energy Balance (PmEB). This mobile
phone application calculates real-time caloric balance as
users enter their diet (caloric consumption) and physical
activity (caloric expenditure) throughout the day. The first
three phases focused on employing human-computer interaction
methods to guide the evolution of the mobile phone
prototype. The fourth phase, a feasibility study with 15