Ecological Momentary Assessment (EMA) via smartphone app could be used as a self-report tool to assess multiple sedentary behaviors among adolescents in their daily lives.
Using a Smartphone Application to Capture Sedentary Behavior and Multitasking among Adolescents
1. Yue Liao, MPH
Eldin Dzubur, MS
Genevieve Dunton, PhD, MPH
University of Southern California
Institute for Health Promotion & Disease Prevention Research
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Multiple Behaviors and Multitasking
Most studies examined effects of one sedentary behavior
or sitting time in general
Little is known about whether multiple sedentary
behaviors might pose a greater health risk
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Measurement of Sedentary Behavior
Hardy et al., 2013; http://www.acaorn.org.au/streams/activity/method-selection/sedentary.php
Objective Methods Subjective Methods
Observation
Activity Monitor
Screen Monitoring Device
SenseCam
Questionnaire
• Proxy/self-report
• Usual/recall
Time Use Diary
Ecological Momentary
Assessment (EMA)
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Aims of Current Study
• To demonstrate the use of EMA via a smartphone app
to capture multiple behaviors in adolescents’
daily lives
• To describe the prevalence and type of multiple
behaviors in a sample of adolescents
• To preliminarily test whether the engagement of
multiple behaviors differed by demographic
factors (i.e., age, gender, ethnicity, and weight
category)
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Data Source
• The current study analyzed signal-contingent (i.e.,
random) EMA survey prompts from Mobile TEEN
An app that designed for Android-based mobile
phone
• EMA survey was prompted up to 3 times per day on
weekdays (3 pm – 9 pm) and 7 times per day on
weekend days (7 am – 9 pm) for 14 consecutive
days
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Analytical Plan
• A selection of “sitting” or “lying down” was defined
as a sedentary behavior for that activity
• A selection of more than one activity occurring
during the same 30-min period indicates
engagement of multiple behaviors
• Analysis only included prompts with at least one
self-reported sedentary activity
• Multilevel logistic regression was conducted to test
whether the probability of multiple behaviors
(yes/no) differs by demographic variables
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Results
• On average, each participant answered 67 random
survey prompts across the 14 days
ranged 20 – 143 answered prompts each
• 90% of these prompts had at least one sedentary
activity reported
ranged 68% - 100%
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Multiple Behaviors and Multitasking
• Of all the sedentary prompts, 85% reported one
activity and 15% reported multiple activities
• Of all the multiple activity prompts
75% reported engaging in 2 activities during the
past 30 minutes
22% reported engaging in 3 activities
3% reported engaging in 4 or more activities
• The average combined length of all activity during
the past 30 minutes was 59.3 minutes for
multiple activity prompts, implying some degree
of multitasking
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Multiple Behaviors – Using Technology
• Of all the sedentary prompts where using technology
was chosen, 73% reported one activity and 27%
reported multiple activities
• Of these multiple activity prompts reporting
technology use:
69% reported engaging in 2 activities
34% with reading/doing homework
29% with eating/drinking
14% with hanging out
27% reported engaging in 3 activities
26% with eating/drinking and hanging out
17% with hanging out and reading/doing homework
14% with eating/drinking and reading/doing homework
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Multiple Behaviors – Using Technology by Gender
0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
100%
Female Male
PredictedMarginalProbability
Using Technology and Other Behaviors
Using Technology Only
Adj. Wald F = 4.64, p = .04
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Multiple Behaviors – Using Technology by Weight Category
0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
100%
Normal Weight Overweight Obese
PredictedMarginalProbability
Using Technology and Other Behaviors
Using Technology Only
Adj. Wald F = 2.66, p = .08
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Discussion
• EMA via smartphone app could be used as a self-
report tool to assess multiple sedentary
behaviors among adolescents in their daily lives
• Future research could explore the predictors and
health outcomes of multiple sedentary behaviors
• Protocol design needs to consider keeping the
balance between capturing multiple behaviors/
multitasking and participant burden
American Academy of Pediatrics recommends that children and adolescents do not exceed 2 hours a day in screen time.
However, according to a recent nationwide study, an average U.S. adolescent spent 2.4 hours/day in TV viewing, 1.5 hours/day in computer use, and 1.3 hours/day in video gaming.
Sedentary behavior in children and adolescents has been recognized as a risk factor for a number of adverse health outcomes. Active Living Research recently has put together a nice infographic that summarizes some of these evidence based on their review of the literature. For example, children who watch TV for more than 3 hours a day have a 65% high chance of being obese than children who watch for less than 1 hour. In addiction, total screen time in adolescents is linked with higher risk of adult obesity.
Currently, most studies that examined the effects of sedentary behavior on health outcomes could not differentiate whether the sedentary time was spent in one behavior or multiple behaviors.
However, it is possible that adolescents might engage in multiple behaviors at one time, especially given the increasing availability of technology gadgets in adolescents’ daily lives.
Therefore, it will be important to investigate whether multiple sedentary behaviors might pose a greater health risk than single sedentary behaviors. While previous research on this topic is limited, there is some evidence of increased energy intake due to unhealthy food choices during TV watching.
If multiple sedentary behaviors is the research topic of interest, it is necessary to take a step back and see how sedentary behavior is being measured by researchers.
The Australian Child and Adolescent Obesity Research Networkhas put together a nice review of some common measurement used by researchers to capture sedentary behavior in adolescents. Generally, these measurements can be either objective methods or subjective methods.
So if the goal is to capture multiple behaviors, it is obvious that some objective methods would not work since they cannot distinguish different types of behaviors at one time; and other methods might be very time consuming and labor intensive.
So subjective methods in this case might be a better choice as a tool to measure multiple behaviors. Then researchers could choose from the subjective methods, depending whether the researcher is interested in assessing usual behaviors, past behaviors, or current behaviors that occur in adolescents daily lives.
http://www.sciencedirect.com/science/article/pii/S1440244012001089 (ACAORN)
Time use diary: Typically 7 days to capture habitual behaviour.
Upon receiving an auditory EMA prompt (a pleasant but loud 4s chime), participants were instructed to stop their current activity and complete a short electronic survey question sequence using the touch screen of the smartphone. This process usually requires about 2-3 min. If an EMA prompt occurred during an incompatible activity (e.g., sleeping or bathing), participants were instructed to ignore it. If no entry was made, the app emitted up to two reminder prompts at 3-min intervals.
3 weekdays 7 weekends, during non-school waking hours
22% overweight, 18% obese
Of at least one sedentary activity reported prompts.
Average was 36.9 minutes for single activity
27% (n=262)
69% (n=180), 27% (n=72),
Female: 34%, male: 21%
Normal weight: 25%, overweight: 12%, obese: 51%
Overweight vs. obese, p = .02
Targeting TV time… harder to intervene than just simply turn off the TV
doing so much at once, can’t say just stop doing one thing
Results from this study also show that adolescents are doing multiple things at one time. Interventions might need to consider this factor when trying to reduce sedentary time in adolescent.