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Yue Liao, MPH
Eldin Dzubur, MS
Genevieve Dunton, PhD, MPH
University of Southern California
Institute for Health Promotion & Disease Prevention Research
SOCIETYOFBEHAVIORALMEDICINE,APRIL,2015
Sedentary Behavior in Adolescents
An average U.S. adolescent spent
2.4 hours/day in TV viewing
1.5 hours/day in computer use
1.3 hours/day in video gaming
Iannotti & Wang, 2013
SOCIETYOFBEHAVIORALMEDICINE,APRIL,2015
Sedentary Behavior as a Risk Factor
www.activelivingresearch.org/sedentaryreview
SOCIETYOFBEHAVIORALMEDICINE,APRIL,2015
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
SOCIETYOFBEHAVIORALMEDICINE,APRIL,2015
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)
SOCIETYOFBEHAVIORALMEDICINE,APRIL,2015
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)
SOCIETYOFBEHAVIORALMEDICINE,APRIL,2015
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
SOCIETYOFBEHAVIORALMEDICINE,APRIL,2015
Mobile Phone EMA Questions
• Each EMA survey assessed
 type
 body position
 duration
of all activities performed in the past 30 minutes
SOCIETYOFBEHAVIORALMEDICINE,APRIL,2015
Sample Screenshots
Activity Type Body Position Length
SOCIETYOFBEHAVIORALMEDICINE,APRIL,2015
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
SOCIETYOFBEHAVIORALMEDICINE,APRIL,2015
Sample Characteristics
• 51 high school students from Los Angeles
 Ages 14 – 19 years
 54.9% female
 56.9% Hispanic
 39.2% overweight/obese
SOCIETYOFBEHAVIORALMEDICINE,APRIL,2015
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%
SOCIETYOFBEHAVIORALMEDICINE,APRIL,2015
Sedentary Behavior by Type of Activity
98% 95% 92%
68%
0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
100%
Reading/Doing
Homework
Using
Technology
(TV/phone)
Eating/Drinking Hanging Out
SOCIETYOFBEHAVIORALMEDICINE,APRIL,2015
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
SOCIETYOFBEHAVIORALMEDICINE,APRIL,2015
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
SOCIETYOFBEHAVIORALMEDICINE,APRIL,2015
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
SOCIETYOFBEHAVIORALMEDICINE,APRIL,2015
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
SOCIETYOFBEHAVIORALMEDICINE,APRIL,2015
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
SOCIETYOFBEHAVIORALMEDICINE,APRIL,2015
Acknowledgements
• Funding agencies
 NHLBI (1R21HL108018) (Dunton, Intille PIs)
 NHLBI (1R01HL119255-01) (Dunton, PI)
 NIEHS(5 P30 ES07048-16) (Dunton, PI on pilot)
• Participants
• Project staff
 Bin Bo (App Developer)
 Keito Kawabata (Project Manager)
 Student interns

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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
  • 2. SOCIETYOFBEHAVIORALMEDICINE,APRIL,2015 Sedentary Behavior in Adolescents An average U.S. adolescent spent 2.4 hours/day in TV viewing 1.5 hours/day in computer use 1.3 hours/day in video gaming Iannotti & Wang, 2013
  • 3. SOCIETYOFBEHAVIORALMEDICINE,APRIL,2015 Sedentary Behavior as a Risk Factor www.activelivingresearch.org/sedentaryreview
  • 4. SOCIETYOFBEHAVIORALMEDICINE,APRIL,2015 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
  • 5. SOCIETYOFBEHAVIORALMEDICINE,APRIL,2015 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)
  • 6. SOCIETYOFBEHAVIORALMEDICINE,APRIL,2015 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)
  • 7. SOCIETYOFBEHAVIORALMEDICINE,APRIL,2015 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
  • 8. SOCIETYOFBEHAVIORALMEDICINE,APRIL,2015 Mobile Phone EMA Questions • Each EMA survey assessed  type  body position  duration of all activities performed in the past 30 minutes
  • 10. SOCIETYOFBEHAVIORALMEDICINE,APRIL,2015 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
  • 11. SOCIETYOFBEHAVIORALMEDICINE,APRIL,2015 Sample Characteristics • 51 high school students from Los Angeles  Ages 14 – 19 years  54.9% female  56.9% Hispanic  39.2% overweight/obese
  • 12. SOCIETYOFBEHAVIORALMEDICINE,APRIL,2015 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%
  • 13. SOCIETYOFBEHAVIORALMEDICINE,APRIL,2015 Sedentary Behavior by Type of Activity 98% 95% 92% 68% 0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100% Reading/Doing Homework Using Technology (TV/phone) Eating/Drinking Hanging Out
  • 14. SOCIETYOFBEHAVIORALMEDICINE,APRIL,2015 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
  • 15. SOCIETYOFBEHAVIORALMEDICINE,APRIL,2015 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
  • 16. SOCIETYOFBEHAVIORALMEDICINE,APRIL,2015 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
  • 17. SOCIETYOFBEHAVIORALMEDICINE,APRIL,2015 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
  • 18. SOCIETYOFBEHAVIORALMEDICINE,APRIL,2015 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
  • 19. SOCIETYOFBEHAVIORALMEDICINE,APRIL,2015 Acknowledgements • Funding agencies  NHLBI (1R21HL108018) (Dunton, Intille PIs)  NHLBI (1R01HL119255-01) (Dunton, PI)  NIEHS(5 P30 ES07048-16) (Dunton, PI on pilot) • Participants • Project staff  Bin Bo (App Developer)  Keito Kawabata (Project Manager)  Student interns

Hinweis der Redaktion

  1. 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.
  2. 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.
  3. 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.
  4. 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.
  5. 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.
  6. 3 weekdays 7 weekends, during non-school waking hours
  7. 22% overweight, 18% obese
  8. Of at least one sedentary activity reported prompts.
  9. Average was 36.9 minutes for single activity
  10. 27% (n=262) 69% (n=180), 27% (n=72),
  11. Female: 34%, male: 21%
  12. Normal weight: 25%, overweight: 12%, obese: 51% Overweight vs. obese, p = .02
  13. 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.