Physical inactivity during adolescence increases risk for a number of serious health conditions. Surveillance, epidemiological, and intervention studies seeking to increase physical activity and/or decrease sedentary behaviors in adolescents could be enhanced through more informative and accurate methods of measuring these behaviors. Concerns about the validity of retrospective self report of physical activity and sedentary behavior have led to increasing use of objective measures, e.g., accelerometers and Global Positioning System (GPS) loggers, which can be complemented by subjective or contextual information using self-initiated event-contingent electronic ecological momentary assessment (EMA) after exercise or other critical activities. Regardless of the technique used, device non-wear, equipment malfunction, and participant non-response result in missing and ambiguous data that complicate statistical analysis. Adolescents recruited into objective PA monitoring studies will increasingly have so-called """"""""smart phones,"""""""" which are miniature computers with built in motion sensors and location-finding capabilities. Sophisticated programs (i.e., """"""""apps"""""""") can be easily installed on the phones. The overall objective of this project is to develop new software for common mobile phones that can both reduce and explain missing data collected during objective and EMA activity monitoring studies with free living adolescents. This technology will supplement objective monitors already used today, with minimal additional cost. Our solution will have three novel components: (1) A phone """"""""app"""""""" that uses the mobile device's built-in sensors to detect major transitions in type of movement or location, after which timely, context-sensitive questions and reminders are triggered that will reduce and explain missing or incomplete activity, location, and event- contingent EMA data, regardless of whether built-in or external objective monitors are used, (2) A second phone """"""""app"""""""" that has an entertaining, game-like feel and allows adolescents to interactively """"""""fill in gaps"""""""" in their own data at the end of the day using cues from automatically-detected major transitions to explain this missing data, and (3) Server-side software that will remotely collect data from the two apps in real-time and provide researchers with a cost-efficient way to reduce missing data and improve characterization of transition in activity. The system's feasibility, acceptability, and performance will be compared to the current state of the art in a within-subjects study with a free-living sample 40 low-to-middle income, ethnically diverse adolescents in 9-12th grade. The source code for all the software will be made freely available to other researchers.

Public Health Relevance

The goal of this proposal is to provide a low-cost way to use common mobile phones to reduce and explain missing and ambiguous data collected in studies using objective monitors to measure physical activity and sedentary behavior in adolescents. By improving the quality of data collected, and minimizing amount of missing data, the proposed work will enable researchers to better measure and understand the relationship between physical activity, sedentary behaviors, and the risk of metabolic, cardiovascular and other chronic disease. .

Agency
National Institute of Health (NIH)
Institute
National Heart, Lung, and Blood Institute (NHLBI)
Type
Exploratory/Developmental Grants (R21)
Project #
5R21HL108018-02
Application #
8433321
Study Section
Kidney, Nutrition, Obesity and Diabetes (KNOD)
Program Officer
Bonds, Denise
Project Start
2012-02-24
Project End
2014-01-31
Budget Start
2013-02-01
Budget End
2014-01-31
Support Year
2
Fiscal Year
2013
Total Cost
$187,328
Indirect Cost
$31,797
Name
Northeastern University
Department
Type
Schools of Arts and Sciences
DUNS #
001423631
City
Boston
State
MA
Country
United States
Zip Code
02115
Spruijt-Metz, Donna; Wen, Cheng K Fred; Bell, Brooke M et al. (2018) Advances and Controversies in Diet and Physical Activity Measurement in Youth. Am J Prev Med 55:e81-e91
Dunton, Genevieve Fridlund (2017) Ecological Momentary Assessment in Physical Activity Research. Exerc Sport Sci Rev 45:48-54
Liao, Yue; Chou, Chih-Ping; Huh, Jimi et al. (2017) Examining acute bi-directional relationships between affect, physical feeling states, and physical activity in free-living situations using electronic ecological momentary assessment. J Behav Med 40:445-457
Ponnada, Aditya; Haynes, Caitlin; Maniar, Dharam et al. (2017) Microinteraction Ecological Momentary Assessment Response Rates: Effect of Microinteractions or the Smartwatch? Proc ACM Interact Mob Wearable Ubiquitous Technol 1:
Dunton, Genevieve Fridlund; Dzubur, Eldin; Intille, Stephen (2016) Feasibility and Performance Test of a Real-Time Sensor-Informed Context-Sensitive Ecological Momentary Assessment to Capture Physical Activity. J Med Internet Res 18:e106
Dunton, Genevieve; Dzubur, Eldin; Li, Marilyn et al. (2016) Momentary Assessment of Psychosocial Stressors, Context, and Asthma Symptoms in Hispanic Adolescents. Behav Modif 40:257-80
Intille, Stephen; Haynes, Caitlin; Maniar, Dharam et al. (2016) ?EMA: Microinteraction-based Ecological Momentary Assessment (EMA) Using a Smartwatch. Proc ACM Int Conf Ubiquitous Comput 2016:1124-1128
Liao, Yue; Shonkoff, Eleanor T; Dunton, Genevieve F (2015) The Acute Relationships Between Affect, Physical Feeling States, and Physical Activity in Daily Life: A Review of Current Evidence. Front Psychol 6:1975
Tate, E B; Wood, W; Liao, Y et al. (2015) Do stressed mothers have heavier children? A meta-analysis on the relationship between maternal stress and child body mass index. Obes Rev 16:351-61
Dzubur, Eldin; Li, Marilyn; Kawabata, Keito et al. (2015) Design of a smartphone application to monitor stress, asthma symptoms, and asthma inhaler use. Ann Allergy Asthma Immunol 114:341-342.e2

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