Leveraging intensive longitudinal data to better understand health behaviors

2014 36th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2014

Volumn , Issue , 2014, Pages 6888-6891

  Timms, Kevin P ^a   Martin, Cesar A ^a   Rivera, Daniel E ^a   Hekler, Eric B ^b   Riley, William ^c  

^a Arizona State University   (United States)

^b ARIZONA STATE UNIVERSITY   (United States)

^c NATIONAL CANCER INSTITUTE   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

COGNITIVE SYSTEMS; DYNAMICAL SYSTEMS;

BEHAVIORAL SCIENCE; DYNAMICAL SYSTEMS MODEL; HEALTH BEHAVIORS; LONGITUDINAL DATA; PHYSICAL ACTIVITY; QUANTITATIVE DESCRIPTION; SOCIAL COGNITIVE THEORY; TIME VARYING BEHAVIOR;

BEHAVIORAL RESEARCH;

ALGORITHM; HEALTH BEHAVIOR; HUMAN; LONGITUDINAL STUDY; SELF CONCEPT; THEORETICAL MODEL;

ALGORITHMS; HEALTH BEHAVIOR; HUMANS; LONGITUDINAL STUDIES; MODELS, THEORETICAL; SELF EFFICACY;

EID: 84929497795     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/EMBC.2014.6945211     Document Type: Conference Paper

References (13)

1. C.A. Martn, D.E. Rivera, W.T. Riley, E.B. Hekler, M.P. Bunam, M.A. Adams, and A.C. King. A dynamical systems model of Social Cognitive Theory. Proceedings of the 2014 American Control Conference, pages 2407-2412, 2014.
2. L.M. Collins. Analysis of longitudinal data: The integration of theoretical model, temporal design, and statistical model. Annual Review of Pscychology, 57(1):505-528, 2006.
3. T.A. Walls and J.L. Schafer, editors. Models for Intensive Longitudinal Data. Oxford University Press, Cary, NC, USA, 2006.
4. D.E. Rivera. Optimized behavioral interventions: What does system identification and control systems engineering have to offer? Proceedings of the 16th IFAC Symposium on System Identification, Brussels, Belgium, pages 882-893, July 2012.
5. K.P. Timms, D.E. Rivera, L.M. Collins, and M.E. Piper. Continuous-time system identification of a smoking cessation intervention. International Journal of Control, 87(7):1423-1437, 2014.
6. B. Ogunnaike and W. Ray. Process dynamics, Modeling, and Control. Oxford University Press, New York City, NY, 1994.
7. L. Ljung. System Identification: Theory for the User (2nd ed.). Prentice-Hall, Inc., Englewood Cliffs, NJ, 1999.
8. L. Ljung. System Identification Toolbox User's Guide. The MathWorks, Inc., 2003.
9. N.N. Nandola and D.E. Rivera. An improved formulation of Hybrid Model Predictive Control with application to production-inventory systems. IEEE Transactions on Control Systems Technology, 21(1):121-135, 2013.
10. A. Bandura. Social foundations of thought and action: a social cognitive theory. Prentice-Hall, Inc., 1986.
11. D. MacKinnon. Introduction to Statistical Mediation Analysis. Rout-ledge Academic, 2008.
12. A.C. King, E.B. Hekler, L.A. Grieco, S.J. Winter, J.L. Sheats, M.P. Buman, B. Banerjee, T.N. Robinson, and J. Cirimele. Harnessing different motivational frames via mobile phones to promote daily physical activity and reduce sedentary behavior in aging adults. PLOS One, page e62613, 2013.
13. D.E. McCarthy, T.M. Piasecki, D.L. Lawrence, D.E. Jorenby, S. Shiffman, M.C. Fiore, and T.B. Baker. A randomized controlled clinical trial of bupropion SR and individual smoking cessation counseling. Nicotine and Tobacco Research, 10(4):717-729, 2008.