Control Engineering Methods for the Design of Robust Behavioral Treatments

IEEE Transactions on Control Systems Technology

Volumn 25, Issue 3, 2017, Pages 979-990

  Bekiroglu, Korkut ^a   Lagoa, Constantino ^a   Murphy, Suzan A ^b   Lanza, Stephanie T ^c  

^a The Pennsylvania State University   (United States)

^b UNIVERSITY OF MICHIGAN   (United States)

^c PENNSYLVANIA STATE UNIVERSITY   (United States)

Author keywords

Adaptive treatment design; Adaptive robust intervention; Behavioral treatment design; Min max structured robust optimization; Receding horizon control

Indexed keywords

ALGORITHMS; OPTIMIZATION; ROBUST CONTROL; SOCIAL SCIENCES; UNCERTAINTY ANALYSIS;

BEHAVIORAL RESPONSE; CONTROL ENGINEERING; EXTERNAL PERTURBATIONS; IDENTIFICATION TOOLS; LEAST ABSOLUTE SHRINKAGE AND SELECTION OPERATORS; NUMERICAL EXPERIMENTS; OPTIMIZATION ALGORITHMS; UNCERTAIN MODELING;

BEHAVIORAL RESEARCH;

EID: 84976514373     PISSN: 10636536     EISSN: None     Source Type: Journal    
DOI: 10.1109/TCST.2016.2580661     Document Type: Article

References (36)

1. K. L. Bierman, R. L. Nix, J. J. Maples, S. A. Murphy, "Examiningclinical judgment in an adaptive intervention design: The fast trackprogram, " J. Consulting Clin. Psychol. , vol. 74, no. 3, pp. 468-481, 2006.
2. D. E. Rivera, "Optimized behavioral interventions: What does systemidentification and control engineering have to offer" in Proc. 16th IFACSymp. Syst. Identificat. , 2012, pp. 882-893.
3. K. P. Timms, D. E. Rivera, L. M. Collins, M. E. Piper, "Continuoustimesystem identification of a smoking cessation intervention, " Int. J. Control, vol. 87, no. 7, pp. 1423-1437, 2014.
4. J.-E. Navarro-Barrientos, D. E. Rivera, L. M. Collins, "A dynamicalmodel for describing behavioural interventions for weight loss andbody composition change, " Math. Comput. Model. Dyn. Syst. , vol. 17, pp. 183-203, Jan. 2011.
5. Y. Dong, et al. , "A dynamical systems model for improving gestationalweight gain behavioral interventions, " in Proc. Amer. ControlConf. (ACC), 2012, pp. 4059-4064.
6. D. E. Rivera, M. D. Pew, L. M. Collins, "Using engineering controlprinciples to inform the design of adaptive interventions: A conceptualintroduction, " Drug Alcohol Dependence, vol. 88, no. 2, pp. S31-S40, May 2007.
7. N. N. Nandola and D. E. Rivera, "Model-on-demand predictive controlfor nonlinear hybrid systems with application to adaptive behavioralinterventions, " in Proc. 19th IEEE Conf. Decision Control, Dec. 2010, pp. 6113-6118.
8. A. Zafra-Cabeza, D. E. Rivera, L. M. Collins, M. A. Ridao, andE. F. Camacho, "A risk-based model predictive control approach toadaptive interventions in behavioral health, " IEEE Trans. Control Syst. Technol. , vol. 19, no. 4, pp. 891-901, Jul. 2011.
9. N. N. Nandola and D. E. Rivera, "An improved formulation ofhybrid model predictive control with application to production-inventorysystems, " IEEE Trans. Control Syst. Technol. , vol. 21, no. 1, pp. 121-135, Jan. 2013, doi: 10. 1109/TCST. 2011. 2177525.
10. S. Deshpande, N. N. Nandola, D. E. Rivera, J. W. Younger, "Optimized treatment of fibromyalgia using system identificationand hybrid model predictive control, " Control Eng. Pract. , vol. 33, pp. 161-173, Dec. 2014.
11. R. Tibshirani, "Regression shrinkage and selection via the lasso, "J. Roy. Statist. Soc. B, Methodol. , vol. 58, no. 1, pp. 267-288, 1996.
12. L. M. Collins, S. A. Murphy, K. L. Bierman, "A conceptualframework for adaptive preventive interventions, " Prevention Sci. , vol. 5, no. 3, pp. 185-196, Sep. 2004.
13. S. A. Murphy and L. M. Collins, "Customizing treatment to the patient:Adaptive treatment strategies, " Drug Alcohol Dependence, vol. 88, no. 2, pp. S1-S3, May 2007.
14. M. S. Glasgow, B. T. Engel, B. C. D'Lugoff, "A controlledstudy of a standardized behavioral stepped treatment for hypertension, "Psychosomatic Med. , vol. 51, no. 1, pp. 10-26, 1989.
15. W. F. Velicer and J. O. Prochaska, "An expert system intervention forsmoking cessation, " Patient Edu. Counseling, vol. 36, pp. 119-129, Feb. 1999.
16. A. Bemporad and M. Morari, "Robust model predictive control:A survey, " in Robustness in Identification and Control (Lecture Notesin Control and Information Sciences), vol. 245. London, U. K. : Springer, 1999, pp. 207-226.
17. H. A. Hindi and S. P. Boyd, "Robust solutions to l1, l2, l8 uncertainlinear approximation problems using convex optimization, " in Proc. Amer. Control Conf. (ACC), vol. 6. 1998, pp. 3487-3491.
18. L. El Ghaoui and H. Lebret, "Robust solutions to least-squares problemswith uncertain data, " SIAM J. Matrix Anal. Appl. , vol. 18, pp. 1035-1064, Oct. 1997.
19. M. Salhov, "A subgradient solution to structured robust least squaresproblems, " IEEE Trans. Signal Process. , vol. 58, no. 9, pp. 4761-4770, Sep. 2010.
20. K. P. Timms, D. E. Rivera, M. E. Piper, L. M. Collins, "A hybridmodel predictive control strategy for optimizing a smoking cessationintervention, " in Proc. Amer. Control Conf. , Jun. 2014, pp. 2389-2394.
21. D. B. Marlowe, D. S. Festinger, K. L. Dugosh, K. M. Benasutti, G. Fox, J. R. Croft, "Adaptive programming improves outcomes indrug court: An experimental trial, " Criminal Justice Behavior, vol. 39, pp. 514-532, Apr. 2012.
22. A. J. Rush, et al. , "Sequenced treatment alternatives to relieve depression(STARD): Rationale and design, " Controlled Clin. Trials, vol. 25, pp. 119-142, Feb. 2004.
23. L. S. Schneider, et al. , "National Institute of Mental Health clinicalantipsychotic trials of intervention effectiveness (CATIE): Alzheimerdisease trial methodology, " Amer. J. Geriatric Psychiatry, vol. 9, no. 4, pp. 346-360, Jan. 2001.
24. K. Bekiroglu, C. Lagoa, S. A. Murphy, S. T. Lanza, "A robust MPCapproach to the design of behavioural treatments, " in Proc. IEEE 52ndAnnu. Conf. Decision Control, Dec. 2013, pp. 3505-3510.
25. S. Shiffman, et al. , "Dynamic effects of self-efficacy on smoking lapseand relapse, " Health Psychol. , vol. 19, no. 4, pp. 315-323, Jul. 2000.
26. M. P. Shiyko, S. T. Lanza, X. Tan, R. Li, S. Shiffman, "Usingthe time-varying effect model (TVEM) to examine dynamic associationsbetween negative affect and self confidence on smoking urges:Differences between successful quitters and relapsers, " Prevention Sci. , vol. 13, pp. 288-299, Jul. 2012.
27. R. M. P. Van Zundert, S. G. Ferguson, S. Shiffman, andR. C. M. E. Engels, "Dynamic effects of self-efficacy on smokinglapses and relapse among adolescents, " Health Psychol. , vol. 29, pp. 246-254, May 2010.
28. K. P. Timms, D. E. Rivera, L. M. Collins, M. E. Piper, "A dynamicalsystems approach to understand self-regulation in smoking cessationbehavior change, " Nicotine Tobacco Res. , vol. 16, pp. S159-S168, Sep. 2013.
29. K. A. Bollen and M. D. Noble, "Structural equation models andthe quantification of behavior, " Proc. Nat. Acad. Sci. USA, vol. 108, pp. 15639-15646, Oct. 2011.
30. C. Ramirez, V. Kreinovich, M. Argaez, "Why-1 is a goodapproximation to-0: A geometric explanation, " J. Uncertain Syst. , vol. 7, no. 3, pp. 203-207, 2013.
31. F. Paganini, "A set-based approach for white noise modeling, " IEEETrans. Autom. Control, vol. 41, no. 10, pp. 1453-1465, Oct. 1996.
32. K. Gallacher, et al. , "Qualitative systematic reviews of treatment burdenin stroke, heart failure and diabetes-Methodological challenges andsolutions, " BMC Med. Res. Methodol. , vol. 13, p. 10, Jan. 2013.
33. A. Sav, et al. , "Burden of treatment for chronic illness: A conceptanalysis and review of the literature, " Health Expectations, vol. 18, no. 3, pp. 312-324, Jan. 2013.
34. B. Spring, S. Pagoto, R. Pingitore, N. Doran, K. Schneider, andD. Hedeker, "Randomized controlled trial for behavioral smoking andweight control treatment: Effect of concurrent versus sequential intervention, "J. Consulting Clin. Psychol. , vol. 72, no. 5, pp. 785-796, Oct. 2004.
35. M. Grant and S. Boyd, "Graph implementations for nonsmooth convexprograms, " in Recent Advances in Learning and Control (Lecture Notesin Control and Information Sciences), V. Blondel, S. Boyd, H. Kimura, Eds. Springer-Verlag, pp. 95-110, 2008.
36. S. Boyd, L. El Ghaoui, E. Feron, V. Balakrishnan, Linear MatrixInequalities in System and Control Theory, vol. 15. Philadelphia, PA, USA: SIAM, 1994.