Rivera, Daniel E.

Health behavior models in the age of mobile interventions: are our theories up to the task?

Riley, W. T., Rivera, D. E., Atienza, A. A., Nilsen, W., Allison, S. M., & Mermelstein, R. (2011) · Translational Behavioral Medicine

Mobile Health and mHealth ApplicationsBehavioral Health and Interventions

Cited by 978

Evaluating Digital Health Interventions

Murray, E., Hekler, E. B., Andersson, G., Collins, L. M., Doherty, A., Hollis, C., Rivera, D. E., West, R., & Wyatt, J. C. (2016) · American Journal of Preventive Medicine

Mobile Health and mHealth ApplicationsDigital Mental Health Interventions

Cited by 847

Agile science: creating useful products for behavior change in the real world

Hekler, E. B., Klasnja, P., Riley, W. T., Buman, M. P., Huberty, J., Rivera, D. E., & Martin, C. A. (2016) · Translational Behavioral Medicine

Behavioral Health and InterventionsHealth Policy Implementation Science

Cited by 208

Advancing Models and Theories for Digital Behavior Change Interventions

Hekler, E. B., Michie, S., Pavel, M., Rivera, D. E., Collins, L. M., Jimison, H. B., Garnett, C., Parral, S., & Spruijt-Metz, D. (2016) · American Journal of Preventive Medicine

Behavioral Health and InterventionsDigital Mental Health Interventions

Cited by 174

Using engineering control principles to inform the design of adaptive interventions: A conceptual introduction

Rivera, D. E., Pew, M. D., & Collins, L. M. (2007) · Drug and Alcohol Dependence

Substance Abuse Treatment and OutcomesDigital Mental Health Interventions

Cited by 151

An Improved Formulation of Hybrid Model Predictive Control With Application to Production-Inventory Systems

Nandola, N. N., & Rivera, D. E. (2013) · IEEE Transactions on Control Systems Technology

Advanced Control Systems OptimizationAdvanced Optimization Algorithms Research

Cited by 64

Adaptive, behavioral intervention impact on weight gain, physical activity, energy intake, and motivational determinants: results of a feasibility trial in pregnant women with overweight/obesity

Downs, D. S., Savage, J. S., Rivera, D. E., Pauley, A. M., Leonard, K. S., Hohman, E. E., Guo, P., McNitt, K. M., Stetter, C., & Kunselman, A. (2021) · Journal of Behavioral Medicine

Gestational Diabetes Research and ManagementMobile Health and mHealth Applications

Cited by 51

Goal setting and achievement for walking: A series of N-of-1 digital interventions.

Chevance, G., Baretta, D., Golaszewski, N., Takemoto, M., Shrestha, S., Jain, S., Rivera, D. E., Klasnja, P., & Hekler, E. (2021) · Health Psychology

Physical Activity and HealthBehavioral Health and Interventions

Cited by 37

Advancing Behavioral Intervention and Theory Development for Mobile Health: The HeartSteps II Protocol

Spruijt-Metz, D., Marlin, B. M., Pavel, M., Rivera, D. E., Hekler, E., De La Torre, S., El Mistiri, M., Golaszweski, N. M., Li, C., Braga De Braganca, R., et al. (2022) · International Journal of Environmental Research and Public Health

Mobile Health and mHealth ApplicationsDigital Mental Health Interventions

Cited by 30

Advancing Understanding of Just-in-Time States for Supporting Physical Activity (Project JustWalk JITAI): Protocol for a System ID Study of Just-in-Time Adaptive Interventions

Park, J., Kim, M., El Mistiri, M., Kha, R., Banerjee, S., Gotzian, L., Chevance, G., Rivera, D. E., Klasnja, P., & Hekler, E. (2023) · JMIR Research Protocols

Mobile Health and mHealth ApplicationsPhysical Activity and Health

Cited by 29

A control systems engineering approach for adaptive behavioral interventions: illustration with a fibromyalgia intervention

Deshpande, S., Rivera, D. E., Younger, J. W., & Nandola, N. N. (2014) · Translational Behavioral Medicine

Fibromyalgia and Chronic Fatigue Syndrome ResearchAdvanced Control Systems Optimization

Cited by 24

A system identification approach for improving behavioral interventions based on Social Cognitive Theory

Martin, C. A., Deshpande, S., Hekler, E. B., & Rivera, D. E. (2015) · 2015 American Control Conference (ACC)

Control Systems and IdentificationMobile Health and mHealth Applications

Cited by 23

Hybrid model predictive control for optimizing gestational weight gain behavioral interventions

Dong, Y., Rivera, D. E., Downs, D. S., Savage, J. S., Thomas, D. M., & Collins, L. M. (2013) · 2013 American Control Conference

Advanced Control Systems OptimizationGestational Diabetes Research and Management

Cited by 23

A decision framework for an adaptive behavioral intervention for physical activity using hybrid model predictive control

Martin, C. A., Rivera, D. E., & Hekler, E. B. (2016) · 2016 American Control Conference (ACC)

Mobile Health and mHealth ApplicationsAdvanced Control Systems Optimization

Cited by 20

An identification test monitoring procedure for MIMO systems based on statistical uncertainty estimation

Martin, C. A., Rivera, D. E., & Hekler, E. B. (2015) · 2015 54th IEEE Conference on Decision and Control (CDC)

Control Systems and IdentificationOptimal Experimental Design Methods

Cited by 13

A Risk-based Model Predictive Control Approach to Adaptive Interventions in Behavioral Health

Zafra-Cabeza, A., Rivera, D. E., Collins, L. M., Ridao, M. A., & Camacho, E. F. (2006) · Proceedings of the 45th IEEE Conference on Decision and Control

Advanced Control Systems OptimizationSubstance Abuse Treatment and Outcomes

Cited by 3