Optimizing Digital Integrated Care via Micro‐Randomized Trials

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The Law of Attrition

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Just-in-time adaptive interventions (JITAIs) in mobile health: key components and design principles for ongoing health behavior support

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The Effectiveness of Mobile-Health Technology-Based Health Behaviour Change or Disease Management Interventions for Health Care Consumers: A Systematic Review

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Healthcare in the pocket: Mapping the space of mobile-phone health interventions

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Developing and evaluating digital interventions to promote behavior change in health and health care: recommendations resulting from an international workshop

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Evaluating Digital Health Interventions

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Microrandomized trials: An experimental design for developing just-in-time adaptive interventions.

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Behavioral and neuroeconomics of drug addiction: Competing neural systems and temporal discounting processes

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Building health behavior models to guide the development of just-in-time adaptive interventions: a pragmatic framework

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Feasibility, Acceptability, and Preliminary Efficacy of a Smartphone Intervention for Schizophrenia

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Using context-aware computing to reduce the perceived burden of interruptions from mobile devices

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The n-of-1 Randomized Controlled Trial: Clinical Usefulness

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No longer wearing

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Optimization of Behavioral, Biobehavioral, and Biomedical Interventions: The Multiphase Optimization Strategy (MOST)

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A systematic review of smartphone applications for smoking cessation

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Advancing the science of mHealth

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Combining single patient (N-of-1) trials to estimate population treatment effects and to evaluate individual patient responses to treatment

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The state of the art and future opportunities for using longitudinal n-of-1 methods in health behaviour research: a systematic literature overview

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Individual (N-of-1) trials can be combined to give population comparative treatment effect estimates: methodologic considerations

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Single-Case Experimental Designs to Evaluate Novel Technology-Based Health Interventions

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Environmental determinants of severity in sickle cell disease

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Assessing time-varying causal effect moderation in mobile health

Boruvka, A., Almirall, D., Witkiewitz, K., & Murphy, S. A. (2018) · Journal of the American Statistical Association · doi:10.1080/01621459.2017.1305274 · Cited by 152 · see citing works

Sample size calculations for micro‐randomized trials in mHealth

Liao, P., Klasnja, P., Tewari, A., & Murphy, S. A. (2015) · Statistics in Medicine · doi:10.1002/sim.6847 · Cited by 147 · see citing works

A MECHANISM FOR REDUCING DELAY DISCOUNTING BY ALTERING TEMPORAL ATTENTION

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Exercise limitation, exercise testing and exercise recommendations in sickle cell anemia

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Using N-of-1 Trials to Improve Patient Management and Save Costs

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Aggregating single patient (n-of-1) trials in populations where recruitment and retention was difficult: The case of palliative care

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Technology-based interventions for weight management: current randomized controlled trial evidence and future directions

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Development of a Theoretically Driven mHealth Text Messaging Application for Sustaining Recent Weight Loss

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Fluid replacement therapy for acute episodes of pain in people with sickle cell disease

Okomo, U. A., & Meremikwu, M. M. (2017) · Cochrane Database of Systematic Reviews · doi:10.1002/14651858.cd005406.pub5 · Cited by 63 · see citing works

Randomised Trials for the Fitbit Generation

Dempsey, W., Liao, P., Klasnja, P., Nahum-Shani, I. B., & Murphy, S. A. (2015) · Significance · doi:10.1111/j.1740-9713.2015.00863.x · Cited by 55 · see citing works

Center of excellence for mobile sensor data-to-knowledge (MD2K)

Kumar, S., Abowd, G. D., Abraham, W. T., Al’Absi, M., Beck, J. G., Chau, D. H., Condie, T., Conroy, D. E., Ertin, E., Estrin, D. L., et al. (2015) · Journal of the American Medical Informatics Association · doi:10.1093/jamia/ocv056 · Cited by 49 · see citing works

Effects of episodic future thinking on discounting: Personalized age-progressed pictures improve risky long-term health decisions.

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SARA

Rabbi, M., Philyaw-Kotov, M. L., Lee, J. S., Mansour, A., Dent, L. M., Wang, X., Cunningham, R. M., Bonar, E. E., Nahum-Shani, I. B., Klasnja, P., et al. (2017) · ACM International Joint Conference on Pervasive and Ubiquitous Computing (UbiComp) · doi:10.1145/3123024.3125611 · Cited by 38 · see citing works

e wrapper

Wagner, B., Liu, E., Shaw, S. D., Iakovlev, G., Zhou, L., Harrington, C., Abowd, G. D., Yoon, C., Kumar, S., Murphy, S. A., et al. (2017) · ACM International Joint Conference on Pervasive and Ubiquitous Computing (UbiComp) · doi:10.1145/3123024.3125612 · Cited by 21 · see citing works

Daily Pain, Physical Activity, and Home Fluid Intake in Pediatric Sickle Cell Disease

Karlson, C., Baker, A. M., Bromberg, M. H., Elkin, T. D., Majumdar, S., & Palermo, T. M. (2016) · Journal of Pediatric Psychology · doi:10.1093/jpepsy/jsw061 · Cited by 20 · see citing works

N-of-1 Trials in the Behavioral Sciences

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Design Lessons from a Micro-Randomized Pilot Study in Mobile Health

Smith, S. N., Lee, J. S., Hall, K., Seewald, N. J., Boruvka, A., Murphy, S. A., & Klasnja, P. (2017) · Springer eBooks · doi:10.1007/978-3-319-51394-2_4 · Cited by 17 · see citing works

Fluid replacement therapy for acute episodes of pain in people with sickle cell disease

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MRT-SS Calculator: An R Shiny Application for Sample Size Calculation in Micro-Randomized TrialsPreprint

Seewald, N. J., Sun, J., & Liao, P. (2016) · arXiv (Cornell University) · doi:10.48550/arxiv.1609.00695 · Cited by 6 · see citing works

Mobile Health for Illness Management

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Assessing Time-Varying Causal Effect Moderation in Mobile HealthPreprint

Boruvka, A., Almirall, D., Witkiewitz, K. A., & Murphy, S. A. (2016) · arXiv (Cornell University) · doi:10.48550/arxiv.1601.00237 · Cited by 3 · see citing works

Digital Micro Interventions for Behavioral and Mental Health Gains: Core Components and Conceptualization of Digital Micro Intervention Care

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Developments in Mobile Health Just-in-Time Adaptive Interventions for Addiction Science

Carpenter, S. M., Menictas, M., Nahum-Shani, I. B., Wetter, D. W., & Murphy, S. A. (2020) · Current Addiction Reports · doi:10.1007/s40429-020-00322-y · Cited by 97 · see citing works

Toward Precision Medicine

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Online Guide for Electronic Health Evaluation Approaches: Systematic Scoping Review and Concept Mapping Study

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The application of digital health to the assessment and treatment of substance use disorders: The past, current, and future role of the National Drug Abuse Treatment Clinical Trials Network

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Big Data and the Precision Medicine Revolution

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Digital Interventions for Mental Disorders: Key Features, Efficacy, and Potential for Artificial Intelligence Applications

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Intervention Optimization: A Paradigm Shift and Its Potential Implications for Clinical Psychology

Collins, L. M., Nahum-Shani, I. B., Guastaferro, K., Strayhorn, J. C., Vanness, D. J., & Murphy, S. A. (2024) · Annual Review of Clinical Psychology · doi:10.1146/annurev-clinpsy-080822-051119 · Cited by 73 · see citing works

From Personalized Medicine to Population Health: A Survey of mHealth Sensing Techniques

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Consolidated guidance for behavioral intervention pilot and feasibility studies

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The future of psychological treatments: The Marburg Declaration

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Microrandomized Trial Design for Evaluating Just-in-Time Adaptive Interventions Through Mobile Health Technologies for Cardiovascular Disease

Golbus, J. R., Dempsey, W., Jackson, E. A., Nallamothu, B. K., & Klasnja, P. (2021) · Circulation Cardiovascular Quality and Outcomes · doi:10.1161/circoutcomes.120.006760 · Cited by 44 · see citing works

Understanding Disengagement in Just-in-Time Mobile Health Interventions

Park, J., & Lee, U. (2023) · Proceedings of the ACM on Interactive Mobile Wearable and Ubiquitous Technologies · doi:10.1145/3596240 · Cited by 40 · see citing works

Digital Prompts to Increase Engagement With the Headspace App and for Stress Regulation Among Parents: Feasibility Study

Militello, L. K., Sobolev, M., Okeke, F., Adler, D. A., & Nahum-Shani, I. B. (2021) · JMIR Formative Research · doi:10.2196/30606 · Cited by 36 · see citing works

How Notifications Affect Engagement With a Behavior Change App: Results From a Micro-Randomized Trial

Bell, L., Garnett, C., Bao, Y., Cheng, Z., Qian, T., Perski, O., Potts, H. W. W., & Williamson, E. (2023) · JMIR mHealth and uHealth · doi:10.2196/38342 · Cited by 35 · see citing works

Contextual Predictors of Engagement in a Tailored mHealth Intervention for Adolescent and Young Adult Cancer Survivors

Psihogios, A. M., King‐Dowling, S., O’Hagan, B., Darabos, K., Maurer, L. A., Young, J., Fleisher, L. G., Barakat, L. P., Szalda, D. E., Hill‐Kayser, C. E., et al. (2021) · Annals of Behavioral Medicine · doi:10.1093/abm/kaab008 · Cited by 34 · see citing works

Hybrid Experimental Designs for Intervention Development: What, Why, and How

Nahum-Shani, I. B., Dziak, J. J., Walton, M. A., & Dempsey, W. (2022) · Advances in Methods and Practices in Psychological Science · doi:10.1177/25152459221114279 · Cited by 32 · see citing works

Toward Individualized Prediction of Binge-Eating Episodes Based on Ecological Momentary Assessment Data: Item Development and Pilot Study in Patients With Bulimia Nervosa and Binge-Eating Disorder

Arend, A., Kaiser, T., Pannicke, B., Reichenberger, J., Naab, S., Voderholzer, U., & Jens Blechert, A. (2022) · JMIR Medical Informatics · doi:10.2196/41513 · Cited by 31 · see citing works

Notifications to Improve Engagement With an Alcohol Reduction App: Protocol for a Micro-Randomized Trial

Bell, L., Garnett, C. V., Qian, T., Perski, O., POTTS, H. W. W., & Williamson, E. (2020) · JMIR Research Protocols · doi:10.2196/18690 · Cited by 28 · see citing works

Effectiveness of Digital Health Interventions Containing Game Components for the Self-management of Type 2 Diabetes: Systematic Review

Ossenbrink, L., Haase, T., Timpel, P., Schoffer, O., Scheibe, M., Schmitt, J., Deckert, S., & Harst, L. (2023) · JMIR Serious Games · doi:10.2196/44132 · Cited by 27 · see citing works

Digital and Mobile Health Technology in Collaborative Behavioral Health Care: Scoping Review

Moon, K. C., Sobolev, M., & Kane, J. M. (2022) · JMIR Mental Health · doi:10.2196/30810 · Cited by 24 · see citing works

Optimizing a Just-in-Time Adaptive Intervention to Improve Dietary Adherence in Behavioral Obesity Treatment: Protocol for a Microrandomized Trial

Goldstein, S. P., Zhang, F., Klasnja, P., Hoover, A., Wing, R. R., & Thomas, J. G. (2021) · JMIR Research Protocols · doi:10.2196/33568 · Cited by 26 · see citing works

Just-in-Time Adaptive Interventions: Where Are We Now and What Is Next?

Nahum-Shani, I. B., & Murphy, S. A. (2025) · Annual Review of Psychology · doi:10.1146/annurev-psych-121024-044244 · Cited by 30 · see citing works

The recent history and near future of digital health in the field of behavioral medicine: an update on progress from 2019 to 2024

Arigo, D., Jake‐Schoffman, D. E., & Pagoto, S. (2024) · Journal of Behavioral Medicine · doi:10.1007/s10865-024-00526-x · Cited by 24 · see citing works

Computer clinical decision support that automates personalized clinical care: a challenging but needed healthcare delivery strategy

Morris, A. H., Horvat, C. M., Stagg, B. C., Grainger, D. W., Lanspa, M. J., Orme, J. F., Clemmer, T. P., Weaver, L. K., Thomas, F. O., Grissom, C. K., et al. (2022) · Journal of the American Medical Informatics Association · doi:10.1093/jamia/ocac143 · Cited by 20 · see citing works

A Theory-Informed, Personalized mHealth Intervention for Adolescents (Mobile App for Physical Activity): Development and Pilot Study

Domin, A., Uslu, A. S., Schulz, A., Ouzzahra, Y., & Vögele, C. (2022) · JMIR Formative Research · doi:10.2196/35118 · Cited by 21 · see citing works

Exploring Breaks in Sedentary Behavior of Older Adults Immediately After Receiving Personalized Haptic Feedback: Intervention Study

Compernolle, S., Dyck, D. V., Cardon, G., & Brondeel, R. (2021) · JMIR mhealth and uhealth · doi:10.2196/26387 · Cited by 18 · see citing works

A Gambling Just-In-Time Adaptive Intervention (GamblingLess: In-The-Moment): Protocol for a Microrandomized Trial

Dowling, N. A., Merkouris, S., Youssef, G. J., Lubman, D. I., Bagot, K. L., Hawker, C. O., Portogallo, H. J., Thomas, A. C., & Rodda, S. N. (2022) · JMIR Research Protocols · doi:10.2196/38958 · Cited by 18 · see citing works

Applying the Just-In-Time Adaptive Intervention Framework to the Development of Gambling Interventions

Dowling, N. A., Rodda, S. N., & Merkouris, S. (2023) · Journal of Gambling Studies · doi:10.1007/s10899-023-10250-x · Cited by 17 · see citing works

The Promise of Just-in-Time Adaptive Interventions for Organizational Scholarship and Practice: Conceptual Development and Research Agenda

Zhu, Z., Aitken, J. A., Dalal, R. S., & Kaplan, S. A. (2023) · Organizational Research Methods · doi:10.1177/10944281231202740 · Cited by 16 · see citing works

Opportunity for efficiency in clinical development: An overview of adaptive clinical trial designs and innovative machine learning tools, with examples from the cardiovascular field

Sverdlov, O., Ryeznik, Y. V., & Wong, W. K. (2021) · Contemporary Clinical Trials · doi:10.1016/j.cct.2021.106397 · Cited by 16 · see citing works

Predicting postprandial glucose excursions to personalize dietary interventions for type-2 diabetes management

Brügger, V., Kowatsch, T., & Jovanova, M. (2025) · Scientific Reports · doi:10.1038/s41598-025-08003-4 · Cited by 17 · see citing works

Advancing the science of biosocial transactions related to aggression in children and young people: A brief review and steps forward

Baskin-Sommers, A., Viding, E., Barber, M., Ruiz, S. G., Paskewitz, S., & Hyde, L. W. (2024) · Aggression and Violent Behavior · doi:10.1016/j.avb.2024.102001 · Cited by 10 · see citing works

The Sequential Multiple Assignment Randomized Trial for Controlling Infectious Diseases: A Review of Recent Developments

Wang, X., & Chakraborty, B. (2022) · American Journal of Public Health · doi:10.2105/ajph.2022.307135 · Cited by 12 · see citing works

Design of experiments with sequential randomizations on multiple timescales: the hybrid experimental design

Nahum-Shani, I. B., Dziak, J. J., Venera, H., Pfammatter, A. F., Spring, B. J., & Dempsey, W. (2023) · Behavior Research Methods · doi:10.3758/s13428-023-02119-z · Cited by 8 · see citing works

Participant Engagement in Microrandomized Trials of mHealth Interventions: Scoping Review

Leong, U., & Chakraborty, B. (2023) · JMIR mhealth and uhealth · doi:10.2196/44685 · Cited by 7 · see citing works

Optimization of a Mobile Transdiagnostic Emotion Regulation Intervention for University Students: A Micro‐Randomized Trial

Laure, T., Remmerswaal, D., Konigorski, S., Engels, R. C. M. E., & Boffo, M. (2024) · Stress and Health · doi:10.1002/smi.3507 · Cited by 7 · see citing works

Remote Monitoring Devices and Heart Failure

Gupta, K., Mastoris, I., & Sauer, A. J. (2023) · Cardiac Electrophysiology Clinics · doi:10.1016/j.ccep.2026.06.007 · Cited by 7 · see citing works

Microrandomized trials for promoting engagement in mobile health data collection: Adolescent/young adult oral chemotherapy adherence as an example

Li, S., Psihogios, A. M., McKelvey, E. R., Ahmed, A., Rabbi, M., & Murphy, S. A. (2020) · Current Opinion in Systems Biology · doi:10.1016/j.coisb.2020.07.002 · Cited by 7 · see citing works

Optimization of a Transdiagnostic Mobile Emotion Regulation Intervention for University Students: Protocol for a Microrandomized Trial

Laure, T., Engels, R. C. M. E., Remmerswaal, D., Spruijt-Metz, D., Konigorski, S., & Boffo, M. (2023) · JMIR Research Protocols · doi:10.2196/46603 · Cited by 6 · see citing works

"All Day, Every Day, Listening to Trauma": Investigating Features of Digital Interventions for Empathy-Based Stress and Burnout

Chau, C. W., Norton, C., Kruzan, K. P., & Jacobs, M. L. (2025) · CHI Conference on Human Factors in Computing Systems · doi:10.1145/3706598.3713588 · Cited by 5 · see citing works

Digital Technology: The Future Is Bright

Smith, B. P., & Sverdlov, A. (2018) · Clinical Pharmacology & Therapeutics · doi:10.1002/cpt.1092 · Cited by 5 · see citing works

The Independent Walking for Brain Health Intervention for Older Adults: Protocol for a Pilot Randomized Controlled Trial

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The JITAI Code: A Primer on Just‐In‐Time‐Adaptive Interventions

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Microrandomized Trial Design for Evaluating Just-in-Time Adaptive Interventions Through Mobile Health Technologies for Cardiovascular Disease

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Micro-Randomized Trials in mHealthPreprint

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Microrandomized trials: An experimental design for developing just-in-time adaptive interventions.

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