Grant Number:	5U01CA229437-04 Interpret this number
Primary Investigator:	Nahum-Shani, Inbal
Organization:	University Of Michigan At Ann Arbor
Project Title:	Novel Use of Mhealth Data to Identify States of Vulnerability and Receptivity to Jitais
Fiscal Year:	2021

Abstract: Smoking cessation decreases morbidity and mortality and is a cornerstone of cancer prevention. The ability to impact current and future vulnerability (e.g., high risk for a lapse) in real-time via engagement in self-regulatory activities (e.g., behavioral substitution, mindful attention) is considered an important pathway to quitting success. However, poor engagement represents a major barrier to maximizing the impact of self- regulatory activities. Hence, enhancing real-time, real-world engagement in evidence-based self-regulatory activities has the potential to improve the effectiveness of smoking cessation interventions. Just-In-Time Adaptive Interventions (JITAIs) delivered via mobile devices have been developed for preventing and treating addictions. JITAIs adapt over time to an individual’s changing status and are optimized to provide appropriate intervention strategies based on real time, real world context. Organizing frameworks on JITAIs emphasize minimizing disruptions to the daily lives and routines of the individual, by tailoring strategies not only to vulnerability, but also to receptivity (i.e., an individual’s ability and willingness to utilize a particular intervention). Although both vulnerability and receptivity are considered latent states that are dynamically and constantly changing based on the constellation and temporal dynamics of emotions, context, and other factors, no attempt has been made to systematically investigate the nature of these states, as well as how knowledge of these states can be used to optimize real-time engagement in self-regulatory activities. To close this gap, the proposed project will apply innovative computational approaches to one of the most extensive and racially/ethnically diverse collection of real time, real world data on health behavior change (smoking cessation). Intensive longitudinal self-reported and sensor data from 5 studies (3 completed and 2 ongoing) of ~1,500 smokers attempting to quit will be analyzed with advanced probabilistic latent variable models and machine learning to investigate how the temporal dynamics and interactions of emotions, self-regulatory capacity (SRC), context, and other factors can be used to detect (Aim 1) states of vulnerability to a lapse and (Aim 2) states of receptivity to engaging in self-regulatory activities. We will also investigate (Aim 3) how knowledge of these states can be used to optimize real-time engagement in self-regulatory activities by conducting a Micro-Randomized Trial (MRT) enrolling 150 smokers attempting to quit. Utilizing a mobile smoking cessation app, the MRT will randomize each individual multiple times per day to either (a) no intervention prompt; (b) a prompt recommending engagement in brief (low effort) strategies; or (c) a prompt recommending a more effortful practice of self-regulation strategies. The proposed research will be the first to yield a comprehensive conceptual, technical, and empirical foundation necessary to develop effective JITAIs based on dynamic models of vulnerability and receptivity.




Data integration methods for micro-randomized trials.
Authors: Huch E. , Nahum-Shani I. , Potter L. , Lam C. , Wetter D.W. , Dempsey W. .
Source: Biometrics, 2025-04-02 00:00:00.0; 81(2), .
PMID: 40326461
Related Citations

Momentary predictors of tobacco lapse among African Americans during a quit attempt.
Authors: Potter L.N. , Jones D.R. , Schlechter C.R. , Lam C.Y. , Nahum-Shani I. , Fagundes C.P. , Wetter D.W. .
Source: Addictive Behaviors, 2025 Mar; 162, p. 108231.
EPub date: 2024-12-12 00:00:00.0.
PMID: 39693676
Related Citations

Is dosage of a meditation app associated with changes in psychological distress? It depends on how you ask.
Authors: Goldberg S.B. , Kendall A.D. , Hirshberg M.J. , Dahl C.J. , Nahum-Shani I. , Davidson R.J. , Bray B.C. .
Source: Clinical Psychological Science : A Journal Of The Association For Psychological Science, 2025 Mar; 13(2), p. 332-349.
EPub date: 2024-08-26 00:00:00.0.
PMID: 40162042
Related Citations

Examining Bi-directional links between distinct affect states and tobacco lapse during a cessation attempt.
Authors: Jones D.R. , Potter L.N. , Lam C.Y. , Nahum-Shani I. , Fagundes C. , Wetter D.W. .
Source: Drug And Alcohol Dependence, 2025-02-01 00:00:00.0; 267, p. 112526.
EPub date: 2024-12-19 00:00:00.0.
PMID: 39740306
Related Citations

Correlates of nicotine patch adherence in daily life.
Authors: Potter L.N. , Jones D.R. , Braudt D.B. , Nahum-Shani I. , Lam C.Y. , Fagundes C. , Wetter D.W. .
Source: Drug And Alcohol Dependence, 2025-01-01 00:00:00.0; 266, p. 112499.
EPub date: 2024-11-17 00:00:00.0.
PMID: 39577027
Related Citations

A Deployed Online Reinforcement Learning Algorithm In An Oral Health Clinical Trial.
Authors: Trella A.L. , Zhang K.W. , Jajal H. , Nahum-Shani I. , Shetty V. , Doshi-Velez F. , Murphy S.A. .
Source: Proceedings Of The ... Aaai Conference On Artificial Intelligence. Aaai Conference On Artificial Intelligence, 2025; 39(28), p. 28792-28800.
EPub date: 2025-04-11 00:00:00.0.
PMID: 40452862
Related Citations

Towards the Science of Engagement with Digital Interventions.
Authors: Nahum-Shani I. , Yoon C. .
Source: Current Directions In Psychological Science, 2024 Aug; 33(4), p. 239-246.
EPub date: 2024-06-03 00:00:00.0.
PMID: 39552747
Related Citations

A latent variable approach to jointly modeling longitudinal and cumulative event data using a weighted two-stage method.
Authors: Abbott M.R. , Nahum-Shani I. , Lam C.Y. , Potter L.N. , Wetter D.W. , Dempsey W.H. .
Source: Statistics In Medicine, 2024-07-18 00:00:00.0; , .
EPub date: 2024-07-18 00:00:00.0.
PMID: 39030763
Related Citations

Did we personalize? Assessing personalization by an online reinforcement learning algorithm using resampling.
Authors: Ghosh S. , Kim R. , Chhabria P. , Dwivedi R. , Klasnja P. , Liao P. , Zhang K. , Murphy S. .
Source: Machine Learning, 2024 Jul; 113(7), p. 3961-3997.
EPub date: 2024-04-10 00:00:00.0.
PMID: 39221170
Related Citations

Examining Links Between Distinct Affective States and Tobacco Lapse During a Cessation Attempt Among African Americans: A Cohort Study.
Authors: Jones D.R. , Potter L.N. , Lam C.Y. , Schlechter C.R. , Nahum-Shani I. , Fagundes C. , Wetter D.W. .
Source: Annals Of Behavioral Medicine : A Publication Of The Society Of Behavioral Medicine, 2024-06-18 00:00:00.0; 58(7), p. 506-516.
PMID: 38740389
Related Citations

Is informal practice associated with outcomes in loving-kindness and compassion training? Evidence from pre-post and daily diary assessments.
Authors: Xie Q. , Riordan K.M. , Baldwin S.A. , Simonsson O. , Hirshberg M.J. , Dahl C.J. , Nahum-Shani I. , Davidson R.J. , Goldberg S.B. .
Source: Behaviour Research And Therapy, 2024-04-08 00:00:00.0; 177, p. 104537.
EPub date: 2024-04-08 00:00:00.0.
PMID: 38608409
Related Citations

Optimizing an adaptive digital oral health intervention for promoting oral self-care behaviors: Micro-randomized trial protocol.
Authors: Nahum-Shani I. , Greer Z.M. , Trella A.L. , Zhang K.W. , Carpenter S.M. , Rünger D. , Elashoff D. , Murphy S.A. , Shetty V. .
Source: Contemporary Clinical Trials, 2024 Apr; 139, p. 107464.
EPub date: 2024-02-01 00:00:00.0.
PMID: 38307224
Related Citations

Design of experiments with sequential randomizations on multiple timescales: the hybrid experimental design.
Authors: Nahum-Shani I. , Dziak J.J. , Venera H. , Pfammatter A.F. , Spring B. , Dempsey W. .
Source: Behavior Research Methods, 2024 Mar; 56(3), p. 1770-1792.
EPub date: 2023-05-08 00:00:00.0.
PMID: 37156958
Related Citations

Understanding the Implementation of Informal Meditation Practice in a Smartphone-Based Intervention: A Qualitative Analysis.
Authors: Xie Q. , Dyer R.L. , Lam S.U. , Frye C. , Dahl C.J. , Quanbeck A. , Nahum-Shani I. , Davidson R.J. , Goldberg S.B. .
Source: Mindfulness, 2024 Feb; 15(2), p. 479-490.
EPub date: 2024-01-22 00:00:00.0.
PMID: 39070019
Related Citations

Digital Adaptive Behavioral Interventions to Improve HIV Prevention and Care: Innovations in Intervention Approach and Experimental Design.
Authors: Nahum-Shani I. , Naar S. .
Source: Current Hiv/aids Reports, 2023 Dec; 20(6), p. 502-512.
EPub date: 2023-11-04 00:00:00.0.
PMID: 37924458
Related Citations

Reward Design For An Online Reinforcement Learning Algorithm Supporting Oral Self-Care.
Authors: Trella A.L. , Zhang K.W. , Nahum-Shani I. , Shetty V. , Doshi-Velez F. , Murphy S.A. .
Source: Proceedings Of The ... Innovative Applications Of Artificial Intelligence Conference. Innovative Applications Of Artificial Intelligence Conference, 2023-06-27 00:00:00.0; 37(13), p. 15724-15730.
PMID: 37637073
Related Citations

How Notifications Affect Engagement With a Behavior Change App: Results From a Micro-Randomized Trial.
Authors: Bell L. , Garnett C. , Bao Y. , Cheng Z. , Qian T. , Perski O. , Potts H.W.W. , Williamson E. .
Source: Jmir Mhealth And Uhealth, 2023-06-09 00:00:00.0; 11, p. e38342.
EPub date: 2023-06-09 00:00:00.0.
PMID: 37294612
Related Citations

Socio-economic status moderates within-person associations of risk factors and smoking lapse in daily life.
Authors: Potter L.N. , Schlechter C.R. , Nahum-Shani I. , Lam C.Y. , Cinciripini P.M. , Wetter D.W. .
Source: Addiction (abingdon, England), 2023 May; 118(5), p. 925-934.
EPub date: 2023-01-10 00:00:00.0.
PMID: 36564898
Related Citations

Integrating Intensive Longitudinal Data (ILD) to Inform the Development of Dynamic Theories of Behavior Change and Intervention Design: a Case Study of Scientific and Practical Considerations.
Authors: Potter L.N. , Yap J. , Dempsey W. , Wetter D.W. , Nahum-Shani I. .
Source: Prevention Science : The Official Journal Of The Society For Prevention Research, 2023-04-15 00:00:00.0; , .
EPub date: 2023-04-15 00:00:00.0.
PMID: 37060480
Related Citations

The ILHBN: challenges, opportunities, and solutions from harmonizing data under heterogeneous study designs, target populations, and measurement protocols.
Authors: Chow S.M. , Nahum-Shani I. , Baker J.T. , Spruijt-Metz D. , Allen N.B. , Auerbach R.P. , Dunton G.F. , Friedman N.P. , Intille S.S. , Klasnja P. , et al. .
Source: Translational Behavioral Medicine, 2023-01-20 00:00:00.0; 13(1), p. 7-16.
PMID: 36416389
Related Citations

Streamlined Variational Inference for Linear Mixed Models with Crossed Random Effects.
Authors: Menictas M. , Di Credico G. , Wand M.P. .
Source: Journal Of Computational And Graphical Statistics : A Joint Publication Of American Statistical Association, Institute Of Mathematical Statistics, Interface Foundation Of North America, 2023; 32(1), p. 99-115.
EPub date: 2022-09-01 00:00:00.0.
PMID: 36873962
Related Citations

Time-varying model of engagement with digital self reporting: Evidence from smoking cessation longitudinal studies.
Authors: Sobolev M. , Anand A. , Dziak J.J. , Potter L.N. , Lam C.Y. , Wetter D.W. , Nahum-Shani I. .
Source: Frontiers In Digital Health, 2023; 5, p. 1144081.
EPub date: 2023-04-13 00:00:00.0.
PMID: 37122813
Related Citations

Multiple imputation of missing data in multilevel ecological momentary assessments: an example using smoking cessation study data.
Authors: Ji L. , Li Y. , Potter L.N. , Lam C.Y. , Nahum-Shani I. , Wetter D.W. , Chow S.M. .
Source: Frontiers In Digital Health, 2023; 5, p. 1099517.
EPub date: 2023-11-10 00:00:00.0.
PMID: 38026834
Related Citations

Editorial: Digital technology for tobacco control: Novel data collection, study designs, and interventions.
Authors: Potter L.N. , Nahum-Shani I. , Wetter D.W. .
Source: Frontiers In Digital Health, 2023; 5, p. 1341759.
EPub date: 2023-12-01 00:00:00.0.
PMID: 38107825
Related Citations

BATCH POLICY LEARNING IN AVERAGE REWARD MARKOV DECISION PROCESSES.
Authors: Liao P. , Qi Z. , Wan R. , Klasnja P. , Murphy S.A. .
Source: Annals Of Statistics, 2022 Dec; 50(6), p. 3364-3387.
EPub date: 2022-12-21 00:00:00.0.
PMID: 37022318
Related Citations

mRisk: Continuous Risk Estimation for Smoking Lapse from Noisy Sensor Data with Incomplete and Positive-Only Labels.
Authors: Ullah M.A. , Chatterjee S. , Fagundes C.P. , Lam C. , Nahum-Shani I. , Rehg J.M. , Wetter D.W. , Kumar S. .
Source: Proceedings Of The Acm On Interactive, Mobile, Wearable And Ubiquitous Technologies, 2022 Sep; 6(3), .
EPub date: 2022-09-07 00:00:00.0.
PMID: 36873428
Related Citations

Designing Reinforcement Learning Algorithms for Digital Interventions: Pre-Implementation Guidelines.
Authors: Trella A.L. , Zhang K.W. , Nahum-Shani I. , Shetty V. , Doshi-Velez F. , Murphy S.A. .
Source: Algorithms, 2022 Aug; 15(8), .
EPub date: 2022-07-22 00:00:00.0.
PMID: 36713810
Related Citations

Just-in-Time Adaptive Interventions for Suicide Prevention: Promise, Challenges, and Future Directions.
Authors: Coppersmith D.D.L. , Dempsey W. , Kleiman E.M. , Bentley K.H. , Murphy S.A. , Nock M.K. .
Source: Psychiatry, 2022-07-18 00:00:00.0; , p. 1-17.
EPub date: 2022-07-18 00:00:00.0.
PMID: 35848800
Related Citations

Self-relevant appeals to engage in self-monitoring of alcohol use: A microrandomized trial.
Authors: Carpenter S.M. , Yap J. , Patrick M.E. , Morrell N. , Dziak J.J. , Almirall D. , Yoon C. , Nahum-Shani I. .
Source: Psychology Of Addictive Behaviors : Journal Of The Society Of Psychologists In Addictive Behaviors, 2022-07-14 00:00:00.0; , .
EPub date: 2022-07-14 00:00:00.0.
PMID: 35834200
Related Citations

Hybrid Experimental Designs for Intervention Development: What, Why, and How.
Authors: Nahum-Shani I. , Dziak J.J. , Walton M.A. , Dempsey W. .
Source: Advances In Methods And Practices In Psychological Science, 2022 Jul-Sep; 5(3), .
EPub date: 2022-09-07 00:00:00.0.
PMID: 36935844
Related Citations

Data-driven Interpretable Policy Construction for Personalized Mobile Health.
Authors: Bertsimas D. , Klasnja P. , Murphy S. , Na L. .
Source: 2022 Ieee International Conference On Digital Health (ieee Icdh 2022) : Proceedings : Hybrid Conference, Barcelona, Spain, 11-15 July 2022. International Conference On Digital Health (2022 : Barcelona, Spain; Online), 2022 Jul; 2022, p. 13-22.
EPub date: 2022-08-24 00:00:00.0.
PMID: 37965645
Related Citations

Digital Prompts to Increase Engagement With the Headspace App and for Stress Regulation Among Parents: Feasibility Study.
Authors: Militello L. , Sobolev M. , Okeke F. , Adler D.A. , Nahum-Shani I. .
Source: Jmir Formative Research, 2022-03-21 00:00:00.0; 6(3), p. e30606.
EPub date: 2022-03-21 00:00:00.0.
PMID: 35311675
Related Citations

Engagement in digital interventions.
Authors: Nahum-Shani I. , Shaw S.D. , Carpenter S.M. , Murphy S.A. , Yoon C. .
Source: The American Psychologist, 2022-03-17 00:00:00.0; , .
EPub date: 2022-03-17 00:00:00.0.
PMID: 35298199
Related Citations

The microrandomized trial for developing digital interventions: Experimental design and data analysis considerations.
Authors: Qian T. , Walton A.E. , Collins L.M. , Klasnja P. , Lanza S.T. , Nahum-Shani I. , Rabbi M. , Russell M.A. , Walton M.A. , Yoo H. , et al. .
Source: Psychological Methods, 2022-01-13 00:00:00.0; , .
EPub date: 2022-01-13 00:00:00.0.
PMID: 35025583
Related Citations

New Directions for Motivational Incentive Interventions for Smoking Cessation.
Authors: Coughlin L.N. , Bonar E.E. , Walton M.A. , Fernandez A.C. , Duguid I. , Nahum-Shani I. .
Source: Frontiers In Digital Health, 2022; 4, p. 803301.
EPub date: 2022-02-28 00:00:00.0.
PMID: 35310552
Related Citations

MCMTC: A Pragmatic Framework for Selecting an Experimental Design to Inform the Development of Digital Interventions.
Authors: Nahum-Shani I. , Dziak J.J. , Wetter D.W. .
Source: Frontiers In Digital Health, 2022; 4, p. 798025.
EPub date: 2022-03-09 00:00:00.0.
PMID: 35355685
Related Citations

Predicting short-term suicidal thoughts in adolescents using machine learning: developing decision tools to identify daily level risk after hospitalization.
Authors: Czyz E.K. , Koo H.J. , Al-Dajani N. , King C.A. , Nahum-Shani I. .
Source: Psychological Medicine, 2021-12-09 00:00:00.0; , p. 1-10.
EPub date: 2021-12-09 00:00:00.0.
PMID: 34879890
Related Citations

Statistical Inference with M-Estimators on Adaptively Collected Data.
Authors: Zhang K.W. , Janson L. , Murphy S.A. .
Source: Advances In Neural Information Processing Systems, 2021 Dec; 34, p. 7460-7471.
PMID: 35757490
Related Citations

Translating strategies for promoting engagement in mobile health: A proof-of-concept microrandomized trial.
Authors: Nahum-Shani I. , Rabbi M. , Yap J. , Philyaw-Kotov M.L. , Klasnja P. , Bonar E.E. , Cunningham R.M. , Murphy S.A. , Walton M.A. .
Source: Health Psychology : Official Journal Of The Division Of Health Psychology, American Psychological Association, 2021-11-04 00:00:00.0; , .
EPub date: 2021-11-04 00:00:00.0.
PMID: 34735165
Related Citations

Understanding Adolescent and Young Adult 6-Mercaptopurine Adherence and mHealth Engagement During Cancer Treatment: Protocol for Ecological Momentary Assessment.
Authors: Psihogios A.M. , Rabbi M. , Ahmed A. , McKelvey E.R. , Li Y. , Laurenceau J.P. , Hunger S.P. , Fleisher L. , Pai A.L. , Schwartz L.A. , et al. .
Source: Jmir Research Protocols, 2021-10-22 00:00:00.0; 10(10), p. e32789.
EPub date: 2021-10-22 00:00:00.0.
PMID: 34677129
Related Citations

Rejoinder: 'Estimating time-varying causal excursion effects in mobile health with binary outcomes'.
Authors: Qian T. , Yoo H. , Klasnja P. , Almirall D. , Murphy S.A. .
Source: Biometrika, 2021 Sep; 108(3), p. 551-555.
EPub date: 2021-08-12 00:00:00.0.
PMID: 34400906
Related Citations

IntelligentPooling: Practical Thompson Sampling for mHealth.
Authors: Tomkins S. , Liao P. , Klasnja P. , Murphy S. .
Source: Machine Learning, 2021 Sep; 110(9), p. 2685-2727.
EPub date: 2021-06-21 00:00:00.0.
PMID: 34621105
Related Citations

Estimating time-varying causal excursion effect in mobile health with binary outcomes.
Authors: Qian T. , Yoo H. , Klasnja P. , Almirall D. , Murphy S.A. .
Source: Biometrika, 2021 Sep; 108(3), p. 507-527.
EPub date: 2020-09-04 00:00:00.0.
PMID: 34629476
Related Citations

Sense2Stop: A micro-randomized trial using wearable sensors to optimize a just-in-time-adaptive stress management intervention for smoking relapse prevention.
Authors: Battalio S.L. , Conroy D.E. , Dempsey W. , Liao P. , Menictas M. , Murphy S. , Nahum-Shani I. , Qian T. , Kumar S. , Spring B. .
Source: Contemporary Clinical Trials, 2021-08-08 00:00:00.0; 109, p. 106534.
EPub date: 2021-08-08 00:00:00.0.
PMID: 34375749
Related Citations

Power Constrained Bandits.
Authors: Yao J. , Brunskill E. , Pan W. , Murphy S. , Doshi-Velez F. .
Source: Proceedings Of Machine Learning Research, 2021 Aug; 149, p. 209-259.
PMID: 34927078
Related Citations

The mobile assistance for regulating smoking (MARS) micro-randomized trial design protocol.
Authors: Nahum-Shani I. , Potter L.N. , Lam C.Y. , Yap J.R. , Moreno A. , Stoffel R. , Wu Z. , Wan N. , Dempsey W. , Kumar S. , et al. .
Source: Contemporary Clinical Trials, 2021-07-24 00:00:00.0; , p. 106513.
EPub date: 2021-07-24 00:00:00.0.
PMID: 34314855
Related Citations

mTeeth: Identifying Brushing Teeth Surfaces Using Wrist-Worn Inertial Sensors.
Authors: Akther S. , Saleheen N. , Saha M. , Shetty V. , Kumar S. .
Source: Proceedings Of The Acm On Interactive, Mobile, Wearable And Ubiquitous Technologies, 2021 Jun; 5(2), .
EPub date: 2021-06-24 00:00:00.0.
PMID: 35309968
Related Citations

Smoking Cessation Using Wearable Sensors: Protocol for a Microrandomized Trial.
Authors: Hernandez L.M. , Wetter D.W. , Kumar S. , Sutton S.K. , Vinci C. .
Source: Jmir Research Protocols, 2021-02-24 00:00:00.0; 10(2), p. e22877.
EPub date: 2021-02-24 00:00:00.0.
PMID: 33625366
Related Citations

The Validity of MotionSense HRV in Estimating Sedentary Behavior and Physical Activity under Free-Living and Simulated Activity Settings.
Authors: Kwon S. , Wan N. , Burns R.D. , Brusseau T.A. , Kim Y. , Kumar S. , Ertin E. , Wetter D.W. , Lam C.Y. , Wen M. , et al. .
Source: Sensors (basel, Switzerland), 2021-02-18 00:00:00.0; 21(4), .
EPub date: 2021-02-18 00:00:00.0.
PMID: 33670507
Related Citations

Intersectionality and Smoking Cessation: Exploring Various Approaches for Understanding Health Inequities.
Authors: Potter L.N. , Lam C.Y. , Cinciripini P.M. , Wetter D.W. .
Source: Nicotine & Tobacco Research : Official Journal Of The Society For Research On Nicotine And Tobacco, 2021-01-07 00:00:00.0; 23(1), p. 115-123.
PMID: 32208484
Related Citations