ArticleFrontiers in digital health2022
MCMTC: A Pragmatic Framework for Selecting an Experimental Design to Inform the Development of Digital Interventions.
Article in Frontiers in digital health, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers.
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Who cites it
16 citing papers in PubMed.
- Mobile Intervention for Increasing COVID-19 Testing in K-12 Schools Serving Disadvantaged Communities: Randomized Controlled Trial of SCALE-UP Counts.Journal of medical Internet research · 2025Trial
- Engagement, Acceptability, and Effectiveness of the Self-Care and Coach-Supported Versions of the Vira Digital Behavior Change Platform Among Young Adults at Risk for Depression and Obesity: Pilot Randomized Controlled Trial.JMIR mental health · 2024Trial
- A bibliometric analysis of research on the application of just-in-time adaptive interventions in mental health.Medicine · 2026Review
- Co-Develop-IT! Unifying Methodological Guideline for the Co-Design, Development, and Evaluation of Individually Tailored Technology-Enhanced Training and Rehabilitation Concepts: Consensus Development Study and Tutorial.Journal of medical Internet research · 2026Article
- Just-in-Time Adaptive Interventions: Where Are We Now and What Is Next?Annual review of psychology · 2026Review
- Optimizing the impact of supportive cancer care digital health interventions: considerations for design, development, and evaluation.Supportive care in cancer : official journal of the Multinational Association of Supportive Care in Cancer · 2025Review
- A Holistic Digital Health Framework to Support Health Prevention Strategies in the First 1000 Days.JMIR pediatrics and parenting · 2025Article
- Designing digital health interventions with causal inference and multi-armed bandits: a review.Frontiers in digital health · 2025Review
- Intervention Optimization: A Paradigm Shift and Its Potential Implications for Clinical Psychology.Annual review of clinical psychology · 2024Review
- The Digital Therapeutics Real-World Evidence Framework: An Approach for Guiding Evidence-Based Digital Therapeutics Design, Development, Testing, and Monitoring.Journal of medical Internet research · 2024Article
- Remote Symptom Monitoring to Enhance the Delivery of Palliative Cancer Care in Low-Resource Settings: Emerging Approaches from Africa.International journal of environmental research and public health · 2023Article
- Digital Adaptive Behavioral Interventions to Improve HIV Prevention and Care: Innovations in Intervention Approach and Experimental Design.Current HIV/AIDS reports · 2023Review
- Sample size estimation for comparing dynamic treatment regimens in a SMART: A Monte Carlo-based approach and case study with longitudinal overdispersed count outcomes.Statistical methods in medical research · 2023Article
- The Sequential Multiple Assignment Randomized Trial for Controlling Infectious Diseases: A Review of Recent Developments.American journal of public health · 2023Review
- Adaptive Interventions for a Dynamic and Responsive Public Health Approach.American journal of public health · 2023Article
- Hybrid Experimental Designs for Intervention Development: What, Why, and How.Advances in methods and practices in psychological scienceArticle
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3 authors.
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Abstract
Advances in digital technologies have created unprecedented opportunities to deliver effective and scalable behavior change interventions. Many digital interventions include multiple components, namely several aspects of the intervention that can be differentiated for systematic investigation. Various types of experimental approaches have been developed in recent years to enable researchers to obtain the empirical evidence necessary for the development of effective multiple-component interventions. These include factorial designs, Sequential Multiple Assignment Randomized Trials (SMARTs), and Micro-Randomized Trials (MRTs). An important challenge facing researchers concerns selecting the right type of design to match their scientific questions. Here, we propose MCMTC - a pragmatic framework that can be used to guide investigators interested in developing digital interventions in deciding which experimental approach to select. This framework includes five questions that investigators are encouraged to answer in the process of selecting the most suitable design: (1) Multiple-component intervention: Is the goal to develop an intervention that includes multiple components; (2) Component selection: Are there open scientific questions about the selection of specific components for inclusion in the intervention; (3) More than a single component: Are there open scientific questions about the inclusion of more than a single component in the intervention; (4) Timing: Are there open scientific questions about the timing of component delivery, that is when to deliver specific components; and (5) Change: Are the components in question designed to address conditions that change relatively slowly (e.g., over months or weeks) or rapidly (e.g., every day, hours, minutes). Throughout we use examples of tobacco cessation digital interventions to illustrate the process of selecting a design by answering these questions. For simplicity we focus exclusively on four experimental approaches-standard two- or multi-arm randomized trials, classic factorial designs, SMARTs, and MRTs-acknowledging that the array of possible experimental approaches for developing digital interventions is not limited to these designs.
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