Skip to main page content
U.S. flag

An official website of the United States government

Dot gov

The .gov means it’s official.
Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you’re on a federal government site.

Https

The site is secure.
The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.

Access keys NCBI Homepage MyNCBI Homepage Main Content Main Navigation
. 2022 Mar 9:4:798025.
doi: 10.3389/fdgth.2022.798025. eCollection 2022.

MCMTC: A Pragmatic Framework for Selecting an Experimental Design to Inform the Development of Digital Interventions

Affiliations

MCMTC: A Pragmatic Framework for Selecting an Experimental Design to Inform the Development of Digital Interventions

Inbal Nahum-Shani et al. Front Digit Health. .

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.

Keywords: Micro-Randomized Trial (MRT); Sequential Multiple Assignment Randomized Trial (SMART); adaptive interventions; digital interventions; factorial designs; just in time adaptive interventions.

PubMed Disclaimer

Conflict of interest statement

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Figures

Figure 1
Figure 1
MCMTC: a pragmatic framework for selecting an experimental design to inform the development of digital interventions.
Figure 2
Figure 2
Hypothetical adaptive intervention (Example C).
Figure 3
Figure 3
SMART study to answer example C scientific questions.
Figure 4
Figure 4
Hypothetical just in time adaptive intervention (Example D).
Figure 5
Figure 5
A MRT to answer Example E scientific questions.

Similar articles

Cited by

References

    1. Whittaker R, McRobbie H, Bullen C, Rodgers A, Gu Y. Mobile phone-based interventions for smoking cessation. Cochrane Database Syst Rev. (2016) 4:CD006611. 10.1002/14651858.CD006611.pub4 - DOI - PMC - PubMed
    1. Han M, Lee E. Effectiveness of mobile health application use to improve health behavior changes: a systematic review of randomized controlled trials. Healthc Inform Res. (2018) 24:207. 10.4258/hir.2018.24.3.207 - DOI - PMC - PubMed
    1. Milne-Ives M, Lam C, De Cock C, Van Velthoven MH, Meinert E. Mobile apps for health behavior change in physical activity, diet, drug and alcohol use, and mental health: systematic review. JMIR mHealth uHealth. (2020) 8:e17046. 10.2196/17046 - DOI - PMC - PubMed
    1. Collins LM. Optimization of Behavioral, Biobehavioral, and Biomedical Interventions: The Multiphase Optimization Strategy (MOST). Cham: Springer; (2018).
    1. Crane D, Garnett C, Michie S, West R, Brown J. A smartphone app to reduce excessive alcohol consumption: identifying the effectiveness of intervention components in a factorial randomised control trial. Sci Rep. (2018) 8:1–11. 10.1038/s41598-018-22420-8 - DOI - PMC - PubMed

LinkOut - more resources