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

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

Journal

Frontiers in digital health
ISSN: 2673-253X
Titre abrégé: Front Digit Health
Pays: Switzerland
ID NLM: 101771889

Informations de publication

Date de publication:
2022
Historique:
received: 19 10 2021
accepted: 24 01 2022
entrez: 31 3 2022
pubmed: 1 4 2022
medline: 1 4 2022
Statut: epublish

Résumé

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.

Identifiants

pubmed: 35355685
doi: 10.3389/fdgth.2022.798025
pmc: PMC8959436
doi:

Types de publication

Journal Article

Langues

eng

Pagination

798025

Subventions

Organisme : NIDA NIH HHS
ID : P50 DA039838
Pays : United States
Organisme : NIDA NIH HHS
ID : P50 DA054039
Pays : United States
Organisme : NIDA NIH HHS
ID : R01 DA039901
Pays : United States
Organisme : NCI NIH HHS
ID : U01 CA229437
Pays : United States

Informations de copyright

Copyright © 2022 Nahum-Shani, Dziak and Wetter.

Déclaration de conflit d'intérêts

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.

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Auteurs

Inbal Nahum-Shani (I)

Insitute for Social Research, University of Michigan, Ann Arbor, MI, United States.

John J Dziak (JJ)

Edna Bennett Pierce Prevention Research Center, The Pennsylvania State University, State College, PA, United States.

David W Wetter (DW)

Huntsman Cancer Institute, University of Utah, Salt Lake City, UT, United States.

Classifications MeSH