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

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. Vario...

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Autores principales: Nahum-Shani, Inbal, Dziak, John J., Wetter, David W.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8959436/
https://www.ncbi.nlm.nih.gov/pubmed/35355685
http://dx.doi.org/10.3389/fdgth.2022.798025
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author Nahum-Shani, Inbal
Dziak, John J.
Wetter, David W.
author_facet Nahum-Shani, Inbal
Dziak, John J.
Wetter, David W.
author_sort Nahum-Shani, Inbal
collection PubMed
description 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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spelling pubmed-89594362022-03-29 MCMTC: A Pragmatic Framework for Selecting an Experimental Design to Inform the Development of Digital Interventions Nahum-Shani, Inbal Dziak, John J. Wetter, David W. Front Digit Health Digital Health 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. Frontiers Media S.A. 2022-03-09 /pmc/articles/PMC8959436/ /pubmed/35355685 http://dx.doi.org/10.3389/fdgth.2022.798025 Text en Copyright © 2022 Nahum-Shani, Dziak and Wetter. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
spellingShingle Digital Health
Nahum-Shani, Inbal
Dziak, John J.
Wetter, David W.
MCMTC: A Pragmatic Framework for Selecting an Experimental Design to Inform the Development of Digital Interventions
title MCMTC: A Pragmatic Framework for Selecting an Experimental Design to Inform the Development of Digital Interventions
title_full MCMTC: A Pragmatic Framework for Selecting an Experimental Design to Inform the Development of Digital Interventions
title_fullStr MCMTC: A Pragmatic Framework for Selecting an Experimental Design to Inform the Development of Digital Interventions
title_full_unstemmed MCMTC: A Pragmatic Framework for Selecting an Experimental Design to Inform the Development of Digital Interventions
title_short MCMTC: A Pragmatic Framework for Selecting an Experimental Design to Inform the Development of Digital Interventions
title_sort mcmtc: a pragmatic framework for selecting an experimental design to inform the development of digital interventions
topic Digital Health
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8959436/
https://www.ncbi.nlm.nih.gov/pubmed/35355685
http://dx.doi.org/10.3389/fdgth.2022.798025
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