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You Don't Need an App—Conducting Mobile Smoking Research Using a Qualtrics-Based Approach

With the increasing availability of smartphones, many tobacco researchers are exploring smartphone-delivered mobile smoking interventions as a disseminable means of treatment. Most effort has been focused on the development of smartphone applications (apps) to conduct mobile smoking research to impl...

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Autores principales: Cui, Yong, Robinson, Jason D., Rymer, Rudel E., Minnix, Jennifer A., Cinciripini, Paul M.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8770325/
https://www.ncbi.nlm.nih.gov/pubmed/35072151
http://dx.doi.org/10.3389/fdgth.2021.799468
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author Cui, Yong
Robinson, Jason D.
Rymer, Rudel E.
Minnix, Jennifer A.
Cinciripini, Paul M.
author_facet Cui, Yong
Robinson, Jason D.
Rymer, Rudel E.
Minnix, Jennifer A.
Cinciripini, Paul M.
author_sort Cui, Yong
collection PubMed
description With the increasing availability of smartphones, many tobacco researchers are exploring smartphone-delivered mobile smoking interventions as a disseminable means of treatment. Most effort has been focused on the development of smartphone applications (apps) to conduct mobile smoking research to implement and validate these interventions. However, developing project-specific smartphone apps that work across multiple mobile platforms (e.g., iOS and Android) can be costly and time-consuming. Here, using a hypothetical study, we present an alternate approach to demonstrate how mobile smoking cessation and outcome evaluation can be conducted without the need of a dedicated app. Our approach uses the Qualtrics platform, a popular online survey host that is used under license by many academic institutions. This platform allows researchers to conduct device-agnostic screening, consenting, and administration of questionnaires through Qualtrics's native survey engine. Researchers can also collect ecological momentary assessment data using text messaging prompts with the incorporation of Amazon Web Services' Pinpoint. Besides these assessment capabilities, Qualtrics has the potential for delivering personalized behavioral interventions through the use of JavaScript code. By customizing the question's web elements in Qualtrics (e.g., using texts, images, videos, and buttons), researchers can integrate interactive web-based interventions and complicated behavioral and cognitive tasks into the survey. In conclusion, this Qualtrics-based methodology represents a novel and cost-effective approach for conducting mobile smoking cessation and assessment research.
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spelling pubmed-87703252022-01-21 You Don't Need an App—Conducting Mobile Smoking Research Using a Qualtrics-Based Approach Cui, Yong Robinson, Jason D. Rymer, Rudel E. Minnix, Jennifer A. Cinciripini, Paul M. Front Digit Health Digital Health With the increasing availability of smartphones, many tobacco researchers are exploring smartphone-delivered mobile smoking interventions as a disseminable means of treatment. Most effort has been focused on the development of smartphone applications (apps) to conduct mobile smoking research to implement and validate these interventions. However, developing project-specific smartphone apps that work across multiple mobile platforms (e.g., iOS and Android) can be costly and time-consuming. Here, using a hypothetical study, we present an alternate approach to demonstrate how mobile smoking cessation and outcome evaluation can be conducted without the need of a dedicated app. Our approach uses the Qualtrics platform, a popular online survey host that is used under license by many academic institutions. This platform allows researchers to conduct device-agnostic screening, consenting, and administration of questionnaires through Qualtrics's native survey engine. Researchers can also collect ecological momentary assessment data using text messaging prompts with the incorporation of Amazon Web Services' Pinpoint. Besides these assessment capabilities, Qualtrics has the potential for delivering personalized behavioral interventions through the use of JavaScript code. By customizing the question's web elements in Qualtrics (e.g., using texts, images, videos, and buttons), researchers can integrate interactive web-based interventions and complicated behavioral and cognitive tasks into the survey. In conclusion, this Qualtrics-based methodology represents a novel and cost-effective approach for conducting mobile smoking cessation and assessment research. Frontiers Media S.A. 2022-01-06 /pmc/articles/PMC8770325/ /pubmed/35072151 http://dx.doi.org/10.3389/fdgth.2021.799468 Text en Copyright © 2022 Cui, Robinson, Rymer, Minnix and Cinciripini. 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
Cui, Yong
Robinson, Jason D.
Rymer, Rudel E.
Minnix, Jennifer A.
Cinciripini, Paul M.
You Don't Need an App—Conducting Mobile Smoking Research Using a Qualtrics-Based Approach
title You Don't Need an App—Conducting Mobile Smoking Research Using a Qualtrics-Based Approach
title_full You Don't Need an App—Conducting Mobile Smoking Research Using a Qualtrics-Based Approach
title_fullStr You Don't Need an App—Conducting Mobile Smoking Research Using a Qualtrics-Based Approach
title_full_unstemmed You Don't Need an App—Conducting Mobile Smoking Research Using a Qualtrics-Based Approach
title_short You Don't Need an App—Conducting Mobile Smoking Research Using a Qualtrics-Based Approach
title_sort you don't need an app—conducting mobile smoking research using a qualtrics-based approach
topic Digital Health
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8770325/
https://www.ncbi.nlm.nih.gov/pubmed/35072151
http://dx.doi.org/10.3389/fdgth.2021.799468
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