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Increasing Physical Activity Amongst Overweight and Obese Cancer Survivors Using an Alexa-Based Intelligent Agent for Patient Coaching: Protocol for the Physical Activity by Technology Help (PATH) Trial
BACKGROUND: Physical activity has established health benefits, but motivation and adherence remain challenging. OBJECTIVE: We designed and launched a three-arm randomized trial to test artificial intelligence technology solutions to increase daily physical activity in cancer survivors. METHODS: A si...
Autores principales: | , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
JMIR Publications
2018
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5826976/ https://www.ncbi.nlm.nih.gov/pubmed/29434016 http://dx.doi.org/10.2196/resprot.9096 |
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author | Hassoon, Ahmed Schrack, Jennifer Naiman, Daniel Lansey, Dina Baig, Yasmin Stearns, Vered Celentano, David Martin, Seth Appel, Lawrence |
author_facet | Hassoon, Ahmed Schrack, Jennifer Naiman, Daniel Lansey, Dina Baig, Yasmin Stearns, Vered Celentano, David Martin, Seth Appel, Lawrence |
author_sort | Hassoon, Ahmed |
collection | PubMed |
description | BACKGROUND: Physical activity has established health benefits, but motivation and adherence remain challenging. OBJECTIVE: We designed and launched a three-arm randomized trial to test artificial intelligence technology solutions to increase daily physical activity in cancer survivors. METHODS: A single-center, three-arm randomized clinical trial with an allocation ration of 1:1:1: (A) control, in which participants are provided written materials about the benefits of physical activity; (B) text intervention, where participants receive daily motivation from a fully automated, data-driven algorithmic text message via mobile phone (Coachtext); and (C) Voice Assist intervention, where participants are provided with an in-home on demand autonomous Intelligent Agent using data driven Interactive Digital Voice Assist on the Amazon Alexa/Echo (MyCoach). RESULTS: The study runs for 5 weeks: a one-week run-in to establish baseline, followed by 4 weeks of intervention. Data for study outcomes is collected automatically through a wearable sensor, and data are transferred in real-time to the study server. The recruitment goal is 42 participants, 14 in each arm. Electronic health records are used to prescreen candidates, with 39 participants recruited to date. DISCUSSION: This study aims to investigate the effects of different types of intelligent technology solutions on promoting physical activity in cancer survivors. This innovative approach can easily be expanded and customized to other interventions. Early lessons from our initial participants are helping us develop additional advanced solutions to improve health outcomes. TRIAL REGISTRATION: Retrospectively registered on July 10, 2017 at ClinicalTrials.gov: NCT03212079; https://clinicaltrials.gov/ct2/show/NCT03212079 (Archived by WebCite at http://www.webcitation.org/6wgvqjTji) |
format | Online Article Text |
id | pubmed-5826976 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2018 |
publisher | JMIR Publications |
record_format | MEDLINE/PubMed |
spelling | pubmed-58269762018-03-01 Increasing Physical Activity Amongst Overweight and Obese Cancer Survivors Using an Alexa-Based Intelligent Agent for Patient Coaching: Protocol for the Physical Activity by Technology Help (PATH) Trial Hassoon, Ahmed Schrack, Jennifer Naiman, Daniel Lansey, Dina Baig, Yasmin Stearns, Vered Celentano, David Martin, Seth Appel, Lawrence JMIR Res Protoc Protocol BACKGROUND: Physical activity has established health benefits, but motivation and adherence remain challenging. OBJECTIVE: We designed and launched a three-arm randomized trial to test artificial intelligence technology solutions to increase daily physical activity in cancer survivors. METHODS: A single-center, three-arm randomized clinical trial with an allocation ration of 1:1:1: (A) control, in which participants are provided written materials about the benefits of physical activity; (B) text intervention, where participants receive daily motivation from a fully automated, data-driven algorithmic text message via mobile phone (Coachtext); and (C) Voice Assist intervention, where participants are provided with an in-home on demand autonomous Intelligent Agent using data driven Interactive Digital Voice Assist on the Amazon Alexa/Echo (MyCoach). RESULTS: The study runs for 5 weeks: a one-week run-in to establish baseline, followed by 4 weeks of intervention. Data for study outcomes is collected automatically through a wearable sensor, and data are transferred in real-time to the study server. The recruitment goal is 42 participants, 14 in each arm. Electronic health records are used to prescreen candidates, with 39 participants recruited to date. DISCUSSION: This study aims to investigate the effects of different types of intelligent technology solutions on promoting physical activity in cancer survivors. This innovative approach can easily be expanded and customized to other interventions. Early lessons from our initial participants are helping us develop additional advanced solutions to improve health outcomes. TRIAL REGISTRATION: Retrospectively registered on July 10, 2017 at ClinicalTrials.gov: NCT03212079; https://clinicaltrials.gov/ct2/show/NCT03212079 (Archived by WebCite at http://www.webcitation.org/6wgvqjTji) JMIR Publications 2018-02-12 /pmc/articles/PMC5826976/ /pubmed/29434016 http://dx.doi.org/10.2196/resprot.9096 Text en ©Ahmed Hassoon, Jennifer Schrack, Daniel Naiman, Dina Lansey, Yasmin Baig, Vered Stearns, David Celentano, Seth Martin, Lawrence Appel. Originally published in JMIR Research Protocols (http://www.researchprotocols.org), 12.02.2018. https://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work, first published in JMIR Research Protocols, is properly cited. The complete bibliographic information, a link to the original publication on http://www.researchprotocols.org, as well as this copyright and license information must be included. |
spellingShingle | Protocol Hassoon, Ahmed Schrack, Jennifer Naiman, Daniel Lansey, Dina Baig, Yasmin Stearns, Vered Celentano, David Martin, Seth Appel, Lawrence Increasing Physical Activity Amongst Overweight and Obese Cancer Survivors Using an Alexa-Based Intelligent Agent for Patient Coaching: Protocol for the Physical Activity by Technology Help (PATH) Trial |
title | Increasing Physical Activity Amongst Overweight and Obese Cancer Survivors Using an Alexa-Based Intelligent Agent for Patient Coaching: Protocol for the Physical Activity by Technology Help (PATH) Trial |
title_full | Increasing Physical Activity Amongst Overweight and Obese Cancer Survivors Using an Alexa-Based Intelligent Agent for Patient Coaching: Protocol for the Physical Activity by Technology Help (PATH) Trial |
title_fullStr | Increasing Physical Activity Amongst Overweight and Obese Cancer Survivors Using an Alexa-Based Intelligent Agent for Patient Coaching: Protocol for the Physical Activity by Technology Help (PATH) Trial |
title_full_unstemmed | Increasing Physical Activity Amongst Overweight and Obese Cancer Survivors Using an Alexa-Based Intelligent Agent for Patient Coaching: Protocol for the Physical Activity by Technology Help (PATH) Trial |
title_short | Increasing Physical Activity Amongst Overweight and Obese Cancer Survivors Using an Alexa-Based Intelligent Agent for Patient Coaching: Protocol for the Physical Activity by Technology Help (PATH) Trial |
title_sort | increasing physical activity amongst overweight and obese cancer survivors using an alexa-based intelligent agent for patient coaching: protocol for the physical activity by technology help (path) trial |
topic | Protocol |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5826976/ https://www.ncbi.nlm.nih.gov/pubmed/29434016 http://dx.doi.org/10.2196/resprot.9096 |
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