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A recommender system to quit smoking with mobile motivational messages: study protocol for a randomized controlled trial
BACKGROUND: Smoking cessation is the most common preventative for an array of diseases, including lung cancer and chronic obstructive pulmonary disease. Although there are many efforts advocating for smoking cessation, smoking is still highly prevalent. For instance, in the USA in 2015, 50% of all s...
Autores principales: | , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
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BioMed Central
2018
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6230227/ https://www.ncbi.nlm.nih.gov/pubmed/30413176 http://dx.doi.org/10.1186/s13063-018-3000-1 |
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author | Hors-Fraile, Santiago Malwade, Shwetambara Spachos, Dimitris Fernandez-Luque, Luis Su, Chien-Tien Jeng, Wei-Li Syed-Abdul, Shabbir Bamidis, Panagiotis Li, Yu-Chuan(Jack) |
author_facet | Hors-Fraile, Santiago Malwade, Shwetambara Spachos, Dimitris Fernandez-Luque, Luis Su, Chien-Tien Jeng, Wei-Li Syed-Abdul, Shabbir Bamidis, Panagiotis Li, Yu-Chuan(Jack) |
author_sort | Hors-Fraile, Santiago |
collection | PubMed |
description | BACKGROUND: Smoking cessation is the most common preventative for an array of diseases, including lung cancer and chronic obstructive pulmonary disease. Although there are many efforts advocating for smoking cessation, smoking is still highly prevalent. For instance, in the USA in 2015, 50% of all smokers attempted to quit smoking, and only 5–7% of them succeeded – with slight deviation depending on external assistance. Previous studies show that computer-tailored messages which support smoking abstinence are effective. The combination of health recommender systems and behavioral-change theories is becoming increasingly popular in computer-tailoring. The objective of this study is to evaluate patients’s smoking cessation rates by means of two randomized controlled trials using computer-tailored motivational messages. A group of 100 patients will be recruited in medical centers in Taiwan (50 patients in the intervention group, and 50 patients in the control group), and a group of 1000 patients will be recruited on-line (500 patients in the intervention group, and 500 patients in the control group). The collected data will be made available to the public in an open-source data portal. METHODS: Our study will gather data from two sources. The first source is a clinical pilot in which a group of patients from two Taiwanese medical centers will be randomly assigned to either an intervention or a control group. The intervention group will be provided with a mobile app that sends motivational messages selected by a recommender system that takes the user profile (including gender, age, motivations, and social context) and similar users’ opinions. For 6 months, the patients’ smoking activity will be followed up, and confirmed as “smoke-free” by using a test that measures expired carbon monoxide and urinary cotinine levels. The second source will be a public pilot in which Internet users wanting to quit smoking will be able to download the same mobile app as used in the clinical pilot. They will be randomly assigned to a control group that receives basic motivational messages or to an intervention group, that receives personalized messages by the recommender system. For 6 months, patients in the public pilot will be assessed periodically with self-reported questionnaires. DISCUSSION: This study will be the first to use the I-Change behavioral-change model in combination with a health recommender system and will, therefore, provide relevant insights into computer-tailoring for smoking cessation. If our hypothesis is validated, clinical practice for smoking cessation would benefit from the use of our mobile solution. TRIAL REGISTRATION: ClinicalTrials.gov, ID: NCT03108651. Registered on 11 April 2017. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1186/s13063-018-3000-1) contains supplementary material, which is available to authorized users. |
format | Online Article Text |
id | pubmed-6230227 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2018 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-62302272018-11-19 A recommender system to quit smoking with mobile motivational messages: study protocol for a randomized controlled trial Hors-Fraile, Santiago Malwade, Shwetambara Spachos, Dimitris Fernandez-Luque, Luis Su, Chien-Tien Jeng, Wei-Li Syed-Abdul, Shabbir Bamidis, Panagiotis Li, Yu-Chuan(Jack) Trials Study Protocol BACKGROUND: Smoking cessation is the most common preventative for an array of diseases, including lung cancer and chronic obstructive pulmonary disease. Although there are many efforts advocating for smoking cessation, smoking is still highly prevalent. For instance, in the USA in 2015, 50% of all smokers attempted to quit smoking, and only 5–7% of them succeeded – with slight deviation depending on external assistance. Previous studies show that computer-tailored messages which support smoking abstinence are effective. The combination of health recommender systems and behavioral-change theories is becoming increasingly popular in computer-tailoring. The objective of this study is to evaluate patients’s smoking cessation rates by means of two randomized controlled trials using computer-tailored motivational messages. A group of 100 patients will be recruited in medical centers in Taiwan (50 patients in the intervention group, and 50 patients in the control group), and a group of 1000 patients will be recruited on-line (500 patients in the intervention group, and 500 patients in the control group). The collected data will be made available to the public in an open-source data portal. METHODS: Our study will gather data from two sources. The first source is a clinical pilot in which a group of patients from two Taiwanese medical centers will be randomly assigned to either an intervention or a control group. The intervention group will be provided with a mobile app that sends motivational messages selected by a recommender system that takes the user profile (including gender, age, motivations, and social context) and similar users’ opinions. For 6 months, the patients’ smoking activity will be followed up, and confirmed as “smoke-free” by using a test that measures expired carbon monoxide and urinary cotinine levels. The second source will be a public pilot in which Internet users wanting to quit smoking will be able to download the same mobile app as used in the clinical pilot. They will be randomly assigned to a control group that receives basic motivational messages or to an intervention group, that receives personalized messages by the recommender system. For 6 months, patients in the public pilot will be assessed periodically with self-reported questionnaires. DISCUSSION: This study will be the first to use the I-Change behavioral-change model in combination with a health recommender system and will, therefore, provide relevant insights into computer-tailoring for smoking cessation. If our hypothesis is validated, clinical practice for smoking cessation would benefit from the use of our mobile solution. TRIAL REGISTRATION: ClinicalTrials.gov, ID: NCT03108651. Registered on 11 April 2017. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1186/s13063-018-3000-1) contains supplementary material, which is available to authorized users. BioMed Central 2018-11-09 /pmc/articles/PMC6230227/ /pubmed/30413176 http://dx.doi.org/10.1186/s13063-018-3000-1 Text en © The Author(s). 2018 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated. |
spellingShingle | Study Protocol Hors-Fraile, Santiago Malwade, Shwetambara Spachos, Dimitris Fernandez-Luque, Luis Su, Chien-Tien Jeng, Wei-Li Syed-Abdul, Shabbir Bamidis, Panagiotis Li, Yu-Chuan(Jack) A recommender system to quit smoking with mobile motivational messages: study protocol for a randomized controlled trial |
title | A recommender system to quit smoking with mobile motivational messages: study protocol for a randomized controlled trial |
title_full | A recommender system to quit smoking with mobile motivational messages: study protocol for a randomized controlled trial |
title_fullStr | A recommender system to quit smoking with mobile motivational messages: study protocol for a randomized controlled trial |
title_full_unstemmed | A recommender system to quit smoking with mobile motivational messages: study protocol for a randomized controlled trial |
title_short | A recommender system to quit smoking with mobile motivational messages: study protocol for a randomized controlled trial |
title_sort | recommender system to quit smoking with mobile motivational messages: study protocol for a randomized controlled trial |
topic | Study Protocol |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6230227/ https://www.ncbi.nlm.nih.gov/pubmed/30413176 http://dx.doi.org/10.1186/s13063-018-3000-1 |
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