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A recommender system to quit smoking with mobile motivational messages: study protocol for a randomized controlled trial.

ABSTRACT: 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.

SUBMITTER: Hors-Fraile S

PROVIDER: S-EPMC6230227 | biostudies-literature | 2018 Nov

REPOSITORIES: biostudies-literature

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A recommender system to quit smoking with mobile motivational messages: study protocol for a randomized controlled trial.

Hors-Fraile Santiago S Malwade Shwetambara S Spachos Dimitris D Fernandez-Luque Luis L Su Chien-Tien CT Jeng Wei-Li WL Syed-Abdul Shabbir S Bamidis Panagiotis P Li Yu-Chuan Jack YJ

Trials 20181109 1

<h4>Background</h4>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 s ...[more]

PMID: 30413176

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Project description:BACKGROUND:Smoking is one of the most avoidable health risk factors, and yet the quitting success rates are low. The usage of tailored health messages to support quitting has been proved to increase quitting success rates. Technology can provide convenient means to deliver tailored health messages. Health recommender systems are information-filtering algorithms that can choose the most relevant health-related items-for instance, motivational messages aimed at smoking cessation-for each user based on his or her profile. The goals of this study are to analyze the perceived quality of an mHealth recommender system aimed at smoking cessation, and to assess the level of engagement with the messages delivered to users via this medium. METHODS:Patients participating in a smoking cessation program will be provided with a mobile app to receive tailored motivational health messages selected by a health recommender system, based on their profile retrieved from an electronic health record as the initial knowledge source. Patients' feedback on the messages and their interactions with the app will be analyzed and evaluated following an observational prospective methodology to a) assess the perceived quality of the mobile-based health recommender system and the messages, using the precision and time-to-read metrics and an 18-item questionnaire delivered to all patients who complete the program, and b) measure patient engagement with the mobile-based health recommender system using aggregated data analytic metrics like session frequency and, to determine the individual-level engagement, the rate of read messages for each user. This paper details the implementation and evaluation protocol that will be followed. DISCUSSION:This study will explore whether a health recommender system algorithm integrated with an electronic health record can predict which tailored motivational health messages patients would prefer and consider to be of a good quality, encouraging them to engage with the system. The outcomes of this study will help future researchers design better tailored motivational message-sending recommender systems for smoking cessation to increase patient engagement, reduce attrition, and, as a result, increase the rates of smoking cessation. TRIAL REGISTRATION:The trial was registered at clinicaltrials.org under the ClinicalTrials.gov identifier NCT03206619 on July 2nd 2017. Retrospectively registered.

Project description:BackgroundAlthough the current Clinical Practice Guideline recommend Motivational Interviewing for use with smokers not ready to quit, the strength of evidence for its use is rated as not optimal. The purpose of the present study is to address key methodological limitations of previous studies by ensuring fidelity in the delivery of the Motivational Interviewing intervention, using an attention-matched control condition, and focusing on unmotivated smokers whom meta-analyses have indicated may benefit most from Motivational Interviewing. It is hypothesized that MI will be more effective at inducing quit attempts and smoking cessation at 6-month follow-up than brief advice to quit and an intensity-matched health education condition.Methods/designA sample of adult community resident smokers (N = 255) who report low motivation and readiness to quit are being randomized using a 2:2:1 treatment allocation to Motivational Interviewing, Health Education, or Brief Advice. Over 6 months, participants in Motivational Interviewing and Health Education receive 4 individual counseling sessions and participants in Brief Advice receive one brief in-person individual session at baseline. Rigorous monitoring and independent verification of fidelity will assure the counseling approaches are distinct and delivered as planned. Participants complete surveys at baseline, week 12 and 6-month follow-up to assess demographics, smoking characteristics, and smoking outcomes. Participants who decide to quit are provided with a self-help guide to quitting, help with a quit plan, and free pharmacotherapy. The primary outcome is self-report of one or more quit attempts lasting at least 24 hours between randomization and 6-month follow-up. The secondary outcome is biochemically confirmed 7-day point prevalence cessation at 6-month follow-up. Hypothesized mediators of the presumed treatment effect on quit attempts are greater perceived autonomy support and autonomous motivation. Use of pharmacotherapy is a hypothesized mediator of Motivational Interviewing's effect on cessation.DiscussionThis trial will provide the most rigorous evaluation to date of Motivational Interviewing's efficacy for encouraging unmotivated smokers to make a quit attempt. It will also provide effect-size estimates of MI's impact on smoking cessation to inform future clinical trials and inform the Clinical Practice Guideline.Trial registrationClinicalTrials.gov NCT01188018.

Project description:BackgroundMotivational messaging is a frequently used digital intervention to promote positive health behavior changes, including smoking cessation. Typically, motivational messaging systems have not actively sought feedback on each message, preventing a closer examination of the user-system engagement. This study assessed the granular user-system engagement around a recommender system (a new system that actively sought user feedback on each message to improve message selection) for promoting smoking cessation and the impact of engagement on cessation outcome.MethodsWe prospectively followed a cohort of current smokers enrolled to use the recommender system for 6 months. The system sent participants motivational messages to support smoking cessation every 3 days and used machine learning to incorporate user feedback (i.e., user's rating on the perceived influence of each message, collected on a 5-point Likert scale with 1 indicating strong disagreement and 5 indicating strong agreement on perceiving the influence on quitting smoking) to improve the selection of the following message. We assessed user-system engagement by various metrics, including user response rate (i.e., the percent of times a user rated the messages) and the perceived influence of messages. We compared retention rates across different levels of user-system engagement and assessed the association between engagement and the 7-day point prevalence abstinence (missing outcome = smoking) by using multiple logistic regression.ResultsWe analyzed data from 731 participants (13% Black; 73% women). The user response rate was 0.24 (SD = 0.34) and user-perceived influence was 3.76 (SD = 0.84). The retention rate positively increased with the user response rate (trend test P < 0.001). Compared with non-response, six-month cessation increased with the levels of response rates: low response rate (odds ratio [OR] = 1.86, 95% confidence interval [CI]: 1.07-3.23), moderate response rate (OR = 2.30, 95% CI: 1.36-3.88), high response rate (OR = 2.69, 95% CI: 1.58-4.58). The association between perceived message influence and the outcome showed a similar pattern.ConclusionsHigh user-system engagement was positively associated with both high retention rate and smoking cessation, suggesting that investigation of methods to increase engagement may be crucial to increase the impact of the recommender system for smoking cessation.Trial registrationRegistration Identifier: NCT03224520 . Registration date: July 21, 2017.

Project description:BackgroundAutomatic processes to approach smoking-related cues have been repeatedly linked to smoking status, intensity of smoking, and cigarette craving. Moreover, recent findings suggest that targeting those tendencies directly by means of approach bias modification (ABM) has merit in changing maladaptive approach tendencies for drug cues and reducing drug consumption. However, training effects tend to be small. Embedding the training into virtual reality (VR) technology could be a promising way to improve training efficacy. The present protocol describes a randomized controlled trial that aims to assess the efficacy of a newly developed VR-ABM as a means of reducing smoking-related approach biases or nicotine consumption in smokers seeking abstinence.MethodsOne hundred daily smokers who are motivated to quit smoking will be recruited into the randomized controlled trial. All participants will attend a brief smoking cessation intervention (TAU) and will be randomly assigned either to the experimental (VR-avoidance training) or the placebo-control group (VR-placebo training). During the VR-avoidance training, participants are implicitly instructed to make an avoidance movement in response to smoking-related objects (e.g., cigarettes) and an approach movement in response to alternative objects (e.g., healthy food). During the VR-placebo training, no such contingency between arm movement and item content exists. Trainings are administered in six sessions within two weeks. Training effects on automatic approach tendencies and smoking behavior are measured immediately after training and at a 7-week follow-up.DiscussionEmbedding the training into virtual reality (VR) technology could be a promising new way to improve ecological validity, realism, and immersion and thereby increase ABM training effects. The results of this study can inform future research in the optimization and advancement of treatment for addiction.Trial registrationRegistered with Current Controlled Trials: study ID ISRCTN16006023. Registered on 28 March 2019.

Project description:BACKGROUND:Several large studies have shown that the risk of cardiovascular, respiratory, and wound-healing complications (including death) within 30 days of surgery is greater for smokers than for nonsmokers. However, there is evidence that even short-term perioperative smoking cessation may reduce postoperative morbidity. Over the past few years, it has become more evident that short message service (SMS)-based interventions can help individuals quit smoking. OBJECTIVE:The overall aim of this project is to fill the knowledge gap on whether an SMS-based smoking-cessation intervention can be effective in helping patients stop smoking perioperatively. The aim of this trial is to evaluate the effectiveness of an SMS-based intervention on smoking behavior of patients undergoing elective surgery. METHODS:A two-arm parallel-group randomized controlled trial will be conducted at 20 surgical departments in southeast Sweden. Smokers undergoing elective surgery who own a mobile phone will be included. Power calculations indicate that it will be necessary to randomize 434 participants. One group will be given access to a novel 12-week SMS program, which includes daily SMS messages with behavior change-enforcing text content and hyperlinks to interactive modules, while the other group will not be given access to the intervention. Both groups will have access to the surgical departments' current routine for smoking cessation prior to surgery. Primary outcome measures, prolonged abstinence, and point prevalence of smoking cessation will be measured through questionnaires at 3, 6, and 12 months after randomization. Logistic regression models adjusted using baseline characteristics will be explored to identify potential effects of the intervention. RESULTS:Recruitment started in late October 2018 and is expected to last for a maximum of 30 months. The first results are expected to be available approximately 3 months after the final date of recruitment. CONCLUSIONS:Owing to the structural problems and scarcity of time and resources, patients at most Swedish surgical departments are simply instructed to quit smoking, and perhaps, referred to a primary health care clinic. An SMS-based smoking-cessation aid can be effective in helping individuals quit smoking and is a very simple and time-efficient tool for surgical departments to use. TRIAL REGISTRATION:ISRCTN Registry ISRCTN33869008; http://www.isrctn.com/ISRCTN33869008. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID):PRR1-10.2196/12511.

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A recommender system to quit smoking with mobile motivational messages: study protocol for a randomized controlled trial.

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A recommender system to quit smoking with mobile motivational messages: study protocol for a randomized controlled trial.

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