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A Health Recommeder System to Tailor Message Preferences in a Smoking Cessation Programme

Study on Patient Acceptance and Engagement of Timely Tailored Motivational Messages Sent by a Health Recommender System and Delivered Via a Mobile App for Smoking Cessation

Status
Completed
Phases
Unknown
Study type
Observational
Source
ClinicalTrials.gov
Registry ID
NCT03206619
Enrollment
120
Registered
2017-07-02
Start date
2016-09-30
Completion date
2018-10-31
Last updated
2019-06-25

For informational purposes only — not medical advice. Sourced from public registries and may not reflect the latest updates. Terms

Conditions

Health Behavior, Smoking, Smoking Cessation, Smoking, Tobacco

Keywords

smoking, habit, preference, behavior, tailoring, cessation, engagement, digital, mobile app, recommender system

Brief summary

Patients attending the smoking cessation programme at the Virgen del Rocío University Hospital under the SoLoMo clinical trial of the SmokeFreeBrain project and provided with the SoLoMo mobile app will be observed for one year. This mobile app which sends the patients tailored health motivational messages selected by a health recommender system, and based on their user profile retrieved from an electronic health record. Patients' messages feedback and interactions with the app will be analyzed and evaluated following an observational prospective methodology to see whether patients like the messages, and measure the patient engagement with the health recommender system.

Interventions

OTHERSocial, Local and Mobile

Patients in a smoking cessation program will use a mobile application to receive messages and rate them from their smartphones. The messages patient will receive belong to one of the following five topics: general motivation, diet tips, physical exercise tips, personal performance, and the benefits of being a non-smoker. For each one of these topics, there will be a pool of 150 different messages with tailored information for the patient. Topics and messages were approved by a smoking cessation psychologist and a pulmonologist. The selection of the time the messages have to be sent, and the message topic is selected by an health recommender system algorithm based on the patients' user profile (demographic information, message rating information, and app interaction information).

Sponsors

Hospitales Universitarios Virgen del Rocío
CollaboratorOTHER
Salumedia Tecnologías
CollaboratorUNKNOWN
Aristotle University Of Thessaloniki
CollaboratorOTHER
Northern Greece Neurofeedback Center
CollaboratorUNKNOWN
University of Seville
Lead SponsorOTHER

Study design

Observational model
COHORT
Time perspective
PROSPECTIVE

Eligibility

Sex/Gender
ALL
Age
18 Years to No maximum
Healthy volunteers
No

Inclusion criteria

* Patients must be taken from the the smoking cessation unit of the Virgen del Rocio University Hospital (Seville, Spain) * Patients must be willing to start the treatment to quit smoking * Patients must own an Android smartphone and be able to interact with it * Patients must be willing to and install the Libre de Humos smoking cessation app recommended by the doctor in the SmokeFreeBrain study. * Patients must sign an informed consent

Exclusion criteria

* Patients have known previous adverse effects on the pharmacological treatment included in the study (Bupropion & Varenicline)

Design outcomes

Primary

MeasureTime frameDescription
Subjective quality of the health recommender systemUp to 18 monthsThe subjective quality of the health recommender systems is determined by eighteen questions which will be answered using a 1 to 5 point Likert scale by all patients finishing their smoking cessation programme.
Engagement at aggregated level - Mobile application rolling retentionUp to 18 monthsThe percentage of users still active N days after installation. This is a ratio of the number of users whose last day of activity is past day N to the number of users who could have been active on day N. This metric will be assessed throughout the observation until its end.
Objective quality of the health recommender systemUp to 18 monthsThe objective quality of the health recommender system is calculated by measuring its precision. The precision of the health recommender system is the relation between the number of messages patients have rated with positive and/or positive and neutral feedback the first month (baseline), and all subsequent months.
Engagement at aggregated level - Mobile application session length distributionUp to 18 monthsThe session length is defined as the length of time between the start of the application event and the end of the application event. The session length determines the engagement as it is relevant to know how much time patients spend in the app per session. This metric will be assessed throughout the observation until its end.
Engagement at aggregated level - Mobile application usage frequencyUp to 18 monthsThe frequency of use is a measure of how often each unique patient used the app within a given time interval. This metric will be assessed throughout the observation until its end.
Engagement at aggregated level - Number of sessions per userUp to 18 monthsA session is one use of the mobile application by a patient. This begins when the application is launched and ends when the application is terminated. This metric will be assessed throughout the observation until its end.
Engagement at aggregated level - Return rateUp to 18 monthsReturn rate measures the percentage of patients who return to the app on a specific time after installation. It is measured by cohort group - that is, based on when patients first opened the app. It is calculated as the ratio of the number of users active on a given period to the size of the cohort. This metric will be assessed throughout the observation until its end.
Engagement at individual levelUp to 18 monthsEngagement at individual level will be assessed based on the rate of read messages by the patients. This is calculated as the quotient between the messages the patients have read, and the total number of messages the system has sent to the patients. This metric will be assessed throughout the observation until its end.

Countries

Spain

Outcome results

None listed

Source: ClinicalTrials.gov · Data processed: Mar 6, 2026