Developing Smokers for Smoker (S4S): A Collective Intelligence Tailoring System

Study Overview
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Brief Summary
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This study will advance computer tailoring by adapting machine learning collective intelligence algorithms that have been used outside healthcare by companies like Amazon and Google to enhance the personal relevance of the health communication.

Detailed Description
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Smoking is still the number one preventable cause of cancer death. New approaches are needed to engage smokers in the 21st century in smoking cessation. I propose to develop S4S (Smokers for Smoker), a next-generation patient-centered computer tailored health communication (CTHC) system. Unlike current rule-based CTHCs, S4S will replace rules with complex machine learning algorithms, and use the collective experiences of thousands of smokers engaged in a web-assisted tobacco intervention to enhance personally-relevant tailoring for new smokers entering the system. The investigators will adapt collective intelligence algorithms that have been used outside healthcare by companies like Amazon and Google to enhance CTHC. Using knowledge from scientific experts, current CTHC collect baseline patient profiles and then use expert-written, rule-based systems to tailor messages to patient subsets. Such theory-based market segmentation has been effective in helping patients reach lifestyle goals. However, there is a natural limit in the ability of a rule-based system to truly personalize content, and adapt personalization over time. Current CTHC have reached this limit, and the investigators propose to go beyond. The investigators first aim is to develop the Web 2.0 S4S recommender system. The investigators second aim is to evaluate S4S within the context of a NCI funded web-assisted tobacco intervention (Decide2Quit.org).

Official Title
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Developing Smokers for Smoker (S4S): A Collective Intelligence Tailoring System

Conditions
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Tobacco Smoking

Intervention / Treatment
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* Behavioral: Collective-Intelligence computer tailored health communication
* Behavioral: Rule-based computer tailored health communication


Participation Criteria
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Eligibility Criteria
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Inclusion Criteria: Current Smokers Exclusion Criteria: -

Ages Eligible for Study
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Minimum Age: 19 Years

Sexes Eligible for Study
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All

Accepts Healthy Volunteers
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Accepts Healthy Volunteers

Study Plan
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How is the study designed?
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Design Details

Primary Purpose: Treatment
Allocation: Randomized
Intervention Model: Parallel Assignment
Masking: Double


Arms and Interventions

| Participant Group/Arm | Intervention/Treatment |
| --- | --- |
| Experimental: Collective-Intelligence computer tailored health communication<br>Smokers will have access to all Decide2quit.org website functions and will receive 4 tailored emails per week based on a collective intelligence recommender systems algorithm for up to 6 months | Behavioral: Collective-Intelligence computer tailored health communication<br> <br> |
| Active Comparator: Rule-based computer tailored health communication<br>Smokers will have access to all Decide2quit.org website functions and will receive 4 tailored emails per week based on a rule-based algorithm for up to 6 months | Behavioral: Rule-based computer tailored health communication<br> <br> |

What is the study measuring?
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Primary Outcome Measures

| Outcome Measure | Measure Description | Time Frame |
| --- | --- | --- |
| Repeated Use of website measure | This measure is an ordinal scale of the number of functions used after the first visit to the Decide2Quit.org website (0: use of no functions, 1: use of 1-2 functions, 2: use of 2-4 functions, see Table 9 list of functions). We will use scripts on the website to assess this information | Every Login for 6 months | 

Secondary Outcome Measures

| Outcome Measure | Measure Description | Time Frame |
| --- | --- | --- |
| 30-day point prevalent smoking cessation at six months | Did you smoke any cigarettes during the past 30 days? This will be assessed using a follow-up Telephone or Internet survey | At 6 months | 

 Terms related to the study
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Keywords Provided by Centre Hospitalier Valida
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Tobacco Smoking Cessation, Computer tailored health communication, messaging, collective intelligence, recommender systems, machine learning