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

Tobacco Smoking Clinical Trial

— S4S  

Official title:

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

Clinical Trial Details — Status: Completed

Administrative data

• NCT number: NCT02265354
• Other study ID #: H00002005
• Secondary ID: K07CA172677
• Status: Completed
• Phase: N/A
• Start date: January 11, 2017
• Est. completion date: June 28, 2020

Study information

• Verified date: October 2020
• Source: University of Massachusetts, Worcester
• Contact: n/a
• Is FDA regulated: No
• Study type: Interventional

Clinical Trial Summary

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.

Description:

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).

Recruitment information / eligibility

• Status: Completed
• Enrollment: 260
• Est. completion date: June 28, 2020
• Est. primary completion date: December 28, 2017
• Accepts healthy volunteers: Accepts Healthy Volunteers
• Gender: All
• Age group: 19 Years and older

Eligibility

Inclusion Criteria:

• Current Smokers

Exclusion Criteria:

-

Related Conditions & MeSH terms

• Tobacco Smoking

Intervention

Behavioral:
• Collective-Intelligence computer tailored health communication

• Rule-based computer tailored health communication

Locations

Country	Name	City	State
United States	UMass Medical School	Worcester	Massachusetts

Sponsors (3)

Lead Sponsor	Collaborator
University of Massachusetts, Worcester	National Cancer Institute (NCI), University of Massachusetts, Amherst

Country where clinical trial is conducted

United States, 

Outcome

Type	Measure	Description	Time frame	Safety issue
Primary	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	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