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Computer Decision Support Systems for Smokers with Severe Mental Illness

Funding Source

National Institute on Disability and Rehabilitation Research (NIDRR)

Project Period

3/1/11 - 10/31/12

Principal Investigator

Mary Brunette, MD

Other Project Staff

University of Illinois at Chicago (Cook, PI); Joelle Ferron, PhD, Geisel School of Medicine at Dartmouth; Dror Ben-Zeev, PhD, Geisel School of Medicine at Dartmouth; Steven Andrews, PhD, Geisel School of Medicine at Dartmouth; Greg McHugo, PhD, Geisel School of Medicine at Dartmouth

Project Summary

Up to 80% of Americans with serious mental illnesses (SMI; schizophrenia and severe mood disorders) smoke cigarettes, and most suffer related health consequences. We have developed an easy-to-use, web-based electronic decision support system (EDSS) that aims to educate and motivate smokers with SMI to quit using evidence based treatment. Preliminary testing has demonstrated excellent usability and increased engagement in smoking cessation treatments. One critical issue is the use of personalized health feedback. Motivational interventions for smoking cessation for smokers with SMI, including our EDSS, have included personal feedback from a breath monitor that measures carbon monoxide, a toxic component of cigarette smoke. Feedback regarding carbon monoxide is thought to motivate the user by personalizing the health risks of smoking. Health checklists with feedback give may also motivate smokers, and are simpler and less expensive to use, but they have not been assessed separately from carbon monoxide monitor feedback among SMI smokers. We are conducting a randomized clinical trial among SMI smokers to assess whether the EDSS with carbon monoxide monitor and checklist feedback leads to higher rates of initiating smoking cessation treatment than the EDSS with checklist feedback alone. We will also assess whether symptoms, cognition, smoking-related attitudes and beliefs, and smoking characteristics impact treatment initiation and outcomes.

Public Health Relevance

Inexpensive strategies are needed to engage people into effective smoking cessation treatments. By helping this disparity group quit smoking, this decision support system has the potential to reduce early morbidity and mortality in millions of smokers with severe mental illnesses.