J. Med. Internet Res. - Who participates in Web-assisted tobacco interventions? The QUIT-PRIMO and National Dental Practice-Based Research Network Hi-Quit studies.

Tópicos

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Resumo

TRODUCTION: Smoking is the most preventable cause of death. Although effective, Web-assisted tobacco interventions are underutilized and recruitment is challenging. Understanding who participates in Web-assisted tobacco interventions may help in improving recruitment.OBJECTIVES: To understand characteristics of smokers participating in a Web-assisted tobacco intervention (Decide2Quit.org).METHODS: In addition to the typical Google advertisements, we expanded Decide2Quit.org recruitment to include referrals from medical and dental providers. We assessed how the expanded recruitment of smokers changed the users' characteristics, including comparison with a population-based sample of smokers from the national Behavioral Risk Factors Surveillance Survey (BRFSS). Using a negative binomial regression, we compared demographic and smoking characteristics by recruitment source, in particular readiness to quit and association with subsequent Decide2Quit.org use.RESULTS: The Decide2Quit.org cohort included 605 smokers; the 2010 BRFSS dataset included 69,992. Compared to BRFSS smokers, a higher proportion of Decide2Quit.org smokers were female (65.2% vs 45.7%, P=.001), over age 35 (80.8% vs 67.0%, P=.001), and had some college or were college graduates (65.7% vs 45.9%, P=.001). Demographic and smoking characteristics varied by recruitment; for example, a lower proportion of medical- (22.1%) and dental-referred (18.9%) smokers had set a quit date or had already quit than Google smokers (40.1%, P<.001). Medical- and dental-referred smokers were less likely to use Decide2Quit.org functions; in adjusted analysis, Google smokers (predicted count 17.04, 95% CI 14.97-19.11) had higher predicted counts of Web page visits than medical-referred (predicted count 12.73, 95% CI 11.42-14.04) and dental-referred (predicted count 11.97, 95% CI 10.13-13.82) smokers, and were more likely to contact tobacco treatment specialists.CONCLUSIONS: Recruitment from clinical practices complimented Google recruitment attracting smokers less motivated to quit and less experienced with Web-assisted tobacco interventions.

Resumo Limpo

troduct smoke prevent caus death although effect webassist tobacco intervent underutil recruit challeng understand particip webassist tobacco intervent may help improv recruitmentobject understand characterist smoker particip webassist tobacco intervent decidequitorgmethod addit typic googl advertis expand decidequitorg recruit includ referr medic dental provid assess expand recruit smoker chang user characterist includ comparison populationbas sampl smoker nation behavior risk factor surveil survey brfss use negat binomi regress compar demograph smoke characterist recruit sourc particular readi quit associ subsequ decidequitorg useresult decidequitorg cohort includ smoker brfss dataset includ compar brfss smoker higher proport decidequitorg smoker femal vs p age vs p colleg colleg graduat vs p demograph smoke characterist vari recruit exampl lower proport medic dentalref smoker set quit date alreadi quit googl smoker p medic dentalref smoker less like use decidequitorg function adjust analysi googl smoker predict count ci higher predict count web page visit medicalref predict count ci dentalref predict count ci smoker like contact tobacco treatment specialistsconclus recruit clinic practic compliment googl recruit attract smoker less motiv quit less experienc webassist tobacco intervent

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