Article

Prochaska JO, Velicer WF, Fava JL, Rossi JS, Tsoh JY. Evaluating a population-based recruitment approach and a stage-based expert system intervention for smoking cessation. Addict Behav 26: 583-602

Cancer Prevention Research Center, University of Rhode Island, 2 Chafee Road, Kingston, RI 02881-0808, USA
Addictive Behaviors (Impact Factor: 2.76). 07/2001; 26(4):583-602. DOI: 10.1016/S0306-4603(00)00151-9
Source: PubMed

ABSTRACT

A stage-matched expert system intervention was evaluated on 4144 smokers in a two-arm randomized control trial with four follow-ups over 24 months. Smokers were recruited by random digit-dial calls, and 80.0% of the eligible smokers were enrolled. Individualized and interactive expert system computer reports were sent at 0, 3, and 6 months. The reports provided feedback on 15 variables relevant for progressing through the stages. The primary outcomes were point prevalence and prolonged abstinence rates. At 24 months, the expert system resulted in 25.6% point prevalence and 12% prolonged abstinence, which were 30% and 56% greater than the control condition. Abstinence rates at each 6-month follow-up were significantly greater in the Expert System (ES) condition than in the comparison condition with the absolute difference increasing at each follow-up. A proactive home-based stage-matched expert system smoking cessation program can produce both high participation rates and relatively high abstinence rates.

    • "ES has been effective in treating smokers at different stages of readiness to quit (J. O.Prochaska, Velicer, Fava, Rossi, & Tsoh, 2001;W. F. Velicer, Prochaska, & Redding, 2006;W. "
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    ABSTRACT: This study implemented a smoking cessation Readiness Group (RG) in two women-focused residential substance abuse treatment programs, with the aim of engaging women in smoking cessation services. The primary outcome was defined as attending at least one cessation group after the RG ended. The RG combined features of the Expert Systems (ES) approach with a practice quit attempt. ES is an interactive system which tailors intervention to the smokers’ stage of change, while the practice quit attempt rehearses the process of quitting smoking. As a secondary aim we tested whether incentives, used to promote participation and engagement in the RG, would increase initiation of smoking cessation services. Participants (N = 75) were women smokers enrolled in two residential programs, and intention to quit smoking was not required for participation. Twelve participant cohorts were randomly assigned to receive the RG with or without incentives. Following the RG intervention, 38.7% of participants (n = 29) attended at least one smoking cessation session. Both the number of RG sessions attended and a successful practice quit attempt predicted the later use of cessation services, while incentives did not. From pre to post RG, participants reported decreased cigarettes per day (CPD: 11.8 v. 7.6, p < .0001) and decreased nicotine dependence as measured by the Heaviness Smoking Index (HSI: 2.3 v. 1.8, p < .001). The 3-session group-format RG intervention was associated with initiation of smoking cessation services and with changes in smoking behavior.
    No preview · Article · Dec 2015 · Journal of substance abuse treatment
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    • "The Transtheoretical Model [14] provides a model of intentional behavior change which has proven useful as a framework to explain variability in personal “readiness” as a barrier to engagement in advance care planning [5, 15]. According to the model's proponents, people move through stages of precontemplation, contemplation, preparation, action, and maintenance as they consider making a change. "
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    ABSTRACT: Background. While rates of advance care documentation amongst the general public remain low, there is increasing recognition of the value of informal planning to address patient preferences in serious illness. Objectives. To determine the associations between personal attributes and formal and informal planning for serious illness across age groups. Methods. This population-based, online survey was conducted in Saskatchewan, Canada, in April, 2012, using a nonclinical sample of 827 adults ranging from 18 to 88 years of age and representative of age, sex, and regional distribution of the province. Associations between key predictor variables and planning for serious illness were assessed using binary logistic regression. Results. While 16.6% of respondents had completed a written living will or advance care plan, half reported having conversations about their treatment wishes or states of health in which they would find it unacceptable to live. Lawyers were the most frequently cited source of assistance for those who had prepared advance care plans. Personal experiences with funeral planning significantly increased the likelihood of activities designed to plan for serious illness. Conclusions. Strategies designed to increase the rate of planning for future serious illness amongst the general public must account for personal readiness.
    Full-text · Article · Dec 2013 · Family Practice
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    • "However, despite the promising prospects of the Internet, actual reach of effective interventions within the target population remains inadequate [19-22], as only a limited proportion of people is actually reached by the interventions [21,23]. These suboptimal levels of reach might be partially explained by the fact that most effective interventions are offered reactively to the target population [24]. The use of reactive dissemination strategies implies that a rather passive approach is taken in which users themselves must undertake action in order to use and optimally benefit from the intervention content [25]. "
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    ABSTRACT: The use of reactive strategies to disseminate effective Internet-delivered lifestyle interventions restricts their level of reach within the target population. This stresses the need to invest in proactive strategies to offer these interventions to the target population. The present study used a proactive strategy to increase reach of an Internet-delivered multi component computer tailored intervention, by embedding the intervention in an existing online health monitoring system of the Regional Public Health Services in the Netherlands. The research population consisted of Dutch adults who were invited to participate in the Adult Health Monitor (N = 96,388) offered by the Regional Public Health Services. This Monitor consisted of an online or a written questionnaire. A prospective design was used to determine levels of reach, by focusing on actual participation in the lifestyle intervention. Furthermore, adequacy of reach among the target group was assessed by composing detailed profiles of intervention users. Participants' characteristics, like demographics, behavioral and mental health status and quality of life, were included in the model as predictors. A total of 41,155 (43%) people participated in the Adult Health Monitor, ofwhich 41% (n = 16,940) filled out the online version. More than half of the online participants indicated their interest (n = 9169; 54%) in the computer tailored intervention and 5168 participants (31%) actually participated in the Internet-delivered computer tailored intervention. Males, older respondents and individuals with a higher educational degree were significantly more likely to participate in the intervention. Furthermore, results indicated that especially participants with a relatively healthier lifestyle and a healthy BMI were likely to participate. With one out of three online Adult Health Monitor participants actually participating in the computer tailored lifestyle intervention, the employed proactive dissemination strategy succeeded in ensuring relatively high levels of reach. Reach among at-risk individuals (e.g. low socioeconomic status and unhealthy lifestyle) was modest. It is therefore essential to further optimize reach by putting additional effort into increasing interest in the lifestyle intervention among at-risk individuals and to encourage them to actually use the intervention.Trial registration: Dutch Trial Register (NTR1786) and Medical Ethics Committee of Maastricht University and the University Hospital Maastricht (NL2723506809/MEC0903016).
    Full-text · Article · Aug 2013 · BMC Public Health
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