Xiaowu Sun

University of Rhode Island, Kingston, RI, United States

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Publications (6)20.61 Total impact

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    ABSTRACT: This cross-sectional study (N = 4,144) compared three longitudinal dynatypes (Maintainers, Relapsers, and Stable Smokers) of smokers on baseline demographics, stage, addiction severity, and transtheoretical model effort effect variables. There were significant small-to-medium-sized differences between the Stable Smokers and the other two groups on stage, severity, and effort effect variables in both treatment and control groups. There were few significant, very small differences on baseline effort variables between Maintainers and Relapsers in the control, but not the treatment group. The ability to identify Stable Smokers at baseline could permit enhanced tailored treatments that could improve population cessation rates.
    Substance Use &amp Misuse 03/2011; 46(13):1664-74. · 1.11 Impact Factor
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    ABSTRACT: Rates of preventive counseling remain below national guidelines. We explored physician and patient predictors of preventive counseling across multiple cancer risk behaviors in at-risk primary care patients. We surveyed 3557 patients, with at least one of four cancer risk behaviors: smoking, diet, sun exposure, and/or mammography screening, at baseline and 24 months. Patients reported receipt of 4A's (Ask, Advise, Assist, Arrange follow-up); responses were weighted and combined to reflect more thorough counseling (Ask=1, Advise=2, Assist=3, Arrange=4, score range 0-10) for each target behavior. A series of linear-regression models, controlling for office clustering, examined patient, physician and other situational predictors at 24 months. Risk behavior topics were brought up more often for mammography (90%) and smoking (79%) than diet (56%) and sun protection (30%). Assisting and Arranging follow-up were reported at low frequencies across all behaviors. More thorough counseling for all behaviors was associated with multiple visits and higher satisfaction with care. Prior counseling predicted further counseling on all behaviors except smoking, which was already at high levels. Other predictors varied by risk behavior. More thorough risk behavior counseling can be delivered opportunistically across multiple visits; doing so is associated with more satisfaction with care.
    Preventive Medicine 04/2008; 46(3):252-9. · 3.50 Impact Factor
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    ABSTRACT: Intervention effectiveness can potentially be affected by membership in different demographic subgroups (race, ethnicity, gender, age, and education level) or smoking behavior variables (time to first cigarette, longest previous quit attempt, number of attempts in the past year, number of cigarettes, and stage of change). Previous research on these 2 sets of variables has produced mixed results. This secondary data analysis combined data from 5 effectiveness trials (a random-digit-dial sample [N=1,358], members of an HMO [N=207], parents of students recruited for a school-based study [N=347], patients from an insurance provider list [N=535], and employees [N=175]) in which smokers were all proactively recruited from a defined population and all received the same expert system intervention. The intervention produced a consistent 22% to 26% point prevalence cessation rate across the 5 studies. The main outcome measures were 24-hr point prevalence, 7-day point prevalence, 30-day prolonged abstinence, and 6-month prolonged abstinence. There were no significant differences in outcome across gender, race, and ethnicity subgroups. There were significant differences and small effect sizes for age and education subgroups. There were significant differences and large effect sizes for all 5 smoking behavior variables. Demographic variables are static variables, whereas the smoking variables are more dynamic, that is, open to change. Given the dynamic nature of the smoking variables and the large effect sizes, interventions tailored on the smoking variables should be more successful.
    Health Psychology 06/2007; 26(3):278-87. · 3.83 Impact Factor
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    ABSTRACT: Pharmacological interventions for smoking cessation are typically evaluated using volunteer samples (efficacy trials) but should also be evaluated in population-based trials (effectiveness trials). Nicotine replacement therapy (NRT) alone and in combination with behavioral interventions was evaluated on a population of smokers from a New England Veterans Affairs Medical Center. Telephone interviews were completed with 3,239 smokers, and 2,054 agreed to participate (64%). Participants were randomly assigned to one of four conditions: stage-matched manuals (MAN); NRT plus manuals (NRT + MAN); expert system plus NRT and manuals (EXP + NRT + MAN); and automated counseling plus NRT, manuals, and expert system (TEL + EXP + NRT + MAN). Assessments were completed at baseline, 10, 20, and 30 months. The point prevalence cessation rates at final follow-up (30 months) were MAN, 20.3%; NRT + MAN, 19.3%; EXP + NRT + MAN, 17.6%; and TEL + EXP + NRT + MAN, 19.9%. Stage-matched manuals provided cessation rates comparable with previous studies. The addition of NRT, expert system interventions, and automated telephone counseling failed to produce a further increase in intervention effectiveness.
    Journal of Consulting and Clinical Psychology 01/2007; 74(6):1162-72. · 4.85 Impact Factor
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    ABSTRACT: Treating multiple health behavior risks on a population basis is one of the most promising approaches to enhancing health and reducing health care costs. Previous research demonstrated the efficacy of expert system interventions for three behaviors in a population of parents. The interventions provide individualized feedback that guides participants through the stages of change for each of their risk behaviors. This study extended that research to a more representative population of patients from primary care practice and to targeting of four rather than three behaviors. Stage-based expert systems were applied to reduce smoking, improve diet, decrease sun exposure, and prevent relapse from regular mammography. A randomized clinical controlled trial recruited 69.2% of primary care patients (N = 5407) at home via telephone. Three intervention contacts were delivered for each risk factor at 0, 6, and 12 months. The primary outcome measures were the percentages of at-risk patients at baseline who progressed to the action or maintenance stages at 24-month follow-up for each of the risk behaviors. Significant treatment effects were found for each of the four behaviors, with 25.4% of intervention patients in action or maintenance for smoking, 28.8% for diet, and 23.4% for sun exposure. The treatment group had less relapse from regular mammography than the control group (6% vs. 10%). Proactive, home-based, and stage-matched expert systems can produce relatively high population impacts on multiple behavior risks for cancer and other chronic diseases.
    Preventive Medicine 09/2005; 41(2):406-16. · 3.50 Impact Factor
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    ABSTRACT: Three stage-based expert system interventions for smoking, high-fat diet, and unsafe sun exposure were evaluated in a sample of 2,460 parents of teenagers. Eighty-four percent of the eligible parents were enrolled in a 2-arm randomized control trial, with the treatment group receiving individualized feedback reports for each of their relevant behaviors at 0, 6, and 12 months as well as a multiple behavior manual. At 24 months, the expert system outperformed the comparison condition across all 3 risk behaviors, resulting in 22% of the participants in action or maintenance for smoking (vs. 16% for the comparison condition), 34% for diet (vs. 26%), and 30% for sun exposure (vs. 22%). Proactive, home-based, and stage-matched expert systems can produce significant multiple behavior changes in at-risk populations where the majority of participants are not prepared to change.
    Health Psychology 10/2004; 23(5):503-16. · 3.83 Impact Factor