American Journal of Health Promotion · 2009 · 32 citations · 51 references
Public HealthCounselingPopulation Health SciencesBehavioral HealthOutcomes ResearchRural HealthRelapse PreventionSmoking Cessation SupportTobacco Cessation CounselingTobacco Use CessationTobacco Use DisorderTobacco Use PreventionBehavioral Tobacco Cessation TherapyIndividual Smoking Cessation CounselingLong-term AbstinenceRural Population HealthSmoking Abstinence MaintenanceSmoking Relapse PreventionTobacco Treatment AdherenceTobacco Use Among Rural Populations
PURPOSE: Outcomes from a statewide program that delivered evidence-based, intensive treatment for tobacco dependence to a rural population of lower socioeconomic status (SES) were evaluated. Factors that predicted success and measurement considerations were examined. DESIGN AND ANALYSES: Data were collected at intake, at all treatment sessions, and at 3- and 12-months posttreatment. Abstinence rates were calculated using complete-case analysis and intention-to-treat analysis, and they were estimated for all participants. Logistic regression was used to evaluate the predictive significance of demographic and clinical factors. SETTING: Twenty health care sites across Arkansas. PARTICIPANTS: A total of 2,350 predominantly rural, lower SES, Arkansas residents. INTERVENTION: Evidence-based, six-session, multi-component cognitive-behavioral therapy with relapse prevention. RESULTS: The estimated percent abstinent was 26.47% at 3-months and 21.73% at 12-months posttreatment; 51.02% of patients completed treatment and demonstrated markedly higher quit rates. Although numerous factors predicted outcomes at different points, self-efficacy and dependence levels at intake were robust predictors across time and methods of calculating outcomes. Sex, partner smoking status, and educational level were significant predictors of long-term abstinence. CONCLUSIONS: This study demonstrates that intensive, evidence-based treatment for tobacco dependence can be successfully delivered in a statewide program and can yield long-term outcomes that approximate those seen in more controlled settings. Overall sample estimates may be more appropriate for the assessment of outcomes in this context.
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