Background: Tobacco smoking is the leading cause of disease, death, and disability in the United States. Dental practitioners are advised to provide evidence-based smoking cessation interventions to their patients, yet dental practitioners frequently fail to deliver brief smoking cessation advice.
Objectives: To test whether giving dental practitioners a clinical decisions support (CDS) system embedded in their electronic dental record would increase the rate at which patients who smoke (1) report receiving a brief intervention or referral to treatment during a recent dental visit, (2) taking action related to smoking cessation within 7 days of visit, and (3) stop smoking for 1 day or more or reduce the amount smoked by 50% within 6 months.
Methods: Two-group, parallel arm, cluster-randomized trial. From March through December 2019, 15 nonacademic primary care dental clinics were randomized via covariate adaptive randomization to either a usual care arm or the CDS arm. Adult smokers completed an initial telephone survey within 7 days of their visit and another survey after 6 months.
Results: Forty-three patients from 5 CDS and 13 patients from 2 usual care clinics completed the 7-day survey. While the proportion of patients who reported receipt of a brief intervention or referral to treatment was significantly greater in the CDS arm than the usual care arm (84.3% vs 58.6%; P = .005), the differences in percentage of patients who took any action related to smoking cessation within 7 days (44.4% vs 22.3%; P = .077), or stopped smoking for one day or more and/or reduced amount smoked by 50% within 6 months (63.1% vs 46.2%; P = .405) were large but not statistically significant.
Conclusions: Despite interruption by COVID-19, these results demonstrate a promising approach to assist dental practitioners in providing their patients with smoking cessation screening, brief intervention and referral to treatment.
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http://dx.doi.org/10.1016/j.jebdp.2022.101747 | DOI Listing |
Drug Alcohol Depend Rep
December 2024
Department of Family and Preventive Medicine, College of Medicine, The University of Oklahoma Health Sciences, Oklahoma City, OK, USA.
Background: Smoking prevalence among U.S. adults experiencing homelessness is ≥70 %.
View Article and Find Full Text PDFTob Control
January 2025
Department of Experimental Oncology, IEO European Institute of Oncology IRCCS, Milan, Italy.
BackgroundTobacco use is linked to increased cancer risk, and people who smoke represent a large proportion of newly diagnosed patients with cancer. The fact that smoking cessation at the time of diagnosis can improve the patient's life expectancy is still not broadly understood. We conducted a systematic review and meta-analysis to quantify the survival benefits obtainable by quitting smoking on diagnosis.
View Article and Find Full Text PDFEur J Public Health
January 2025
Department of Cardiology, Faculty of Medicine and University Hospital Cologne, University of Cologne, Cologne, Germany.
We quantified the fraction of cardiovascular deaths attributable to smoking in Germany over time, accounting for population ageing. We calculated population-attributable fractions to quantify cardiovascular deaths attributable to smoking for 1992 to 2021, and compared actual with age-standardized figures. We found a significant decline in the number of cardiovascular deaths attributable to smoking: from about 71 900 cases in 1992 to around 42 000 cases in 2021, with a steeper decline in men.
View Article and Find Full Text PDFIntern Emerg Med
January 2025
Department of Social and Behavioral Sciences, School of Global Public Health, New York University, New York, NY, USA.
Psychol Methods
January 2025
Department of Psychology, University of Pittsburgh.
Intensive longitudinal data analysis, commonly used in psychological studies, often concerns outcomes that have strong floor effects, that is, a large percentage at its lowest value. Ignoring a strong floor effect, using regular analysis with modeling assumptions suitable for a continuous-normal outcome, is likely to give misleading results. This article suggests that two-part modeling may provide a solution.
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