Objectives: We tested a Public Health Service 5As-based clinician-delivered smoking cessation counseling intervention with adolescent smokers in pediatric primary care practice.
Methods: We enrolled clinicians from 120 practices and recruited youth (age ≥14) from the American Academy of Pediatrics Pediatric Research in Office Settings practice-based research network. Practices were randomly assigned to training in smoking cessation (intervention) or social media counseling (attentional control). Youth recruited during clinical visits completed confidential screening forms. All self-reported smokers and a random sample of nonsmokers were offered enrollment and interviewed by phone at 4 to 6 weeks, 6 months, and 12 months after visits. Measures included adolescents' report of clinicians' delivery of screening and counseling, current tobacco use, and cessation behaviors and intentions. Analysis assessed receipt of screening and counseling, predictors of receiving 5As counseling, and effects of interventions on smoking behaviors and cessation at 6 and 12 months.
Results: Clinicians trained in the 5As intervention delivered more screening (β = 1.0605, < .0001) and counseling (β = 0.4354, < .0001). In both arms, clinicians more often screened smokers than nonsmokers. At 6 months, study arm was not significantly associated with successful cessation; however, smokers in the 5As group were more likely to have quit at 12 months. Addicted smokers more often were counseled, regardless of study arm, but were less likely to successfully quit smoking.
Conclusions: Adolescent smokers whose clinicians were trained in 5As were more likely to receive smoking screening and counseling than controls, but the ability of this intervention to help adolescents quit smoking was limited.
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http://dx.doi.org/10.1542/peds.2020-0644 | 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 %.
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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.
Recent data on methods used by adults to stop smoking can inform tobacco control policies. Nationally representative Centers for Disease Control and Prevention survey data from the 2022 National Health Interview Survey (N = 27,651) were used to analyze populations of US adults who self-reported having stopped smoking cigarettes for 6 months or longer in the last year and the methods they used, or who did not stop smoking but tried in the last year (N = 1735). In 2022, an estimated 2.
View Article and Find Full Text PDFPsychol 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.
View Article and Find Full Text PDFEnter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!