Regular ArticleShort-Term Effects of a Randomized Computer-Based Out-of-School Smoking Prevention Trial Aimed at Elementary Schoolchildren☆
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Effects of a randomized controlled trial to assess the six-months effects of a school based smoking prevention program in Saudi Arabia
2016, Preventive MedicineCitation Excerpt :A seven point scale (+ 3 = agree) to − 3 = disagree) was used to measure: Attitude, using nine items (Cronbach's α = 0.89); Self-efficacy, using 12 items asking the respondent if he is able not to smoke in various situations (α = 0.98); Intention using two items, intention to smoke in the future and in the next year (r = 0.65); Social norms using eight items (α = 0.92); Social pressure was assessed by eight items on a five point scale and measured whether the participants had ever felt pressure from others to smoke (mother, father, brother(s), sister(s), best friend, friends, classmates, and teachers: + 4 = very often; 3 = often, 2 = sometimes, 1 = few times and 0 = never) (α = 0.73); Social modelling was assessed: 0 = non-smoking; 1 = smoking for the same eight reference persons (α = 0.68). Smoking behavior was categorized based on an algorithm used by earlier international studies on smoking prevention (Ausems et al., 2002; De Vries et al., 2006; Ariza et al., 2008; Lotrean et al., 2013). A respondent was categorized as: (1) a nonsmoker when the respondent indicated to have never smoked not even one puff; had tried smoking once in a while but did not smoke anymore; had quit smoking; smoked less than once a week; or as (2) a smoker when the respondent indicated to smoke at least once a week; smoked daily; and when having reported to smoked 100 cigarettes or more in his life unless reporting to have quit smoking (De Vries et al., 2006; Lotrean et al., 2013).
Calculating sample sizes for cluster randomized trials: We can keep it simple and efficient!
2012, Journal of Clinical EpidemiologyCitation Excerpt :Examples from primary care are patient-centered care of newly diagnosed diabetes [4] and detection and treatment of depression [5] in general practice. Examples from public health are smoking prevention [6] and stress management [7] in primary school. Cluster randomization is less efficient than individual randomization because outcome variation between clusters, reflected by the so-called intraclass correlation (ICC), increases the sampling error of the treatment effect estimate in a cluster randomized trial [8–11].
Health benefits and cost-effectiveness of brief clinician tobacco counseling for youth and adults
2017, Annals of Family MedicineCitation Excerpt :To obtain an estimate of effectiveness for youth counseling, we reviewed studies identified in the USPSTF systematic review.7 We excluded 3 studies41–43 because their measures of youth smoking were inconsistent with those in the simulation model. We excluded another study44 because the tobacco intervention was just 1 aspect of an intensive intervention that targeted a range of substance abuse and sexual health behaviors.
Primary Care-Relevant Interventions for Tobacco and Nicotine Use Prevention and Cessation in Children and Adolescents: Updated Evidence Report and Systematic Review for the US Preventive Services Task Force
2020, JAMA - Journal of the American Medical AssociationPrimary Care Interventions for Prevention and Cessation of Tobacco Use in Children and Adolescents: US Preventive Services Task Force Recommendation Statement
2020, JAMA - Journal of the American Medical AssociationOptimal designs for group randomized trials and group administered treatments with outcomes at the subject and group level
2020, Statistical Methods in Medical Research
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This study was made possible by grants from the European Commission and the Dutch Cancer Foundation. This study is part of a European three-country project, called “Octopus,” in which the United Kingdom (University of Birmingham), Spain (University of Oviedo), and The Netherlands (Maastricht University) were participating. We are grateful to coproject leaders M.L. Lopes and H. Thomas and their colleagues for their cooperation in the project. We thank J. Berben for software construction, and all schools and health educators of local departments for their participation in the project.
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