Six-months follow-up of a cluster randomized trial of school-based smoking prevention education programs in Aceh, Indonesia

BACKGROUND Most smokers start smoking during their early adolescence under the impression that smoking entails positive attributes. Given the addictive nature of cigarettes, however, many of them might end up as long-term smokers and suffering from tobacco-related diseases. To prevent tobacco use among adolescents, the large international medical students’ network Education Against Tobacco (EAT) educates more than 40,000 secondary school students per year in the classroom setting, using evidence-based self-developed apps and strategies. OBJECTIVE This study aimed to evaluate the long-term effectiveness of the school-based EAT intervention in reducing smoking prevalence among seventh-grade students in Germany. Additionally, we aimed to improve the intervention by drawing conclusions from our process evaluation. METHODS We conduct a cluster-randomized controlled trial with measurements at baseline and 9, 16, and 24 months postintervention via paper-and-pencil questionnaires administered by teachers. The study groups consist of randomized schools receiving the 2016 EAT curriculum and control schools with comparable baseline data (no intervention). The primary outcome is the difference of change in smoking prevalence between the intervention and control groups at the 24-month follow-up. Secondary outcomes are between-group differences of changes in smoking-related attitudes and the number of new smokers, quitters, and never-smokers. RESULTS A total of 11,268 students of both sexes, with an average age of 12.32 years, in seventh grade of 144 secondary schools in Germany were included at baseline. The prevalence of cigarette smoking in our sample was 2.6%. The process evaluation surveys were filled out by 324 medical student volunteers, 63 medical student supervisors, 4896 students, and 141 teachers. CONCLUSIONS The EAT cluster randomized trial is the largest school-based tobacco-prevention study in Germany conducted to date. Its results will provide important insights with regards to the effectiveness of medical student–delivered smoking prevention programs at school. INTERNATIONAL REGISTERED REPOR DERR1-10.2196/13508

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A School-Based Sleep Education Program for Adolescents: A Cluster Randomized Trial

PEDIATRICS ◽

10.1542/peds.2014-2419d ◽

2015 ◽

Vol 135 (3) ◽

pp. X23-X23

Keyword(s):

Randomized Trial ◽

Education Program ◽

Cluster Randomized Trial ◽

Sleep Education ◽

School Based ◽

Cluster Randomized

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Sustainability of Benefits from Parenting Interventions Delivered Through Health Services: Follow-Up at Age 6 Years of a Cluster Randomized Trial

SSRN Electronic Journal ◽

10.2139/ssrn.3279187 ◽

2018 ◽

Author(s):

Joanne A Smith ◽

Susan M Chang ◽

Florencia Lopez-Boo ◽

Susan P Walker

Keyword(s):

Health Services ◽

Randomized Trial ◽

Cluster Randomized Trial ◽

Parenting Interventions ◽

Cluster Randomized

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Design and analysis of a 2-year parallel follow-up of repeated ivermectin mass drug administrations for control of malaria: Small sample considerations for cluster-randomized trials with count data

Clinical Trials ◽

10.1177/17407745211028581 ◽

2021 ◽

pp. 174077452110285

Author(s):

Conner L Jackson ◽

Kathryn Colborn ◽

Dexiang Gao ◽

Sangeeta Rao ◽

Hannah C Slater ◽

...

Keyword(s):

Randomized Trial ◽

Cluster Randomized Trial ◽

Mixed Effects ◽

Small Sample ◽

Mixed Effects Models ◽

Type I ◽

Cluster Randomized ◽

Cluster Level ◽

Generalized Estimating

Background: Cluster-randomized trials allow for the evaluation of a community-level or group-/cluster-level intervention. For studies that require a cluster-randomized trial design to evaluate cluster-level interventions aimed at controlling vector-borne diseases, it may be difficult to assess a large number of clusters while performing the additional work needed to monitor participants, vectors, and environmental factors associated with the disease. One such example of a cluster-randomized trial with few clusters was the “efficacy and risk of harms of repeated ivermectin mass drug administrations for control of malaria” trial. Although previous work has provided recommendations for analyzing trials like repeated ivermectin mass drug administrations for control of malaria, additional evaluation of the multiple approaches for analysis is needed for study designs with count outcomes. Methods: Using a simulation study, we applied three analysis frameworks to three cluster-randomized trial designs (single-year, 2-year parallel, and 2-year crossover) in the context of a 2-year parallel follow-up of repeated ivermectin mass drug administrations for control of malaria. Mixed-effects models, generalized estimating equations, and cluster-level analyses were evaluated. Additional 2-year parallel designs with different numbers of clusters and different cluster correlations were also explored. Results: Mixed-effects models with a small sample correction and unweighted cluster-level summaries yielded both high power and control of the Type I error rate. Generalized estimating equation approaches that utilized small sample corrections controlled the Type I error rate but did not confer greater power when compared to a mixed model approach with small sample correction. The crossover design generally yielded higher power relative to the parallel equivalent. Differences in power between analysis methods became less pronounced as the number of clusters increased. The strength of within-cluster correlation impacted the relative differences in power. Conclusion: Regardless of study design, cluster-level analyses as well as individual-level analyses like mixed-effects models or generalized estimating equations with small sample size corrections can both provide reliable results in small cluster settings. For 2-year parallel follow-up of repeated ivermectin mass drug administrations for control of malaria, we recommend a mixed-effects model with a pseudo-likelihood approximation method and Kenward–Roger correction. Similarly designed studies with small sample sizes and count outcomes should consider adjustments for small sample sizes when using a mixed-effects model or generalized estimating equation for analysis. Although the 2-year parallel follow-up of repeated ivermectin mass drug administrations for control of malaria is already underway as a parallel trial, applying the simulation parameters to a crossover design yielded improved power, suggesting that crossover designs may be valuable in settings where the number of available clusters is limited. Finally, the sensitivity of the analysis approach to the strength of within-cluster correlation should be carefully considered when selecting the primary analysis for a cluster-randomized trial.

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School-based mental health intervention for children in war-affected Burundi: a cluster randomized trial

BMC Medicine ◽

10.1186/1741-7015-12-56 ◽

2014 ◽

Vol 12 (1) ◽

Cited By ~ 74

Author(s):

Wietse A Tol ◽

Ivan H Komproe ◽

Mark JD Jordans ◽

Aline Ndayisaba ◽

Prudence Ntamutumba ◽

...

Keyword(s):

Mental Health ◽

Randomized Trial ◽

Cluster Randomized Trial ◽

Health Intervention ◽

Mental Health Intervention ◽

School Based ◽

Cluster Randomized

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Assessing the impact of a school-based latrine cleaning and handwashing program on pupil absence in Nyanza Province, Kenya: a cluster-randomized trial

Tropical Medicine & International Health ◽

10.1111/tmi.12360 ◽

2014 ◽

Vol 19 (10) ◽

pp. 1185-1197 ◽

Cited By ~ 22

Author(s):

Bethany A. Caruso ◽

Matthew C. Freeman ◽

Joshua V. Garn ◽

Robert Dreibelbis ◽

Shadi Saboori ◽

...

Keyword(s):

Randomized Trial ◽

Cluster Randomized Trial ◽

Nyanza Province ◽

School Based ◽

Cluster Randomized ◽

The Impact

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Abstract P494: Long-term Outcomes of a Cluster-randomized Trial Testing the Effects Blood Pressure Telemonitoring and Pharmacist Management

Hypertension ◽

10.1161/hyp.70.suppl_1.p494 ◽

2017 ◽

Vol 70 (suppl_1) ◽

Author(s):

Karen L Margolis ◽

Stephen E Asche ◽

Anna R Bergdall ◽

Steven P Dehmer ◽

Beverly B Green ◽

...

Keyword(s):

Blood Pressure ◽

Randomized Trial ◽

Clinical Care ◽

Cluster Randomized Trial ◽

Home Blood Pressure ◽

Uncontrolled Hypertension ◽

Routine Clinical Care ◽

Differential Reduction ◽

Cluster Randomized

Background/Aims: Hypertension is a common condition and leading cause of cardiovascular disease. We previously reported results of a cluster-randomized trial evaluating a home blood pressure (BP) telemonitoring and pharmacist management intervention, with significant reductions in BP favoring the intervention arm over 18 months. This analysis examined the durability of the intervention effect on BP through 54 months of follow-up and compared BP measurements performed in the research clinic and in routine clinical care. Methods: The Hyperlink trial randomized 16 primary care clinics having 450 study-enrolled patients with uncontrolled hypertension to either Telemonitoring Intervention (TI) or usual care (UC) study arms. BP was measured as the mean of 3 measurements obtained at each research clinic visit. General linear mixed models utilizing a direct likelihood-based ignorable approach for missing data were used to examine change from baseline to 54 months in systolic and diastolic BP (SBP and DBP). Results: Research clinic BP measurements were obtained from 326 (72%) study patients at the 54 month follow-up visit. Routine clinical care BP measurements were obtained from 444 (99%) of study patients from 7025 visits during the follow-up period. For TI patients, based on research clinic measurements baseline SBP was 148.2 mm Hg and 54 month follow-up was 131.2 mm Hg (-17.0 mm Hg, p<.001). For UC patients, baseline SBP was 147.7 mm Hg and 54 month follow-up was 131.7 mm Hg ( -16.0 mm Hg, p<.001). The differential reduction by study arm in SBP from baseline to 54 months was -1.0 mm Hg (95% CI: -5.4 to 3.4, p=0.63). For TI patients, baseline DBP was 84.4 mm Hg and 54 month follow-up was 77.8 (-6.6 mm Hg, p<.001). For UC patients, baseline DBP was 85.1 mm Hg and 54 month follow-up was 79.1 mm Hg (-6.0 mm Hg, p<.001). The differential reduction by study arm in DBP from baseline to 54 months was -0.6 mm Hg (95% CI: -3.5 to 2.4, p=0.67). SBP and DBP results from routine clinical measurements closely approximated the pattern of results from research clinic measurements. Conclusion: Significant BP reductions in the TI arm relative to UC were no longer seen at 54 month follow-up. To maintain intervention benefits over a longer period of time additional intervention is needed.

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