Study Outline: Smoking-Behaviour Articles and Dataset

Lessons in this plan

1. 1 Research scope across the smoking-behaviour materials Identify the main research aims in the two articles: monthly population-level associations between smoking and alcohol-related behaviours in England, and associations between smoking-onset age and cardiovascular or mortality outcomes. 20 min Video Explanation
2. 2 Study designs and populations Differentiate the study designs and samples used in the sources, including monthly representative household surveys in England for 2014–2016 and the REGICOR population-based cohort with follow-up, and summarize who was included in each study. 25 min Explanation
3. 3 Key variables in Beard et al. (2017) List and define the core variables in Beard et al. 2017: smoking prevalence, motivation to quit, quit attempts, high-risk drinking, motivation to reduce alcohol consumption, and attempts to reduce alcohol consumption, including high-risk drinking defined by AUDIT score greater than 8. 25 min Explanation
4. 4 Key variables in Fa-Binefa et al. and outcome interpretation Explain the main exposure and outcomes in Fa-Binefa et al., especially smoking-onset age, cardiovascular disease outcomes, all-cause mortality, and adjusted hazard ratios, including the reported cut-point analysis around age 12. 25 min Explanation
5. 5 How the smoking-behaviour dataset is structured Read the workbook structure and variable dictionary in the dataset, identifying the Rawdata, ListVariables, and Source sheets and the variables Age, Alcohol, AgeOnset, Gender, and Smoking with their measurement scales and coded values. 20 min Explanation
6. 6 Working with dataset coding and data quality checks Practice translating dataset codes into analysis-ready variables, such as Alcohol categories, AgeOnset groups, and Gender labels, and perform basic checks on ranges, category values, and consistency with the provided metadata. 30 min Explanation
7. 7 Interpreting analytic methods and reported findings Interpret the main analytical approaches used in the articles—ARIMAX time-series modelling in Beard et al. and Cox regression with spline and bootstrap-based cut-point assessment in Fa-Binefa et al.—and connect them to the kinds of conclusions each study can support. 35 min Explanation
8. 8 Applying the articles to the dataset responsibly Use the article concepts to frame exploratory questions for the provided dataset, describing which variables can support simple descriptive or group-comparison analyses and which article-level constructs are not directly available in the workbook. 30 min Explanation