DrugEpi 4-3 Chance Module 4 Overview Context Content Area: Interpretation of Epidemiological Evidence Essential Question (Generic): Is the association causal? Essential Question (Drug Abuse Specific): Is an association with drug abuse causal? Enduring Epidemiological Understanding: Causation is only one explanation for finding an association between an exposure and a disease. Because observational studies are complicated by factors not controlled by the observer, other explanations must also be considered. Synopsis: In Module 4, students explore the rationale and methods of interpreting epidemiological studies. Students develop skills to assess possible explanations for an association found in a study, with consideration of explanations of causality, chance, confounding, reversed time order, and bias. Module 4 concludes with consideration of methods for weighing the overall evidence for an association. Lessons: Lesson 4-1: Introduction to Interpreting Associations Lesson 4-2: Causality Lesson 4-3: Chance Lesson 4-4: Bias Lesson 4-5: Confounding Lesson 4-6: Reverse Time Order Lesson 4-7: Weighing the Evidence

DrugEpi 4-3 Chance Module 4 - Interpretation of Epidemiological Evidence Lesson 4-3 Chance Content A class exercise with 100 cards to illustrate “chance” as a possible explanation for an association Big Ideas When an association is found, several possible explanations must be considered, including the possibility that the association is due to chance The larger the sample size, the less likely that an observed association is due to chance This project is supported by a Science Education Drug Abuse Partnership Award, Grant Number 1R24DA , from the National Institute on Drug Abuse, National Institutes of Health.

DrugEpi 4-3 Chance Where are we? Essential QuestionsEnduring Understandings 1.How is this disease distributed? Health-related conditions and behaviors are not distributed uniformly in a population. They have unique distributions that can be described by how they are distributed in terms of person, place, and time. 2.What hypotheses might explain the distribution of disease? Clues for formulating hypotheses can be found by observing the way a health-related condition or behavior is distributed in a population. 3.Is there an association between the hypothesized cause and the disease? Causal hypotheses can be tested by observing exposures and diseases of people as they go about their daily lives. Information from these observational studies can be used to make and compare rates and identify associations. 4.Is the association causal? Causation is only one explanation for an association between an exposure and a disease. Because observational studies are complicated by factors not controlled by the observer, other explanations also must be considered. 5.What should be done when preventable causes of disease are found? Policy decisions are based on more than the scientific evidence. Because of competing values - social, economic, ethical, environmental, cultural, and political factors may also be considered.

DrugEpi 4-3 Chance Chance Is the association due to chance? 1.Cause 2.Chance

DrugEpi 4-3 Chance Population All the people in a particular group. Review

DrugEpi 4-3 Chance Sample A selection of people from a population Review

DrugEpi 4-3 Chance Sample Population Process of predicting from what is observed to what is not observed. (Observed) (Not Observed) Review Inference

DrugEpi 4-3 Chance Deck of 100 cards Population

DrugEpi 4-3 Chance a 25 cards b c d Population

DrugEpi 4-3 Chance = Population abc d Exposure = eating chocolate Outcome = trying marijuana

DrugEpi 4-3 Chance = Population a 25 cards bc d = ab cd Odd # Even # No Marijuana Population Total

DrugEpi 4-3 Chance Exposed Not Exposed Outcome No Outcome Total Review - The 2x2 Table The 2x2 table can express relationships between exposure and outcome Optional

DrugEpi 4-3 Chance The 2x2 table is a tool used to express the numbers of people with and without the exposure and with and without the outcome. Review - The 2x2 Table Optional

DrugEpi 4-3 Chance A cross-classification of data where categories of one variable are presented in rows and categories of another variable are presented in columns. Review - Another Way To Say... Optional

DrugEpi 4-3 Chance Total Outcome No Outcome Exposed Not Exposed ExposureExposure Outcome / Disease ab cd Review - The 2x2 Table Are there controls in this 2x2 table? If yes, where are they? Optional

DrugEpi 4-3 Chance = Population a 25 cards bc d = Total Odd # Even # No Marijuana Population

DrugEpi 4-3 Chance = Population = M&M’s No M&M’s Flu No Flu Total = Total a 25 cards bc d Odd # Even # No Marijuana Population

DrugEpi 4-3 Chance Relative Risk A way of showing the relationship between two risks Tells us the number of times one risk is larger or smaller than another Calculated by dividing the risk of an outcome in one group by the risk of the outcome in another group Review Risk A measure of how often an event occurs in a defined group of people in a defined period of time The likelihood of developing a disease

DrugEpi 4-3 Chance = Population = Total a 25 cards bc d Risk 25 / 50 or 50% Odd # Even # No Marijuana Population

DrugEpi 4-3 Chance = Population a 25 cards bc d = TotalRiskRelative Risk 25 / 50 or 50 % 50 % / 50% = = 1 50 % ____ Odd # Even # No Marijuana Population

DrugEpi 4-3 Chance 25 cards Population

DrugEpi 4-3 Chance Definition Chance To occur accidentally To occur without design A coincidence

DrugEpi 4-3 Chance Chance

DrugEpi 4-3 Chance Chance

DrugEpi 4-3 Chance Population Sample b Sample of 20 cards 25 cards Sample

DrugEpi 4-3 Chance Population Sample b Sample of 20 cards 25 cards 10 Total Chocolate No Chocolate No Marijuana Sample

DrugEpi 4-3 Chance Population Sample b Sample of 20 cards 25 cards 10 Total Risk 5 / 10 or 50 % Chocolate No Chocolate No Marijuana Sample

DrugEpi 4-3 Chance Population Sample b Sample of 20 cards 25 cards 10 Total Risk 5 / 10 or 50 % Chocolate No Chocolate No Marijuana Sample Relative Risk 50 % / 50% = = % ____

DrugEpi 4-3 Chance b Sample of 20 cards Total Risk 5 / 10 = 50 % 50 1 Relative Risk By Chance CDC % ___ % = Chocolate No Chocolate No Marijuana Sample

DrugEpi 4-3 Chance 10 Total Risk 5 / 10 or 50 % Relative Risk How many students picked a sample with 5 people in each cell? = % ____ Chocolate No Chocolate No Marijuana Chance By Chance

DrugEpi 4-3 Chance Worksheet

DrugEpi 4-3 Chance Relative Risks Greater than 1.0Less than 1.0 Chance

DrugEpi 4-3 Chance Study of High School Students Links Chocolate-Eating Habit to a Higher Risk of Trying Marijuana In the News

DrugEpi 4-3 Chance Relative Risks Greater than 1.0Less than 1.0 Possible Explanations for Finding an Association

DrugEpi 4-3 Chance In the News Study of High School Students Links Eating Chocolate to a Lower Risk of Trying Marijuana

DrugEpi 4-3 Chance Relative Risks Greater than 1.0Less than 1.0 By Chance 25 cards Chance Range? 20 card s

DrugEpi 4-3 Chance b Sample of 20 cards Total Risk 5 / 10 = 50 % 50 Relative Risk 50 % ___ % = Odd # Even # No Marijuana Different Sample Sizes

DrugEpi 4-3 Chance Relative Risks Greater than 1.0Less than 1.0 By Chance 25 cards Chance 50 card s Range?

DrugEpi 4-3 Chance b Sample of 20 cards Total Risk 5 / 10 = 50 % 50 Relative Risk 75 % ___ % = Odd # Even # No Marijuana Different Sample Sizes

DrugEpi 4-3 Chance Relative Risks Greater than 1.0Less than 1.0 By Chance 25 cards Chance 75 card s Range?

DrugEpi 4-3 Chance b Sample of 20 cards Total Risk 5 / 10 = 50 % 50 1 Relative Risk 99 % ___ % = Odd # Even # No Marijuana Different Sample Sizes

DrugEpi 4-3 Chance Review Results

DrugEpi 4-3 Chance Chance Could the association have occurred by chance? 1.Cause 2.Chance

DrugEpi 4-3 Chance Big Ideas in this Lesson (4-3) When an association is found, several possible explanations must be considered, including the possibility that the association is due to chance The larger the sample size, the less likely that an observed association is due to chance This project is supported by a Science Education Drug Abuse Partnership Award, Grant Number 1R24DA , from the National Institute on Drug Abuse, National Institutes of Health. Re-Cap

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