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We’re ready to TEST our Research Questions! In science, how do we usually test a hypothesis?

We’re ready to TEST our Research Questions! In science, how do we usually test a hypothesis?. Is EPIDEMIOLOGY an EXPERIMENTAL or OBSERVATIONAL study ?. Was our ACT passage today EXPERIMENTAL or OBSERVATIONAL ?.

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We’re ready to TEST our Research Questions! In science, how do we usually test a hypothesis?

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  1. We’re ready to TEST our Research Questions!In science, how do we usually test a hypothesis?

  2. Is EPIDEMIOLOGY an EXPERIMENTAL or OBSERVATIONAL study? Was our ACT passage today EXPERIMENTAL or OBSERVATIONAL?

  3. Example: Suppose we want to study theeffect of smoking on lung capacity in women… What might be a problem here? Which type of study would be more reliable?

  4. Why can’t we always do experiments if they are more reliable? • Ethics • Ex: Trying to determine if abortion causes breast cancer • Why experimental design wouldn’t work: It’s unethical to ask subject to have abortions • Lack of Control • Ex: Trying to determine if smoking bans reduce lung cancer rates • Why experimental design wouldn’t work: Researchers can’t control laws and policies • Impractical • Ex: Trying to determine if a certain medicine causes rare symptoms • Why experimental design wouldn’t work: Population size would have to be extremely large

  5. Steps to Testing your Research Question: • Determine whether primary or secondary data is best for answering your research question • Choose a study design • Collect & analyze data 1 m

  6. Step 1: Determine whether primary or secondary data is best for answering your research question What would you guess is the DIFFERENCE between Primary and Secondary data?

  7. Primary and Secondary Data • Primary data: you collect it yourself • Ex:a survey that you administer that asks about the health behaviors of people in your community. • Secondary data: has already been collected by someone else, and you analyze it in a new way to answer the question that you are interested in • Ex: data collected by the Centers for Disease Control and Prevention (CDC) on disease rates in different states

  8. Quick Quiz • If your question is: Why are rates of heart disease different around the US? What type of data would you most likely collect? Primary data ORSecondary data This is probably not data you would be able to collect yourself!

  9. Step 2: Choose a Study Design • Descriptive:answers who, what, when, where • Analytical: answers why or how Steps to Identifying the Problem: • Choose health-related outcome • Clearly define the outcome (“case”) • Choose a population • Describe the problem (descriptive study) Prevalence Incidence

  10. Step 2: Choose a Study Design • Descriptive:answers who, what, when, where • Analytical: answers why or how Case-Control Cohort Cross-Sectional

  11. Analytical Study Design Cohort Case-Control Cross-Sectional

  12. Cohort Set-up

  13. Cohort Example What might be some drawbacks to a cohort study?

  14. Case-Control Set-up Population Controls (No Outcome) Cases (Outcome) (Outcome) RF No RF RF No RF (Risk Factor) (Risk Factor)

  15. Case-Control Example Illinois Population Controls (no Brain Tumors) Cases of Brain Tumors (Outcome) High usage of cell phone Low usage of cell phone High usage of cell phone Low usage of cell phone (Risk Factor) (Risk Factor) What might be some advantages of a case-control study over a cohort study?

  16. Quick Quiz:Identify the study method below as CASE-CONTROL or COHORT 1) Assemble a group of 300 persons with lung cancer and a group of 300 persons without lung cancer and question them about their past smoking history 2) Follow a group of smokers and a group of nonsmokers over time to see who develops lung cancer

  17. Cross-sectional Study • Information on the exposure or risk factor is collected at the same time as information about the health outcome • Often performed by using a survey Example: High school athletes given a survey including questions on: 1) Risk factors:helmet use, training,&type of sport they play 2) Outcomes: types of injuries, severity of injuries

  18. Step 3: Collect & Analyze Data • We’ll practice this during the case!

  19. Extension: MOST Reliable • Clinical trial (experimental) • Cohort • Case-control • Cross-sectional LEAST Reliable

  20. Extension: What calculation would I use? • Cohort: Follows population forward in time, from suspected cause to effect • Quantified by calculating the relative risk for the exposure • Case-control: Works backwards, from suspected effect to cause • Quantified by calculating the odds ratio (we’ll learn about odds ratio later on, but it’s quite similar to relative risk!)

  21. In general, five criteria must be met to establish a cause-and-effect relationship: • Strength of association—the relationship must be clear. • Consistency—observation of the association must be repeatable in different populations at different times. • Temporality—the cause must precede the effect. • Plausibility—the explanation must make sense biologically. • Biological gradient—there must be a dose-response relationship.

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