Bringing Change by Measuring Impact

Health Information Management and Applied Epidemiology for Health Care Workers in South Africa

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Module 7

Introduction to Applied Epidemiology: Determinants of Disease, Research & Study Design

Learning Objectives

At the end of Module 7, you will be able to:

  • List the criteria that epidemiologists use to assess the likelihood of a causal exposure-disease relationship.
  • Explain the purpose of sampling in research and evaluation in the health field, and identify different sampling techniques.
  • Explain the concepts of estimate, 95% confidence interval, hypothesis testing, and p-value.
  • Define bias and confounding in epidemiologic studies, and describe the main categories of bias.
  • Describe the characteristics of different types of studies: descriptive vs. analytical, qualitative vs. quantitative, observational vs. experimental, and prospective vs. retrospective.
  • Describe the characteristics, strengths, and weaknesses of different types of analytic studies (cross-sectional studies, case-control studies, and cohort studies) and randomised controlled trials.
  • Describe different quantitative data collection techniques, and their advantages and disadvantages.
  • Identify principles for the ethical conduct of research studies, and for the protection of human subjects.

In Module 7, we will build upon what we learned in Module 6. This includes learning about causality in terms of the exposure-disease relationship, how sampling works, and the concepts of estimate, confidence intervals, hypothesis testing, and p-values. We will also learn about different types of epidemiological studies, along with their strengths and weaknesses, and how bias can affect results. We will end the module with a discussion about ways to collect data, and ethics around data collection.

Pre-test (10 minutes)

Part 1: Causality (20 minutes)

Part 2: Judging Strength of Association: Estimates, 95% Confidence Interval (30 minutes)

Part 3: Judging Causality in Epidemiologic Studies: Sampling, Bias, and Confounding (45 minutes)

Part 4: Judging Causality in Epidemiologic Studies: Bias (15 minutes)

Part 5: Judging Causality in Epidemiologic Studies: Confounding (15 minutes)

Part 6: Study Designs (60 minutes)

Part 7: Data Collection in Studies (15 minutes)

Part 8: Ethics in Studies (20 minutes)

  • Summary

    In this module, we built upon the basic concepts of applied epidemiology from Module 6, covering determinants of disease, research, and study design.

    In Part 1, we explored causality, so that we could learn how to assess the likelihood of a causal exposure-disease relationship. Criteria for causality include:

    • Temporal relationship
    • Plausibility
    • Consistency
    • Strength
    • Dose response relationship

    We then looked at how to assess the strength of an association by learning about estimates and confidence intervals (Part 2). This led into a deeper study of causality in epidemiology, including looking at how sampling, bias, and confounding can affect the results of a study (Parts 3, 4, and 5).

    In Part 6, we expanded our knowledge about study design. We had already learned about descriptive vs. analytical studies in Module 6; here we looked at study design in more detail, covering qualitative vs. quantitative, observational vs. experimental, and prospective vs. retrospective studies, and the specific types of investigations that fall under each category.

    In Part 7 we learned about different qualitative and quantitative data collection techniques.

    Finally, in Part 8, we explored issues around ethical conduct in studies, in terms of how to best conduct them and protect research participants.

    In Module 8, we will learn about Excel, and how to display the results that we get from our studies.

Post-test (10 minutes)

  • References

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    Exercise adapted from Adapted from: http://www.epidemiolog.net/epid168/labs/ConfoundingExerInstGuid2000.pdf