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Critiquing Presented Content – Critical Thinking and Evidence Based Medicine (EBM)

by Raywat Deonandan, PhD
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    00:01 Hello and welcome epidemiology. In this lecture we're going to learn a little bit about critical thinking and evidence-based medicine. And I want to start off by telling you about my first consulting opportunity when I was a graduate student learning epidemiology.

    00:15 I was assisting some scientists, we were trying to determine if gynecological practice was largely evidence-based. And to do this we looked through the literature and attempted to tell if the things a gynecologist were doing commonly with pregnant women, like shaving their pubic hair and giving them enemas before birth, was worthwhile. We determined it was not worthwhile, so much of these practices weren't evidence-based, the problem though, is that we couldn't convince the gynecologist to stop doing these practices, so lesson there is, even though things may or may not be evidence-based, clinical practice is still based upon values and experiences.

    00:52 Having said that, today you're going to learn about how to apply epidemiological principles to help you make evidence-based medical decisions. So we're going to learn how to apply the steps of EBM, which is evidence-based medicine, we're going to learn how to rank the different kinds of study designs that you're going to discover in the process of doing your EBM searches and you're going to learn how to phrase a research question using a method that we call PICO.

    01:19 To begin with, I want to show you this image. This is an image that I saw on the subways of Toronto many years ago, essentially it says, a couple of things. It has two bits of information, the first is, that at approximately 3 to 5 children in every Canadian classroom have witnessed their mother being assaulted, a dire statistic, a little depressing.

    01:39 In the second is that 70% of men in court ordered treatment for domestic violence witnessed it as a child. Okay, so let's think about what this is actually saying. It's telling us that obviously some children are seeing domestic violence at home, that's not a good thing, it's further implying that those children may grow up to be abusers themselves. I don't mean to minimize this issue, it's a serious issue, we should take it very seriously. Now I want you to think about those numbers through a new epidemiological lens. What are the numbers actually saying to you? What information is missing? What additional information do you think you need to add a bit more nuance and wisdom to these numbers? First thing is 3 to 5 children, is that a large number? Think about it. What's the denominator? How many children are in the classroom totally? If there are 10 children, then that's 3 to 50% of kids in that class saw domestic abuse. That's a high number we can agree, that bad, but if it's a 100 kids in the classroom, that's 3 to 5%, still one child is bad enough, but 3 to 5% isn't as bad as 30 to 50%, so the denominator matters. The second bit of information is that 70% of men in a court ordered treatment for domestic violence saw it as a child, okay that seems like a large number, but I want you to think about again, what should we be comparing that to? How many men who weren't in a court ordered treatment saw it as a child? I don't know the answer, but think about this, maybe 70% of men in a court ordered treatment for domestic violence also ate rice pudding at some point in their lives. Is the implication that rice pudding causes you to be a domestic abuser? Again, I don't mean to minimize this issue, my point is, the numbers are meaningless without a control group or a denominator, get my point? I hope so.

    03:29 So epidemiology is a way of thinking, it's a way of adding wisdom to numbers that otherwise are alone in a void without context. Some of the things we do in epidemiology is to critically evaluate published studies, using many of the tools that we're going to learn in the course of this lecture and other lectures. We are going to identify the biases that may affect the conclusions that we draw from the published evidence. Again in another lecture we are going to talk more deeply about what those biases are, but I want you to be aware that biases exist, they always exist, the question is, how much those biases interrupt your ability to make meaningful conclusions that are valid for your practice? Lastly we're going to assess the qualities of different types of evidence. Not all evidence is the same; some are ranked more highly than others, so we'll talk a little bit about how those rankings occur.


    About the Lecture

    The lecture Critiquing Presented Content – Critical Thinking and Evidence Based Medicine (EBM) by Raywat Deonandan, PhD is from the course Epidemiology and Biostatistics: Introduction.


    Included Quiz Questions

    1. What is determined to be worthwhile in clinical practice is still based upon values and experiences
    2. The clinicians assessed the studies and determined they were not methodologically sound
    3. The clinicians did not have access to computers to determine whether or not the practices were worthwhile
    4. The studies that were presented as evidence were of low quality
    5. Evidence based medicine had not yet become a common tool used by clinicians
    1. 5% of men who are NOT in court ordered treatment for domestic violence have witnessed domestic violence as a child
    2. 10% of all men are in court-ordered treatment for domestic violence
    3. 75% of men who are NOT in court-ordered treatment for domestic violence have witnessed domestic violence as a child
    4. 5% of all men who have witnessed domestic violence as a child ate rice pudding at some point during their childhood
    5. 50% of all men have witnessed domestic violence as a child
    1. Control group comparison
    2. The number of mothers involved
    3. Association with age
    4. Causal relationship
    5. Number of men in the world

    Author of lecture Critiquing Presented Content – Critical Thinking and Evidence Based Medicine (EBM)

     Raywat Deonandan, PhD

    Raywat Deonandan, PhD


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