Epidemiology 1
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Questions and Answers

Which form of bias occurs when the sample population does not accurately represent the larger population?

  • Selection Bias (correct)
  • Causal Bias
  • Measurement Bias
  • Response Bias

    • What type of bias arises from errors in how data is collected or measured?

  • Survivorship Bias
  • Measurement Bias (correct)
  • Sampling Bias
  • Confounding Bias

    • Which of the following represents a confounding factor in a study examining the effect of physical activity on depression?

  • The timing of the survey administration
  • Dietary habits of the participants (correct)
  • The measurement of physical activity levels
  • The method of analysis used

    • In determining causation from an observed association, which of the following must be considered?

    <p>Bias Types (D)</p> Signup and view all the answers

    What does the concept of reverse causation imply in epidemiological studies?

    <p>The outcome happens before the exposure (D)</p> Signup and view all the answers

    What is primarily introduced by the investigator during a study that is not intentionally meant to skew results?

    <p>Bias (A)</p> Signup and view all the answers

    What method is employed to minimize the effects of confounding in a study design?

    <p>Restriction (B)</p> Signup and view all the answers

    Which type of bias occurs when the method of selecting participants results in a misrepresentation of a population?

    <p>Selection bias (A)</p> Signup and view all the answers

    What is an example of a confounding variable that could affect the outcome of a study?

    <p>A participant's age (D)</p> Signup and view all the answers

    What is the primary difference between observational and experimental study designs?

    <p>Whether the investigator assigned the exposure (C)</p> Signup and view all the answers

    Which of the following is NOT a type of bias that can occur in study designs?

    <p>Confounding bias (A)</p> Signup and view all the answers

    In a case-control study, what is the primary starting point for the research?

    <p>Case status (A)</p> Signup and view all the answers

    How does a longitudinal study help in addressing the issue of reverse causality?

    <p>It follows individuals over time to observe outcomes. (A)</p> Signup and view all the answers

    Which Bradford-Hill consideration emphasizes that the exposure must precede the outcome for a causal link?

    <p>Temporality (D)</p> Signup and view all the answers

    What type of study is mainly concerned with assessing frequency and distribution of diseases at a specific point in time?

    <p>Cross-sectional study (D)</p> Signup and view all the answers

    What is selection bias?

    <p>Bias that occurs when the sample is not representative of the population. (B)</p> Signup and view all the answers

    Which of the following is an example of measurement bias?

    <p>A researcher who subconsciously influences participant responses. (D)</p> Signup and view all the answers

    Which statement about confounding factors is true?

    <p>A confounder is related to both the exposure and the outcome. (A)</p> Signup and view all the answers

    How does sample size affect confidence intervals?

    <p>Larger samples narrow the confidence interval and reduce p-values. (D)</p> Signup and view all the answers

    Which of the following errors represents a Type 1 error?

    <p>A statistically significant result that occurs by chance. (C)</p> Signup and view all the answers

    What characterizes observer bias?

    <p>Unintentional reporting errors influenced by the observer's knowledge. (B)</p> Signup and view all the answers

    How can selection bias affect study results?

    <p>It leads to an untrue estimation of the association being measured. (C)</p> Signup and view all the answers

    What does a confidence interval that crosses 1 indicate?

    <p>Failure to reject the null hypothesis. (A)</p> Signup and view all the answers

    Which method can help control confounding in studies?

    <p>Collecting data on potential confounders during study design. (B)</p> Signup and view all the answers

    Which of the following describes recall bias?

    <p>Participants' inability to remember past exposures accurately. (C)</p> Signup and view all the answers

    Flashcards

    Confounding

    An alternative explanation for an observed association between exposure and outcome, not related to the exposure itself.

    Residual Confounding

    Even after adjusting for known confounders, there's always a possibility of unknown confounders influencing the results. This is unavoidable

    Reverse Causality

    The outcome might be causing the exposure, not the other way around. Meaning: disease first, then exposure in retrospect.

    Randomized Controlled Trial

    A study where participants are randomly assigned to different exposure groups and followed to observe outcomes; gold standard for causality.

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    Cohort Study

    A study where a group of people (cohort) is followed over time to observe who develops a particular disease.

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    Case-Control Study

    A study that begins by identifying individuals with a disease (cases) and comparing them to individuals without the disease (controls).

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    Cross-Sectional Study

    A study conducted at a single point in time to assess the prevalence of a disease.

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    Ecological Study

    A study that compares disease frequencies in different groups or populations over time or at one point in time

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    Bradford Hill Criteria

    A set of considerations used to assess the likelihood of a causal relationship between exposure and disease(s).

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    Temporality

    Exposure must precede the outcome for a causal relationship to be considered.

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    Epidemiology in Mental Health Research

    The study of the distribution and determinants of mental illness in populations. It uses research methods to investigate the causes of mental health conditions.

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    Core Principles of Epidemiology Research

    Core concepts include identifying research questions and systematically collecting, analyzing data, and evaluating methodological concerns (validity threats).

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    Causal Inference in Epidemiology

    Determining if an observed relationship between an exposure (e.g., physical activity) and an outcome (e.g., depression) is truly causal, considering factors like chance, bias, confounding, and reverse causality.

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    Threats to Validity in Studies

    Factors that can affect the validity of a study, including chance, bias (selection/measurement), confounding, and reverse causality. They could lead to incorrect conclusions.

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    Association vs. Causation

    Just because two things are related (associated) doesn't mean one causes the other. Additional investigation is needed to determine if something is really the cause.

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    Sampling Uncertainty

    The inherent variability in results due to studying a sample instead of the entire population.

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    Statistical Inference

    Using sample data to draw conclusions about a larger population.

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    Type 1 Error

    When a study incorrectly concludes there's a significant effect, when in reality there isn't.

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    Type 2 Error

    When a study incorrectly concludes that there is no significant effect, when in reality there is.

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    Confidence Interval (CI)

    A range of values that likely contains the true value in the population,

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    Selection Bias

    A systematic error in the way people are selected to be in a study.

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    Measurement Bias

    A systematic error in the way information is collected about participants

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    Odds Ratio

    A measure of association used to quantitatively determine the likelyhood of an outcome

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    95% Confidence Intervals

    A range indicating where the true value is likely to lie, with 95% certainty.

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    Study Notes

    Core Principles of Mental Health Research

    • Epidemiology research examines the history of both epidemiology and psychiatry to understand disease frequency. It looks at key investigation methods like chance, bias and confounding and reverse causality.
    • Investigating causes: Physical activity is hypothesized to reduce depression risk. A cross-sectional survey is a study design used for this investigation. Outcomes and exposure are depression and physical activity. This research method looks at data gathered at one point in time. Data from labs, disease surveillance, case reports, and theoretical reasoning are used to investigate this relationship

    Epidemiological Reasoning

    • Study design includes identifying the research question, collecting data systematically, analyzing it systematically, and interpreting the results.
    • Assessing validity and making inferences from associations is key. Determining if a relationship is causal involves considering chance, bias (selection and measurement), and confounding. Reverse causality needs to be considered; for example, depression may cause less exercise, not the other way around.

    Making Inferences from Epidemiological Observations

    • Using statistical methods is necessary to gauge the impact of chance. Confidence intervals and p-values help in this process. Sample size is important, as well as a defined sampling strategy that adequately generates a statistically robust population inference.
    • Bias is systematic error introduced during the study design or conduct, which affects the validity of the study results. Selection bias arises during individual selection procedures for studies. Measurement bias refers to issues in measuring the exposure, outcome, or other information on participants. Confounding presents an alternate explanation for the relationship between an exposure and an outcome. Using methods like randomisation strategies, and adjusting for confounding variables are crucial to address this. Residual confounding may occur even after adjusting for known confounders.

    Models of Causation

    • The causality of a disease does not need to be sufficient or necessary. The example given is that smoking is not always the cause of disease, and smoking does not always cause disease.
    • Bradford Hill's considerations for causality include temporality (exposure before outcome), strength of the association, dose-response relationship, consistency in studies, specificity, coherence, plausibility, and experimental studies.
    • There are different types of epidemiological studies: descriptive; and analytical (case-control and cohort studies).
      • Descriptive epidemiology: observational research. Example studies include ecological studies (looking at populations).
      • Analytical epidemiology: observational and experimental (case-control, cohort and intervention studies).

    Strengths and Limitations

    • Different study designs have varying degrees of strength and limitations for determining causal inferences from epidemiological studies and experiments. The study designs discussed include cross-sectional and longitudinal study designs. The strength of a study design depends on sampling strategy, measurements used, the study design itself, and issues with confounders and adjustments for confounders. Randomised controlled trials are considered the strongest, and ecological studies as having weak causal inferences.

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    Introduction to Epidemiology 1 PDF

    Description

    This quiz explores the foundational concepts of mental health research, focusing on the role of epidemiology in understanding disease frequency. It covers various investigation methods, study designs, and the relationship between physical activity and depression, providing insights into validity and causal relationships.

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