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51 Cards in this Set

  • Front
  • Back
Basic Ethical Principles
Beneficence
Respect for Persons
Justice
Basic Ethical Principle:
-do not harm
Beneficence
Basic Ethical Principle:
-a person is autonomous and has the right to make his own decisions
Respect for Persons
Basic Ethical Principle:
-the risks and benefits of research are equally distributed, and no one population should be burdened while another receives the benefits
Justice
Person:
-external and internal environment explains diseases
-defines “epidemic vs endemic”
Hippocrates
Person:
-external and internal environment explains diseases
-defines “epidemic vs endemic”
Farr
Person:
-published “The Nature and Political Observations Made Upon the Bills of Mortality”
-founder of medical stats, births, deaths, by season, year and parish
Graunt
Person:
-first planned clinical trial
-treated sailors with scurvy
Lind
Person:
-first to propose and test a hypothesis: cholera is transmitted by a contaminated water supply
-father of modern epidemiology
Snow
Type of Epidemiology:
-hypothesis generating
-person, place, time
Descriptive Epidemiology
Type of Epidemiology:
-hypothesis testing
1.Cohort
2. Case-Control
3. Intervention Studies
Analytic Epidemiology
-grouped based on exposure status
Cohort Studies
-grouped based on disease status
Case-Control
-case-control within cohort study
Nested Case-Control
-cases serves as own controls
Case-Crossover
Advantages:
-rare diseases
-relatively fast
-relatively inexpensive
Disadvantages:
-cannot establish temporality
-subject to recall, observer and selection biases
-selection of controls difficult
-bad for rare exposures
Case-Control Studies
Advantages:
-can establish temporality
-direct calculation of incidence rates
-no recall bias
Disadvantages:
-subject to attrition bias, exposure, and outcome misclassification
-relatively expensive (large sample size)
-relatively time consuming (follow-up)
Cohort Studies
Disease Pattern
-i.e. food outbreak
Short-term fluctuations
Disease Pattern
-long term changes in morbidity and mortality patterns
Secular Trends
Disease Pattern
-periodic, often predictable, changes in frequency of morbidity/mortality
Cyclic Patterns
Disease Pattern
-a rise in disease that is clearly in excess of what is normally expected
Epidemic
Disease Pattern
-constant presence or usual frequency of a disease
Endemic
Using group-level associations to make conclusions about individual-level associations
(for example, association found when national salt consumption and national heart disease levels are compared across countries cannot be used to say eating more salt leads to heart disease)
Ecological Fallacy (Aggregation Bias)
(# death from a specific disease/ # cases over same time period) x 10^n
Case Fatality Rate
(# of new cases with C - # deaths from x/ # cases with the same disease) x 10^n
Survival Rate
(# existing cases at a point in time/# at risk at that point in time)
Point Prevalence – “Snapshot”
(# existing cases at beginning + new cases over time period/ # in population (or in study))
Period Prevalence
New cases in a population over a time period
Incidence
Risk of developing a disease:
(# new cases/ # at risk)
-exclude prevalent cases
Cumulative Incidence
Frequency of disease development
(# new cases/ total person-years at risk)
Incidence Rate/ Incidence Density (ID)
(CI in exposed/ CI in unexposed)
Risk Ratio
(ID in exposed/ ID in unexposed)
Rate Ratio
(Odds of disease among exposed/ Odds of disease among unexposed)
Odds Ratio
(Prevalence Rate among exposed/ Prevalence Rate among unexposed)
Prevalence Rate Ratio
Compares the observed amount of D among exposed cohort to what would be exposed in an unexposed cohort- indirect adjustment; estimates increased risk of one group over another
(observed deaths/expected deaths) x 100
Standardized Mortality Ratio
Proportion of deaths from a specific cause relative to all deaths in the exposed cohort is compared with the proportion of deaths from a specific cause relative to all deaths in the unexposed cohort
(prop. (%) deaths from X (cohort)/ prop. Deaths from X (comparions)
Proportional Mortality Ratio
Evaluating Validity:
-not due to chance alone
Precision
Evaluating Validity:
-study results are true, real unbiased, lack systematic error
Internal Validity
Evaluating Validity:
-study results are generalizable to your target population
External Validity
Two methods to evaluate chance
Hypothesis Testing
Confidence Interval
-P-value
-probability that your study result is different from null solely due to chance
-what is the chance that there is truly no association in the population but by some luck of the sample draw, you managed to see the study result you did
-Cannot tell the magnitude of the association
Hypothesis Testing
-relative magnitude of the association
-general precision: wider, less precise
-tells you whether the result is statistically significantly different from null/no association
Confidence Interval
If the CI does NOT include the measure of no association, then it is __________
Significant
If the CI does include the measure of no association, then it is __________
Not Significant
Probability of finding an association if one exist
Power
Bias:
-systematic error that results from the way subjects are selected, recruited or retained in a study
Selection Bias
Bias:
-systematic error that arises from inaccurate measurements or misclassification of subjects with regard to exposure or outcome status
Measurement
-systematic error that occurs because of differential recall about pass exposure status between those who have disease and those who do not
-occurs in case-control and cross-sectional studies
Recall Bias
-related to BOTH exposure and disease, and it is NOT on the exposure-disease casual pathway
Confounder
Eliminate Confounding in Design Phase
Randomization
Restriction
Matching
Eliminate Confounding in Analysis Phase
Stratification
Multivariate Analysis
Direct/Indirect Standardization or Adjustment