Lecture 6 Flashcards by Hannah Fern

Epidemiologic
(population health &
clinical)
Studies can be split into two groups

Observational and
experimental

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Observational Studies can be split into two groups

Descriptive
Analytic

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Descriptive Studies

Case Reports
Case Series
Ecological
Cross-Sectional

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Analytic Studies

-Ecological
-Cross-sectional
-Case-Control
Cohort

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Experimental Studies can be split into two groups

Randomized controlled trial
Community trial

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Descriptive health research

No hypothesis
Not looking to prove or disprove anything
1. To monitor the public’s health
2. To evaluate the success of
intervention programs
3. To generate hypotheses about causes of disease

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Analytic

Evaluate hypothesis about the causes of disease
To evaluate the success of
intervention programs

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Components of a Study

Population
Exposure
Outcome
Potential Confounders
Analysis
Communication of Findings

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Differences between Selection bias and Generalizability/external validity (ON EXAM)

Selection bias is a flaw in the sampling process that can affect the validity of study results even within the sample itself.
Generalizability is about how well the results of the study can be applied beyond the study sample.

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Exposure

Determinant of interest upon which an outcome depends;
can be constitutional, environmental, or behavioral
➢ Genetic polymorphism, female sex, short stature
➢ Fluoridated water, air pollution, passive cigarette smoke
➢ Cigarette smoker, fitness enthusiast, high fiber diet

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The goal of knowing exposures

to minimize errors

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Potential Confounders

Extraneous risk factor for an outcome;
can be constitutional, environmental, or behavioral

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Analysis

examination of your study data;
estimation of measures of disease frequency and association

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Communication of Findings

Tell the appropriate persons or community
what you found even if you found no association
examples
➢Peer-reviewed journals
➢Conferences and meetings
➢Government reports
➢What about popular and social media?

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Hierarchy of evidence from least to highest

In vitro (test tube research)
Animal research
Ideas, editorial, opinions
Case reports
Case series
Case control studies
Cohort studies
Randomized controlled double blind studies
Systemic Reviews and meta analysis

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What kind of evidence is good for formulating research questions, theory generating

Ideas, editorial, opinions
Case reports
Case series

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What kind of evidence is used in most health research

Case control studies
Cohort studies
Randomized controlled double blind studies
Systemic Reviews and meta analysis

Evidence that is a good starting point more in the domain of biology

In vitro (test tube research)
Animal research

There is no good or bad TYPE of design but

poorly vs. properly conducted studies

Case report:

a report of a health issues in one patient, A disease, a disorder, or undergoing a procedure

Case series:

a report that describes a group of individuals who have the same health issue

The history of AIDS

Was identified in SanFran
(Was everywhere in the world)
Very rare type of skin cancer caused by immune deficiency
Was originally thought to be related to homosexuality due to discrimination

Case Report and Case Series

No theory, no research question, goal is not researching, only reporting
Often done by clinicians. They do not want to prove a theory only wish to report.
➢ May generate ideas for research questions

The main scientific part of Case report and case series:

defining the case

Sign vs Symptom

Sign: an objective indication of disease that can be clinically observed, such as a rash, cough, fever, or elevated blood pressure Symptom: a subjective indication of illness that is experienced by an individual but cannot be directly observed by others

Several coding systems

➢ International Classification of Diseases (ICD) ➢ Diagnostic and Statistical Manual of Mental Disorders (DSM)

Case Report and Case Series

➢ Mostly in medical settings but data collection usually with standard questionnaires ➢ Ethical issues should be respected ➢ Privacy ➢ Sometimes a group will be labeled unjustly because of the original case series ➢ Few or no data analysis is required ➢ Clinical discussion dominates the report

Types of Analytic Studies

Experimental Observational

Experimental

Investigator actively manipulates which groups receive agent under study -Clinical Trial -Community Trial

Observational

Investigator observes as nature takes its course -Cross-sectional -Cohort Study -Case-Control Study

Differences btwn Observational and experimental

Data: Collect vs Create Exposure assessment: Inquiry vs Random Assignment Outcome assessment Inquiry vs Inquiry Analysis of the association Depends, .... vs Complex but more straightforward

In cohort studies you call this formula (a / (a+b)) / (c / (c+d))

relative risk

In cross sectional study you call the same formula, as the relative risk formula in cohort studies a: (refer to slides if you are confused)

prevalence ratio

In prevalence ratio formula(a / (a+b)) / (c / (c+d))

high is over the low

Limitations of Cross-sectional Studies

Because a cross-sectional study has no time dimension, it cannot be used to assess causality

In cross sectional study An exposure can be said to be “associated” or “related” to a disease,

but a cross-sectional study cannot show that an exposure caused a disease

Repeated cross-sectional study:

a series of cross-sectional studies that re-sample and re-survey representatives from the same source population at two or more different time points > does not track the same New set of participants is sampled from the source population for each round of data collection

Correlational Studies

In these studies, the unit of analysis is the group, not the individual. The group, or ecological unit, represents an aggregate of individuals

Terminology: ➢ Correlational studies ➢ Ecological studies ➢ Aggregate studies

The same

Ecological Fallacy

The incorrect assumption that individuals follow the trends observed in population-level data, not a methodological error or bias > The experience of individuals in a population may vary significantly from the population average