A Brief Introduction to Epidemiology - XI (Epidemiologic Research
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A Brief Introduction to
Epidemiology - XI
(Epidemiologic Research Designs:
Experimental/Interventional Studies)
Betty C. Jung, RN, MPH, CHES
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Learning Objectives
To understand:
– What experimental studies are
– The value of such studies
– The basic methodology
– Pros and Cons of such studies
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Introduction
The primary purpose of research is to
conduct a scientific, or, scholarly
investigation into a phenomenon, or
to answer a burning question.
Research is defined as a systematic
approach to problem solving.
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Epidemiological Study Designs
Observational Studies - examine
associations between risk factors and
outcomes (Analytical - determinants and
risk of disease, and descriptive - patterns
and frequency of disease)
Intervention Studies - explore the
association between interventions and
outcomes. (Experimental studies or
clinical trials)
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Epidemiological Study Designs
Observational
– Cross-Sectional
– Case-control
– Cohort
Interventional
– Natural Experiment (Community Trial)
– Field Trial
– Experiment/Randomized Trails (ex. Clinical Trial)
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Examples of Experimental
Epidemiologic Studies
Prophylactic vaccines tested on children
populations to prove the efficacy of the
vaccines in preventing the diseases (i.e., polio)
Prophylaxis with drugs in preventing disease
(i.e., penicillin to prevent rheumatic fever)
Impact on health-related behavior and
coronary heart disease in response to
community-wide heart disease prevention
intervention
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Value
Experiments are seen as the “Supreme Court” of
epidemiologic research as they provide the
strongest possible evidence of disease causation.
Experimental study designs can rule out with
greater certainty factors that may confound
potential cause and affect relationships.
A study’s degree of internal validity depends on
the study design’s ability to determine whether
an antecedent causes an effect (or outcome).
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Community Trials
Communities rather than individuals
comprise the treatment groups
Appropriate for diseases that have their
origins in social conditions that can be
influenced by intervention directed at
group behavior as well as individuals
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Limitations of Community Trials
Random allocation of communities is
not practical
Only a small number of communities
can be included
Other methods are needed to ensure any
difference found can be attributed to the
intervention rather than to any inherent
differences between the communities
studied
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Field Trials
Involve people who are disease-free
but presumed to be at risk
Data collection – “in the field” –
among non-institutionalized people
in the general population
Used to evaluate interventions that
reduce exposure without measuring
the occurrence of health effects.
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Limitations of Field Trials
Hugh undertaking
Major logistic considerations
Major financial considerations
Think of how much work is required
to randomize and allocate
participants to various treatment
groups!
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Experimental Study Design
Time Treated - Improved
Treated (T)
Treated – Not Improved
Sample of
Cases
Not Treated - Improved
Not Treated (NT)
(Control) Not Treated – Not Improved
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Randomized Trial Methodology
Random allocation - Each subject has an
equal chance of being assigned to any
group in the study, so that all groups in a
study are similar in all characteristics not
controlled by other methods, such as
subject selection.
Random allocation can be used with
matching to ensure the study groups are
comparable
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Randomized Trial Design
Time
Improved
R New
A
N
Treatment
Defined D
Not Improved
Population O
M
I Improved
Z
Current
E Treatment
D Not Improved
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Four Possibilities
The treatments do not differ and we
correctly conclude they do not differ
The treatments do not differ but we
conclude they do differ
The treatments differ but we conclude
they do not differ
The treatments do differ and we
correctly conclude that they do differ
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Pros
Helpful in assessing the value of new
therapies to combat acute diseases in
developing countries
Can evaluate a single variable in a precisely
defined patient group
Prospective design
Eliminates bias by comparing two otherwise
identical groups
Allows for meta-analysis
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Cons
Expensive and time consuming
Not always properly conducted – too few
subjects, too short a time period
Influence of sponsorship
Use of surrogate endpoints may
introduce “hidden bias”
Failure to randomize all eligible subjects
Failure to blind assessors to randomized
status of subjects
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References
For Internet Resources on the
topics covered in this lecture,
check out my Web site:
http://www.bettycjung.net/
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