1. Study Designs Observational Experimental Analytical Descriptive Animal
Case report
Case control
Case series
Human
Intervention
Clinical trial
Cohort
Cross section
Ecological

2. Observational Studies
non-experimental
observational because there is no individual intervention
treatment and exposures occur in a “non-controlled” environment
individuals can be observed prospectively, retrospectively, or currently

3. Case Reports Careful and detailed report by one
or more clinicians of the profile of
a single patient
e.g. previous un-described disease
e.g. unexpected link between diseases
e.g. unexpected new therapeutic effect
e.g. adverse events

4. Case Reports
• exposures (i.e. a case report gave the clue OC use increases the risk of venous thromboembolism.
• “Luck” in being the first to encounter an
interesting case.
• Rigor in diagnosis, testing and
documentation of clinical findings

5. Strengths
over one million case reports indexed on Medline.
uses language that is familiar to clinicians and easy to interpret.
useful reminder about conditions, diagnoses etc. that are rarely seen in most practices.
for researchers, case reports generate hypotheses that can be tested using other study designs.

6. Case Reports Limitations: • No appropriate comparison group.
• Cannot be used to test for presence of a valid statistical association.
• Since based on the experience of one person:
--- presence of any risk factor
may be purely coincidental
--- not a true epidemiologic
design

7. • Tendency to publish "gee whiz" reports
of strange conditions that have little
relevance to daily practice.
• Some authors erroneously try to imply
causation, therapeutic benefits, etc.

8. Case report from Medline
Authors: Smart ER. Macleod RI. Lawrence CM.
Title: Allergic reactions to rubber gloves in dental patients: report of three cases.
Source: British Dental Journal. 172(12):445-7, 1992 Jun 20.
Abstract:
Three cases of allergy to rubber are described, in which the patients
exhibited peri-oral rashes following dental treatment by personnel
wearing latex rubber gloves. Two of the patients were aware of possible allergy to domestic rubber products but did not reveal this as part of their medical history. With the increase in numbers of dentists wearing rubber gloves it is probable that there will be many more such cases reported in the future. Rubber products must then be added to the list of potential allergens which may be of some import to the practice of dentistry.

9. Case Series
Experience of a group of patients with a similar diagnosis.
Cases may be identified from a single or multiple sources.
Generally report on new/unique condition.
May be only realistic design for rare disorders

10. Case Series Advantages Cannot study cause and effect relationships.
Cannot assess disease frequency.

11. Case Series Strengths: • Useful for hypothesis generation.
Used as an early means to identify the beginning or presence of an epidemic.
• Can suggest the emergence of a new disease (i.e. AIDS).
Informative for very rare disease with
few established risk factors.
Case Series

12. Case Series Limitations: • Lack of an appropriate comparison group
• Cannot be used to test for presence of a valid statistical association
• Not a true epidemiologic design.

13. Cross-sectional studies
An “observational” design that surveys exposures and disease status at a single point in time (a cross-section of the population)
time
Study only exists at this point in time

14. Cross-sectional Design
factor present
No Disease
factor absent
Study
population
factor present
Disease
factor absent
Prevalence
time
Study only exists at this point in time

15. Cross-sectional Studies
Often used to study conditions that are relatively frequent with long duration of expression (nonfatal, chronic conditions).
It measures prevalence, not incidence of disease.
Not suitable for studying rare or highly fatal diseases or a disease with short duration of expression.

16. Cross-Sectional Studies
Strengths:
• Provides prevalence estimates of exposure and disease for a well-defined population.
• Easier to perform than studies that require follow-up (hence relatively inexpensive).
• Can evaluate multiple risk (and protective) factors and health outcomes at the same point in time.

17. Strengths:
• May identify groups of persons at high or low risk of disease
• Can be used to generate hypotheses about associations between predictive factors and disease outcomes

18. Cross-Sectional Studies
Limitations:
• Prevalent rather than incident (new) cases are used – the exposure could be associated with survival after disease occurrence, rather than development of the disease
• Temporal sequence between exposure and disease cannot be established
* i.e. Which came first, chicken or the egg?

19. Cross-sectional studies
Usually don’t know when disease occurred.
Rare events a problem. Quickly emerging diseases a problem

20. Health Survey
Survey (n): Information gathered by asking a group of individuals the same questions related to their characteristics, attributes.
Survey (v): The process of collecting such information

21. Knowing what to expect
A good survey has the potential to reach a large number of respondents;
Generate standardized, quantifiable, empirical data - as well as some qualitative data; and offers confidentiality / anonymity
Credible data, however, can be difficult to generate

22. Surveys can be:
Descriptive:
These surveys pretty much do what they say - they describe. The goal is to get a snapshot - of your ‘respondents’
Explanatory:
These surveys go beyond description and attempt to establish why things might be the way they are

23. Surveys can also involve populations or samples of populations:
Census: This is a survey that does not rely on a sample. A census surveys every single person in a defined or target population
Cross-sectional surveys: This type of survey uses a sample or cross-section of respondents selected to represent a target population

24. Surveys administration:
Face to face
Telephone
Self-administered.
Electronic e.g. E mail

25. Conducting a survey capable of generating credible data requires:
thorough planning
meticulous instrument construction
comprehensive piloting
reflexive redevelopment
deliberate execution
and appropriate analysis

26. Survey questions can either be open or closed:
Open questions: Open questions can generate rich and candid data, but it can be data that is difficult to code and analyze.
Closed questions: These questions force respondents to choose from a range of predetermined responses, and are generally easy to code and statistically analyze.

27. Considerations in Survey Construction
Providing clear background information and lucid instructions.
Logical organization.
Comprehensive coverage without undue length.
User friendly and aesthetically pleasing layout and design.

28. Ecologic Studies
• Measures that represent characteristics of entire populations are used to describe disease and to postulate causal associations.
• Measure of interest is correlation between exposure rates and disease rates among different groups.
• Correlation coefficient (denoted as r)
Range of r is from –1.0 to 1.0
R evaluated in relation to difference
from 0.

29. Ecologic Studies Strengths:
• Cheap, quick, and simple (generally make use of secondary data)
Limitations:
• Cannot link exposure-disease relationship at the individual level
• Uses average exposure levels rather than actual levels of exposure
• Inability to control for confounding factors

30. EXAMPLE: Country A: Country B
Prevalence-Hypertension % %
Average Salt Consumption Moderate Low
Country A Country B
Person Salt Intake Hyp. Salt Intake Hyp.
Yes 1 Yes
Yes 1 Yes
Yes 1 No
No 1 No
No 1 No
No 2 No
No 2 No
No 2 No
No 2 No
No 2 No
Avg % %

31. Ecologic Studies The “Ecologic Fallacy”:
• Erroneous conclusions based on grouped data
• Patterns observed on the aggregate level are not observed on the individual level