This document provides an overview of different study designs including observational and experimental designs. It defines key observational designs like case reports, case series, ecological studies, cross-sectional studies, case-control studies and cohort studies. It notes their strengths and weaknesses. Experimental designs discussed include randomized controlled trials and their key elements like selection of subjects, allocation of exposure, blinding and analysis. Clinical trial phases and ethical principles in trials are also summarized.

1. STUDY DESIGNS
Joaniter Nankabirwa-Wandera
MMED /MSc

2. Learning Objectives
• Classify study designs
• Define the unique features of the study
designs
• Discuss weaknesses and strengths
associated with each study design
• Discuss the most appropriate study design
to answer certain research questions

3. Determining a study design
• Identify topic of
interest
• State question of
interest
• State objectives of
the study
• Choose the best
design to answer
question
Topic
Research
question
Objectives
(Hypothesis)

4. Types of Study Designs
Observational
• -- Case report
• -- Case series
• -- Ecological Studies
• -- Cross-sectional
• -- Case-control
• -- Cohort
Experimental
• -- Randomized clinical trial

6. Overview of study designs

7. Observational studies

8. Case Report /Case Series
Case
reports
Case
series
Selective by
nature, providing
little information
May help identify
potential health
problems
Uses of case series
and reports
1 patient: Case Report
More patients: Case Series

9. Ecological Studies
Describe disease
occurrence on
population level
Evaluate an association
using the population -not
the individual -as the unit
of analysis.
The rates of disease are
examined in relation to
factors described on the
population level
Example: Association between
cancer and fat intake?
National Cancer Rate
High Low
High Low
National Diet Fat-Intake

10. Ecological Studies Key issues
Ecological fallacy: We do not know if the individuals who
have cancer were also the individuals with the high fat intake
• Explores correlations between group level exposure
and outcomes
• Unit of analysis: usually not individual, but clusters
(e.g. countries, counties, schools)
• Useful for generating hypothesis
• Cannot adjust well for confounding due to lack of
comparability (due to lack of data on all potential
covariates)
• Missing data is another concern

11. Example

12. Types of ecological studies
• Multiple group study
Compares disease rates among many regions during the
same period
• Time-trend studies
Comparison of disease rates over time in one population
• Mixed designs
Multiple groups + multiple time periods

14. Examples of time series

15. Uses of ecological studies
• Are appropriate designs when generating
• May be used for testing a new hypothesis
BUT have limited value due to in-built
design errors
• Only design possible when adequate
measurement of individual-level variables
is not possible/not ethical Example:
Holding off immunization
• When funds or time is limited to do
individual level studies

16. Advantages of ecological studies
• Are low cost and convenience
• Simple to analyze and present
• Often helpful for generating new hypotheses for
further research
• Aggregated data on exposure and health outcomes
often publicly available in state and national
databases

17. Disadvantages of ecological studies
• Cannot adjust well for confounding due to lack of
data on all potential covariates
• Measures of exposure are only a proxy based on the
average in the population
• Lack of available data on confounding factors.
• Missing data is another concern
• Prone to Ecological fallacy: We do not know if
grouped results apply on the individual level

18. Ecological fallacy
• Also called ecological inference fallacy or population
fallacy
• is an error where conclusions are inappropriately
inferred about individuals from the results of aggregate
data
• Example: If countries with more Protestants tend to
have higher suicide rates, then Protestants must be
more likely to commit suicide
• How can it be avoided: If individual data is not
available difficult to control for except through
modelling

19. Why ecological studies
• Low cost and convenience
• Some measurements cannot be made on individuals
• Ecologic effects are the main interest (at the
population level)
• Simplicity of analyses and presentation
• Often helpful for generating new hypotheses for
further research

20. Cross-sectional studies
• Exposure and disease are determined
simultaneously for each person  a snapshot of
the population at one point in time
• No follow up in this design
• This can only indicate association, but cannot give
a time-sequence.
• Good for prevalence studies and testing
association

23. Strengths
• Fast
• Inexpensive
• May answer question of interest
• Used to determine both prevalence of outcomes and
exposures
• May be used to design future studies
• Start of cohort study
• May even be used for repeat cross-sectional analyses

24. Weaknesses
• Only prevalence cases, can’t measure incidence
• Cannot determine whether exposure preceded
outcome (Outcome may precede exposure)
• Unable to establish causal relations – need for
longitudinal study designs

25. Case-Control study
Start: Cases and Control
Population
Cases
(with
disease)
Controls
(Without
disease)
Exposed
Non-
Exposed
Non-
Exposed
Exposed
Direction of inquiry
Present
Past

26. Case-Control study
• Compares cases to
controls in order find
out what factors are
associated and could
possibly have
contributed to the
problem
• Cases: Diseased
• Controls: Not diseased
• Association measure =
OR

27. Features of case control studies
• Less expensive than cohort studies and
experiments
• Small number of participants needed
• Bes t design for diseases with long latent period
• Very efficient for rare diseases
• Multiple etiologic factors can be studied at one time
• Cannot yield estimates of incidence or prevalence
• Riskier due to biases (especially recall bias)

28. Cohort studies
• A cohort is a group of subjects that are followed
over time starting at a specified point in time and
usually have something in common at the start
• Cohort study is where participants are selected
with respect to exposure
• Individuals exposed to a risk factor (study group)
are compared those not exposed (the control
group).
• Starts with measuring exposure, looks forward to
the outcome

29. Cohort cont….
Purpose
• To study incidence of
disease or other
conditions
• To study associations
between exposures
and outcomes (risk
factors,
determinants)
Measure association
= OR /RR

30. Nested Case-Control Study
Special case-control study and is within an ongoing
cohort study
advantage:
no recall bias, temporal relation between exposure and disease
possible, on selected group of persons more expensive test can be
performed

31. WHY OBSERVATIONAL STUDIES
• Usually the only option if the predictor is a
potentially harmful exposure or risk factor
• Even if the predictor is an intervention, an RCT may
not be feasible due to duration between exposure
and outcome
• Financial reasons: intervention studies can be
significantly more expensive than observational studie
• More intellectually interesting than RCTs?

32. .

33. END
OBSERVATIONAL STUDIES

34. Experimental
Designs

35. Clinical Trial: Definition
A clinical trial is a prospective study comparing the
effect of intervention(s) against a control
A research activity that involves the administration of
a test regimen
Note: A proper clinical trial
 Always prospective
 Must have 1 or more interventions
 Must have a control group

37. Clinical Trial Objectives
• To asses the efficacy of a new intervention or drug
• To asses the effectiveness of a new intervention or
drug
• To asses the safety of a new intervention or drug

38. History of Clinical Trials
• Daniel 1:12-16. A diet experiment (Royal food and wine versus
vegetables and water) for 10 days
• 17th century: Lancaster (captain of a ship)
– experiment to examine the effect of lemon juice on scurvy for sailors.
– Ships with lemons were free of scurvy compared to ships without
lemons having scurvy.
• Lind (1753) – Study of 5 tx for scurvy in 10 pts (2/tx) plus 2 pts
without tx (control).
– First two pts given orange and lemons recovered quickly and was fit for
duty after 6 days, compared favorably with all other patients
• Smallpox experiment (1721) at the Newgate prison in Great
Britain. Voluntary inmates were inoculated and were free from
smallpox.

39. Key Elements of a Clinical Trial
• Selection of subjects
• Allocation of exposure
• Blinding
• Data collection
• Statistical issues
• Ethical considerations

40. Selection of Subjects
Population at risk/Target population
 ENTIRE group of individuals to generalize results
 The intervention is intended to benefit this population
Accessible population
 Population to which the researcher has reasonable access
 May be a subset of the target
Study population
 Group of participants actually studied
 Subset of population meeting eligibility criteria
 Inclusion criteria – identifies the target population
 Exclusion criteria – excludes people from the study, mainly for
safety reasons

41. Allocation of exposure
• Studies without controls –
 not a clinical trial although still an experiment
• Studies with controls: Types of controls/Comparison groups
 Historical controls (compare with the past)
 Simultaneous non-randomized controls (concurrent
group/quasi experiment)
 Randomization - true controls
• Importance of controls
 For comparisons
 Allow to determine if outcome is caused by intervention vs
other factors

42. Randomized controlled Trials (RCT)
• Exposure assigned in a random way, participant have
equal chance of being in either control or intervention
group
• Balances the known and unknown risk factors for the
outcome under study
– eliminates confounding due to measured and unmeasured
factors
• Methods for randomization
 Simple randomization (fish bowel method, tossing a coin)
 Random number table
 Computer-generated list of assignments

43. Blinding/ Masking
• The team assessing the outcome are not aware of
treatment assignment
• To prevent the biased assessment of the outcome
Single-blinded study
• Either pts or physicians are blinded to the tx
allocation
Double-blinded study
• Both pts and physicians are blinded to the tx
allocation

44. Analysis of trials
• Should always start with a baseline comparison of
groups
Note: Investigator cannot dictate what a participant does
in a clinical trial, may or may not comply with Rx
Intent-to-treat (ITT)
– Participants are analyzed according to the groups they were
randomized
– If 100 randomized to a treatment, all analysed whether took
it or not
Per-protocol analysis
• Analysis is only for participants who completed the treatment
Both analyses are recommended and compare
conclusions

45. Phases of Clinical Trials
• Phase I: clinical pharmacology and toxicity
– 1st experiment in human for new drug
– Primary concern: Safety
– Typically required 15-30 patients
• Phase II: Initial Assessment of Efficacy
– examine the efficacy and refine the safety
– Goal is to screen out ineffective drugs
– Has 30-100 participants
• Phase III: Full-scale Evaluation of Treatment Efficacy
– Compare new treatment with standard treatment
– Aim is to define the ‘best’ treatment
– Hundreds to thousands of participants
• Phase IV: Postmarking Surveillance
– monitoring the adverse effects

46. Ethical Principles in Trials
• Respect for Persons
– Voluntary, informed consent
– Protection of vulnerable populations
– Right to end participation in research at any time
– Right to safeguard integrity
– Protection of privacy and well-being
• Beneficence
– Non-malfeasance
– Benefits should outweigh cost/risks
• Justice
– Protection from physical, mental and emotional harm
– Fairness
ALL TRIALS MUST BE REGISTERED IN A CLINICAL TRIAL REGISTRY

47. Cross-over Design
Population
Sample
Intervention
Randomization
Placebo
Washout
Washout
Placebo
Intervention
Outcome Outcome

48. Factorial Design
Population
Sample
Int A and Int B
Int A and Pbo B
Pbo A and Int B
Pbo A and Pbo B
Outcome
Outcome
Outcome
Outcome

49. Experimental vs. Observational
Observational
• Predictor = exposure or
risk factor
• Usually biased
• Confounding usually an
issue
Experimental
• Predictor = intervention
(treatment or therapy)
•Minimize bias
•Confounding eliminated