Overview

1. Introduction
2. ‘Standard’ designs
3. Experimental Study Designs
4. Descriptive Study Designs
5. Other designs
6. Conclusions

1. Introduction

• Descriptive vs experimental
• Most important thing is to use the best design for the specific question being asked

1. Introduction

• Descriptive studies:
  • Involve observing and assessing
  • Can be used for things where it isn’t ethical to randomise
• Experimental studies:
  • Involve the researchers changing something
  • Tend to be more difficult and expensive

2. 'Standard' Designs

• Three standard designs we should all know:
  • Randomised controlled trials
  • Cross-sectional surveys
  • Longitudinal surveys
• These tend to form the standard by which other study designs are considered
  • eg how is a particular design better or worse than an RCT

2. 'Standard' Designs

Randomised Controlled Trials

• Randomise to group; give each group a different intervention; follow-up and compare the groups
• Gold standard for causation
  • Ignorability
• Efficacy vs Effectiveness
• Not always appropriate

2. 'Standard' Designs

Randomised Controlled Trials

2. 'Standard' Designs

Cross-sectional survey

• Tends to be exploratory
  • Hard to design an RCT when you don’t know what the intervention should be
• Can be cheap and easy to design, run, analyse and report
• Difficult to recruit representative samples

2. 'Standard' Designs

Prospective Cohort

• In some ways, just an extension of cross-sectional
  • But there are a range of specific issues that arise in longitudinal research that do not apply in cross-sectional research
  • There are also specific benefits
• Can be either descriptive or analytic
• With limitations, can be used for causal inference

2. 'Standard' Designs

Descriptive Prospective Cohort

2. 'Standard' Designs

Analytic Prospective Cohort

3. Experimental Designs

• There are lots of other experimental designs:
  • Pre/post experimental trials
  • Cluster RCTs
  • Stepped-wedge
  • Cross-over Trials

3. Experimental Designs

Pre/post Designs

• Measure participants, then administer intervention and measure again
• Participants form their own control
• Within subjects designs reduces variance, so requires smaller sample sizes
• Don’t know what would have happened without the experiment

3. Experimental Designs

Pre/post Designs

3. Experimental Designs

Cluster RCTs (1)

• Instead of randomisation at the individual level, randomises at the cluster eg hospital, school
• Good for systemic interventions eg new hospital process
• Also good for interventions where there is risk of cross-contamination eg participants talking to each other while in hospital

3. Experimental Designs

Cluster RCTs

3. Experimental Designs

Stepped Wedge (2)

• Instead of randomising clusters to intervention or control, randomises the order that intervention begins
• Eventually rolls out to all clusters
• Pragmatic design – not great for efficacy trials

3. Experimental Designs

Stepped Wedge

3. Experimental Designs

Cross-over Trials (3)

• Randomise to order; give participants intervention; wait for effect to fade; give participants intervention they didn’t receive in the first round
• Very good for experiments with multiple, short-acting interventions
• Similar benefit to pre/post – ppnts form their own control
• Allows for testing of multiple interventions

3. Experimental Designs

Cross-over Trials

4. Non-experimental Designs

• These include:
  • Qualitative studies
  • Case studies
  • Case-control studies
  • Ecological studies

4. Non-experimental Designs

Qualitative Studies

• Very in-depth
• Great for explaining WHY something happens
• Don't generalise (and aren't intended to)

4. Non-experimental Designs

Case Studies (4)

• In-depth
• Illustrative, rather than representative

4. Non-experimental Designs

Case-control Studies (5)

• Find ‘cases’ (ie people where the outcome has occurred), then see how they differ from others in whom the outcome did not occur
• Good for rare outcomes that might not be expected to occur in a prospective study
• Can be unreliable – relies on data that has already been collected

4. Non-experimental Designs

Case-control Studies

4. Non-experimental Designs

Ecological Studies (6)

• Defined by the 'level' of measurement
  • Namely, measurement is at a macro rather than individual level
• Can be used to measure very rare diseases etc
• Can lead to the 'ecological fallacy'
  • Where the nature of the group is falsely used to describe the nature of individuals in the group

5. Other Designs

Interrupted Time Series (7)

• Measures the change in a trend that is ‘interrupted’
• Technically involves an intervention – but often out of the researchers hands
• Sometimes the only way to assess whether high-level interventions have any effect.
• Can be problematic because effects often aren't instant

5. Other Designs

Interrupted Time Series

5. Other Designs

Linkage Studies (8)

• Can be either descriptive or experimental
• Can involve linking administrative data to an existing study such as a cohort study, or linking different administrative datasets to each other
• Can be very complex, and involve extremely large datasets

6. Conclusions

• There are lots of study designs that can be used
• Most important thing is to use the best design for the specific question being asked

7. References

7. References