5.3 Experimental and Quasi-Experimental Designs Flashcards

1
Q

Types of Quantitative Research Designs

A
  • Experimental
  • Quasi-experimental
  • Non-experimental
How well did you know this?
1
Not at all
2
3
4
5
Perfectly
2
Q

Experimental

A

Gold Standard - Randomized control trial (RCT) - Level 2 evidence.
Systematic review of RCT’s are level 1 evidence

CONCEPTS THAT MUST BE PRESENT IN EXPERIMENTAL DESIGN
- Randomization
- Control
- Manipulation (All experimental designs involve the manipulation of the independent variable (cause) and measurement of a dependent variable (effect).
- NOTE casual relationships are difficult to establish so researchers should avoid the word “prove” when discussing hypothesis testing

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
3
Q

Types of Experimental Designs

A
  • Classic Randomized Clinical Trials
  • Solomon four-group design
  • After-Only Experimental Design
How well did you know this?
1
Not at all
2
3
4
5
Perfectly
4
Q

Classic Randomized Clinical Trial

A

STEPS
- Sample is selected from the population
- Baseline is collected
- Subjects are randomized
- 2 Groups (intervention and control group)
- Post intervention data is collected from each group

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
5
Q

Solomon Four-Group Design

A

STEPS
- Sample is selected from the population
- Subjects are randomized into 4 groups that vary based on collected baseline data
- Control and intervention groups are created for both when baseline data is collected and baseline data is not collected
- After this postintervention data is collected

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
6
Q

After-Only Experimental Design

A

STEPS
- Subjects are randomized into an intervention and control group
- Post intervention data is collected

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
7
Q

Strengths/Weaknesses of an Experimental Design

A

Strengths
- Gold standard and best at testing cause-effect relationships.
- Control, manipulation, and randomization is one of the best ways to measure differences between 2 groups

Cons
- Complicated and costly
- Many variables related to patient care outcomes cannot be manipulated due to ethical concerns

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
8
Q

Quasi-Experimental Design

A
  • Difference between experimental and quasi-experimental is that quasi does not contain either a control group or random assignment
  • Weaker cause-effect relationship
  • Level 3 evidence
How well did you know this?
1
Not at all
2
3
4
5
Perfectly
9
Q

Types of Quasi-Experimental Designs

A
  • Nonequivalent Control Group
  • After-Only Nonequivalent control design
  • One-group (Pretest/Posttest)
  • Time series design
How well did you know this?
1
Not at all
2
3
4
5
Perfectly
10
Q

Nonequivalent Control Group Design

A

STEPS
- 2 groups are created, control and intervention group
- Baseline data is collected
- Intervention is applied to the experimental group
- Postintervention data is collected for the experimental group and data is collected again for the control group.

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
11
Q

After-Only Non-equivalent Control Group Design

A

STEPS
- 2 Groups created (control and intervention)
- Intervention is applied to experimental group
- Postintervention data collected for experimental group, data collected from control group

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
12
Q

One-Group (Pretest, Posttest) Design

A

STEPS
- Only experimental group is created
- Baseline data is collected
- Intervention is applied
- Postintervention data is collected

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
13
Q

Time-Series Design

A

STEPS
- Experimental design is collected
- Data is collected twice prior to intervention
- Intervention is applied
- Post-Intervention data is collected twice

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
14
Q

Strengths/Weaknesses of Quasi-experimental Design

A

Strengths
- Practical, feasible, cost-effective, potential generalizable findings, more adaptable to real-world settings

Weakness
- Inability to make clear cause-effect determinations. Did manipulation of independent variable actually affect the change in the dependent variable

How well did you know this?
1
Not at all
2
3
4
5
Perfectly