1. Understanding Quantitative Research Design
GERO 586
Understanding Quantitative Research Design
Donna B. Konradi, DNS, RN, CNE

2. Types of Quantitative Research Designs
Experimental research
Quasi-experimental research
Nonexperimental research
Donna B. Konradi, DNS, RN, CNE

3. Properties of Experimental Designs
Experimental designs include the following three properties
Manipulation
Control
Randomization
Donna B. Konradi, DNS, RN, CNE

4. Donna B. Konradi, DNS, RN, CNE
Experimental Designs
After-only design
Random assignment of subjects into control and experimental groups
Data collection for both groups at a point in time following the intervention
Pretest-posttest design
Data collection for both groups prior to and following the intervention
Donna B. Konradi, DNS, RN, CNE

5. Donna B. Konradi, DNS, RN, CNE
Experimental Designs
Factorial design
Used for testing multiple hypotheses in a single experiment
Random assignment of subjects into treatment groups
Evaluates for both the main effect and interaction effects
The factorial design example in the text would be strengthened by the use of a control group
Donna B. Konradi, DNS, RN, CNE

6. Donna B. Konradi, DNS, RN, CNE
Experimental Designs
Repeated measures design
Study sample participants are exposed to more than one experimental treatment
Participants are randomly assigned to different groups and the ordering of the treatment varies by group
Subjects serve as their own control
Inappropriate for certain research questions due to a “carry over” effect
Subjects responses to the second treatment may be influenced by the first treatment received. The example in your book is that this design is not typically used for drug studies because the pharmacological nature of drug A interact with drug B.
Donna B. Konradi, DNS, RN, CNE

7. Donna B. Konradi, DNS, RN, CNE
Experimental Designs
Advantages
High level of confidence that the independent variable exerted an effect on the dependent variable (causality…or presumed effect)
Criteria for causality
The cause must precede the effect in time
There must be an empirical relationship between the presumed cause and the presumed effect
The relationship cannot be explained by a third variable
Donna B. Konradi, DNS, RN, CNE

8. Donna B. Konradi, DNS, RN, CNE
Experimental Designs
Disadvantages
Some variables are not amenable to experimental manipulation (age, gender, race, perceptions, aspects of health)
Ethical considerations prohibit the manipulation of some variables
In some situation, impractical
Hawthorne effect
Donna B. Konradi, DNS, RN, CNE

9. Quasi-experimental Designs
Non-equivalent control-group design
Time Series Designs
Donna B. Konradi, DNS, RN, CNE

10. Non-equivalent Control-group Design
Experimental treatment and two or more groups of subjects
Similar to the “pretest-post text” experimental design however subjects are not randomly assigned into groups
Introduces controls to compensate for the lack of randomization and/or the control group component
It can not be assumed that the groups were equal at the start of the experiment
“Comparison group” terminology is used
Donna B. Konradi, DNS, RN, CNE

11. Donna B. Konradi, DNS, RN, CNE
Time Series Designs
Data is collected over a period of time and the experimental treatment is introduced over the course of the data collection
The extended time of data collection strengthens the ability to attribute the change to the experimental manipulation
Includes neither a control group or randomization
Donna B. Konradi, DNS, RN, CNE

12. Quasi-experimental Designs
Advantages
Practical, feasible and somewhat generalizable
Introduce some “control” when it is not possible to use experimental research
Disadvantages
The observed effect can be attributed to other causes (rival hypotheses)
Donna B. Konradi, DNS, RN, CNE

13. Nonexperimental Research
Ex post facto research
Descriptive research
Donna B. Konradi, DNS, RN, CNE

14. Donna B. Konradi, DNS, RN, CNE
Ex Post Facto Research
Also known as correlation research
Attempts to assume cause and effect relationships may be unwarranted because correlation does not prove causation
Retrospective studies
Prospective studies
Donna B. Konradi, DNS, RN, CNE

15. Donna B. Konradi, DNS, RN, CNE
Retrospective Study
A phenomena in the present is linked to other phenomena occurring in the past
Many epidemiological studies use a retrospective study design
Case control design
The researcher matches cases with regard to important background factors
Persons who smoke are matched with non-smokers for factors such as economic status, education, work environment, and education. Both groups are assessed for incidence of lung cancer
An example of an epidemiological study would be to evaluate the effect of a nuclear accident 5 years ago on the incidence of cancer…the effects of Hiroshma on cancer development…the effects of water contamination on incidence of disease…
Donna B. Konradi, DNS, RN, CNE

16. Donna B. Konradi, DNS, RN, CNE
Prospective Study
Begin with a presumed cause and move forward in time to the presumed effect
More costly than retrospective studies but the design is stronger
Greater link between the presumed cause and the presumed effect
Identify a known cause and study a sample of those persons affected over time…costly and difficult due to attrition and ongoing data collection. Persons move, difficult to locate etc.
Donna B. Konradi, DNS, RN, CNE

17. Donna B. Konradi, DNS, RN, CNE
Descriptive Research
Purpose
Observe
Describe
Document
Explanation and prediction are not included as purposes of descriptive research
Donna B. Konradi, DNS, RN, CNE

18. The Time Dimension of Data Collection
Four situations for using multiple points of data collection
Phenomena that evolve over time
The time sequencing of phenomena
Comparative purposes
Enhancement of research control
Cross sectional designs
Longitudinal designs
Phenomena over time may include healing, learning, growth, skill development, tumor size, blood pressure escalation
Time sequenced phenomena: The relationship between cancer diagnosis and depression; the relationship between an spirituality and feelings of hopefulness;
Trends in teen pregnancy rates in a community; the effect of an in school educational program on trends in teen pregnancy rates
The collection of pre-intervention data allows the researcher to identify and control for any differences between groups. For example, if Dr. Ingalsbe and I wanted to use different teaching strategies on our research classes and then assess at the completion of the class which teaching intervention worked best by looking at the grades on the final exam, it would be necessary to have equivalent classes…otherwise, the end result could be attributed to other aspects of the group. Perhaps, this class has a higher GPA….what effect would the GPA have on performance? How might we control for differences?
Donna B. Konradi, DNS, RN, CNE

19. Cross Sectional Designs
One point of data collection
Infer that the group is representative of others at that point in time (dialysis and QOL)
Advantages
Practical, economical and easy to manage
Disadvantages
Problematic to assume that the differences are related to the passage of time vs inherent differences in the groups (value differences, norms, etc)
Collect data regarding perceptions of QOL in dialysis patients. Collect data from persons following their first week of dialysis; collect data from another group of patients who have been in dialysis for three months and collect data from a third group of patients who have been in dialysis for one year. It is assumed that the persons who have been in dialysis for one week will have the QOL identified by the one year group in a year. It is also assumed that the persons who have been in dialysis for a year had a similar QOL as the one week group a year ago.
Donna B. Konradi, DNS, RN, CNE

20. Donna B. Konradi, DNS, RN, CNE
Longitudinal Design
Research projects designed to collect data over an extended period of time
Types
Trend studies
Panel studies
Follow-up studies
Trend studies:
Donna B. Konradi, DNS, RN, CNE

21. Donna B. Konradi, DNS, RN, CNE
Trend Studies
Samples from a general population are studied over time with respect to some phenomena
Arbitron Media studies…samples are selected to assess TV viewing habits. At various intervals, new samples are drawn from the same population to reassess TV viewing habits and predict which shows will be successful
Donna B. Konradi, DNS, RN, CNE

22. Donna B. Konradi, DNS, RN, CNE
Panel Studies
The same participant supplies the data at two or more data collection points
Example: A study to determine the relationship between perceptions of health, self-efficacy and adherence to a diabetic diet with data collection at pre-initiation; 1 week and 1 month
Donna B. Konradi, DNS, RN, CNE

23. Donna B. Konradi, DNS, RN, CNE
Panel Studies
Advantage
Helpful for examining patterns of changes and reasons for change
Disadvantage
Attrition (participant drop out)
Donna B. Konradi, DNS, RN, CNE

24. Donna B. Konradi, DNS, RN, CNE
Follow-up Studies
Used to determine the ongoing status of participants with a specific “condition” or used to assess specified outcomes following an intervention
Example: 50 cancer patients receiving head and neck radiation therapy assessed for nutritional status at initiation of therapy; at the conclusion of therapy and 3 months after therapy
Donna B. Konradi, DNS, RN, CNE

25. Critiquing the Quantitative Design
Indicate if this is a qualitative, quantitative or mixed design study
Identify the type of research design
Describe the data collection procedure
Donna B. Konradi, DNS, RN, CNE