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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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