Kathy trains nurses. She designed a new assertive communication unit to include

Question

Kathy trains nurses. She designed a new assertive communication unit to include in her training. She administers a pretest and then randomly assigns nurses to her treatment or a control condition. She tests their communication skills before and after the treatment. She sees no significant differences at immediate testing but after eight weeks she retests the nurses and finds significant differences between her treatment and control students. Which of the following best represents the design of Kathy’s study? 1. Non-equivalent groups 2. Solomon four group 3. Pretest-posttest control group 4. Post-test only control group

Explanation / Answer

1. Non-equivalent groups

            nonequivalent group design is a quasi-experiment used to assess the relative effects of treatments that have been assigned to groups of participants nonrandomly. Because the participants have been assigned to treatments nonrandomly, differences in the composition of the treatment groups can bias the estimates of the treatment effects. Researchers are advised to minimize selection differences by using groups of participants that are initially as similar as possible.

Equivalence

Non-Equivalence

The model for the design:

Nt-> Pr->I->Po

Nc-> Pr-> Po

Nt=Nonequivalent treatment group

Nc=nonequivalent comparison group

I=intervention

Pr=pre-test (baseline measurement)

Po=Post-test measurement.

2. Solomon four group

The Solomon four group design is a way of avoiding some of the difficulties associated with the pretest-posttest design.

This design contains two extra control groups, which serve to reduce the influence of confounding variables and allow the researcher to test whether the pretest itself has an effect on the subjects.

Whilst much more complex to set up and analyze, this design type combats many of the internal validity issues that can plague research. It allows the researcher to exert complete control over the variables and allows the researcher to check that the pretest did not influence the results.

3. Pretest-posttest control group

Participants are studied before and after the experimental manipulation

You collect your participants and give them a series of tests that will measure their communication skill, treatment and student control.

You give them the same teat after 8 weeks, there is a perfect effect and Defined as an influence on performance from previous experience.

Lastly, compare the participant’s pre and posttests to see communication skills, treatment and student control. The purpose of this experiment was demonstrated if there was a change in the participants brought on by experimental manipulation.

The classic controlled experiments are:

X = Program intervention or introduction

O1 = Outcome measurements for pretest treatment group

O2 = Outcome measurements for the posttest treatment group

O3 = Outcome measurements for the pretest control group

O4 = Outcome measurements for the posttest control group

The impact of the intervention is measured by using the overall difference between the observations for the experimental group and the observations for the control group.

Impact = (O2 – O1) – (O4 – O3) +/- Error (sampling errors due to study design)

4. Post-test only control group

            This design follows all the same steps as the classic pre-test/post-test design except that it omits the pre-test. There are many situations where a pre-test is impossible because the participants have already been exposed to the treatment, or it would be too expensive or too time-consuming. For large enough groups, this design can control for most of the same threats to internal and external validity as the classic controlled experimental design.

For small groups, however, a pre-test is necessary. Also, a pre-test is necessary if the researcher wants to determine the exact amount of change attributable to the independent variable alone.

Unfortunately, it is difficult for public administrators to meet the requirements of the classic controlled experimental design.

X = Program intervention or introduction

O1 = Observations/measurements for the experimental group

O2 = Observations/measurements for the control group

The impact of the intervention is measured by using only the difference between the observations for the experimental group and the observations for the control group.

Impact = (O1-O2) +/- Error (sampling errors due to study design)

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