Russel-Research-Method-in-Anthropology

124 Chapter 5
tions. (2) Half the nurses read only a synopsis of the condition of Mary B. or
Robert B., and half read the same synopsis as the fourth one in a series of
seven. This produced two memory-load conditions. (3) Finally, half the nurses
read that the temperature of Mary B. or Robert B. had just spiked unexpectedly
to 102, and half did not. This produced two patient stability conditions.
The three binary conditions combined to form eight experimental conditions
in a factorial design (more on factorial designs at the end of this chapter).
Next, McDonald and Bridge asked nurses to estimate, to the nearest minute,
how much time they would plan for each of several important nursing actions.
Irrespective of the memory load, nurses planned significantly more time for
giving the patient analgesics, for helping the patient to walk around, and for
giving the patient emotional support when the patient was a man.
The posttest-only design, with random assignment, is not used as much as
I think it should be, despite its elegance and its low cost. This is due partly to
the appealing-but-mistaken idea that matching participants in experiments on
key independent variables (age, ethnicity, etc.) is somehow better than randomly
assigning participants to groups. It’s also due partly to the nagging suspicion
that pretests are essential.
The One-Shot Case Study
The one-shot case study design is shown in figure 5.1e. It is also called
the ex post facto design because a single group of people is measured on
Time 1 Time 2
Assignment Pretest
Intervention Posttest
X
O
Figure 5.1e. The one-shot case study design.
some dependent variable after an intervention has taken place. This is the most
common research design in culture change studies, where it is obviously
impossible to manipulate the dependent variable. You arrive in a community
and notice that something important has taken place. A clinic or a school has
been built. You try to evaluate the experiment by interviewing people (O) and
assessing the impact of the intervention (X).
With neither a pretest nor a control group, you can’t be sure that what you
observe is the result of some particular intervention. Despite this apparent
weakness, however, the intuitive appeal of findings produced by one-shot case
studies can be formidable.