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compare is provided by the control group (11): “The term control group ... refers to a group of subjects whose performance on a dependent variable is used as a basis for evaluating the performance of the experimental group (the group that receives the treatment of interest to the researcher) on the same dependent variable”. The control group may be given the conventional treatment for the condition or a placebo (such as tablets with no active ingredient or a half-hour visit but no therapy) or no treatment at all. Some study designs involve more than one control group such as: • experimental group vs. placebo group vs. no treatment group; or • experimental group vs. conventional treatment group vs. placebo group. The latter design has the ability to demonstrate that the experimental treatment is not only more effective than the placebo but is also more effective than the conventional treatment. Other factors that could affect the dependent variable need to be controlled. For example, the temperature in a laboratory or room might affect biochemical, physical or psychological test results. For this reason, the temperature needs to be constantly controlled throughout the experiment. In a drug trial, patients might take other medicines that could affect the medical condition under study. Such patients must either refrain from taking these medicines or be excluded from the study. A study that has body temperature as a dependent variable must take account of the fact that this varies with the time of day. Body temperature should, therefore, be page 18 Research awareness in nursing and midwifery: a workbook measured at the same time (or times) of day. These additional factors that can affect the dependent variable are known as extraneous variables. Randomization, the third essential element of an experiment, is performed to prevent the researcher(s) from distorting the results through “systematic bias”. The random assignment of individuals to groups aims to make the experimental group and the control group comparable in terms of characteristics such as age, gender, educational status and other factors that could affect the dependent variable. Randomization procedures can be performed by simple means, such as drawing names out of a hat or generating random numbers by computer. There are several types of experimental design. Two common ones are: • the comparison of independent groups; and • the comparison of repeated measures carried out on the same group. In the latter case the experimental group acts as its own control group. The “cross-over” study is a common form of the repeated measures design. In this, participants are divided into two groups. Group I receives treatment A followed by treatment B and group II receives treatment B followed by treatment A. The advantages of repeated measures studies are that they require fewer participants (as each individual is used twice) and that the characteristics of the experimental group and the control group are the same (as they are composed of the same people). The major disadvantage is that it can be claimed that data collected during the second treatment period have been influenced by the fact that there was a previous treatment period. It is possible to carry out some experiments, such as drug trials under double-blind conditions. This means that neither the researchers nor the participants know which is the experimental group or treatment and which is the control group or treatment. Thus, in a doubleblind cross-over drug trial, neither the researchers nor the participants know whether the experimental medication has been administered during the first or the second treatment period (placebo medication is given in the other treatment period). The study is only “unblinded” once data collection and analysis are complete. Quasi-experimental research A quasi-experiment does not possess all three essential attributes of a true experiment, as it lacks either randomization or a control group. There are numerous questions worth researching where randomization is not possible. For example, a researcher may wish to determine the physical and psychological effects of a new shift-work system on nurses working in a particular hospital. Since the new shifts are being introduced for all nurses throughout the hospital, randomization is not possible. It may, however, still be possible to collect pre-test and post-test data and to use the nurses at a similar hospital, which is keeping the old shift system, as a comparison group. In some studies, however, it may not be possible to find an appropriate comparison group. Quasi-experimental designs do not lend themselves to the testing of hypotheses concerned with cause and effect because of the presence of too many uncontrolled factors. It is, however, possible to test whether variables are correlated, i.e. related to each other in a statistically significant way. Survey research Surveys can be used to collect information about variables and, sometimes, to test relationships between variables. There is no experimental intervention in survey work; rather information is Reading and evaluating research reports page 19 collected about (for example) people’s health status, living conditions, health beliefs or satisfaction with services. The information is turned into numerical data, which can be subjected to statistical analysis
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