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Research Methods and Measurement 2 Two Albery-Ch-02.qxd 10/25/2007 4:52 PM Page 19 RESEARCH METHODS AND MEASUREMENT 2 TWO RESEARCH METHODS AND MEASUREMENT and: study design cross-sectional longitudinal experimental qualitative psychometrics Good study design is essential if we are to be confident in our data and in the conclusions that we draw from them, and accurate measurement is an integral part of this. In this chapter we describe the importance of study design, and outline the various primary study designs which are used in health psychology and more widely, including cross-sectional, longitudinal and experimental designs. Each of these has its own strengths and weakness, and is ideally suited to specific kinds of research question. In addition, qualitiative methods are discussed, which offer the potential to answer a completely different kind of research question to quantitative methods, and serve a complementary function. Many important research questions can only be answered meaningfully using qualitative techniques, and good research will know which study design is best suited to answering a specific question. Finally, we discuss the science of psychometrics, which is concerned with ensuring that measurements are accurate and do indeed measure what they are intended to measure. Albery-Ch-02.qxd 10/25/2007 4:52 PM Page 20 Key Concepts in Health Psychology RESEARCH METHODS AND MEASUREMENT and: STUDY DESIGN MEANING The design of the study refers to the means by which the research question will be addressed, specifically in relation to the data that will be collected, the comparisons that will be made, the experimental conditions (if any) that will be manipulated, and so on. In many ways, the design of a study is more important than the analysis of the data resulting from that study; if data are poorly analysed it will always be possible to re-analyse them, but if a study if poorly designed in the first place then it may never be possible to meaningfully interpret the data which result from it. The design of a study will also have an impact on how data are subsequently analysed. ORIGINS Research can be defined as belonging to one of two primary categories: observa- tional studies and experimental studies. As suggested by the name, in observational studies there is no direct manipulation of variables within the study, and data are simply collected on groups of participants. In an observational study, while the research collects information on the attributes or outcomes of interest, no effort is made to influence these. An example might be the prevalence of a particular health behaviour (e.g. cigarette smoking) in different groups defined by socioeconomic status. In an experimental study, on the other hand, the experimenter directly influ- ences events, in order to draw conclusions regarding the impact of that manipula- tion on the resulting observations. An example might be the impact of an intervention (e.g. an increase in self-efficacy beliefs) compared to a control condi- tion on a particular health behaviour (e.g. giving up smoking). A further sub-division which may apply to observational studies is between prospective studies, where information is collected about events subsequent to recruitment into the study, and retrospective studies, where information is col- lected about events in the past. Data regarding past events may be obtained from more objective sources (e.g. school records or patient notes) or, arguably, from more subjective sources (e.g. by self-report by the participant). Note that, in nearly all cases, experimental studies are prospective (even if the period of prospective study may be very short!), whereas observational studies may be retrospective or prospective. It should also be noted that whereas different treatments can be assessed retrospectively, this would not count as an experimental study, since the delivery of different treatments would not be an element of a pre-specified study. In this case, the study would be a retrospective observational study. Another sub-division is that studies may be classified as longitudinal studies or cross-sectional studies. In longitudinal studies, changes over time are investi- gated. Again, note that, in nearly all cases, experimental studies are longitudinal (although once again, the period of longitudinal study may be very short), whereas 20 Albery-Ch-02.qxd 10/25/2007 4:52 PM Page 21 Research Methods and Measurement Experimental Observational Prospective Prospective Retrospective Longitudinal Longitudinal Cross-Sectional Longitudinal Cross-Sectional Figure 2.1 Study design What are the basic categories of research design? The classifications that can be used include Observational versus Experimental, Prospective versus Retrospective, and Longitudinal versus Cross-Sectional. The distinction between observational and experimental relates to the purpose of the study, and is the most important distinction. The other two distinctions relate to the way in which the data are collected. Most of the combinations of these terms are possible, although not all are. These are the basic types of research design. Some of these categories are described in more detail in sub- sequent sections. observational studies may be longitudinal or cross-sectional. In a cross-sectional study participants are observed only once, offering a ‘snapshot’ of the characteris- tics of interest at that particular moment. Most surveys, for example, are cross- sectional, although a variant is the pseudo-longitudinal design, where data on par- ticipants are collected at only one point in time, but this is done, for example, on, participants of different ages in order to indirectly construct a distribution of changes in a population with age. This approach is usually less resource-intensive than a proper longitudinal design, although somewhat more prone to giving erro- neous results. Finally, some kind of comparison is desirable in observational studies, and essen- tial in experimental studies. This comparison group or condition is called the control group, to which the experimental procedure is not applied in the case of an experimental study design, or against which the group of interest is compared in an observational study design. For example, if we want to evaluate whether or not a new treatment or intervention is effective, we would usually do this by means of a comparison of the group given the intervention against one not given the inter- vention (namely, a control group). The presence of a control group, in both exper- imental and observational studies, strengthens the inferences that can be made from the results of the study. While more detailed distinctions can be made, these represent the main ways in which a study can be designed (see Figure 2.1). 21 Albery-Ch-02.qxd 10/25/2007 4:52 PM Page 22 Key Concepts in Health Psychology CURRENT The essence of statistical analysis is the understanding of likely causes of variation, USAGE which in the case of health psychology usually corresponds to variation in behav- ioural or psychological characteristics. Study design is important because it is the means by which we can be more (or less) confident that the apparent causes of variation in our study are in fact the genuine causes of variation. For example, if we find that an intervention designed to improve self-efficacy beliefs is effective, we would need to know that those given the intervention demonstrated higher self-efficacy beliefs than those not given the intervention (namely, the control group), and that these two groups did not differ in their self- efficacy beliefs before the intervention was given. The strength of experimental study designs is that as long as participants are randomly allocated to either the experimental or control group, so that these groups do not differ at the outset of the study, any differences by the end of the study can be argued, with reasonable confidence, to be due to the experimental intervention. We would hope that there were no chance differences between the two groups before they received the inter- vention that might explain the difference observed after the intervention had been given. Observational study designs, on the other hand, are more problematic as they require a comparison to be made where there is no active manipulation of events. For example, we may wish to investigate factors which it is impossible (or unethi- cal) for us to manipulate directly (such as genetic variation). In this case, we would want to compare those with a particular characteristic (e.g. a particular genotype) to those with a different characteristic (e.g. a different genotype) on some measure- ment of interest (e.g. risk of a certain disease). Again, the more confident that we can be that our two groups do not differ in any other way, the more confident we can be that the difference of interest accounts for any observed differences in the measurement we take (in this example that having a particular genotype influences the risk of having a certain disease). SIGNIFICANCE Health psychology is the application of psychological and behavioural theory and TO HEALTH research to the understanding of health, illness and healthcare. In many cases the factors influencing health, illness and so on are not amenable to experimental PSYCHOLOGY manipulation, so that observational study designs are frequently necessary. It is therefore critically important to understand (a) how best to design an observational study in order to maximize the confidence that one may have in the conclusions drawn from the results of the study, and (b) what limitations may exist in the infer- ences that may be drawn. For example, we might be interested in whether or not personality influences alco- hol consumption. A cross-sectional observational study might indeed reveal that people with high levels of trait anxiety do indeed drink more alcohol. However, we would not be able to say from these data alone whether high levels of trait anxiety eventually lead to higher alcohol consumption, or high alcohol consumption eventually leads to higher 22 Albery-Ch-02.qxd 10/25/2007 4:52 PM Page 23 Research Methods and Measurement levels of trait anxiety.
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