Quantitative Methods for Health Research: A Practical Interactive Guide to Epidemiology and Statistics - Hardcover

Bruce, Nigel; Pope, Daniel; Stanistreet, Debbi

Hardcover

ISBN 10: 0470022744 ISBN 13: 9780470022740

Publisher: Wiley-Interscience, 2008

Synopsis

Quantitative Research Methods for Health Professionals: A Practical Interactive Course is a superb introduction to epidemiology, biostatistics, and research methodology for the whole health care community.

Drawing examples from a wide range of health research, this practical handbook covers important contemporary health research methods such as survival analysis, Cox regression, and meta-analysis, the understanding of which go beyond introductory concepts.

The book includes self-assessment exercises throughout to help students explore and reflect on their understanding and a clear distinction is made between a) knowledge and concepts that all students should ensure they understand and b) those that can be pursued by students who wish to do so.

The authors incorporate a program of practical exercises in SPSS using a prepared data set that helps to consolidate the theory and develop skills and confidence in data handling, analysis and interpretation.

About this title

About the Author

Nigel Bruce, PhD is Emeritus Professor of Public Health at the Department of Public Health and Policy, University of Liverpool, UK.

Daniel Pope, PhD is Senior Lecturer in Epidemiology and Public Health at the Department of Public Health and Policy, University of Liverpool, UK.

Debbi Stanistreet, PhD is Senior Lecturer and Faculty Director of Widening Participation at the Department of Public Health and Policy, University of Liverpool, UK.

Excerpt. © Reprinted by permission. All rights reserved.

Quantitative Methods for Health Research

A Practical Interactive Guide to Epidemiology and StatisticsBy Nigel Bruce Daniel Pope Debbi Stanistreet

John Wiley & Sons

Copyright © 2008 John Wiley & Sons, Ltd
All right reserved.
ISBN: 978-0-470-02274-0

Chapter One

Philosophy of science and introduction to epidemiology

Introduction and learning objectives

In this chapter, we will begin by looking at different approaches to scientific research, how these have arisen, and the importance of recognising that there is no single, 'right way' to carry out investigations in the health field. We will then go on to explore the research task, discuss what is meant by epidemiology and statistics, and look at how these two disciplines are introduced and developed in the book. The next section introduces the concept of rates for measuring the frequency of disease or characteristics we are interested in, and in particular the terms incidence and prevalence. These definitions and uses of rates are fundamental ideas with which you should be familiar before we look in more detail at research methods and study design. In the final section, we will look at key concepts in disease prevention, including the commonly used terms primary, secondary and tertiary prevention.

The reason for starting with a brief exploration of the nature of scientific methods is to see how historical and social factors have influenced the biomedical and social research traditions that we take for granted today. This will help you understand your own perceptions of, and assumptions about, health research, based on the knowledge and experience you have gained to date. It will also help you understand the scientific approach being taken in this book, and how this both complements, and differs from, that developed in books and courses on qualitative research methods - as and when you may choose to study these. Being able to draw on a range of research traditions and their associated methods is especially important for the discipline of public health, but also for many other aspects of health and health care.

Learning objectives

By the end of Chapter 1, you should be able to do the following:

Briefly describe the philosophical differences between the main approaches to research that are used in the health field.

Describe what is meant by epidemiology, and list the main uses to which epidemiological methods and thought can be put.

Describe what is meant by statistics, and list the main uses to which statistical methods and thought can be put.

Define and calculate rates, prevalence and incidence, and give examples of their use.

Define primary, secondary and tertiary prevention and give examples of each.

1.1 Approaches to scientific research

1.1.1 History and nature of scientific research

Scientific research in health has a long history going back to the classical period. There are threads of continuity, as well as new developments in thinking and techniques, which can be traced from the ancient Greeks, through the fall of the Roman Empire, the Dark Ages and the Renaissance, to the present time. At each stage, science has influenced, and been influenced by, the culture and philosophy of the time. Modern scientific methods reflect these varied historical and social influences. So it is useful to begin this brief exploration of scientific health research by reflecting on our own perceptions of science, and how our own views of the world fit with the various ways in which research can be approached. As you read this chapter you might like to think about the following questions:

What do you understand by the terms science, and scientific research, especially in relation to health?

How has your understanding of research developed?

What type of research philosophy best fits your view of the world, and the problems you are most interested in?

Thinking about the answers to these questions will help you understand what we are trying to achieve in this section, and how this can best support the research interests that you have and are likely to develop in the years to come. The history and philosophy of science is of course a whole subject in its own right, and this is of necessity a very brief introduction.

Scientific reasoning and epidemiology

Health research involves many different scientific disciplines, many of which you will be familiar with from previous training and experience. Here we are focusing principally on epidemiology, which is concerned with the study of the distribution and determinants of disease within and between populations. In epidemiology, as we shall see subsequently, there is an emphasis on empiricism, that is, the study of observable phenomena by scientific methods, detailed observation and accurate measurement. The scientific approach to epidemiological investigation has been described as:

Systematic - there is an agreed system for performing observations and measurement.

Rigorous - the agreed system is followed exactly as prescribed.

Reproducible - all the techniques, apparatus and materials used in making the observations and measurements are written down in enough detail to allow another scientist to reproduce the same process.

Repeatable - scientists often repeat their own observations and measurements several times in order to increase the reliability of the data. If similar results are obtained each time, the researcher can be confident the phenomena have been accurately recorded.

These are characteristics of most epidemiological study designs and will be an important part of the planning and implementation of the research. However, this approach is often taken for granted by many investigators in the health field (including epidemiologists) as the only way to conduct research. Later we will look at some of the criticisms of this approach to scientific research but first we need to look in more detail at the reasoning behind this perspective.

Positivism

The assumptions of contemporary epidemiological investigations are associated with a view of science and knowledge known as positivism. Positivism is a philosophy that developed in the eighteenth century in a period known as the Enlightenment, a time when scientists stopped relying on religion, conjecture and faith to explain phenomena, and instead began to use reason and rational thought. This period saw the emergence of the view that it is only by using scientific thinking and practices that we can reveal the truth about the world (Bilton et al., 2002).

Positivism assumes a stable observable reality that can be measured and observed. So, for positivists, scientific knowledge is proven knowledge, and theories are therefore derived in a systematic, rigorous way from observation and experiment. This approach to studying human life is the same approach that scientists take to study the natural world. Human beings are believed by positivists to exist in causal relationships that can be empirically observed, tested and measured (Bilton et al., 2002), and to behave in accordance with various laws. As this reality exists whether we look for it or not, it is the role of scientists to reveal its existence, but not to attempt to understand the inner meanings of these laws or express personal opinions about these laws. One of the primary characteristics of a positivist approach is that the researcher takes an objective distance from the phenomena so that the description of the investigation can be detached and undistorted by emotion or personal bias (Davey, 1994). This means that within epidemiology, various study designs and techniques have been developed to increase objectivity, and you will learn more about these in later chapters.

Induction and deduction

There are two main forms of scientific reasoning - induction and deduction. Both have been important in the development of scientific knowledge, and it is useful to appreciate the difference between the two in order to understand the approach taken in epidemiology.

Induction

With inductive reasoning, researchers make repeated observations and use this evidence to generate theories to explain what they have observed. For example, if a researcher made a number of observations in different settings of women cooking dinner for their husbands, they might then inductively derive a general theory:

All women cook dinner for their husbands.

Deduction

Deduction works in the opposite way to induction, starting with a theory (known as an hypothesis) and then testing it by observation. Thus, a very important part of deductive reasoning is the formulation of the hypothesis - that is, the provisional assumption researchers make about the population or phenomena they wish to study before starting with observations. A good hypothesis must enable the researcher to test it through a series of empirical observations. So, in deductive reasoning, the hypothesis would be:

All women will cook dinner for their husbands.

Observations would then be made in order to test the validity of this statement. This would allow researchers to check the consistency of the hypothesis against their observations, and if necessary the hypothesis can be discarded or refined to accommodate the observed data. So, if they found even one woman not cooking for her husband, the hypothesis would have to be reexamined and modified. This characterises the approach taken in epidemiology and by positivists generally.

One of the most influential science philosophers of recent times was Karl Popper (1902-1994), who argued that hypotheses can never be proved true for all time and scientists should aim to refute their own hypothesis even if this goes against what they believe (Popper, 1959). He called this the hypothetico-deductive method, and in practice this means that an hypothesis should be capable of being falsified and then modified. Thus, to be able to claim the hypothesis is true would mean that all routes of investigation had been carried out. In practice, this is impossible, so research following this method does not set out with the intention of proving that an hypothesis is true. In due course we will see how important this approach is for epidemiology and in the statistical methods used for testing hypotheses.

Alternative approaches to research

It is important to be aware that positivism is only one approach to scientific research. Positivism has been criticised by some researchers, in particular social scientists, who think it is an inappropriate approach to studies of human behaviour. From this perspective, they believe that human beings can behave irrationally and do not always act in accordance with any observable rules or laws. This makes them different from phenomena in the natural world, and so they need to be studied in a different way. Positivism has also been criticised because it does not allow for the view that human beings act in response to others around them; that is, that they interpret their own behaviour in response to others. As Green and Thorogood (2004, p. 12) argue:

Unlike atoms (or plants or planets), human beings make sense of their place in the world, have views on researchers who are studying them, and behave in ways that are not determined in law-like ways. They are complex, unpredictable, and reflect on their behaviour. Therefore, the methods and aims of the natural sciences are unlikely to be useful for studying people and social behaviour: instead of explaining people and society, research should aim to understand human behaviour.

Social scientists therefore tend to have a different belief about how we should research human beings. Consequently, they are more likely to take an inductive approach to research because they would argue that they do not want to make assumptions about the social world until they have observed it in and for itself. They, therefore, do not want to formulate hypotheses because they believe these are inappropriate for making sense of human action. Rather, they believe that human action cannot be explained but must be understood.

While positivists are concerned mainly with observing patterns of behaviour, other researchers principally wish to understand human behaviour. This latter group requires a different starting point that will encompass their view of the world, or different theoretical positions to make sense of the world. It turns out that there are many different positions that can be adopted, and while we cannot go into them all here, we will use one example to illustrate this perspective.

Interpretative approaches

An interpretative approach assumes an interest in the meanings underpinning human action, and the role of the researcher is therefore to unearth that meaning. The researcher would not look to measure the reality of the world but would seek to understand how people interpret the world around them (Green and Thorogood, 2004).

Let's look at an example of this in respect of asthma. A positivist approach to researching this condition may be to obtain a series of objective measurements of symptoms and lung function by a standard procedure on a particular sample of people over a specified period of time. An interpretative approach might involve talking in-depth to fewer participants to try to understand how their symptoms affect their lives. Obviously, in order to do this, these two 'types' of researchers would need to use very different approaches. Those planning the interpretative research would be more likely to use qualitative methods (interviews, focus groups, participatory methods, etc.), while positivists (for example, epidemiologists) would choose quantitative methods (surveys, cohort studies, etc., involving lung-function measurements and highly structured questionnaires). These two different approaches are called research paradigms and would therefore produce different types of information.

Interpretative researchers would also criticise positivists for their belief that researchers can have an objective, unimpaired and unprejudiced stance in the research that allows them to make value-free statements. Interpretative researchers accept that researchers are human beings and therefore cannot stand objectively apart from the research. In a sense they are part of the research, as their presence can influence the nature and outcome of the research. Whether or not you agree with the criticism of positivism, you need to be aware that there are alternative approaches to conducting research that neither prioritise objectivity nor set out to measure 'reality'.

One of the most influential writers on the scientific method was Thomas Kuhn (1922-1996) (Davey, 1994). He argued that one scientific paradigm - one 'conceptual worldview' - may be the dominant one at a particular period in history. Over time, this is challenged, and eventually replaced by another view (paradigm), which then becomes accepted as the most important and influential. These revolutions in science were termed 'paradigm shifts'. Although challenged by other writers, this perspective suggests that scientific methods we may take for granted as being the only or best way to investigate health and disease, are to an extent the product of historical and social factors, and can be expected to evolve - and maybe change substantively - over time.

There are no 'answers' provided for this exercise, as it is intended for personal reflection.

1.1.2 What is epidemiology?

The term epidemiology is derived from the following three Greek words:

Epi - among Demos - the people Logos - discourse

We can translate this in more modern terms into 'The study of the distribution and determinants of disease frequency in human populations'. The following exercise will help you to think about the uses to which the discipline of epidemiology is put.

(Continues...)

Excerpted from Quantitative Methods for Health Researchby Nigel Bruce Daniel Pope Debbi Stanistreet Copyright © 2008 by John Wiley & Sons, Ltd. Excerpted by permission.
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Edition details

• Publisher: Wiley-Interscience
• Publication date: 2008
• Language: English
• ISBN 10: 0470022744
• ISBN 13: 9780470022740
• Binding: Hardcover
• Edition number: 1
• Number of pages: 560