Research in Medical and Biological Sciences

From Planning and Preparation to Grant Application and Publication

Petter Laake, Haakon Breien Benestad, Bjorn R. Olsen, Bjorn R. Reino Olsen, Bjorn R. Olsen

• Verlag: Academic Press
• Jahr: 2015
• ISBN:
  9780128001547
• Thema: Biological Sciences
• Thema: Biology

Research in Medical and Biological Sciences covers the wide range of topics that a researcher must be familiar with in order to become a successful biomedical scientist. Perfect for aspiring as well as practicing professionals in the medical and biological sciences, this publication discusses a broad range of topics that are common yet not traditionally considered part of formal curricula, including philosophy of science, ethics, statistics, and grant applications. The information presented in this book also facilitates communication across conventional disciplinary boundaries, in line with the increasingly multidisciplinary nature of modern research projects.

• Covers the breadth of topics that a researcher must understand in order to be a successful experimental scientist
• Provides a broad scientific perspective that is perfect for students with various professional backgrounds
• Contains easily accessible, concise material about diverse methods
• Includes extensive online resources such as further reading suggestions, data files, statistical tables, and the StaTable application package
• Emphasizes the ethics and statistics of medical and biological sciences

Chapter 1

Philosophy of Science

Bjørn Hofmann¹ and Søren Holm², ¹Section for Health, Technology and Society, University College of Gjøvik, Gjøvik, Norway and Centre for Medical Ethics, Institute of Health and Society, University of Oslo, Blindern, Oslo, Norway, ²Centre for Social Ethics and Policy, School of Law, The University of Manchester, England, Centre for Medical Ethics, Institute of Health and Society, University of Oslo, Blindern, Oslo, Norway and Department of Health Science and Technology, Aalborg University, Denmark

This chapter introduces and addresses some basic questions regarding the philosophy of science. For example, what is science, and how can it be differentiated from other social activities? What constitutes a scientific fact, and what characterizes scientific knowledge? What does it mean when one says that smoking causes cancer? What are the modes of inference and the models of explanation in the natural sciences? How do researchers test hypotheses and gain knowledge? What kind of uncertainties do researchers strive to reduce? And even more: what are the entities to which scientists refer, i.e., what is DNA; what is pain—and how do they gain knowledge about them?

In studies of social phenomena, how do social data differ from scientific data? What is the difference between explanation, understanding, and interpretation? What is the validity of scientific interpretations; can results be generalized and if so, how? Do social phenomena have emergent properties, and how can they be studied? How do power, ideology, and interests come into play? The aim of this chapter is to outline some concepts and views that researchers can use to view their own and others’ research in a broader perspective, and to promote scientists’ reflection and modesty.

Keywords

Causation; explanation; realism; idealism; rationalism; empiricism; inference; verification; falsification; philosophy of the social sciences; emergence; hermeneutics; validity; generalization

1.1 Introduction

The sciences provide different approaches to the study of man. Man can be scrutinized in terms of molecules, tissues and organs, as a living creature, and as a social agent and a cultural person. Correspondingly, the philosophy of science investigates the philosophical assumptions, foundations, and implications of the sciences. It is an enormous field that covers the formal sciences, such as mathematics, computer sciences, and logic; the natural sciences; the social sciences; and the methodologies of some of the humanities, such as history. Discussion in the current chapter is limited to the natural sciences (Section 1.2) and the social sciences (Section 1.13), and comprises a brief overview of the philosophical aspects salient to research in the medical and biological sciences.

1.2 Philosophy of the Natural Sciences

What does it mean when one says that “smoking is the cause of lung cancer”? What counts as a scientific explanation? What is science about, e.g., what is a cell? How does one obtain scientific evidence? How can one reduce uncertainty? What are the limits of science? These are but a few of the issues discussed in the philosophy of the natural sciences that will be presented in this chapter.

The traditional philosophy of science has aimed to put forth logical analyses of the premises of science; in particular the logical analysis of the syntax of basic scientific concepts. In the following sections, the principal traditional issues regarding the rationality, method, evidence, and the object of science (the world) are discussed. But first the core concepts of science, knowledge, and truth will be addressed: What is science? What is scientific knowledge, and what constitutes a scientific fact?

1.3 What is Science? Differentiating Science from Nonscience

Science is traditionally defined as “the systematic search for knowledge,” meaning that science has an aim (knowledge) and it is an activity (search) with certain qualifications (systematic). However, not everyone who carries out a systematic search for knowledge can obtain research funding. For example, though a religious man may search for knowledge through highly systematic meditation techniques, it is unlikely that this will be considered a project in need of research funding. Indeed, much of the time even well-funded scientists do not perform systematic searches for knowledge. They struggle with experimental designs, analyze data, present research results, argue with other researchers over conflicting results, and write funding proposals.

Therefore, a more complete definition of science may be: “Scientific research is the systematic and socially organized (a) search for, (b) acquisition of, and (c) use or application of knowledge and insight brought forth by acts and activities involved in (a) and (b).”¹ This definition better reflects what scientists actually do. They search for new knowledge, e.g., by investigating the possibility of using biomolecular tests of cell-free fetal DNA/RNA in the blood of pregnant women to find defects in the fetus (noninvasive prenatal testing, NIPT). They acquire knowledge by testing, accepting, or rejecting a hypothesis, e.g., that NIPT is better than combined ultrasound and serum tests for detecting fetuses with trisomy 13, 18, and 21. Finally, scientists apply knowledge when they argue that a certain study is either appropriate or flawed, and therefore its results either valid or invalid. Although this definition of science is closer to what scientists do, it may still be difficult to differentiate those doing science from those doing nonscience.

Throughout history a series of criteria has been used to demarcate science from nonscience (sometimes also referred to as pseudoscience), and thereby also to define science. Francis Bacon (1561–1626) defined science as a specific method, i.e., performing a systematic analysis of data without preconception. Data analysis framed by preconception was considered nonscience. However, in reality it can be very difficult to analyze data without preconception. To illustrate this fact, if you study the figure below (Figure 1.1), what do you see? A rabbit, a duck, or perhaps both?

Figure 1.1 The duck/rabbit.

When viewed on paper (or on a screen) the figure has black dots on a white background. So where are the duck and the rabbit? Are they figments of the imagination? Are they preconceptions? Hence, to say that science is the systematic analysis of data without preconception is too restrictive; it would rule out most of what is called science today. Indeed, all observations and analyses are based on preconceptions.

Another way to differentiate science from nonscience is to say that preconception is acceptable in the context of discovery but not in the context of justification, i.e., when the data are tested. The basic idea is that the pattern of nature is neutral, and will stand out in the end. However, this does not solve the problem of preconception when the hypothesis is tested, as testing presupposes observations, and observations presuppose preconceptions.

A third classical demarcation criterion is that a scientific hypothesis or theory can be contested with possible observations, i.e., it can be falsified (or refuted).² However, theories are seldom really falsified,³ and to falsify a theory presupposes that the researcher has an idea about what will happen. As scientists we are seldom ready to give up our theories, and instead add specifications or modifications.

It has been argued that scientists are preoccupied with puzzle-solving, i.e., solving puzzles within a given mode of thought (paradigm), when they should be concentrating on falsification.³ Until the 1960s it was commonly thought that science progressed in a linear and piecemeal fashion, in which new knowledge added to existing knowledge. However, Thomas Kuhn (1922–1996) and others argued that science evolved through anomalies. Hard cases that could not be explained within the given paradigm challenged existing theories and resulted in a scientific revolution. A new set of theories established a new paradigm, and scientists turned to puzzle-solving within this new paradigm. The shift from Newton’s mechanics to Einstein’s theory of (special) relativity is a key example. However, if science is defined by a given paradigm, this potentially makes everything science, as long as scientists define it as a paradigm and are preoccupied with solving its small problems.

The above mentioned four demarcation criteria are but a few of many. None of them are flawless, and it has turned out to be quite difficult to differentiate science from nonscience. In order to remedy this, several sets of more pragmatic criteria to identify nonscience have evolved (Box 1.1).

Box 1.1

Selected Characteristics of Nonscience

1. Belief in authority: Some person or persons have a special ability to determine what is true or false, and others have to accept their judgment.

2. Nonrepeatable experiments: Reliance on experiments with outcomes that cannot be reproduced by others.

3. Handpicked examples: Examples that are not representative of the general category to which the investigation refers are considered decisive.

4. Unwillingness to test: A testable theory is not tested.

5. Disregard of refuting information: Ignoring or neglecting observations or experiments that conflict with a theory.

6. Built-in subterfuge: Arranged the testing of a theory so that it can only be verified but never falsified by the outcome.

7. Explanations abandoned without replacement: Giving up tenable explanations without replacing them, so that more is left unexplained in the new theory than in the previous one.^4,5

1.4 Knowledge and Truth: What is Knowledge and What Constitutes a Scienti...