Psychology Research Methods

# Chapter 1: Research Methods ## Learning Intentions In this chapter you will learn how to: - describe and use the concepts and terminology relating to research methods - describe, evaluate and apply the six main research methods - explain and use other concepts relevant to planning and conductin...

# Chapter 1: Research Methods ## Learning Intentions In this chapter you will learn how to: - describe and use the concepts and terminology relating to research methods - describe, evaluate and apply the six main research methods - explain and use other concepts relevant to planning and conducting studies and analysing their results - apply the concepts of research methods to novel situations - consider the debate surrounding ethics in psychology. ## Introduction Psychological phenomena are explored using a research process and the methods used to investigate questions in psychology are called research methods. This chapter will help you to understand how those methods are used by psychologists to find out about human (and animal) cognition, emotions and behaviour. The chapter is divided into several sections, covering the basic research methods that you need to understand: - experiments - self-reports - case studies - observations - correlations - longitudinal studies Once you have studied these sections, you should be able to apply your knowledge of research methods to novel research situations. In addition you will learn about the other features of the research process or research methodology. These features are the steps a psychologist takes in developing and conducting studies to investigate a question or problem. This research process can be thought of as having several stages, the first of which is to develop an aim. Although developing an aim is one of many steps, it is useful to consider it here before moving on to the main part of the chapter. The __aim__ is the intention of the study, the idea it is trying to test, problem it is intended to solve or the question it is attempting to answer. Consider the idea of different ways to help students to study, perhaps using mind maps or revision apps. Imagine that a psychologist, Dr Huang, asks a few of her psychology students which method they prefer, and finds that both are quite popular. Dr Huang wants to know which is most effective. This is Dr Huang's aim - to investigate whether mind maps or revision apps are more effective at helping students to learn. So, the aim tells you the purpose of the investigation - in this case, an experiment. It is generally expressed in terms of what the study intends to show. An aim can also express the intention to investigate a link or relationship between two variables, such as between the number of computer games a student plays and their final A Level grade: in this case, the study would be a correlation. This chapter therefore covers the whole of this research process: - development of an aim - selection of a research method and the designs, formats or techniques to be used within that research method - definition, manipulation, measurement, control of variables and variables in hypotheses - selection of participants - ethical considerations - analysis of data, including the drawing of conclusions - evaluation of research. ## Getting Started ### Why do psychologists do research? As students, you may be bombarded with 'facts' about how to improve your learning. Perhaps you have heard of different learning styles, or the benefits of repetition or mind maps to help you to revise. Each of these ideas should have been tested to see if they actually work (although many haven't!). The process of research allows scientists such as psychologists to test ideas to discover whether there is evidence to support them. This is how we decide which drugs or therapies work best for mental illnesses, whether different displays or music help to sell products, and how we should organise factories to help workers to be efficient and healthy. To be trustworthy, research needs to be planned well and conducted effectively. Imagine an investigation comparing a new classroom technique to an old one. If the researcher didn't know how hard the students worked and used the new technique on a lazy class, and the old one on a highly motivated class, this would produce false results. Consider a study into consumer psychology that compared how many goods were sold with and without music playing in the store. If the researcher only played music at the weekends and played no music on weekdays, would you believe the findings of the study? ## 1.1 Experiments An experiment is an investigation that allows researchers to look for a cause-and-effect relationship. The researcher investigates the way one variable, called the **independent variable**, is responsible for the effect on another, the **dependent variable**. To test this, the researcher manipulates the **independent variable (IV)** to produce two or more 'levels' or conditions, such as creating 'bright' or 'dull' lighting or selecting 'early' and 'late' in the day. The effect of these conditions on the **dependent variable (DV)** is measured. For example, an IV of the brightness of lighting might affect attention, with people being better at paying attention when the light is bright. How well people pay attention would be the DV. If there is a big difference in the DV between the conditions, the researcher would conclude that the IV has caused the difference in the DV, i.e. that the brightness of light affects attention. ### Key Words - **Experiment**: an investigation that allows researchers to look for a causal relationship; an independent variable is manipulated and is expected to be responsible for changes in the dependent variable. - **Independent variable (IV)**: the factor under investigation in an experiment that is manipulated to create two or more conditions (levels) and is expected to be responsible for changes in the dependent variable. - **Dependent variable (DV)**: the factor in an experiment that is measured and is expected to change under the influence of the independent variable. ### Where do we focus when we concentrate on a problem? Watch or imagine someone thinking really hard, perhaps trying to remember a name or work out the answer to a question - where do they focus their eyes? It has been suggested that in such situations, we look upwards and to the left. Consider how you might test whether this is true. Would you wait for people to get confused and then look at what they do, or would you give them a puzzle to make them think? How would you decide where they are looking? What would you do to be sure that they aren't just looking around the room for clues? Being able to decide on the answers to questions such as these is the basis of designing experiments in psychology. ### Key Word - **Uncontrolled variable**: a variable that either acts randomly, affecting the DV in all levels of the IV, or systematically, i.e. on one level of the IV (called a confounding variable) so can obscure the effect of the IV, making the results difficult to interpret, the effects of which have not or cannot be limited or eliminated. ### Controlling Variables The effect of such uncontrolled variables should therefore be minimised, e.g. by keeping all factors except the IV the same in each condition (or 'level of the IV'). The levels of the IV being compared may be two or more **experimental conditions** (such as bright and dull artificial lights) or there may be one or more experimental conditions that are compared to a **control condition** (e.g. artificial light compared to daylight). The **control condition** is simply the absence of the experimental variable. For example, in a comparison of the effect of eating chocolate on paying attention, we might compare either the effect of eating one bar or two bars (two experimental conditions) or the effect of eating one bar to no chocolate at all (one experimental and one control condition). ### Key Words - **Experimental condition**: one or more of the situations in an experiment that represent different levels of the IV and are compared (or compared to a control condition) - **Control condition**: a level of the IV in an experiment from which the IV itself is absent. It is compared to one or more experimental conditions. ### Research Methods in Practice A researcher might conduct an experiment to test the effect of the independent variable of time of day on the dependent variable of happiness of students. They might always use lessons immediately after a break or lunch so the students had always eaten recently since this might affect happiness and act as an uncontrolled variable. This would be a comparison between two experimental conditions. ## 1.2 Self-Reports In a self-report, the participant gives the researcher information about themselves directly. This is different from experimental tests or observations where the researcher finds the data out from the participant. There are two main ways to conduct a self-report: using a questionnaire or an interview. Both types of self-report allow the researcher to ask the participant questions. ## 1.3 Case Studies A case study is a detailed investigation of a single instance, usually just one person, although it could be a single family or institution. The data collected is detailed and in-depth, and may be obtained using a variety of different techniques. For example, in one case study, a participant may be interviewed, observed, given tests and asked to fill in questionnaires. Case studies are particularly useful for looking at rare cases where a detailed description is useful, and for following developmental changes where the progress of a child, or a person with a disorder, can be tracked through their improvement or decline. Case studies are therefore sometimes linked to therapy but it is important to remember that when the case study as a research method is being discussed, the therapeutic purpose is not the main aim. In addition to using different methods or techniques within a case study, different sources of evidence may be used. These could include interviewing the participant themselves, their relatives or other people such as colleagues to obtain a wide range of information about the individual's history, as well as accessing pre-existing information such as medical or school records. ## 1.4 Observations Observations involve watching human or animal participants. There are many different choices in the way that observations are conducted and we will consider each in turn. An awareness of these choices is important both for understanding and planning observational studies. The setting in which the observation takes place is one such choice. A **naturalistic observation** is conducted in the participants' normal environment, without interference from the researchers in either the social or physical environment. A **controlled observation** is conducted in a situation that has been manipulated by the researchers. This may be in terms of the social environment, such as varying group sizes or adding a model, or in terms of the physical environment, such as providing objects for play, different foods or new locations. Controlled observations can be done in either the participants' normal environment or in an artificial situation such as a laboratory. ### Key Words - **Naturalistic observation**: a study conducted by watching the participants' behaviour in their normal environment without interference from the researchers in either the social or physical environment. - **Controlled observation**: a study conducted by watching the participants' behaviour in a situation in which the social or physical environment has been manipulated by the researchers. ## 1.5 Correlations A correlational analysis is a technique used to investigate a link between two co-variables (measured variables). Correlations are useful when it is possible only to measure variables, rather than manipulate them, i.e. when an experiment cannot be conducted. This may be because changing the variables would not be practical or would be unethical. For example, it would not be practical or ethical to conduct an experiment which controlled children's long-term exposure to television and it would not be ethical to increase real-life exposure to violent television programmes. Both of these could, however, be investigated using correlations. Real-life exposure of a group of children to violent television could be measured and correlated with another measured variable, such as how aggressive their behaviour was in school. ### Key Words - **Co-variables**: the two measured variables in a correlation. - **Correlation**: a research method that looks for a relationship between two measured variables. A change in one variable is related to a change in the other (although these changes cannot be assumed to be causal). - **Causal relationship**: a link between two variables such that a change in one variable is responsible for (i.e. causes) the change in the other variable, such as in an experiment. To look for a correlation between two variables, each variable must exist over a range, sometimes called 'continuous data', and it must be possible to measure them numerically. Suitable variables would include durations of time, totals of tallies, numbers from a rating scale or test scores. Several techniques can be used to collect data for correlations, such as self-reports, observations and different kinds of tests and tasks. It is important to recognise that any link found between two variables in a correlation cannot be assumed to be a causal relationship, that is, we cannot know whether the change in one variable is responsible for the change in the other variable. This is possible in the case of an experiment, as we can know that there is a causal relationship between the IV and the DV because changes in the IV are shown to be the cause of changes in the DV. However, we cannot say from one correlation that an increase in one variable has caused an increase (or decrease) in the other because it is possible that the changes in both variables could be the result of another factor. Imagine that two variables are being measured: attention in class and score on a test. If these co-variables correlate it would be tempting to say that paying attention in class is responsible for good test results but we cannot be sure of this. It could be that both of these factors depend on a third variable, such how hard-working the individual student is. The sort of student who pays more attention in class might also study much harder for the test. All we can conclude is that the two factors we have measured vary together, not that there is a cause-and-effect or causal relationship between them. As a consequence, it is important that you refer to 'co-variables' or 'measured variables' in a correlation and not independent and dependent variables. To make judgements about causality, an experiment must be used, so that we can be more certain that it is the manipulation of one variable that is responsible for the change in the other. If, on the other hand, we conduct a correlational study and find that there is no link between two variables, then we can conclude that there is no causal relationship. The nature of the relationship between the two variables in a correlation can be described in terms of its direction. In a **positive correlation**, the two variables increase together. The change is in the same direction, so higher scores on one variable correspond with higher scores on the other. For example, in a positive correlation between exposure to aggressive models and violent behaviour, greater exposure to models would be linked to higher levels of violence. When two variables are **negatively correlated**, higher scores on one variable correspond with lower scores on the other. For example, a negative correlation might exist between number of years in education and level of obedience - people with fewer years of education are more obedient. ## 1.6 Longitudinal Studies A longitudinal study is one that follows a single group of participants over time, studying one or more variables at intervals. By measuring variables over weeks, months, years or even decades, a longitudinal study can detect changes in individuals. People change over time, not just as they age but as they accumulate life experiences. In addition, longitudinal studies can explore the effect of specific 'experiences' such as interventions or events on development. The use of longitudinal studies is an alternative to **cross-sectional studies** as a way to look at effects over time. In a cross-sectional study, differences between people of differing ages, or at different stages (such as different periods after an intervention) are explored by comparing different groups at one point in time. For example, to explore changes in mindfulness with age, a cross-sectional study could look at 10-, 20-, 30-, 40- and 50-year-olds. Although a cross-sectional study allows researchers to investigate long-term influences, it is difficult to separate changes over time from differences due to the individuals growing up at different times. For example, if a cross-sectional study looking at helpfulness in people of different ages found a pattern in the results, this could be due to differences in upbringing at the time when they were children or the changing expectations of society rather than their age. Such problems are avoided in a longitudinal study as a single **cohort**, a group of participants all selected at the same age or stage, are chosen and tested at different time points. A cohort might be individuals born in a certain year, people about to embark on a course of treatment, such as a new drug regime or people experiencing a life change, such as at the beginning of a pregnancy. Longitudinal studies may have different intentions or designs. Some studies track patterns of change in variables to investigate them, such as changing emotions or beliefs as we get older. Other studies record longitudinal changes in two or more variables to investigate possible correlations between them, such as exposure to a multicultural society and prejudice. Yet others use an experimental design where one or more variables, measured over an extended period of time, are expected to change as a consequence of a deliberate manipulation. In the last case, the variables being measured are dependent variables and the testing at different time points in relation to the deliberate manipulation is an independent variable. To provide a baseline for tracking long-term change, the variable is usually measured at the outset of the study, and again after one or more periods of time. This procedure can be thought of as a very long-term repeated measures design, so is sometimes referred to as a 'quasi-experimental' design. This procedure can be used, for example, to measure the consequences of interventions such as educational, health, mental health or occupational ones that aim to improve outcomes. One level of the independent variable is the baseline test or 'pre-intervention' time point and one or more repeat testing sessions occur, providing a 'post-intervention' level of the independent variable and possibly more time points during or long after the intervention as a follow-up. ## 1.7 The Definition, Manipulation, Measurement and Control of Variables Variables are factors that change or can be changed. In experiments, these are the independent and dependent variables as well as variables that are or are not controlled. In correlations, there are two measured variables called co-variables. Experiments look for changes or differences in the **dependent variable (DV)** between two or more levels of the **independent variable (IV)**, which are set up by the experimenter. It is important that the IV is **operationalised**, so that the manipulation of the conditions represents the intended differences. At the beginning of this chapter, we discussed the idea of the **aim** of a study, that is, what the researcher is trying to find out. The aim refers to the variables but not necessarily very clearly. **Operational definitions** of variables help to add clarity to the intention expressed in the aim. ## 1.8 Sampling of Participants A **population** is a group of people (or animals) with one or more characteristics in common. For example, the population of a country is all the people who live there, the population of internet users is everyone who can access the internet. A population could also be people who share a particular interest, such as 'all football supporters' or who have a particular feature, for example all left-handed people. The **sample** is the group of people who participate in a study. They are taken from a population and should ideally be representative of that group so that the findings will be generalisable. Details about the sample, such as age, ethnicity and gender are often important in investigations, so are commonly reported in the core studies. This is because these features may have an influence on psychological differences. Other characteristics of the sample, such as socio-economic status, education, employment, geographical location or occupation, may also be relevant. The size of the sample also matters. Small samples are less reliable and are likely to be less representative. This is because a smaller group of people is unlikely to contain all the differences or variations that exist with the populations and some of those will be important to any study. The different sampling techniques described next produce samples that differ in terms of how well they represent the population. The extent to which they are representative of the population determines how effectively generalisations can be made. ### Key Words - **Population**: the group, sharing one or more characteristics, from which a sample is drawn. - **Sample**: the group of people selected to represent the population in a study. - **Sampling technique**: the method used to obtain the participants for a study from the population. - **Opportunity sample**: participants are chosen because they are available, for example university students are selected because they are present at the university where the research is taking place. ## 1.9 Data and Data Analysis Psychologists, like all scientists, often produce numerical results from their investigations. These results are called the 'raw data'. As it is difficult to gain an understanding from large amounts of figures, the results are often simplified mathematically so they can be represented visually on graphs. This makes the meaning of the results easier to interpret. We will discuss a range of analytical techniques in this section. It is important that you are confident that you can count up scores, find the mode or the range of a data set, make simple comparisons and interpret data from tables or graphs. ### Types of Data As you may know from the core studies or from earlier parts of this chapter, psychologists use a variety of different research methods. These methods can produce a range of different types of data. The main types are quantitative and qualitative data. When psychologists collect data, they can collect either numerical results, called **quantitative data**, or they can collect **qualitative data**, which is detailed and descriptive. ### Key Words - **Quantitative data**: numerical results about the amount or quantity of a psychological measure, such as pulse rate or a score on an intelligence test. - **Qualitative data**: descriptive, in-depth results indicating the quality of a psychological characteristic, such as responses to open questions in self-reports or case studies and detailed observations. #### Quantitative Data Quantitative data indicates the quantity of a psychological measure, such as a total or frequency. Many psychological variables are measured as the strength of a response and tend to be measured on scales, such as time or ratings. Alternatively, quantitative data can be a numerical score on a test such as for IQ or personality. Quantitative data is associated with experiments and correlations which use numerical scales but it is also possible to obtain quantitative data from observations, questionnaires or interviews. For example, a record of the number of times a behaviour is seen or the total number of different responses to a closed question in an interview would be quantitative data. The sources of quantitative data are typically highly objective, as the scales or questions used need little if any interpretation making them high in validity. In addition, the sources are highly reliable, as the measures are fixed quantities. #### Qualitative Data Qualitative data indicates the quality of a psychological characteristic. Such data is more in-depth than quantitative data and includes detailed observer accounts and responses to open questions in questionnaires, interviews or case studies. Although there is a risk of subjectivity in the interpretation of such data by the researcher, qualitative data may be more representative as the participant can express themselves fully, so in some senses qualitative data can also be valid. ## 1.10 Ethical Considerations As you will see from the discussion of the core studies, psychologists need to consider ethical issues when they conduct research. It is important that they take steps to make sure that their research follows ethical guidelines. In this section, we will look at some of these ethical issues and consider the ethical guidelines that help psychologists to deal with these issues effectively. ### Ethical Issues As you will have seen from examples of psychological research, investigations using humans or animals have the potential to cause concerns about the welfare of the participants. Such concerns are called **ethical issues**. Problems may arise through the nature of the study, such as the potential for psychological discomfort caused by a study about stress, or from aspects of the procedure, such as the need to hide the real aim of the study. Ethical issues may also arise from the implications of the research, for example the possibility for results having a negative impact on part of society. ### Key Word - **Ethical issues**: problems in research that raise concerns about the welfare of participants (or have the potential for a wider negative impact on society). To help psychologists to cope with potential ethical issues that could arise in their research, many countries have an organisation that produces a code of conduct. In addition, research that is being conducted at university is likely to require approval from the institution's ethical committee. An ethical code provides advice, for example as a set of ethical guidelines, that helps psychologists to work in a way that satisfies the primary concern of the welfare of individuals involved in the research as well as the perception of psychology in society. Participants who are deceived or distressed may not want to participate again, may view psychology badly and pass this message on to others, and are less likely to trust the findings of psychological research. These are all outcomes that should be avoided. ### Key Word - **Ethical guidelines**: pieces of advice that guide psychologists to consider the welfare of participants and wider society. ### Ethical Guidelines Relating to Human Participants The discussion that follows is based on the British Psychological Society Code of Ethics and Conduct (2018), although there are many other similar ethical codes in use throughout the world. All of these guidelines help to contribute to the objective of minimising harm and maximising benefit, which is one of the key principles of the Code of Ethics and Conduct. #### Protection From Harm Sometimes research carries risks for participants. Although this should be minimised in the planning of the study, some level of risk may be inevitable. A study may have the potential to cause participants psychological harm (e.g. embarrassment, self-doubt or stress) or physical harm (e.g. engaging in risky behaviours or receiving injections). Participants in such studies have the right to be protected and should not be exposed to any greater risk than they would be in their normal life. Care should be taken to eliminate such risks (e.g. by screening participants), experienced researchers should be used and studies should be stopped if unexpected risks arise. #### Valid Consent Sometimes it is important in experiments to hide the aims from participants to reduce demand characteristics. However, participants have the right to know what will happen in a study so they can give their informed consent. The researcher's need to hide the aim makes it hard to get genuine consent. Ideally, valid consent should be obtained from participants before the study starts. To do this, the researcher must get agreement or permission from potential participants by giving them sufficient information about the procedure for them to decide whether they want to participate, so that their decision is informed. This is often possible without needing to misinform i.e. lie to or otherwise mislead participants. Participants can be told what will happen to them in the study and any possible risks so that they can consent to the procedure without the researchers telling them the full aim. This can satisfy to needs of ethical requirements without leading to demand characteristics causing a change in the participants' behaviour. For consent to be valid it must not only be informed but must also be freely given by a competent individual. The researcher must be sure that the participant understands what is being asked of them and feels that they have a choice about participating. This may be difficult for some groups of potential participants, such as people with mental health problems, learning difficulties or a low level of literacy, people who are working in an additional language or have amnesia, and for children. Furthermore, researchers should ensure that participants do not feel pressured to participate, such as prisoners may under some circumstances, or if the process of recruitment of participants is inappropriately persuasive. When working with child participants, it may be difficult to obtain valid consent in the same way as with adults. It is therefore important to ask their parents or guardians for consent, but also the children themselves where possible. In this case, consent should be requested in a 'child friendly' way that is suitable for the level of understanding the child has. In some situations, it is not even possible to ask for consent. This is often the case in naturalistic observations and field experiments. In such situations, a researcher may ask a group of people similar to those who will become participants whether they would find the study acceptable if they were involved. This is called **presumptive consent** because it allows the researcher to presume that the actual participants would also have agreed to participate if asked. Especially when participants have not been fully informed, it is important to **debrief** them at the end of the study. ### Key Words - **Presumptive consent**: this can be obtained when informed consent cannot be obtained from actual participants. A similar group of people to the anticipated sample are given full details of the proposed study and asked if they would find the study acceptable or not. If they would be happy to be involved, the study can continue. - **Debriefing**: giving participants a full explanation of the aims and potential consequences of the study at the end of a study so that they leave in at least as positive a condition as they arrived. #### Right to Withdraw Participants should be able to leave a study whenever they wish. This is their right to withdraw and it must be made clear to participants at the start of the study. Although participants can be offered incentives to join a study, these cannot be taken away if they leave. This prevents participants thinking that they have to continue. Researchers should not use their position of authority to encourage participants to remain in a study if they want to stop. So in practice, participants may need to be reminded of this right and researchers should follow this guideline even if data will be lost. #### Lack of Deception Participants should not be deliberately misinformed, i.e. deception should be avoided. When it is essential to deceive participants, e.g. to avoid the effects of demand characteristics, they should be told the real aim as soon as possible and be allowed to remove their results if they want to. When participants have been deceived and they know they have been in a study, a debrief should follow (see later section on debriefing). #### Confidentiality All data should be stored separately from the participants' names and personal information held, and names should never be published unless the individuals have specifically agreed to this. Such information should be stored securely and should not be shared with anyone outside the study. These measures ensure confidentiality. The identity of participants should be protected by destroying personal information. However, where it is needed to re-contact participants or to pair up an individual's scores in each condition in a repeated measures design, each participant can be allocated a number that can be used to identify them. When conducting a case study or field experiment with institutions, confidentiality is still important and identities must be hidden. For example, the names of schools or hospitals should be concealed. One common way to anonymise individuals is to use their initials. However, where an individual is well known, this may not be sufficient to conceal their identity. For example, one participant in the study about sleep and dreams by William Dement and Nathanial Kleitman had the initials WD. #### Privacy Observations, self-reports that ask personal questions, and any study that uses personal information all risk invading privacy. This means that the researcher may enter physical space or emotional territory that the individual would want to keep to themselves. In a questionnaire, interview or case study, participants should be aware of their right to ignore questions they do not want to answer. When completing a questionnaire in a laboratory situation, participants should be given an individual space. In observations, people should only be watched in situations where they would expect to be on public display, see Figure 1.20. #### Debriefing All participants who are aware that they have been in a study should be thanked and given the chance to ask questions. Debriefing participants provides them with an explanation at the end of the study that explains fully the aims of the study and ensures that they do not want to withdraw their data. If participants have been negatively affected by a study the researcher must return them to their previous condition. However, debriefing is not an alternative to designing an ethical study, so it is important to consider all the ways in which a study could cause distress and to minimise them. ### Ethical Guidelines Relatiing to the Use of Animals Animals are used in psychological research for a number of different reasons. Driscoll and Bateson (1988) suggested animals may be: - convenient models (e.g. for processes such as learning), - a way to carry out procedures that could not be done ethically on humans (e.g. isolation or brain surgery) - be good or interesting examples in their own right (e.g. communication in birds, bats or whales). As a consequence, much psychological research is conducted on animals and therefore their welfare needs protecting. The discussion that follows is based on the British Psychological Society Guidelines for Psychologists Working with Animals (2020), although there are many other similar ethical codes in use throughout the world. Animals are also often protected by law. These guidelines encompass appropriate legal requirements and specifically consider the effects of psychological research in which animals may be confined, harmed, stressed or in pain, so suffering should be minimised. Veterinary advice should be sought in any case of doubt. Researchers must aim to ensure that in any research, the means justify the ends, i.e. that the animal suffering caused by the planned experiment is outweighed by the benefits. One way to consider this question is to use Bateson's (1986) cube (see Figure 1.21). When the certainty of benefit (e.g. to humans) is high, the research is good and the suffering is low, the research can be argued to be worthwhile. The following guidelines help to contribute to the objective of minimising harm and maximising benefit. #### Replacement Researchers should consider replacing animal experiments with alternatives, such as videos from previous studies or computer simulations. #### Species The chosen species should be the one least likely to suffer pain or distress. Other relevant factors include whether the animals were bred in captivity, their previous experience of experimentation and the sentience of the species (its ability to think and feel). #### Number of Animals Only the minimum number of animals needed to produce valid and reliable results should be used. To minimise the number, pilot studies, reliable measures of the dependent variable, good experimental design and appropriate data analysis should all be used. #### Procedures Research on animals is controlled by legal requirements and/or guidelines from relevant organisations because studies will, necessarily, affect the animals in some way. However, for research on animals to be effective the animals' experience should, as far as possible within the constraints of the research being conducted, be a normal and positive one. There are therefore guidelines to help psychologists to care for their research animals well. #### Pain, Suffering and Distress Research causing death, or suffering, such as disease, pain, injury, physiological or psychological distress and discomfort should be avoided. Where possible, designs which improve rather than worsen the animals' experience should be used (e.g. studying the effect of early enrichment on development compared to normal rather than early deprivation). Alternatively, naturally occurring instances may be used (e.g. where stress arises naturally in the animal's environment or lifetime). During research, attention should be paid to the animals' daily care and veterinary needs and any costs to the animals should be justified by the scientific benefit of the work (see Bateson's cube). #### Housing Isolation and crowding can cause animals distress. Caging conditions should depend on the social behaviour of the species (e.g. isolation will be more distressing for social animals than solitary ones). Overcrowding can cause distress and aggression (therefore also physical harm). The level of stress experienced by individuals should also be considered (e.g. the animal's age and gender). Between testing, animals should be housed with enough space to move freely and with sufficient food and water for their health and well-being, both in terms of their biological and ecological needs. However, the artificial environment only needs to recreate the aspects of the natural environment that are important to welfare and survival, e.g. warmth, space for exercise or somewhere to hide. Environments that are 'visually appealing' to people may not be those that are best for an individual species. Cage cleaning should balance cleanliness against avoiding stress, e.g. caused by unfamiliar smells or disturbance by humans. #### Reward, Deprivation and Aversive Stimuli Deprivation is the removal of resources that are important to an animal. In planning studies using deprivation the normal feeding or drinking patterns of the animals should be considered so that their needs can be satisfied (e.g. carnivores eat less frequently than herbivores, young animals need greater access to food and water). The use of preferred food should be considered as an alternative to deprivation (e.g. for rewards in learning studies) and alternatives to aversive (unpleasant) stimuli and deprivation should be used where possible. ## 1.11 Evaluating Research: Methodological Issues As well as evaluating research in terms of ethics, it can also be considered in terms of whether it is 'good science', i.e. by looking at methodological issues. There are several key methodological issues that you have encountered elsewhere in the chapter, such as reliability, validity and generalisability. ### Reliability Whenever research is conducted data is obtained, researchers must attempt to ensure that the way in which these results are collected is the same each time, otherwise differences could occur (between participants, between conditions in an experiment or between the data obtained by different researchers). Such inconsistencies would be problems of reliability. The reliability of the measures used to collect data depends on the 'tool' used. A researcher collecting reaction times or pulse rates as data will probably have reliability as the machines used are likely to produce very consistent measures of time or rates. One way to check reliability is to use the **test-retest procedure**. This involves using a measure once, and then using it again in the same situation. If the reliability is high, the same results will be obtained on both occasions, i.e. there will be a high correlation between the two sets of scores. Imagine an experiment on emotions in which a researcher is not sure whether their questionnaire is a reliable measure of 'happiness'. They use a group of participants and give them the questionnaire on two separate occasions. All the participants would need to be tested at the same time of day and the same day of the week to ensure that their happiness levels were indeed the same. If the 'happiness scale' was reliable, this test retest procedure would produce a high correlation