2. http://columsblog.wordpress.com/2012/03/25/making-the-case-for-more-field-experiments/#comment-76
3. http://ellislee15.wordpress.com/2012/03/21/can-we-trust-an-eyewitness-testimony/#comment-73
4. http://robinson8040.wordpress.com/2012/03/24/culture-context-of-definitions-and-research/#comment-42
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There are many different research designs that a researcher can choose from when planning their experiment. One of the most commonly used research design is the laboratory experiment. This week I am going to be exploring this type of experiment and underlining why I believe the weaknesses of laboratory experiments outweigh the strengths.
A laboratory experiment is conducted under highly controlled conditions. Participants are brought to a lab setting to be tested. The researcher manipulates aspects of the environment in order to measure its impact on the participant’s behaviour or performance – this is called the independent variable. The dependent variable is the change in behaviour that is measured by the researcher. The dependent variable is believed to be under the control of the independent variable. All other variables are controlled as far as possible. This way, conclusions of cause and effect can be made since only the independent variable is controlled so it is assumed that this is what causes the behaviour change.
One clear example of a laboratory study was conducted by Liebert and Baron (1972)*, who were investigating aggression in children. The participants in this study consisted of 5 – 9 year old children. The children were split into two groups; the first group watched a violent video clip that contained fighting, shooting and stabbing, whereas the second group watched a nonviolent, exciting video clip. Making the independent variable the type of program watched. The children were then taken to another room, in which there was two buttons. The children were told that another child in the next room was completing a handle-turning game, and that if they pressed the ‘HELP’ button, the handle would become easier to turn for the other child, but if they pressed the ‘HURT’ button the handle would become very hot and hurt the child. The amount of times each button was pressed was measured by the researcher as aggression – this was the dependent variable in the study. It was found that both boys and girls were more likely to press the ‘HURT’ button if they had watched the violent video.
Although laboratory experiments are thought to have high levels of control, it is very difficult to control every single different variable that may be having an effect on the results. Confounding variables are factors (other than the independent variable) that could cause changes in participants’ performance on the dependent variable if not properly controlled by the experimenter. For example, in the study conducted by Liebert and Baron, the children who watched the violent video clip and pressed the ‘HURT’ button more frequently may have been naturally more aggressive than the other participants. So, the children’s pre-existing levels of aggression may have been acting as a confounding variable, and the independent variable may have had no effect. Although people can argue that laboratory experiments can display cause and effect due to their high levels of control, it is next to impossible to completely control every variable. There may be other variables having an impact that the researcher is unaware of, which is why I believe that the results from laboratory experiments cannot always be fully trusted.
This high level of control leads to experiment settings that are very unnatural, and participants are often asked to complete very strange and bizarre tasks. Therefore, individuals are more than likely going to behave very differently in laboratory experiment situations than they would in real and natural settings. Consequently, laboratory experiments lack ecological validity and mundane realism, as they are not true to real life. For example, in the study conducted by Loftus and Palmer (1974)** into the eyewitness testimony, participants watched a video clip of a car crash and then asked to estimate the speed of the travelling car. This study was obviously conducted in an artificial setting. Watching a video of a car crash would not create the same emotional impact as seeing a car crash in real life. This lack of ecological validity that surrounds laboratory experiments also makes it very difficult to generalise finding from experiments to real life situations.
Although it is believed that laboratory studies should have high internal validity, this can be greatly reduced by demand characteristics. Demand characteristics are cues that may allow participants to guess the aim of the experiment. If a participant is aware of certain aspects of the experiments they may try to behave in a way that they think they are expected to behave. For example, whilst on their way to participate in Bandura’s bobo doll study, a four-year-old whispered to her mother: ‘Look mummy, there’s the doll we have to hit’ (Noble, 1975)*** (hitting the doll was one of the dependent variables being measured in this study). This is a clear example of a participant displaying demand characteristics. So, again, the realism of laboratory studies is reduced by demand characteristics.
One further problem of laboratory experiments concerns ethics. There must always be some form of deception involved in such experiments. If the participants knew every aspect of the study, then it would be pointless to carry it out. In order to produce valid results, participants must be deceived to some extent. However, there are guidelines that must be followed regarding ethics, making it difficult for researchers to produce ethical research.
All of these points lead me to believe that laboratory experiments are more trouble than they are worth. The only positive aspect is that they are highly controlled, therefore cause and effect can be established. However, it is next to impossible to control ever variable within an experiment, therefore confounding variable may be causing the behaviour change instead of the independent variable. Furthermore, this high control can lead to experiments lacking ecological validity, which leads to problems with generalising the results. Demand characteristics may cause participants to behave in an unusual way in order to please the experimenter, again causing a reduction in the validity of the results. Finally, ethical issues of deception may get in the way of researchers creating efficient experiments. Overall, I believe laboratory experiments to be very unnatural and they produce distorted views of how individuals behave in certain situations. Due to the many weaknesses surrounding laboratory experiments, I conclude that results from such experiments cannot be trusted.
* Liebert, R. M., & Baron, R. A. (1972). Some immediate effects of televised violence on children’s behaviour. Developmental Psychology, 6, 469 – 475.
** http://www.sciencedirect.com/science/article/pii/S0022537174800113
*** Noble, G. (1975). Children in front of the small screen. London: Constable.
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1. http://statsbloggy.wordpress.com/2012/03/11/can-correlation-show-causality/#comment-30
3. http://psucfb.wordpress.com/2012/03/11/animal-research/#comment-72
4. http://laf1993.wordpress.com/2012/03/11/longitudinal-v-cross-sectional/#comment-40
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Developmental research designs are a type of nonexperimental research that can be used in order to study age related changes in behaviour. One principal type of developmental research design is the longitudinal design, in which one group of subjects are studied repeatedly over a period of time. This week I am going to be describing this form of longitudinal design and outlining its strengths and weaknesses.
Within a longitudinal developmental research design, the same participants are observed recurrently over a period of time. This period of time may be quite brief (six months to a year), or very long – sometimes even spanning a lifetime! The researcher may be studying one specific aspect of development (for example, intelligence) or many. The subjects being studied are usually cohort, which means they are roughly the same age and have grown up in similar circumstances. The Longitudinal research design is an example of within-subjects design. However, no treatment is administrated, instead the ‘treatment’ is the age. Longitudinal studies are often described as a number of observations followed by a period of aging and development then another set of observations.
One example of a longitudinal developmental study is that of Howes and Matheson (1992)1, in which the pretend play of a group of 1-to-2 year old children were repeatedly observed every 6 months over a period of 3 years. Howes and Matheson found that complexity of pretend play increases with age and is also a reliable predictor of children’s future social competence with peers.
There are several strengths and weaknesses associated with the longitudinal developmental research design. Firstly, main advantage of the design is that it allows researchers to assess the stability and continuity of several attributes of a sample by repeatedly observing the same participants (Kagan & Moss, 1962)2. Additionally, this type of design also allows researchers to identify developmental trends by looking for common attributes that the subjects share, for example, points at which most children undergo changes (Newman et al, 1997) 3. Another major strength of the longitudinal design is that it avoids cohort effects because the researcher examines one group of people over time, rather than comparing several different groups that represent different ages and generations. Longitudinal research designs also allow researchers to discuss how a single individual’s behaviour changes with age. Finally, this type of design combines both qualitative and quantitative data, creating more in-depth research (Ruspini 1999) 4.
Although so far I have portrayed the longitudinal research design in a positive and beneficial manner, it is important to recognize its limitations and the disadvantages associated with using this form of research design. Firstly, longitudinal research is very time consuming, for everyone involved. The participants must be highly committed in order to continue and complete the duration of the study, and the researcher must remain interested in the research whilst they wait for years to see the final results. As well as being time consuming, this form of research is also very expensive to conduct, since the researchers must track people down and persuade them to come back and participate in the study. Additionally, there is added expense of repeatedly training experimenters to conduct the study if it is going to span over many years. Also, focus of the theory and research into the developmental sciences is constantly changing, thus longitudinal studies may seem new and exciting to start with, but by the end of a 10 or 20 year project the outcome may seem trivial.
Further disadvantages can be identified when assessing the validity of the longitudinal research design. Practice effects may threaten the validity of a study: participants who are repeatedly tested and interviewed may become increasingly familiar with contents. As a result, they may display performance improvements that are unrelated to the normal patterns of development. Furthermore, the longitudinal research design is subject to high drop out rates of participants, which may also weaken the internal validity of such studies. A study conducted by Colby et al. (1983)5 is one example of a longitudinal study to suffer participant attrition: participants were interviewed at intervals of 3 to 4 years over a 20 year period and the sample size decreased from 84 participants to only 51. Since longitudinal studies may go on for a number of years, participants may lose interest in the study, move away or die. When participants drop out of a study, it is known as participant attrition, which can result in smaller and non-representative samples. The participants who drop out may have different attributes as those who stay, consequently, the group at the end of the study may have completely different characteristics as the initial group at the beginning. For example, if the less-motivated participants drop out during a study, the group of participants at the end will be more motivated than the group at the start and this higher level of motivation may explain the changes made over time, rather than the age.
One final limitation of the longitudinal developmental research design is the cross-generational problem. As I mentioned earlier, children in a longitudinal study are usually drawn from one cohort, therefore they are likely to have very different experiences than children from other eras. For example, consider how much change there has been since the 1940s and 1950s, when children in some of the early longitudinal studies were growing up. Family dynamics have changed drastically since then, and modern families are a lot smaller now, move houses more frequently and often use day-care centers and nurseries. Children now have access to computers, video games, and televisions, which were not available in the 1940s and 1950s. Children of earlier eras grew up in a completely different world, so it cannot be certain that children today develop in exactly the same way. As a result, these cross-generational changes may limit the conclusions of the longitudinal studies to only the participants growing up whilst the study was in progress.
In conclusion, in the longitudinal developmental research design, the same group of participants are observed and measured at different intervals over a period of time, thus cohort effects are not a problem. Stability, continuity and normative trends can easily be identified and quantitative methods are combined with qualitative methods. However, I believe the weaknesses of this type of research design outweigh the strengths. Longitudinal studies are very time consuming for both researchers and participants, as well as being extremely expensive. The validity of such studies can be questioned due to practice effects, and participant attrition may create biased and non-representative samples. Finally, cross-generational problems can make it difficult to generalize finding from studies between different eras. In all, researchers must take into account the many disadvantages of using this type of research design before undertaking a study. However, these disadvantages may be overcome by using a very similar research design called the sequential design, which combines the best features of longitudinal research. I will discuss this design further next time.
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3. http://robinson8040.wordpress.com/2012/02/19/apa-format-necessary/#comment-24
4. http://roisin07m.wordpress.com/2012/02/04/week-2-can-correlation-show-causality/#comment-40
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Research studies are distinct events that involve a particular group of participants. However, researchers usually intend on answering a general question about a larger population of individuals rather than a small select group. Therefore, the main aim of psychological research is to be able to make valid generalisations and extend their results beyond those who participate. For this reason, the selection of participants is a very crucial issue when planning research. Obviously, researchers cannot collect data from every single individual from their population of interest, since this would be extremely expensive and take a very long time! So instead they use a small group of individuals – called a sample. The sample is chosen from the population and is used to represent the population. Researchers use sampling techniques to select the participants for their sample – these techniques help to minimise cost whilst maximising generalisability. So, in this weeks blog I am going to be discussing the different sampling techniques and methods, and considering the issue of sampling bias and the problems associated in research.
There are a variety of different sampling methods available to researchers to select individuals for a study. Sampling method fall into two categories:
Simple random is an example of probability sampling. This is when a list containing all of the population is created and used to obtain participants by random selection. This random selection guarantees that each individual has an independent and equal chance of being selected. This method is very fair, unbiased and easy to carry out. However, with simple random sampling there is no assurance of complete representativeness of the sample. Another example of simple random sampling is cluster sampling. This is when the sample is gained by the random selection of clusters (pre-existing groups of individuals) from a list containing all of the clusters existing within a population. Cluster sampling is often used to estimate number of mortalities in events such as war and natural disaster¹. This method is easy for obtaining a large and relatively random selection of participants, however, the selections lack independence.
Convenience sampling is a method of nonprobability sampling. With convenience sampling, the sample is made up of individual participants who are easy to get. For example, Milgram (1963) used convenience sampling in his famous study ². The participants were individuals who had volunteered by responding to a newspaper article. Convenience sampling is easy to carry out, but one large disadvantage is that the sample is likely to be biased. Milgram’s participants were all male – which could be agued to be a biased sample. Finally, quota sampling is another method of nonprobability sampling. This is when different subgroups are identified and participants are selected through convenience from each different subgroup. For example, say a researcher wanted to select a sample of students to participate in a study using a convenience sample but wanted to ensure that an equal number of boys and girls were selected – quota sampling would be the best method for them to use. This type of sampling can help to control a convenience sample but may results in a biased sample, which would not be a good representative of the wider population.
As I mentioned earlier, the goal of research is to study a sample of participants and then generalise the results to the larger population. How far we can extend such results to generalise to a population is dependant on how closely the sample resembles the population – the representativeness. The main threat to representativeness is bias. A biased sample is one which contains characteristics that are different from those of the population. This bias may happen by chance, but usually is down to selection bias. Selection bias is when participants are selected in a way that increases the probability of acquiring a biased sample. For example, if a researcher recruits participants from a gym, they are more likely to be healthier and fitter than the rest of the general public.
I can definitely say that the selection of participants is a very vital part of planning research. Without carefully planning and choosing an appropriate method for sampling it is very easy to obtain a biased sample that does not represent the population. When this happens, it is difficult to extend findings to a wider population and the validity of the experiment decreases. In order to produce influential and meaningful results, researchers must ensure that they have chosen an appropriate sampling method to select a representative sample of participants.
¹. David Brown, Study Claims Iraq’s ‘Excess’ Death Toll Has Reached 655,000, Washington Post, Wednesday, October 11, 2006
². Milgram, S. (1963). Behavioral study of obedience. Journal of Abnormal and Social Psychology, 72, 207-217.
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1. http://kennedy92.wordpress.com/2012/02/02/ethics-and-milgram/#comment-28
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This is an excellent topic for debate! When researchers generalise their findings from the participants they used to a whole population, false information could be portrayed. However, without being able to generalise findings, carrying out studies on large populations would be extremely difficult and expensive. I also saw those statistics regarding train satisfaction on a billboard inside the train station last week and as you did, I questioned it in my head too. I regularly use trains in and out of Bangor and have never had an opportunity to give my own feedback!
Psychologists often generalise their findings to larger populations. For example, can we generalise that every person in a prison situation would begin to develop learned helplessness and begin to dehumanise others within a few days because of the results from Zimbardo’s Stanford Prison Experiment? Zimbardo only used male college student participants, so can we really generalise this to the whole population, especially females¹?
Another major problem when generalising results from psychological experiments is the generalisation from non-human animals to humans. Although animals and humans do share similar physiology and evolutionary past, they are not completely identical. For example, morphine calms humans but causes excitement in mice and cats – highlighting physiological difference between the two². Researchers need to be very careful when making generalisations such as these.
¹. Haney, C., Banks, W. C., & Zimbardo, P. G. (1973). Study of prisoners and guards in a simulated prison. Naval Research Reviews, 9, 1–17. Washington, DC: Office of Naval Research.
².http://www.petertatchell.net/animal_rights/animalresearchisbadscience.htm
3. http://serenapsychology.wordpress.com/2012/02/05/62/#comment-47
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Within my last blog post I considered the ethical issues surrounding human participants, and although the majority of psychological research involves the study of humans, non-human animals are also used from time to time. The use of animals within research can sometimes be a sensitive subject and raise many ethical issues. Some people believe that such research should not be conducted at all, however, non-human subjects have been used in the research of behavioural sciences for over 100 years. This week I am going to be discussing the need for animals within research, the pros and cons, and the associated ethical issues.
There are a number of reasons why psychologists choose to carry out their research using non-human animals:
As you know, there are many ethical guidelines that researchers must adhere to in order to be granted permission to undertake experiments with human participants. This is also the case when animal subjects are being used. As well as creating a set of guidelines for the use of animal subjects that is parallel to their guidelines for human participants, the APA also have a specific committee set up called the Committee on Animal Research and Ethics (CARE) to deal with animal use in detail³. Besides ethical guidelines, there is also UK legislation that helps with the monitoring of animal research. The Animals (Scientific Procedures) Act (1986) states that such research can only take place in licensed laboratories. A license may only be granted to researchers if:
Using animals in psychological experiments is certainly a controversial and debatable subject. Many people, such as Peter Singer – a famous philosopher, adopt a utilitarian view. This view is that whatever produces the greater good for the greater number is ethically acceptable and thus, if research using non-human animals can reduce suffering and pain then it is justifiable. In contrast, others believe that animals should never be used in research under any circumstances. The philosopher Tom Regan (1984) believes that animals should never be used in research since they have the right to be treated with respect ⁴. However, this issue of ‘animal rights’ may not be accepted because having rights is dependant on having responsibilities within society, which animals do not have.
Russell and Birch (1959) proposed the 3 Rs in order to improve the conditions of animal research⁵. These 3 Rs include:
Therefore, in conclusion, I do believe animal research can be acceptable in certain situations. If the fewest number of animals are used in professional ways, with little stress or pain caused then I think animal studies are tolerable as long as the potential findings are justifiable. Nevertheless, British law requires that any form of new drug must be tested on at least two different species of living animal. However, there is also the question of how generalizable such results are from animals to humans?
¹. Skinner, B. F. (1947). Superstition in the pigeon. Journal of Experimental Psychology, 38, 168-72.
².Harlow, H.F (1959). Love in infant monkeys. Scientific American, 200(6), 68-74.
³. http://www.apa.org/science/leadership/care/guidelines.aspx
⁴. Regan, T. (1984). The case for animal rights. New York: Routledge.
⁵. Russell, W. M. S. and Birch, R. (1959). The principles of humane experimental teachnique. London: Methuen.
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1. http://hls92.wordpress.com/2011/12/05/why-is-reliability-important/#comment-45
3. http://smmitch.wordpress.com/2011/12/07/ethics-and-children/#comment-47
4. http://prpj.wordpress.com/2011/10/28/why-is-reliability-important/#comment-20
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Okay, this week I am going to be delving into the depths of ethics, especially those concerning psychological research. Being psychology students, we have all stumbled upon the topic of ethics, whether it being within our research skills lectures or whilst conducting our own research project. In a nutshell, ethics can be described as the study of proper action (Ray, 2000)¹. Most professionals have a duty to behave with a proper regard to the rights of others. For us psychologists, this encompasses the treatment of patients as well as the responsibilities surrounding our research participants. Researchers must act in an honest way and respect all individuals affected by their studies. So, I am going to discuss a bit of history behind ethics, describe a few principal guidelines and finally, highlight the importance of ethical guidelines within psychological research.
Before World War II, researchers conducted studies with human participants according to their own established ethical standards. It was assumed at the time, that researchers would use their own morality to avoid harm to their participants. However, as you can probably imagine, not all researchers had such high morals and as a consequence many participants did get hurt. For example, numerous disgusting and callous experiments were conducted in nazi concentration camps on unwilling participants. When atrocities such as these were uncovered, many of those responsible for the crimes were tried at Nuremberg in 1947. From these trials, the Nuremberg Code was developed. It was the first ever ethical code of practise and consisted of 10 guidelines for ethical treatment of human participants (Katz, 1972)². In spite of these guidelines, some researchers still continued to conduct unethical studies. In 1972, the Tuskegee study took place. During this study nearly 400 men were left to suffer with syphilis even though a cure was available – the researchers wanted to examine the final stages of the disease (Jones, 1981)³. This was clearly breaching the safety of participants, and indicated a need for stricter guidelines. Thus, today professional organisations such as the BPS and APA provide guidance for psychologists on how to deal with human participants in psychological research. Such guideline are continuously reviewed and revised in order to keep up to date with changing viewpoints and new moral dilemmas.
The most current BPS code of ethics and conduct (2006) includes four ethical principles and advise on how they should be dealt with. These four principles include:
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Research Methods and Statistics 