research method - psych
Formulation of Testable Hypotheses
A hypothesis is a formal, testable statement about the relationship between two variables.
Used in psychology and other sciences as part of the scientific method.
Not a prediction in the future tense.
Researcher decides if evidence supports the hypothesis at the end of the study.
Types of hypotheses:
Directional
Non-directiona
Null
Alternative
Null Hypothesis
States that observed variables will have no impact and there is no relationship between them.
Assumes any observed difference is due to sampling or experimentation errors.
Example: "watching television before bed has no impact on how well you sleep”
Alternative Hypothesis
Predicts that one variable will affect the other.
The alternative hypothesis does not specify the direction of the outcome, merely that there will be an effect.
Example: "watching scary movies before bed affects how fast you fall asleep”.
Formulating Hypotheses
Experiments often stem from a vague idea.
Variables need to be operationalized.
Independent Variable (IV)
Dependent Variable (DV)
A suitable alternative hypothesis example: “The presence or absence of music has an effect on the score in a learning test”.
A null hypothesis example: “The presence of music has no effect on the score in a learning test”
Types of Variables
Independent variable (IV)
Dependent variable (DV)
Extraneous variables
Independent Variable (IV)
The variable that researchers manipulate to test its effect on the dependent variable.
Example: In an experiment to see if music affects learning, the IV is music.
Two conditions: one group exposed to music, the other not.
Dependent Variable (DV)
The outcome or effect being measured.
Example: How well students learn with or without music - measured via memory test or quiz.
The dependent variable "depends" on what's being changed (the independent variable).
“We measure the effect of the IV on the DV”.
Extraneous Variable
A third variable that may unknowingly affect the outcome (DV).
Experiments aim to measure the effect of the IV on the DV, but extraneous variables can cause changes.
They are “nuisance variables” that make it difficult to determine if the IV affects the DV.
Example: Prior knowledge of test questions may affect learning outcomes.
Intelligence of participants can be an extraneous variable.
Identifying extraneous variables is useful in critically analyzing studies.
Sampling Methods
Strategies researchers use to get participants for studies.
Target population: The group of individuals the researcher is interested in.
Representative sample: A sample from the target population that allows the researcher to make generalisations across the whole population, based on the findings of this sample.
Four sampling methods required to know:
Random sampling
Opportunity sampling
Systematic sampling
Stratified sampling
Volunteer Sampling
Random Sampling
Involves identifying members of the target population, numbering them, and then drawing out the required number of people for their study.
Selection of participants can be done in a randomised way such as drawing out numbers from a hat if the sample size is small or having a computer randomly select the participants if the sample size is large.
Strengths of Random Sampling
Unbiased as all members of the target population have an equal chance of being selected for the study.
The sample is likely to be more representative of the target population making more valid generalisations possible from the research findings.
Reduces the impact of investigator effects which means the findings may have more validity.
Weaknesses of Random Sampling
It is still possible for the researcher to end up with an unbalanced and biased sample by chance, particularly if the sample size is too small.
Gathering randomised samples can also be time-consuming, as attempting to gather enough willing participants from the target population takes a considerable amount of time and effort.
Opportunity Sampling
Asks those who are around you and most easily available, that represent the target population, to participate in the study.
This may involve asking those around you in your class, school or people walking in the street for their involvement.
Strengths of Opportunity Sampling
The main benefit of opportunity sampling is it is one of the fastest and easiest ways to gather participants for a study when compared to other sampling methods.
Weaknesses of Opportunity Sampling
Opportunity samples have a greater chance of being biased because the sample is drawn from a very narrow part of the target population.
Participants may also try to “help” the researcher in a way that would support the hypothesis so the results may be unreliable and invalid.
With opportunity sampling methods, it is possible the researcher can influence those selected as the process is not randomised.
Systematic Sampling
Involves selecting every “nth” member of the target population.
An example of this would be if the researcher decided that “n” will be “5”, every 5th person in the target population is selected as a participant.
This is still unbiased as the researcher has no influence as to who is picked and it is technically not a “random sample” either as not everyone gets an equal opportunity to be selected (it is only the person 5 positions away).
Strengths of Systematic Sampling
A strength of the systematic sampling method is that it is a simple way for researchers to gather participants and there is little risk of research bias influencing this.
Therefore the participants gathered should, in theory, be representative and unbiased which should lead to more reliable results.
Weaknesses of Systematic Sampling
A weakness, however, is participants gathered could still be unrepresentative and biased due to chance selection.
Another weakness of systematic sampling is you need a bigger sample size to be able to filter out participants based on the “nth” selection.
Therefore gathering participants for a study based on systematic sampling methods can be very time-consuming.
Stratified Sampling
Most complex of the sampling methods and it is most often used in questionnaires.
Sub-groups (or strata) within the population are identified (e.g. boys and girls or age groups: 10-12 years, 13-15 years etc) and then participants are gathered from each strata in proportion to their occurrence in the population.
The selection of participants is generally done using a random technique.
For example, in a school, there are several subgroups such as teachers, support staff, students and other staff. If the teachers made up 10\% of the whole school’s population, then 10\% of the sample must be teachers.
Strengths of Stratified Sampling
A major strength of using stratified sampling techniques is that they are very representative of the target population.
This means the findings should have high reliability and validity to make generalisations to the target population.
Weaknesses of Stratified Sampling
A major weakness of using stratified sampling is that it is very time-consuming to identify the subgroups, select necessary participants and attempt to get a proportionate sample involved in the study.
Therefore this form of sampling method is extremely difficult to execute and can be impractical.
Volunteer Sampling
A volunteer sample consists of people that have volunteered to take part in the study.
Volunteers can be gathered in a number of ways such as putting an advert out on the newspaper, internet or some media outlet to try and gather people to take part.
Volunteers may put themselves forward to be part of the study but they may not necessarily be told the aim of the study or what they are really being tested in.
For example, Milgram’s shock study gathered volunteers who agreed to take part but did not necessarily know what they were being tested on (obedience).
Strengths of Volunteer Sampling
A strength of using volunteer sampling is participants should be willing to give their informed consent to be a part of the study.
The people that tend to volunteer tend to be those motivated to take part in the study.
Volunteer sampling can also be a fast and efficient way of gathering research participants.
Weaknesses of Volunteer Sampling
A weakness of using volunteer sampling is the people that tend to volunteer may be a biased sample that are not representative of the target population.
For example, volunteers are already motivated to engage in the research (volunteer bias) and more motivated than those that do not and this can influence the outcome of the study in some way.
Designing Research
Topics you need to know for research methods include:
The experimental method including:
Independent group design
Repeated measures design
Matched pairs design
Strengths and weaknesses of each design
Laboratory experiments
Field and natural experiments
Interviews
Questionnaires
Case studies
Observation studies
Strengths and weaknesses of each research method and types of behaviour for which they are suitable.
Independent Group Design
An independent group design is the simplest to understand and conducted with participants involved in the study usually divided into two subgroups.
One group will take part in the experimental condition (with the independent variable introduced), while the other group would not be exposed to this and form the control group for comparison.
Let’s use the example we mentioned earlier with a study that measures the effects of music on learning. In an independent group design, one group of participants would be measured on their ability to learn with music being played while the other group would be tested on their learning ability without music.
The results (dependent variable) are then compared between the two groups to measure the effects.
If the results are significantly different then researchers may conclude that this is because of the independent variable, which in our case would be music affecting learning ability.
Strengths of Independent Group Design
There are no order effects that can invalidate the results, as participants only take part in one of the conditions.
Materials or apparatus can usually be used across both the experimental condition and the control group (minus the independent variable being manipulated or introduced as required).
Participants are less likely to display demand characteristics.
Weaknesses of Independent Group Design
Differences between the experimental condition and control group may be due to participant variables, such as individual differences between the two groups, rather than the independent variable.
You need to gather more participants.
Repeated Measures Design
A repeated measures design sees all the gathered participants of the study being exposed to both conditions of the experiment.
Referring to our music and learning scenario (once again!), we would have a group of 50 participants that would first be exposed to the experimental condition whereby they attempt to learn with music present and then they would attempt to learn without music.
The results would then be compared between the conditions to assess what impact the IV had on the DV.
In experiments where there were numerous different conditions, the same participants would be used across them while exposed to different independent variables.
Strengths of Repeated Measures Design
They require less effort to gather participants as they use the same people across the different experimental conditions.
Participant variables are eliminated.
Weaknesses of Repeated Measures Design
There is a high risk of order effects affecting the validity of findings.
You need to create multiple different tasks or materials between the conditions.
There is a higher risk of demand characteristics when using repeated measure designs.
Matched Pairs Design
Involves gathering participants and testing them prior to them taking part in the study on certain characteristics.
The tests allow them to be matched in pairs with someone who is deemed to have similar qualities as to them which may be relevant to the study.
The pairs may be identified as Pair Aa or Pair Bb etc.
In conducting a matched pairs design research study, one pair will take part in one experimental condition while their matched partner/pair is exposed to another experimental condition.
The results are then compared by the researcher between the conditions and treated as if they were gathered from one individual despite coming from two individuals.
Within psychological research, the most ideal matched pairs participants tend to be identical twins as they account have identical biology (as they are similar) and potentially very similar personality factors too.
Strengths of Matched Pairs Design
Reduce participant variables which can affect the results.
No order effect.
Matched pairs designs can re-use the same materials/apparatus across the pairs as everyone will only be exposed to them once.
Weaknesses of Matched Pairs Design
Matching people on key variables is time-consuming and not always successful.
It is difficult to match people based on personality variables or filter out individual differences for certain. You can generally only match people based on fixed traits such as gender (sex), age, height etc, however, personality factors may be what determine differences in the experiments.
Laboratory Experiments
Laboratory experiments are experiments that are conducted in a controlled setting, usually a research laboratory where participants are aware of being observed and part of a study.
Laboratory experiments tend to have high internal validity because researchers can control all the variables so the main differences between the experimental condition and control group are only the independent variable whose effect is being monitored.
This allows researchers to more confidently assume that any differences between the conditions are due to the independent variable.
Strengths of Laboratory Experiments
Have high validity.
Limits the role of extraneous variables from influencing the results as researchers have complete control of the environment.
Can be checked for reliability as they are easier to replicate.
Weaknesses of Laboratory Experiments
They lack ecological validity.
Participants in laboratory setups may display demand characteristics and adjust their behaviour due to the contrived setup and being aware that they are being observed.
Field Experiments
A field experiment is conducted in a more natural or everyday environment, unlike the laboratory experiment where the behaviour being measured is more likely to occur.
The field experiment can be conducted anywhere in real-world settings with researchers manipulating an independent variable to measure its impact on the dependent variable.
A field experiment can include confederates that participants are unaware of also being involved to test their response in the field setting.
One key difference between a field experiment compared to a laboratory experiment, are participants may not be aware of being observed or studied.
Strengths of Field Experiments
High in ecological validity as the setup and environments are more realistic.
Weaknesses of Field Experiments
They are at higher risk of extraneous variables influencing the behaviour of participants.
They are difficult to replicate.
They raise ethical issues in regards to informed consent.
Natural Experiments
A natural experiment is conducted when ethical or practical reasons to manipulate an independent variable (IV) are not possible. It is therefore said that the IV occurs 'naturally'.
The dependent variable (DV), may however, be tested in a laboratory, for example, the effects of institutionalisation in some form, which may occur naturally due to imprisonment or disruption of attachment through the care system and how it may affect psychological development such as intellect or emotional development.
Another good example of a natural experiment is the study by Charlton et al. (2000) which measured the effects of television. Prior to 1995, the people of St. Helena, a small island in the Atlantic had no access to TV however it's arrival gave the researchers to examine how exposure to western programmes may influence their behaviour.
The IV in this case was the introduction of TV which was not controlled by researchers and something they took advantage of would be practically difficult to control.
The DV was measures of pro or anti-social behaviours that were assessed through the use of questionnaires, observations and psychological tests.
Strengths of Natural Experiments
They are high in ecological validity.
They often produce no demand characteristics as the participants are unaware of the experiment.
Weaknesses of Natural Experiments
The lack of control.
They are difficult to replicate to double check the findings.
Participants are often not aware of being observed or taking part in natural experiments and this raises ethical issues, in particular, informed consent.
Interviews
One way psychologists find out about peoples behaviour is to quite simply ask them through the form of interviews.
Interviews involve a researcher in direct contact with the participant and this could either be face to face or via phone/video call.
The vast majority of interviews involve a questionnaire that the researcher records the responses on at the time of the interview.
There are different forms of interviews used which vary in structure and we will look at specifically structured and unstructured interviews for GCSE psychology.
Structured Interviews
Structured interviews involve all participants being asked the same pre-set questions in the same order.
The researcher is unable to ask additional questions outside of this.
The questions are often closed questions that require a yes or no response, or they can be open questions that simply require the researcher to record the participant’s response.
Open questions can be questions that begin with who, what, where, when, why and how. These force a participant to explain their answers beyond simply saying yes or no.
Strengths of Structured Interviews
Can be replicated far more easily than unstructured interviews as the questions are all pre-set.
This helps in testing the reliability of research findings to check for consistency and validity in the conclusions drawn.
Weaknesses of Structured Interviews
Can be incredibly time consuming and require skilled researchers. People’s responses can also be affected by social desirability bias.
Gather quantitative data but lack qualitative data.
Unstructured Interviews
In unstructured interviews, participants are free to discuss anything freely.
The interviewer may devise new questions as the interview progresses or on the previous answers given, to explore further.
With unstructured interviews, each participant is likely to be asked different sets of questions within the interview.
The questions asked in unstructured interviews may be a mix of open and closed questions.
Strengths of Unstructured Interviews
Provide rich and detailed information however they cannot be replicable and people’s responses cannot be easily compared.
Have the benefit of allowing participants to explain their responses which can help us understand why they think or behave in particular ways which may be more valuable than structured interviews telling us merely how they would behave.
Weaknesses of Unstructured Interviews
Can be more time-consuming as there is no structure or guideline to follow in regards to how many questions are being asked.
They also require more trained interviewers who are able to articulate themselves and the questions they wish to ask, unlike structured interviews which can merely be read from a list and explained more easily.
Questionnaires
Questionnaires are an example of a survey method that are used to collect large amounts of information from a target group that may be spread out across the country.
The researcher must design a set of questions for participants to answer; people taking part in a survey are referred to as “respondents” because their answers or behaviours are in response to the questions presented.
Questionnaires can be conducted face to face, via phone or video call too.
Questionnaires are similar to structured interviews as respondents all answer the same questions, in the same order and they often narrow the possible responses to closed questions (yes or no answers).
Strengths of Questionnaires
Practical ways for researchers to gather large amounts of information very quickly on topics where the responses are best suited for yes or no responses.
Can be replicated very easily as all the questions are pre-set.
Weaknesses of Questionnaires
Problems arise in the use of questionnaires when the questions are unclear or if they suggest or lead respondents into a desirable response.
Another criticism of using questionnaires in research is respondents can only answer yes or no.
Respondents may misunderstand the meaning of questions and therefore answer incorrectly.
Case Studies
A case study is a very detailed study of the life and background of either one person, a small group of people or an institution or an event.
Case studies use information from a range of sources, such as the person concerned, related family members or even friends.
Various techniques may be used such as interviewing people or observing people as they engaged in daily life. Psychologists may also use various tests such as IQ tests, personality tests or some questionnaire to produce psychological data about the target in question.
Researchers may also refer to school or work records for an individual or carry out observations of the individual or groups in question.
The case study is then written up as a description of the target individual or group and interpreted information based on psychological theories.
Case studies tend to be longitudinal and follow the target over a long period of time (often many years).
Strengths of Case Studies
Provide detailed information about individuals (or target group/institution) rather than collecting a score on a metric test from a person.
Collect information over a long period of time so changes in behaviour can be observed and comparisons are drawn over this period to understand the changes.
Weaknesses of Case Studies
They target a single individual and this makes it difficult to generalise the findings to others.
The data collected is also very subjective as it relies on usually peoples perceptions of things and their memories may not be so reliable over such a long period of time.
There can be ethical concerns with using case studies as the people or group being followed are usually of interest because of some psychological problem. This could make them vulnerable and raise ethical concerns about whether they can give informed consent.
Observation Studies and the Observational Method
In an observational study, the researcher watches or listens to the participants engaging in whatever behaviour is being studied and records their behaviour.
In most natural observations, people are observed in their normal environments without interference from the researcher.
In some studies, a researcher may cause something to happen to gauge the responses of people and record these.
Strengths of Observation Studies and the Observational Method
What people say is often very different from what they may do in a given situation.
The observational method is high in ecological validity and its use is very suitable for social behaviours as it allows researchers to gauge peoples true responses.
The behaviours observed in observational studies have higher external validity as they can be more easily generalised.
Weaknesses of Observation Studies and the Observational Method
Although researchers see and record behaviour in an observational study, they do not know why the behaviour happened.
Researchers may record incorrect responses.
Observational studies also raise ethical issues particularly around informed consent as participants are usually not aware of being observed or part of a study.
Categories of Behaviour
In order to make sure that accurate records of behaviour are made, researchers use categories of behaviour systems.
If researchers wanted to observe “playground behaviour”, researchers would not necessarily know what they were looking for in this definition or what may be classified as “playground behaviour”.
The observers would need to know what they are looking for to make accurate recordings and therefore behavioural categories are created to make it clear what behaviours are to be recorded.
Inter-Observer Reliability
When an observation study is conducted, observers record the number of times certain behaviours occur (usually in the form of a tally chart).
This record of the number of incidents for the different behaviours needs to be accurate and ensure that the observer is recording the correct behaviour within the correct categories.
In observation studies, observers may miss the behaviour and so accuracy of recording the behaviour becomes an issue as it cannot be seen again in live environments.
A solution to this problem is to design a record sheet with the pre-defined suitable behaviour categories and then have two observers independently observe the targets at the same time and location.
Each would then record what they see in their own individual sheets independently from the other.
At the end of the study, the observers may compare their record sheets to check for consistency. If the sheets have been recorded correctly, they should have matching or very similar recordings of their observations. If this occurs, they have established inter-observer reliability. If the record sheets are considered vastly different, this would mean the study lacks inter-observer reliability and the results lack validity as they are not measuring what they are supposed to measure accurately.
Correlation
A correlation is quite simply a relationship between two variables.
There are 3 types of correlations which are:
Positive correlation
Negative correlation
Zero correlation
With positive and negative correlations, the relationship is seen as a “cause and effect” relationship whereby one variable has a direct impact on the other. Correlations form part of a statistical technique to analyse and display the possible relationship between the two variables.
Let’s assume there is a correlation (relationship) between the two variables age and beauty. As people get older they may be seen to be more beautiful. This would be considered a positive correlation because both the variables increase together.
If however people disagreed and thought that as people age and get older, they are less beautiful, this would be a negative correlation. This is because as one variable increases, the other one decreases which in our case would be age increasing while beauty decreases.
The third way of looking at this is thinking that age has no effect on perceived beauty. As people get older you may think this has no bearing on a person’s beauty so the two variables would be seen as having zero correlation.
Strengths of Correlations
Can be very useful as they allow a researcher to see if two variables are connected in some way. Once a relationship has been established between two variables, a researcher can then use an experiment to try and find the true cause of the correlation.
Can be used in situations where it may be unethical or impossible to carry out an experiment. For example, if we wanted to check for the relationship between smoking and cancer, this would be unethical to test (asking people to smoke to see if they develop cancer). However, plotting the rates of cancer developing in people who already smoke can help us establish links between these two variables. This knowledge can then be helpful in influencing future research.
Weaknesses of Correlations
Although this type of tool can tell us if two variables are related, it does not tell us which of the two variables caused the relationship. It is also possible that there may be third unknown variables that lay in between and influence the two we measure in research which may be the actual cause.
For correlational research to be helpful, we first need to gather large amounts of data to establish the pattern in the scatter graph. This means researchers are required to make lots of measurements of both variables so that the patterns in the data can be reliably established. Using correlational research for small populations is not reliable so it can be very time-consuming establishing a large data set.
Research Procedures
What the GCSE Psychology specification says you need to learn for this section on Research Procedures:
Standardised procedures
Instructions to participants
Randomisation,
Allocation to conditions
Counterbalancing
Extraneous variables (including explaining the effect of extraneous variables and how to control for them).
Standardised Procedures
When conducting experiments, researchers need to ensure that standardised procedures are used.
Standardised procedures are a set of sequences that apply to all the participants when necessary to ensure the experiment is unbiased.
Standardised procedures allow the researcher to try and control all the variables and events so the results of the experiment can be safely attributed to the independent variable.
Instructions to Participants
When standardising procedures, another issue researchers need to be mindful of is how instructions to participants are put across to make sure they know what to do but without biasing the study in any way. This can include verbal and written instructions.
Instructions can be interpreted in a way that can influence their performance and these can become extraneous variables. For example, if instructions were worded with leading questions, this may cause participants to answer in one particular way. If instructions are ambiguous, this can also affect the results of the study.
To address this issue, the usual practice is to write as much information as possible for participants and ensure they all receive this same information. This is usually done in sections as follows:
Briefings: this is where participants are encouraged to participate with a log of what is discussed to gain their consent. This can include ethical information about consent, anonymity, the right to withdraw etc.
Standardised instructions are given: these are clear instructions given to each participant explaining their role and what they need to do.
Debriefing: at the end of the study, participants are given a detailed explanation about the aims of it, what their role was and why they were given their tasks or roles. Ethical issues are also raised again with participants given the opportunity to withdraw their data/contributions if they feel unhappy about their performance or participation.
Randomisation
Randomisation simply means to make sure there are no biases in the procedures.
Let’s use our music and learning example again for a moment to highlight how randomisation may be implemented in a psychological study. Participants are being tested on their ability to learn through the use of 20 random words they are presented with. All the words are considered to be of equal difficulty because they are everyday nouns with only six letters.
The researcher has to decide which order they should be presented to each of the participants in the study however instead of the researcher determining the order, randomisation is used. All 20 words are written down on a piece of paper and put into a hat. They are then randomly selected one after the other with their order being written down in which they have been selected. This order is then determined to be the order to which all participants will be exposed within the experiment. Using randomisation, all the words had an equal chance of selection and now with an order established, all participants will be exposed to them in the same way. Randomisation can be implemented in a number of ways within an experiment to filter out biases and you may be given a question on how to best implement this or its benefits.
Another major issue researchers face, is how to allocate the participants to the experimental condition or control group. To reduce researcher bias, two methods used are random allocation and counterbalancing.
Random Allocation
When the design of the study uses an independent group design, the researcher can use random allocation to avoid any potential researcher bias.
Participants can be randomly selected in turns for either condition A or condition B by pulling their name out of a hat for example.
A similar method can be employed if the design of the experiment is a matched pairs design. Participants can be randomly allocated to their pairs by them pulling out the letters for each pair from a hat e.g. the two people who pull out A+a from a hat form a pair, the same with B+b, C+c etc and so forth.
Counterbalancing
For experimental designs such as the repeated measures design, all the participants are required to take part in the experiment for both conditions.
The problem with this is that order effects can occur whereby participants learn from experience and thus do better in all the following conditions after their initial one.
Counterbalancing helps balance out order effects by splitting the group of participants into two groups.
One half will then complete condition 1 while the other half complete condition 2.
After completing this, they swap and complete the opposite condition so those who completed condition 1, then move on to complete condition 2, those that completed condition 2, go on to complete condition 1.
Using counterbalancing does not get rid of order effects but allows for the effects of it to be balanced out equally between the two conditions for participants and thus providing more valid results.
Ethical Considerations
For Ethical Considerations, the specification states you need to know the following:
Ethical issues in psychological research as outlined in the British Psychological Society guidelines
Ways of dealing with each of these issues.
This next section focuses on all the ethical considerations based on the British Psychological Society guidelines and ways in which each can be dealt.
Ethical issues arise when there are two conflicting points of view;
One is what the researcher needs to do in order to conduct a useful and meaningful study
The second is the rights of the participants which need to be considered.
Ethical issues are therefore all the conflicts that arise about what is acceptable to do as part of the research.
As part of your GCSE psychology course, you need to be able to highlight ethical concerns and generate ways in which to deal with them. You may also be given a scenario where you need to highlight the relevant concerns and comment on how to deal with them.
The Code of Ethics and Conduct (2009) and Code of Human Research Ethics (2014) from the British Psychological Society underpin the activities of all practising psychologists.
The British Psychological Society Guidelines
Respect
Participants should be respected as individuals and unfair or prejudiced practices are to be avoided.
The data collected should also be confidential and anonymised so participants cannot be identified from the research.
Participants should have also given informed consent and know fully what they are consenting to. They should also be told at the beginning what the study is about prior to taking part.
Deception must be avoided although the BPS recognises that some studies are not possible without this to gather meaningful results. Any deceptions that do take place must be explained to participants as soon as possible once the study concludes.
They should also be aware of their right to withdraw from the study at any time.
Competence
Psychologists should maintain high standards in their professional work which includes:
Being aware of the code of conduct
Recognising that ethical dilemmas will inevitably arise and seeking to resolve them
They should only give advice if they are qualified to do so and not trying to do things that are beyond their competence.
Staying within the law if ethical principles conflict with the law but try to maintain the ethical principles as far as possible
Monitoring their own health and lifestyle to recognise times when they may be unable to carry out their work competently
Responsibility
Responsibility within the British Psychological Society (BPS) is generally about avoiding harm to clients, avoiding misconduct that would bring psychology into disrepute and looking out for other psychologists that may be breaching these guidelines. The BPS states researchers should:
"Consider all research from the standpoint of research participants, for the purpose of eliminating potential risks to psychological well-being, physical health, personal values, or dignity"
This can be done by:
Ensuring researchers protect participants from physical and psychological harm.
Making sure the risk of physical or psychological harm is no greater than what one would expect from everyday life and their wellbeing should not be at risk.
At the end of the experiment, participants should be debriefed at the end of the investigation so they fully understand the true aim of the study. This would then allow them to make an informed decision about whether they wish to withdraw their results.
Informed Consent
Informed consent means revealing to the participant the real aims of the study or telling them what will happen within the study.
This becomes an ethical issue because revealing the true aims or details may lead to the participants adjusting their behaviour which could lead to invalid results.
For example, if we wanted to study whether people are more likely to obey a male or female as part of research into obedience, revealing the aims of this study will almost certainly affect their behaviour and invalidate findings.
Researchers may therefore not always give out the full details of the study however this means participants can not give their full informed consent. From a participants point of view, they should be told what they are required to do in the study so they can make an informed decision about whether they wish to take part. This became a basic human right that was established during the Nuremberg war trials after the second world war.
During the war, Nazi doctors conducted various experiments on prisoners without their consent and the war trials afterwards decided that consent should become a basic human right for participants to be involved in a study.
Epstein and Lasagna found that only a third of participants volunteering for experiments really understood what they had agreed to take part in despite giving informed consent. This demonstrates that even if researchers sought to and obtained informed consent, this does not always guarantee that participants understand what they are involved in or doing.
How to deal with ethical issues of informed consent
Participants could be asked to formally indicate their agreement to take part based on information concerning the nature and purpose of the study and how their role fits in.
Presumptive consent may also be gained; this can be done by asking a group of people whether they feel a planned study is acceptable and assume that the participants themselves would have felt the same if given the opportunity to say so.
Researchers can offer the right to withdraw at any stage of the study to participants so if at any stage they feel uncomfortable or do not wish to continue, they can exit the research.
Deception
Some experiments require deception about the true aims of research otherwise participants might alter their behaviour and the study’s findings become meaningless.
A distinction could be made in some cases between withholding some details about the study (reasonably acceptable) compared to deliberately providing false information (less acceptable).
From the participant’s point of view, deception would be unethical and thus they should not be misled without good reason. An issue with deception is it prevents participants from giving informed consent. Participants may agree to take part without fully knowing what they have agreed to