Research methods Flashcards
Experimental method definition
Involves the manipulation of an independent variable (IV) to measure the effect on the dependent variable (DV). Experiments may be laboratory, field, natural or quasi.
Aim definition:
a general statement of what the researcher intends to investigate, the purpose of the study.
hypothesis definition
A clear, precise, testable statement that states the relationship between the variables to be investigated. Stated at the outset of any study.
directional hypothesis definition
States the direction of the difference or relationship.
Non directional hypothesis definition
Does not state the direction of the difference or relationship.
Variables definition
Any ‘thing’ that can vary or change within an investigation. Variables are generally used in experiments to determine if changes in one thing result in changes to another.
Independent variable definition
Some aspect of the experimental situation that is manipulated by the researcher - or changes naturally - so the effect on the DV can be measured.
Dependent variable definition
(DV) The variable that is measured by the researcher. Any effect on the DV should be caused by the change in the IV.
operationalisation definition
Clearly defining variables in terms of how they can be measured.
Experimental method aims (AO1)
theory that energy drinks affect how much people talk based on understanding (having read a few research studies on the Internet) that energy drinks contain sugar and caffeine, and that these substances increase alertness, making people chattier
a new energy drink - SpeedUpp - is tested to know whether it might affect the talkativeness of those who drink it.
- then produce an aim which are developed from theories, like our energy drink theory, except they tend to be much more sophisticated and are based on many more hours of research!
Aims are general statements that describe the purpose of an investigation.
the aim would be something along the lines of:
To investigate whether drinking energy drinks makes people more talkative.
hypothesis (AO1)
A hypothesis is a statement that is made at the start of a study and clearly describes the relationship between variables as stated by the theory.
e.g Drinking SpeedUpp causes people to become more talkative.
Hypotheses can be directional or non-directional. In a directional hypothesis the researcher makes clear the difference that is anticipated between two conditions or two groups of people. For this reason, directional hypotheses include words like more or less, higher or lower, faster or slower, etc.
People who drink SpeedUpp become more talkative than people who don’t.
People who drink water are less talkative than people who drink SpeedUpp.
A non-directional hypothesis states there is a difference between conditions or groups of people but, unlike in a directional hypothesis, the nature of the difference is not specified.
People who drink SpeedUpp differ in terms of talkativeness compared with people who dont drink SpeedUpp.
doing an experiment (AO1)
energy drink test done by experimental method. First gather together two groups of people, e.g ten in each group. Then, starting with the first group, we will give each person (or each participant - because that’s what you call people in studies a can of SpeedUp to drink.
- participants in other group will just have a glass of water each. then record how many words each participant says in a five-minute perio immediately after they have had their drink.
Deciding which hypothesis to use (AO1)
we are taking the whole design process slowly) and the exact details of how it would work, which type of hypothesis should we choose?
Researchers tend to use a directional hypothesis when a theory or the findings of previous research studies suggest a particular outcome. When there is no theory or previous research, or findings from earlier studies are contradictory, researchers instead decide to use a non-directional hypothesis.
Even though SpeedUpp is a new energy drink, the effects of caffeine and sugar on talkativeness are well-documented. so we will opt for a directional hypothesis on this occasion.
Independent and dependent variables (AO3)
researcher changes or manipulates the independent variable (IV) and records or measures the effect of this change on the dependent variable (DV). other variables that might potentially affect the DV should remain constant in a properly run experiment. researcher can be confident that any change in the DV was due to the IV, and the IV alone.
Levels of the IV (AO3)
to test the effect of IV we need different experimental conditions. If we gave some participants SpeedUpp, how would we know how talkative they were? We need a comparison. We could:
• Compare participants’ talkativeness before + after drinking SpeedUpp.
• Compare two groups of participants - those who drink SpeedUpp with those who drink water
- the two conditions: no SpeedUpp or drinking SpeedUpp.
These are the two levels of the IV: the control condition (no SpeedUpp / drink of water) and the experimental condition (energy drink).
well-written hypothesis: easy to tell what the IV and DV are. directional hypothesis example:
The group that drinks an energy drink will be chattier than the group that drinks water.
- correct as long as they state the operationalised variables and the relationship between them.
Operationalisation of variables (AO3)
and operationalise the variables in the hypothesis in order to make it testable.
e,g social behaviour, intelligence or thinking, are often a little fuzzy and not easy to define. Thus, in any study, one of the main tasks for the researcher is to ensure that the variables being investigated are clear + measurable
e.g After drinking 300 ml of SpeedUpp, participants say more words in the next five minutes than participants who drink 300 ml of water.
Extraneous variable (EV) definition:
Any variable, other than the independent variable (IV), that may affect the dependent variable (DV) if it is not controlled. EVs are essentially nuisance variables that do not vary systematically with the IV.
Confounding variables definition:
A kind of EV but the key feature is that a confounding variable varies systematically with the IV. Therefore we can’t tell if any change in the DV is due to the IV or the confounding variable.
Demand characteristics definition:
Demand characteristics Any cue from the researcher or from the research situation that may be interpreted by participants as revealing the purpose of an investigation.
This may lead to a participant changing their behaviour within the research situation.
Investigator effects definition:
Investigator effects Any effect of the investigator’s behaviour (conscious or unconscious) on the research outcome (the DV). This may include everything from the design of the study to the selection of, and interaction with, participants during the research process.
. Randomisation definition:
The use of chance methods to control for the effects of bias when designing materials and deciding the order of experimental conditions.
Standardisation definition:
Using exactly the same formalised research study.
procedures and instructions for all participants in a
Extraneous variables (AO1)
The key to an experiment is that an inderandent V. ial enV is manipulated (changed) to see how this affects the dependent variable tential iny thing that should influence the DV is the IV. Any other variables that might potentially interfere with the IV or the DV) should be controlled or removed. These additiona, unwanted variables are called extraneous variables and, where possible, are identified at the start of the study by the researcher, who then takes steps to minimise their influence.
Many extraneous variables are straightforward to control such as the age of the participants, the lighting in the lab, etc. These are described as nuisance variables’ that do not vary systematically with the IV. These may muddy the experimental water so to speak but do not confound the findings of the study. They may just make it harder to detect a result.
Confounding variables (AO1)
do change systematically with the IV. Let us imagine in our energy drink study we have twenty participants in total and decide to use the first ten participants who arrive for the Speedupp condition. It happens that these first ten participants are all very excited because they saw Prince William arrive at their school.
This meant that there was some delay before further participants arrived and by then people were less excited. This unexpected event means we have ended up with a second unintended IV - being excited or not.
So when we come to analyse our results and find that the Speedupp group were chattier we can’t be sure if this is because of the drink or the excitement. The problem is that the emotion varied systematically with the IV and this alone could explain changes in the DV.
Demand characteristics (AO1)
Participants are not passive within experiments and are likely to be spending much of their time trying to make sense of the new situation they find themselves in. As such, participant reactivity is a significant extraneous variable in experimental research and one that is very difficult to control.
In the research situation, participants will try to work out what is going on. Certain clues may help them interpret what is going on. These clues (or cues) are the demand characteristics of the experimental situation and may help a participant to second-guess’ the experimenter’s intentions as well as the aims of the study.
Participants may also look for clues to tell them how they should behave in the experimental situation. They may act in a way that they think is expected and over-perform to please the experimenter (the please-U effect), or, they may deliberately underperform to sabotage the results of the study (the screw-U effect), Either way, participan: behaviour is no longer natural - an extraneous variable that may affect the DV.
Investigator effects (AO3)
Participant reactivity also leads to investigator effects. Consider this: it is possible that during our energy drink study, as we are recording the words spoken by each participant, we may be inclined to smile more during our interactions with some participants than others. Given that we are expecting the energy drink group to speak more than the water group, we may unknowingly - in our unconscious behaviour - encourage a greater level of chattiness from the energy drink participants.
This is an example of an investigator effect, which refers to any unwanted influence of the investigator on the research outcome. As Hugh Coolican (2006) points out, this can include expectancy effects and unconscious cues (such as those described above). It might also refer to any actions of the researcher that were related to the study’s design, such as the selection of the participants, the materials, the instructions, etc. Leading questions, which are discussed in relation to eyewitness testimony on page 58, are a good example of the power of investigator effects.
Randomisation (AO3)
In any investigation there are simple steps that a researcher can take to minimise the effect of extraneous/confounding variables on the outcome.
One of these is randomisation, which refers to the use of chance methods to reduce the researcher’s unconscious biases when designing an investigation. In short, this is an attempt to control investigator effects.
For example, a memory experiment may involve participants recalling words from a list. The order of the list should be randomly generated so that the position of each word is not decided by the researcher.
In an experiment where participants are involved in a number of different conditions, the order of these conditions should be randomly determined. For example, in the energy drink experiment we might want to know what quantity of SpeedUpp caused chattiness. We may set up four experimental conditions: drinking water (Condition A), drinking 100 ml of SpeedUpp (Condition B), drinking 200 ml of SpeedUpp (Condition C), and drinking 300 ml of SpeedUpp (Condition D).
If all participants were to take part in all four conditions, the order in which these conditions were completed would need to be randomised for each participant
Standardisation (AO3)
all participants should be subject to the same environment, information and experience. To ensure this, all procedures are standardised, in other words there is a list of exactly what will be done in the study. This includes standardised instructions that are read to each participant. Such standardisation means that non-standardised changes in procedure do not act as extraneous variables.
Experimental design definition:
The different ways in which participants can be organised in relation to the experimental conditions.
Independent groups design:
participants are allocated to different groups where each group represents one experimental condition.
Repeated measures definition:
All participants take part in all conditions of the experiment.
Matched pairs design definition:
Pairs of participants are first matched on some variables) that may affect the dependent variable. Then one member of the pair is assigned to Condition A and the other to Condition B.
Random allocation definition:
An attempt to control for participant variables in an independent groups design which ensures that each participant has the same chance of being in one condition as any other.
Counterbalancing definition:
An attempt to control for the effects of order in a repeated measures design: half the participants experience the conditions in one order, and the other half in the opposite order.
experimental designs definition:
Experimental design refers to the way it or diner and never cel linged in experiments. By Exed we do not mean taking them out for dine different experimen them again, we mean how participants are arranged in relation to the different experimental conditions.
independent group design (AO1)
when two separate groups of participants experience two different conditions of the experiment. If there are two levels of the independent variable (IV) this means that all participants experience one level of the IV only. In our SpeedUpp energy drink investigation this would involve:
• One group of participants (group a) drinking the energy drink (let’s call this condition A, the experimental condition).
• A different group of participants (group 2) drinking the water (let’s call this condition B, the control condition).
The performance of the two groups would then be compared. In this case, we would compare the difference in the mean number of words spoken in the five-minute period after drinking for each group/condition.
Repeated measures (AO1)
participants experience both conditions of the experiment.
• Each participant would first, for example, experience condition A (the energy drink condition, the experimental condition).
• Each participant would then later be tested again in condition B (the glass of water condition, the control condition).
Following this, the two mean scores from both conditions would be compared to see if there was a difference.
Repeated measures (AO1)
participants experience both conditions of the experiment.
• Each participant would first, for example, experience condition A (the energy drink condition, the experimental condition).
• Each participant would then later be tested again in condition B (the glass of water condition, the control condition).
Following this, the two mean scores from both conditions would be compared to see if there was a difference.
Matched pairs (AO1)
participants are paired together on a variable or variables relevant to the experiment. For instance, in a memory study participants might be matched on their IQ, as this might be a good indicator of their ability to recall information.
The two participants with the first and second highest IQ scores would be paired together, as would the participants with the third and fourth highest, and so on. Then one participant from each pair would be allocated to a different condition of the experiment.
This is an attempt to control for the confounding variable of participant variables and often necessitates the use of a pre-test if matching is to be effective.
So back to our SpeedUpp study, we might observe participants interacting in a room before the experiment begins and select the two people that appear to be the chattiest. One ot the air would be placed in condition A and the other in condition B. We would then do the same with the third and fourth most talkative participants, and so on. The experiment would then be run in the same way as an independent groups design
Independent groups disadvantage(AO3)
disadvantage: participants who occupy the different groups are not the same in terms of participant variables. If a researcher finds a mean difference between the groups on the dependent variable (DV) this may be more to do with participant variables than the effects of the IV. These differences may act as a confounding variable, reducing the validity of the findings. To deal with this problem researchers use random allocation (see right).
Independent groups designs are less economical than repeated measures as each participant contributes a single result only. Twice as many participants would be needed to produce equivalent data to that collected in a repeated measures design. This increases the time/money spent on recruiting participants.
Independent groups strength (AO3)
order effects are not a problem whereas they are a problem for repeated measures designs. Participants also are less likely to guess the aims.
repeated measures limitation: (AO3)
limitation: participant has to do at least two tasks and the order of these tasks may be significant (i.e. there are order effects). In the energy drink example, having the energy drink first may have a continuing effect when a participant drinks water afterwards. To deal with this, researchers use counterbalancing (see right).
Order effects also arise because repeating two tasks could create boredom or fatigue that might cause deterioration in performance on the second task, so it matters what order the tasks are in. Alternatively, participants’ performance may improve through the effects of practice, especially on a skill-based task - in this case participants would perform better on the second task. Order acts as a confounding variable.
It is also more likely that participants will work out the aim of the study When they experience all conditions of the experiment. For this reason, demand characteristics tend to be more of a feature of repeated measures designs than independent groups.
repeated measures strength (AO3)
strengths of using repeated measures are that participant variables are controlled (therefore higher validity) and fewer participants are needed (therefore less time spent recruiting them).
matched pairs (AO3)
Participants only take part in a single condition so order effects and demand characteristics are less of a problem.
Although there is some attempt to reduce participant variables in this design, participants can never be matched exactly. Even when identical twins are used as matched pairs, there will still be important differences between them that may affect the DV.
Matching may be time-consuming and expensive, particularly if a pre-test is required, so this is less economical than other designs.
Laboratory (lab) experiment definition:
An experiment that takes place in a controlled environment within which the researcher manipulates the IV and records the effect on the DV, whilst maintaining strict control of extraneous variables.
Field experiment definition:
An experiment that takes place in a natural setting within which the researcher manipulates the IV and records the effect on the DV.
Natural experiment definition:
An experiment where the change in the IV is not brought about by the researcher but would have happened even if the researcher had not been there.
The researcher records the effect on a DV they have decided on.
Quasi-experiment definition:
A study that is almost an experiment but lacks key ingredients.
The IV has not been determined by anyone (the researcher or any other person) - the
‘variables’ simply exist, such as being old or young. Strictly speaking this is not an experiment.
Laboratory experiments (AO1)
Laboratory experiments are conducted in highly controlled encinodtients. This is not always a laborator (a) i could, for example, be a classroom where conditions can be well-controlled.
Strengths of lab experiments: (AO3)
Lab experiments have high control over confounding (CVs) and extraneous variables (EVs) This means that the researcher can ensure that any effect on the dependent variable (DV is likely to be the result of manipulation of the independent variable (V). Thus, we can be more certain. about demonstrating cause and effect (high internal validity).
Replication is more possible than in other types of experiment because of the high level of control. This ensures that new extraneous variables are not introduced when repeating an experiment. Replication is vital to check the results of any study to see whether the finding is valid and not just a one-off.
Limitations if lab experiments (AO3)
lack generalisability. The lab environment may be rather artificial and not like everyday life. In an unfamiliar context participants may behave in unusual ways so their behaviour cannot always be generalised beyond the research setting (low external validity)
As well as this, participants are usually aware they are being tested in a lab experiment (though they may not know why) and this may also give rise to unnatural behaviour
Furthermore, the tasks participants are asked to carry out in a lab experiment may not represent everyday experience; for instance, recalling unconnected lists of words as part of a memory experiment (low mundane realism).
field experiments (AO1)
IV is manipulated in a natural, more everyday setting (in the field).
The researcher goes to the participants’ usual environment rather than, in a lab experiment, participants going to a researcher’s lab.
Strengths of field experiments (AO3)
Field experiments have higher mundane realism than lab experiments because the environment is more natural. Thus field experiments may produce behaviour that is more valid and authentic. This is especially the case as participants may be unaware they are being studied (high external validity).
Limitations of field experiments (AO3)
However, there is a price to pay for increased realism due to the loss of control of CVs and EVs. This means cause and effect between the IV and the DV in field studies may be much more difficult to establish and precise replication is often not possible.
There are also important ethical issues. If participants are unaware they are being studied they cannot consent to being studied and such research might constitute an invasion of privacy.
Nautical experiments (AO1)
are like a lab or field experiment insofar as the researcher measures the effect of an IV on a DV. However, what distinguishes a natural experiment is the researcher has no control over the IV and cannot change it - someone or something else causes the IV to vary. For example, before and after a natural disaster or whether a child is in hospital at age 5 or 10.
Note that it is the IV that is natural, not necessarily the setting - participants may be tested in a lab.
The DV may also be naturally occurring (eg. exam results) or may be devised by the experimenter and then measured in the field or a lab.
Natural experiments strengths (AO3)
Natural experiments provide opportunities for research that may not otherwise be undertaken for practical or ethical reasons, such as the studies of institutionalised Romanian orphans
Natural experiments often have high external validity because they involve the study of real-world issues and problems as they happen, such as the effects of a natural disaster on stress levels.
Natural experiments limitations (AO3)
naturally occurring event may only happen very rarely, reducing the opportunities for research. This also may limit the scope for generalising findings to other similar situations.
Another issue is that participants may not be randomly allocated to experimental conditions (note that this only applies when there is an independent groups design). This means the researcher might be less sure whether the IV affected the DV. For example, in the study of Romanian orphans, the IV was whether children were adopted early or late. However, there were lots of other differences between these groups, such as those who were adopted late may also have been less sociable than some of the other children which may have made them less appealing for prospective parents.
Such research may be conducted in a lab and therefore may lack realism and demand characteristics may be an issue.
Quasi experiments (AO1)
have an IV that is based on an existing difference between people (for instance, age or gender). No one has manipulated this variable, it simply exists and, unlike in a natural experiment, the ‘independent variable cannot be changed. For instance, if the anxiety levels of phobic and non-phobic patients were compared, the IV of having a phobia would not have come about through any experimental manipulation.
As with a natural experiment, the DV may be naturally occurring (eg. exam results) or may be devised by the experimenter and measured in the field or a lab.
Quasi experiments (AO3)
often carried out under controlled conditions and therefore share some strengths of a lab experiment (e.g. replication).
Quasi-experiments, like natural experiments, cannot randomly allocate participants to conditions and therefore there may be confounding variables.
In addition, in both quasi-experiments and natural experiments, the IV is not deliberately changed by the researcher and therefore we cannot claim that the IV has caused any observed change.
Population definition:
A group of people who are the focus of the researcher’s interest, from which a smaller sample is drawn.
Sample definition:
A group of people who take part in a research investigation. The sample is drawn from a (target) population and is presumed to be representative of that population, ie. it stands ‘fairly’ for the population being studied
Sampling techniques definition:
The method used to select people from the population.
Bias definition:
In the context of sampling, when certain groups are over- or under-represented within the sample selected. For instance, there may be too many younger people or too many people of one ethnic origin in a sample. This limits the extent to which generalisations can be made to the target population.
Generalisation definition?
The extent to which findings and conclusions from a particular investigation can be broadly applied to the population. This is possible if the sample of participants is representative of the target population.
Target population definition:
a subset of the general population.
What does the sample drawn have to be?
Representative of the target population so that generalisation of findings becomes possible. In practice, however, it is often very difficult to represent populations in any given sample due to the inevitably diverse nature of populations of people (different gender, age, interests, experience, etc.). Inevitably then, the vast majority of samples contain some degree of bias.
Samples are selected using a sampling technique that aims to produce a representative sample.
random sample (AO1)
- sophisticated form of sampling
- members of the target population have an equal chance of being selected.
1. obtain a complete list of all members of the target population.
2. all of the names on the list are assigned a number.
3. the actual sample is selected through the use of some lottery method (a computer/phone randomiser or picking numbers from hat)
What is a systematic sample?
every nth member of the target population is selected
Systematic sample (AO1):
A sampling frame is produced, which is a list of people in the target population organised into, for instance, alphabetical order. A sampling system is nominated (every 3rd person, etc.). May begin from a randomly determined start to reduce bias. The researcher then works through the sampling frame until the sample is complete.
stratified sample definition:
- sophisticated form of sampling
- the composition of the sample reflects the proportions of people in certain subgroups (strata) within the target population or the wider population.
Stratified sample (AO1):
To carry out a stratified sample the researcher first identifies the different strata that make up the population. Then, the proportions needed for the sample to be representative are worked out.
- Bolton fans selected from Bolton supporters, if there are enough.
Opportunity sample (AO1):
Given that representative samples of the target population are so difficult to obtain, many researchers simply decide to select anyone who happens to be willing and available (an opportunity sample). The researcher simply takes the chance to ask whoever is around at the time of their study
Volunteer sample (AO1):
involves participants selecting themselves to be part of the sample; hence, it is also referred to as self-selection.
To select a volunteer sample a researcher may place an advert in a newspaper or on a common room noticeboard. Alternatively, willing participants may simply raise their hand when the researcher asks.
Random sample (AO3)
- strength potentially unbiased. This means that confounding or extraneous variables should be equally divided between the different groups, enhancing internal validity.
- limitation: difficult and time-consuming to conduct. A complete list of the target population may be extremely difficult to obtain.
- may end up with a sample that is still unrepresentative - laws of probability suggest random sampling is likely to produce a more representative sample than opportunity sampling.
- selected participants may refuse to take part (which means you end up with something more like a volunteer sample). This particular issue applies to all of the methods below.
Systematic sample (AO3)
Limitation: This sampling method is objective. Once the system for selection has been established the researcher has no influence over who is chosen (higher chance if start is randomly selected).
- like random sampling, this method is time-consuming + participants may refuse to take part, resulting in a volunteer sample.
Stratified sample (AO3)
Strength: representative sample as accurately reflects the composition of the population.
- so generalisation of findings becomes possible.
Weakness: stratification is not perfect. The identified strata cannot reflect all the ways that
people are different
-so complete representation of the target population is not possible
Opportunity sample (AO3)
- strength: convenient as less time + money than random sampling as list of members of the target population is not required, and there is no need to divide the population into different strata as there is in stratified sampling.
- limitation: two forms of bias
- sample is unrepresentative of the target population as it is drawn from a very specific area so cannot be generalised to the target population.
- ## the researcher has complete control over the selection of participants and, for instance, may avoid people they do not like the look of (researcher bias).
Volunteer sample (AO3)
- strength: Collecting a volunteer sample is easy. It requires minimal input from the researcher (they come to you) and so is less time-consuming than other forms of sampling. The researcher ends up with participants who are more engaged, more so than someone who was stopped in the street.
- limitation: Volunteer bias is a problem. Asking for volunteers may attract a certain ‘profile of person, that is, one who is curious and more likely to try to please the researcher (which might then affect how far findings can be generalised).
BPS code of ethics definition:
A quasi-legal document produced by the British Psychological Society (BPS) that instructs psychologists in the UK about what behaviour is and is not acceptable when dealing with participants. The code is built around four major principles: respect, competence, responsibility and integrity.
Ethical issues in the design and conduct of psychological studies (AO1):
- ethical issues arise when conflict or dilemma exists between participants rights and researchers’ needs to gain valuable and meaningful findings.
- e.g researcher may not wish to reveal the true purpose of a research study to participants in order to study more ‘natural’ behaviour.
Informed consent (AO1):
- participants in studies should know what they are getting into before they get into it.
- studies should know what they are getting into before they get into it. Informed consent involves making participants aware of the aims of the research, the procedures, their rights (including the right to withdraw partway through the investigation should they so wish), and also what their data will be used for. Participants should then make an informed judgement whether or not to take part without being coerced or feeling obliged
From the researcher’s point of view, asking for informed consent may make the study meaningless because participants’ behaviour will not be ‘natural’ as they know the aims of the study.
Deception definition:
deliberately misleading or withholding information from participants at any stage of the investigation.
Deception (AO1):
Participants who have not received adequate information when they agreed to take part (or worse, have been deliberately lied to) cannot be said to have given informed consent.
- but in some occasions deception can be justified if it does not cause the participant undue distress.
Protection from harm (AO1)
- participants should not be placed at any more risk than they would be in their daily lives, and should be protected from physical and psychological harm.
- or they might be made to feel embarrassed, inadequate or being placed under undue stress or pressure. An important feature of protection from harm, as mentioned above, is participants being reminded of the fact that they have the right to withdraw from the investigation at any point.
Privacy and confidentiality (AO1):
Participants have the right to control information about themselves. This is the right of privacy.
- If this is invaded then confidentiality should be protected.
- The right to privacy extends to the area where the study took place such that
institutions or geographical locations are not named.
Confidentiality definition:
refers to our right, enshrined in law under the Data Protection Act, to have any personal data protected.
What does BPS stand for?
British Psychological Society
BPS code of conduct (AO1)
- has its own BPS code of ethics and this includes a set of ethical guidelines.
-Researchers have a professional duty to observe these guidelines when conducting research - they won’t be sent to prison if they don’t follow them but may lose their job
The guidelines are closely matched to the ethical issues on the facing page and attempt to ensure that all participants are treated with respect and consideration during each phase of research. Guidelines are implemented by ethics committees in research institutions who often use a cost-benefit approach to determine whether particular research proposals are ethically acceptable
Dealing with informed consent (AO1)
Participants should be issued with a consent letter or form detailing all relevant information that might affect their decision to participate. Assuming the participant agrees, this is then signed.
- investigations with children under 16 —> a signature of parental consent is required. There are other ways to obtain consent, which are described on the right.
Dealing with deception and protection from harm (AO1):
- the end of study: participants should be given a full debrief.
- participants should be made aware of the true aims of the investigation and any details they were not supplied with during the study, such as the existence of other groups or experimental conditions.
- should also be told what data will be used for + given the right to withdraw during study + the right to withhold data if they wish.
- important if retrospective consent is a feature of the study
Participants may have natural concerns related to their performance within the investigation, and so should be reassured that their behaviour was typical or normal. In extreme cases, if participants have been subject to stress or embarrassment, they may require counselling, which the researcher should provide.
Dealing with confidentiality (AO1):
- personal details are held these must be protected. However it is more usual to simply record no personal details, i.e. maintain anonymity. Researchers usually refer to participants using numbers or initials when writing up the investigation. In a case study, psychologists often use initials when describing the individual or individuals involved
- Finally, it is standard practice that during briefing and debriefing, participants are reminded that their data will be protected throughout the process and told that the data will not be shared with other researchers.
Pilot study definition:
A small-scale version of an investigation that takes place before the real investigation is conducted. The aim is to check that procedures, materials, measuring scales, etc., work. The aim is also to allow the researcher to make changes or modifications if necessary.
Aims of Pilot studies (AO1):
- involves a handful of participants, rather than the total number, in orderto
‘road-test’ the procedure and check the investigation runs smoothly. - not just restricted to experimental studies. When using self-report methods, such as questionnaires or interviews, it is helpful to try out questions in advance and remove or reword those that are ambiguous or confusing.
In observational studies, a pilot study provides a way of checking coding systems before the real investigation is undertaken. This may be an important part of training observers. - allows the researcher to identify any potential issues and to modify the design or procedure, saving time and money in the long run.
Single-blind procedure (AO1)
- condition of experiment or how many conditions there are may be hidden
- single-blind procedure- any information that might create expectations is not revealed until end of study to control for confounding effects of demand characteristics
Double-blind procedure (AO1)
- neither participants or researcher who conducts study is aware of aims of investigation (often third party conducts investigation without knowing main purpose)
- often used in drug trials
How are Double-blind procedures used in drug trials? (AO1)
Treatment may be administered to participants by someone who is independent of the investigation and who does not know which drugs are real and which are placebos
- If they don’t know what each participant is receiving then expectations cannot influence participant behaviour.
Control groups and conditions (AO1):
- in drug trials: group that receives the real drug is the experimental group and the group that receives the placebo is the control group.
- Control is used in many experimental studies for the purpose of comparison. If the change in behaviour of the experimental group is significantly greater than that of the control group, then the researcher can conclude that the cause of this effect was the independent variable (assuming all other possible confounding variables have remained constant).
Having two groups in an experiment is an independent groups design, but we can aso have control conditions in a repeated measures design. - Each participant takes part twice-once in the experimental condition and then in the control condition.
Comparison definition:
‘control’ in research to refer to the control of variables but we use it here to refer to setting a baseline.
Ethical issues definition:
These arise when a conflict exists between the rights of participants in research studies and the goals of research to produce authentic, valid and worthwhile data.
