Research Methods Flashcards
Identify the two types of research method
• Experimental
• Non-experimental
Identify the types of experimental methods
• Laboratory experiments
• Field experiments
• Natural experiments
• Quasi experiments
Outline lab experiments
• Defined by the high level of control the researcher has over variables in the study. The experimenter will control environmental factors (eg. noise/temperature) as well as the experience the participant has using standardised procedures
Evaluate lab experiments
+ High internal validity as extraneous variables are
controlled
+ Easily replicable due to the use of standardised
procedures
+ Cause and effect is easily determined due to the
isolation of variables
- Lack external validity through ecological validity
and mundane realism - Demand characteristics are present as
participants know they’re in a study - Results may be affected by experimenter bias
Outline field experiments
• Defined by conducting the experiment in naturalistic settings.
• This change in location is an attempt to avoid the artificial nature of lab studies, and can include shops, schools or anywhere participants would be expected to behave naturally.
Evaluate field experiments
+ High external validity as participants will act
naturally in a more usual activity
+ No demand characteristics as participants don’t
know they’re in a study
- Low internal validity due to sample issues
- Lack of control over possible extraneous
variables that can impact the dependent variable - Time consuming, expensive and difficult to
replicate
Identify what lab and field experiments have in common
The independent variable is manipulated by he researcher between conditions.
Any change in the dependent variable is measured while all other extraneous variables are kept consistent between condition if they could affect the DV
Outline natural experiments
• The two levels of independent variables occur naturally without the researchers influence. The researcher simply records the change in the dependent variable
• Natural experiments happen with an event (eg. natural disaster) causes people to form into levels of the independent variable
Evaluate natural experiments
+ The only way to test certain things deemed as
unethical
+ No demand characteristics as it’s real behaviour
in the real world; high external validity
- Extraneous variables impact the dependent
variable - More time consuming, expensive as well as
ethical (informed consent), replication (innate
characteristics/rare events) and sample (may not
be comparable) issues
Outline Quasi experiments
• Participants cannot be randomly assigned between levels of independent variable, often because the level of independent variable is an innate characteristic of participants
• The characteristics psychologists study already exist in participants, (eg. gender or age)
Evaluate Quasi experiments
+ The only way to test certain things deemed as
unethical
+ No demand characteristics, unless the
experiments in a lab, as it’s real behaviour
in the real world; high external validity
- Extraneous variables impact the dependent
variable, unless the experiments in a lab - More time consuming, expensive as well as
ethical (informed consent), replication (innate
characteristics/rare events) and sample (may not
be comparable) issues
Compare and contrast natural and quasi experiments
• COMPARISON:
In both, the independent variables can’t be manipulated as they’re natural
• CONTRAST:
In natural experiments, the two levels of independent variable occur naturally, the researcher simply records the effects on the dependent variable, whereas in quasi experiments the independent variable already exists in the participants they’re studying and extraneous variables can be controlled
What’s the difference between experimental and non-experimental methods
In experimental methods, the researcher manipulates the independent variable, but in non-experimental methods the researcher does not
Identify the types of non-experimental method
• Observations
• Self-report methods
• Correlations
Outline observations
• The researcher watches and records spontaneous/natural behaviour of participants without manipulating levels of independent variable
• These can be structured, involving the use of behavioural categories and likely producing numerical, quantitative data or unstructured where the investigator may want to write down everything they see. This tends to produce qualitative data and be more difficult to record and analyse but may be more appropriate with small sample sizes eg. marriage counselling session
• Behavioural categories should be measurable, observable and self-evident and should be exclusive and not overlap (eg. smiling/grinning) there also shouldn’t be a ‘dustbin category’ of many different behaviours
Identify the possible characteristics of observations
• Controlled vs naturalistic observations
• Covert vs overt observations
• Participant vs non-participant observations
Outline and evaluate controlled observations
• Aspects of the environment are controlled in order to give participants the same experience, often in a laboratory setting
+ High internal validity as extraneous variables are
controlled, reducing the chance they’re
responsible for behaviour
+ Reliable results due to standardised procedure
- Low external validity, behaviours are less likely
to be generalisable to other situations
Outline and evaluate naturalistic observations
• Takes place in the real world, in places participants are likely to spend their time such as school or work
+ High external validity as natural behaviours are
more likely to be generalisable to other
situations
- Low internal validity as uncontrolled extraneous
variables may be responsible for behaviour
Outline overt observations
• The participants can see the researcher and are aware their behaviour is being used as part of an observation
+ Ethical through informed consent as participants
agree to take part in the research
- Demand characteristics present as they know
the researchers watching or social desirability
bias may be a factor
Outline covert observations
• The participants are not aware they’re being observed as they can’t see someone making notes/recordings
+ No demand characteristics or social desirability
bias
- Unethical as participants can’t give informed
consent
Outline participant observations
• The researcher joins the group being observed and takes part in group activities and conversations
+ The researcher’s more likely to remain objective
in their interpretation of the participants
behaviour
- Researchers can lose objectivity; ‘going native’
seeing only from the participant perspective
Outline non-participant observation
• The researcher’s separate from the participants
recording observations without taking part in
the activities
+ The researcher’s more likely remain objective in j
interpretation of participant behaviour
- Due to lack of trust/rapport the researcher may
miss out on important insights/participants don’t
have naturally
Outline self report techniques
The participant reveals personal information about themselves (eg. behaviours, emotions, beliefs, attitudes and memories) in response to a series of questions, this can either be in the form of questionnaires or interviews
Outline questionnaires
Participants give information in response to a set of questions sent to them, this can be in the post or online and consists of one of the following measurement scales:
• Likert scale: respondents indicate level of
agreement eg. strongly agree to strongly disagree
• Rating scale: respondents select a value that resp
resents strength of a feeling eg. very entertaining
to not at all entertaining
• Fixed choice option: includes a list of possible
options and respondents select all that apply
Outline interviews
Participants give information in response to direct questioning from the researcher, and can be conducted in person or over the phone.
There are three types of interview; structured, semi-structured and unstructured
Outline and evaluate structured interviews
• The interviewer reads out a list of prepared
questions as they’re written
+ The interviewer doesn’t have to be highly trained
+ Responses are easily comparable (same q’s)
- Participant responses can be followed up with
additional questions that could provide more
detail
Outline and evaluate semi-structured interviews
• Combination of prepared questions with the
ability to ask additional questions
+ Responses are easily comparable (same q’s)
+ Follow up questions to interesting answers
+ Rapports more likely to make participants
comfortable and answer questions
- The interviewer must be highly trained to think
of questions in the moment
Outline and evaluate unstructured interviews
• No list of set questions, an open conversation
about a topic
+ Follow up questions to interesting answers
+ Rapports more likely to make participants
comfortable and answer questions
- Responses aren’t as comparable as every
interview’s different
- The interviewer must be highly trained to think
of questions in the moment
Evaluate questionnaires
+ Don’t require a trainer interviewer and can be
distributed easily making large data collection
cheap and easy
+ When using closed questions, thousands of
responses are easily compared and it’s easy to
replicate
- Questions can’t be rephrased
- Often not taken seriously leading to acquiesce
(agreement) bias
Evaluate interviews
+ Can rephrase questions that aren’t understood
+ Can build rapport, so participants feel more
comfortable and take them more seriously
- Requires an interviewer, significantly increasing
cost per participant especially if the interviewer
has to be trained - Interviewer effects, personal characteristics of the interviewer can alter the participants response
Identify design points of self-report techniques
• Avoid complex terminology: terms may not be understood and participants may be embarrassed to ask (i) or unable to (q)
• Rewording questions: skilled interviewers can reword a non-understood question in a way that doesn’t affect comparison
• Avoiding leading questions: questions shouldn’t be written in a way that suggests a ‘correct’ way to answer
• Piloting: small scale version to identify confusing questions or questions that provide useless responses or give away the aim
• Filler questions: not linked to the research aim; used to build rapport (i) or help hide research aim (q) reducing demand characteristics
Identify the advantages of self-report methods
Same set of closed questions are easily replicated and provides easy data analysis
Identify the disadvantages of self-report methods
• Social desirability bias: participants responding in a way that makes them look good in front of the researcher
• Demand characteristics: it’s often easy to work out the aim from the questions, people answer what they think the researcher wants
• Researcher bias: the researcher interpreting open question responses in a way that confirms their beliefs (this can be unintentional)
• Invesigator effects: the personal characteristics or the body language of the interviewer may influence participants answers
Define a correlation
A method used to analyse data; a correlations used to analyse the association between two co-variables
Outline correlational studies
• No variables are manipulated unlike experimental designs that manipulate the IV and measure the resultant change on the DV, instead two co-variables are measured and compared to look for a relationship so no causal conclusions can be drawn
Outline how correlations are measured
• Scattergrams
• Correlation coefficient- is a measure if the extent of a correlation that exist ls between two co-variables, it has a numerical value between +1 and -1 indicating the strength of the relationship (+1= a strong positive correlation and -1= a strong negative correlation)
- Positive correlation- when the two variables
increase/decrease together
- Negative correlation- as one variable increases,
the other decreases
- Zero correlation- no relationship between the
two variables
They’re calculated using statistical tests such a Spearman’s Rho and test-retest reliability is measured in this way
Evaluate correlations
+ Justify further research as they can highlight potential causal relationships that can be tested with experimental methods to discover cause and effect relationships
+ Can be used when it’s unethical or impractical to manipulate research
+ Correlation coefficient is useful in describing the direction and strength of relationships
- Correlation doesn’t show causation: we don’t know which variables impacting the other or if the relationships caused by a third variable
- Correlating can be misused or misinterpreted eg. in the media relationships between variables are sometimes presented as causal facts when they aren’t (eg. high crime rate in single parent families)
Outline case studies and when or who they’re used to study
• Range of data collected from an individual, group or institution
• Case studies looking at behaviour over a short period of time are called ‘snapshots’, while longitudinal case studies follow participants over many years to show behavioural change over time but are difficult to continue over the long term due to finding/researchers dying of old age
• Data’s mainly collected using interviews and observations, but content analysis can be performed on written evidence and even experimental techniques can be used
• Case studies are generally conducted on psychological unusual individuals, unusual events, organisational practices or a typical individual within a demographic
What’s clinical psychology
The unusual behaviour of individuals with brain damage indicating the area that’s damaged is in some way related to that behavioural function
Identify examples of case studies in psychology
• Clinical psychology: the case of Tan (Louis Leborgne) could only say the word ‘Tan’ while other functions were unaffected, helped identify Broca’s area
• Psychodynamic psychology: Freud used a number of case studies to support his theory of psychodynamics. He suggested ‘little Hans’ fear of horses represented his fear of his father, helping to support the idea of the Oedipus complex
• Childhood psychology: The case of ‘Genie’ who was deprived of care until 13 years old and never developed normal communication
Evaluate case studies
+ Results of one unusual case study can upend an established theory
+ Often the only way to investigate very unusual/extreme human behaviour that can’t be replicated in labs due to ethics
+ In depth, mostly qualitative data increases realism and provides high detail and valid insights, taking a holistic approach
+ Been used to develop hypothesis that can then be tested experimentally eg. Broca’s area
- Interviews form a large part and can be prone to social desirability bias or memories may be inaccurate
- Findings can’t be generalised as unknown factors can contribute to behaviour
- Subjects are unique so exact replications to check reliability aren’t possible
- Researcher bias as they decide what findings to include/exclude and may only include data that confirms their theory or may lose objectivity after knowing the subject
Outline content analysis
• An indirect observational method that’s used to analyse human behaviour by studying human artefacts (things people make)
• Content analysis is often the written word (non-numerical qualitative data) or transcripts of spoken word that’s then transformed into quantitative data
Describe the process of content analysis
• Decide a research question and select a sample from a larger quantity of all possible data (eg. books, tweets)
• Coding, the researcher decides on categories/coding units to be recorded (eg. occurrences of particular words) based on the research question
• Work through the data, reading the sample and tallying the number of times pre-determined categories appeared
• Data analysis can be performed on quantitative data to look for patterns
• Test for reliability through test-retest reliability by running the same content analysis and comparing data or through inter-rater reliability where a second rater mirrors the process and compares data
• How the closely the two sets of data match in either method is assessed with a test of correlation such as Spearman’s rho. A correlation of 0.8 or higher is usually accepted to show the data’s reliable
Evaluate content analysis
+ Artefacts are usually not created for research purposes but are taken from the real world (easy to gather samples) meaning high external validity and findings are generalisable to real-world situations
+ Other researchers should be able to replicate a content analysis using the same coding units/behavioural categories and access to the same sample
- Researcher/observer bias as researchers must interpret subjective texts and tend to interpret them in a way that supports their view
- Data may lack validity- wasnt created under controlled conditions (made for research) eg. historical records like diaries may contain inaccuracies and not all diaries have equal chance of surviving to the present
Outline thematic analysis
• Researchers start by attempting to identify the deeper meaning of the text by reading it first and allowing themes to emerge
• Themes are not pre-determined by the researcher but emerge from the text
Describe the method of thematic analysis
• Collect a text or turn recordings into a text through transcription
• Read text/transcript first to spot patterns that can be coded and collected
• Re-read the text/transcriptions looking for emergent themes
Evaluate thematic analysis
+ Artefacts are usually not created for research purposes but are taken from the real world (easy to gather samples) meaning high external validity and findings are generalisable to real-world situations
+ Other researchers should be able to replicate a thematic analysis using the same coding units/behavioural categories and access to the same sample
+ Theories come after discovering themes so this potentially removes researcher bias
- Data may lack validity- wasnt created under controlled conditions (made for research) eg. historical records like diaries may contain inaccuracies and not all diaries have equal chance of surviving to the present
Define and outline an aim in psychological research
• A clearly phrased general statement about what the investigator intends to research
• An aim can include the purpose of the study and is phrased as a question or statement that identifies what the researchers intending to investigate and why
Define and outline a hypothesis in psychological research
• A precise, testable statement including levels of independent and dependant variable or both co-variables for a correlational study.
• These variables must be operationalised. Operationalised variables are carefully stated, demonstrating exactly how they’re measured (E.g. the number of words recalled)
• Hypotheses are not predictions, they’re statements of fact that the research accepts or rejects based on the data they collect
Identify the difference between aims and hypotheses
Aims state what the researchers intending to investigate and potentially why, whereas a hypothesis is formulated by the researcher to communicate exactly how the research will be conducted
Identify and explain the types of hypothesis
Watch psych boost video to learn experimental hypothesis to edit flashcards
• The Null hypothesis (N0) states there’s no change (difference) in the measurement of the dependant variable as a result of the manipulation in the independent variable
• The alternate (research) hypothesis (N1) states that there is a change (difference) in measurement of the dependant variable as a result of the manipulation of the independent variable. This can be written as a:
-Non directional (two-tailed) hypothesis that
states there’s a difference in the measurement of
the dependant variable but not the direction the
results will go
-Directional (one-tailed) hypothesis that states
there is a difference in the measurement of the
dependant variable and states the direction the
results will go. Directional hypotheses are only
used by researchers if there is previous research
that suggests which way the results are likely to
go
Describe how you can test hypotheses
• Data’s collected and statistical testing is conducted on said data providing evidence
• If the evidence is strong enough, the Null hypothesis can be rejected and the alternate hypothesis is accepted. If not, the Null hypothesis is accepted and the alternate hypothesis is accepted
Identify the difference between experimental and alternative hypotheses
Experimental hypotheses state there will or won’t be a difference while alternative hypotheses state there will or won’t be a correlation
Define sampling and identify why we use sampling
• The difference between the target population and the sample
• We use sampling to make valid generalisations about behaviour being studied. We use methods to minimise costs while maximising generalisability
Define the ‘target population’
• Every member of the group that the investigator plans to study
• As the whole target population can’t be studied, researchers conduct their experiments on a smaller sample of participants, taken from the larger target population: this is generalisation.
• Whether the results can be generalised or not depends on how representative the sample is of the target population, meaning the sample used in the study share the same characteristics with members of the target population
Identify the types of sampling methods
• Random sampling
• Systematic sampling
• Opportunity sampling
• Volunteer sampling
• Stratified sampling
Outline and evaluate random sampling and identify how the effects of chance can be reduced
• Each member of the target population has a mathematically equal chance of being in the sample
- The researcher needs a full list of the entire
target population - All names are written down and placed in a
container or assigned a unique number and
these numbers are entered into a random
number generator - Names are drawn/generated randomly and
selected from the sample
+ No researcher bias as they can’t choose
participants they want
+ Quick method of there’s a pre-existing list
-If not, it’s difficult/time consuming to get a full list
of names
-Potentially get an unrepresentative sample by
chance
• The effects of chance can be reduced (not eliminated) by using a larger sample size and using statistical analysis of data including tests such as Chi-squared, correlation coefficient and students T-test. These tests can be used to see the extent that random chance has influenced the data
Identify the tests that can be assessed and you must be able to interpret in an exam
• Chi-squared
• Correlation Coefficient
• Students T-test
Outline and evaluate systematic sampling
• Every ‘nth’ participant is chosen from a list of the target population
- The researcher needs a full list of the entire
target population - The researcher reads down the list selecting
every ‘nth’ participant until a sample is chosen
+ No researcher bias as they can’t choose
participants they want
+ Quick method of there’s a pre-existing list
-If not, it’s difficult/time consuming to get a full list
of names
-Potentially get an unrepresentative sample by
chance
Outline and evaluate opportunity sampling
• The researcher directly asks available members of the target population to take part. Likely individuals the researcher has easy access to or is familiar with
- Researcher directly asks members from within
the target population (that they have access to)
to take part in research - Any individuals who agree to take part are
added to the sample until the required number’s
met
+ Fastest way to get a sample
-Researcher bias
-Unlikely to be a representative sample
Outline and evaluate volunteer sampling
• AKA self selecting sample, participants offer to take part after finding out about research (not asking directly)
- Advertisements are placed where they’re likely
to be seen by members of the target population - The adverts will include contact details and the
researcher will enroll the volunteer into the
sample when contacted
+ Easy sample to collect
-Volunteer bias; not generalisable to the wider population
Outline and evaluate stratified sampling
• By selecting from within strata, characteristics of participants with the sample are in the same proportion as the target population
- Strata/subgroups are identified along with their
proportion in the target population (e.g. gender/
ethnicity - Random sampling is used to select the number
of participants required from within each
stratum (e.g. 90% brown eyes and 10% blue
eyes means 9 people with brown eyes and 1
person with blue eyes in a 10 participant
sample)
+ Sample’s representative
+ Random sampling avoids researcher bias
-Time consuming to identify properties of starts
and randomly sample these
-Not every characteristic can be included,
researcher bias in that the researcher decides
which strata are important
Outline pilot studies
• Small scale practice investigations carried out prior to research
• The results of the study are irrelevant, the researcher is using the study to identify problems with the design, method or analysis so they can be rectified.
• Participants can also suggest appropriate changes such as demand characteristics or ethical concerns that may arise. These can be dealt with accordingly
Identify reasons why we need pilot studies
• To check the independent variable has been manipulated correctly and is operationalised
• To check the method method to measure to dependant variable has been used
• To check the test/measure is appropriate
• To check the participants understand the instructions and what they’re required to do (this can be asked at the end)
• To ask participants about their experience of taking part; did it run smoothly, what changes would they make
• To save time and money if necessary changes can be made to the procedure
Outline experimental design
• Refers to how we use the participant sample in combination with different levels of dependant variable and how we allocate those participants to conditions in an experiment
• There are two different conditions; the experimental condition and the control condition and three experimental designs of which we must pick the most appropriate:
1. Independent Groups Design (IGD)
2. Repeated Measures Design (RMD)
3. Matched Pairs Design (MPD)
Outline and evaluate independent groups design
• Different participants are used in each condition so each participant only completes one condition. Participants are randomly allocated to each condition to avoid researcher bias
• Produces unrelated data, the individual data points in one condition cannot be paired with any of the data points in the other condition
+ Reduced chance of demand characteristics as
participants only complete 1 condition
+ No order effects
+ Time saved from random allocation
-More participants are required
-Participant variables- extraneous variable of
more participants with a certain characteristic
being assigned to one condition
Outline and evaluate repeated measures design
• The same participants complete all conditions, each participant acts as their own control and is tested against themselves
• Produces related data, each participants score (data point) can be paired with a data point (their own score) in the other condition
• Counter balancing attempts to control for, but doesn’t eliminate, order effects where the first condition influences the performance of the second condition.
• Counter balancing uses an ABBA format, half the participants complete condition A first, and B second and the other half complete B first and A second.
+ No individual differences/group differences
+ One participant produces twice as much data (2
sets of results) so less participants are needed
-Increased chance of demand characteristics-
more likely to figure out the research aim
because the first condition influences the second condition
Outline and evaluate matched pairs design
• Different participants complete the conditions so each participant completes one condition.
• Participants are first ranked on a characteristic (e.g. aggression) and then the top two, and each of the following two are randomly assigned to separate conditions
• Produces related data, each participant’s data point in one condition can be paired with the data point of the participant matched with them in the other condition
+ No order effects
+ Reduced chance of demand characteristics
+ Reduced participant variables (- But doesny
remove them)
-Time consuming
-Twice as many participants as repeated measures
design
Outline Independent and Dependant variables
• Independent variables are the variables the researcher manipulates in experimental studies. The variations of the IV form the conditions of the study (X-axis)
• The dependant variable: researcher measures the change/difference in the DV in an experimental study (Y-axis)
• Variables should be operationalised clearly stating exactly what the variable is and how it is measured
• (IV: clearly express each level/ DV: include measurement scale (e.g. time in seconds)
• In an experimental study, researchers can claim to have shown a causal relationship between the manipulation of the IV and the change in the DV
Outline co-variables
• Measurements made that are compared to see how they’re associated
• In a correlational study, two co-variables are assessed for a relationship however it’s not necessarily a causal relayionship
Outline confounding variables
• A variable other than the IV that changes systematically between the levels of IV, so when the IV is changed the confounding variable also changes
• This hides the IV’s true (lack of) effect on the DV as measurements are influenced by the confounding variable. It’s an extraneous variable that wasn’t controlled on the experiment.
Outline extraneous variables
• Any variable outside of the IV that could influence the measurement of the DV. This could cause an error, potentially showing a causal relationship between the IV and DV that isn’t there or hiding one that is
Identify and explain types of extraneous variables
• Demand characteristics: If the participant thinks they’ve discovered the research aim, they may alter behaviour to what the researcher wants
• Participant variables: A difference in performance between two groups in an IGD that isn’t related to the IV. Occurs if more people in one group have knowledge or traits that affect results than the other(s)
• Situational variables: Environmental factors in one condition and not the other
• Order effects: In a RMD where completing the first condition may affect the performance of the second condition
Describe how each extraneous variable can be controlled and identify general ways of controlling extraneous variables
• Demand characteristics: Single and double blind trials; a single blind trial is where the participant doesn’t know the aim and a double blind trail is when the researcher testing them also doesn’t know the aim
• Participant variables: Random allocation removes bias in assigning participants or materials to different levels of IV (not 100% effective as the same affect can occur due to chance)
• Situational variables: Standardised procedures
• Order effects: Counter balancing
• Extraneous variables can be controlled through pilot studies to eliminate them and peer review to identify extraneous or confounding variables
Outline ethics in psychological research and identify ethical issues in psychology
• Research is expected to adhere to a code of ethics published by the British Psychological Society (BPS) in the UK that’s designed to inform and assist members in the practical and professional application of society
• Informed Consent
• Deception
• Right to Withdraw
• Protection from Harm
• Confidentiality and Anonymity
• Debrief
Describe informed consent as an ethical issue including how it can be dealt with
• Providing participants with sufficient details of an investigation so they can make an informed decision as to whether they wish to participate or not
• Parental consent is required for people under 18 and consent cannot be obtained from individuals under the influence of drugs or alcohol or those deemed mentally unfit to give consent (severe mental illnesses)
• Revealing the true aims of the study when asking for consent can lead to demand characteristics which reduces the internal validity of the research. This can be avoided by using alternatives to informed consent:
- Presumptive Consent: Asks a group similar to the sample if they’d agree to the research and if they would it’s assumed participants would also agree
- Prior General Consent: participants agree to a long list of potential features not knowing which aspects will be part of this study
- Retroactive Consent: Researcher asks for consent after the study and if the participant doesn’t agree their data is destroyed
Describe informed consent as an ethical issue including how it can be dealt with
• Withholding information or misleading participants is unacceptable, especially if they’re likely to object or show unease once debriefed.
• Participants shouldn’t be mislead without scientific or medical justification. Sometimes it’s necessary for participants to not know the purpose of the study to get realistic results (e.g. research into conformity such as Asch, 1955)
If research requires deception:
• An ethics committee (group of experts) will conduct a cost-benefit analysis
• It should be explained in the debrief as well as in the aim of the study or any other groups.
• It should be checked that no harm was done and offer counselling or other assistance if it was.
• They should be reminded they’re still able to withdraw their data and ensure confidentiality of findings
Identify the issue with cost-benefit analysis
The true value of the study to society often isn’t known for many years and so a cost-benefit analysis can be difficult to accurately conduct
Describe right to withdraw as an ethical issue
Participants should be aware they can leave the study at any time and can withdraw their data after a study is finished. It’s important participants are informed of this in the consent form, standardised instructions and then reminded in the debrief
Describe protection from harm as an ethical issue
Researchers have a responsibility to protect participants from physical and mental harm during the investigation
Describe confidentiality and anonymity as an ethical issue
• Participant data shouldn’t be disclosed to anyone unless agreed in advance. Numbers should be used instead of names in published research papers
• Confidentiality means that the data can be traced back to the names, whereas anonymous data cannot be, as the researchers collect no names. Confidential data is preferable if participants are followed up later
Describe debrief as an ethical issue
• All relevant details of a study should be explained to participants before and after. A debrief is improtant if deception’s been used but doesn’t provide justification for unethical aspects
• Participants should leave the study in no worse state than they started it
