research methods
operationalisation
how a variable is clearly defined or measured
directional
past research
higher, more, less, increase
non-directional
lack of previous research
DIFFERENCE
extraneous variables
potential nuisance variable
have the potential to affect the DV
they do not vary systematically with the IV
situational- temp, noise, time of day
participant- age, gender, intelligence
demand characteristics
cues that may reveal the purpose of an experiment
screw-you: aim to disrupt results
please-you: aim to please
control/minimise: single blind experiment
investigator effects
reseacher unintentionally acts in a way to influence the outcome of the research e.g. smiling/body language
control/minimise: double blind experiment
controlling investigations
counterbalancing: nullify order effects (g1- condition a, then b. g2- condition b, then a)
random allocation: drawing from a hat, random name generator (reduces bias)
randomisation: random order to reduce bias
standardisation: all situational variables are kept identical, reduces investigator effects
reliability
a measure of consistency - if the coefficient is +.80 there is a high kevel of agreeableness, and congruency and therefore the results can be considared meaningful
test-retest reliability
administering the same research on the same person/group but on different occasions
if scores are correlated (+.80 coefficient) then there is a reliable degree of accuracy
behavioural categories
should be operationalised and discussed, observed by more than 1 researcher
then all ratings should be correlated to check for level of agreeableness/congruency
improving reliability
questionnaires: open questions can be changed to closed questions to limit potential ambiguity
interviews: use the same interviewer for all participants to reduce researcher bias
experiments: standardised instructions and procedures can help to control extraneous variables
observations: can lack objectivity due to research subjective interpretations
validity
refers to whether something is true, legitimate or accurate
internal vs external validity
internal- the degree to which the results are accurate and can be used to establish a cause and effect relationship
external- the degree to which the findings of a study can be applied to other people, settings or situations
how to improve internal validity
random allocations
standardized instructions
counterbalancing
single/double blind experiments
peer review
include more questions in questionnaires to reduce demand characteristics, guarantee anonymity
types of external validity (TEMP)
temporal validity: the extent to which studies can be applied over time
ecological validity: the extent to which psychologists can apply their findings to other settings
mundane realism: whete researchers use strange or unusual tasks
population validity: the extent to which the sample is representative of the target population (gender, age, ethnicity)
assessment of validity
face validity: the extent to which a test measures what it says it measures
concurrent validity: where there is close agreement between the data produced by the new test compared to the established test *congruence
how to improve validity
questionnaires: use a lie scale to check for consistency and reduce effects if social desirability bias. anonymity helps to improve validity as participants are less likely to give socially desirable answers
experiments: single/double blind experiments can be used to reduce demand characteristics. standardised instructions used to mitigate participant reactivity
observations: covert observation - behaviour will be more natural and authentic (reducing researcher subjectivity)
qualitative research: higher ecological validity due to the depth of data that is collected
order effects
fatigue, boredom, practice
piolet study
small scale prototypes of a study carried out in advance to fin out if there was any problems
they ensure time, effort and money are not wasted on a flawed methodology
repeated measures design
the same participants take part in each condition of the experiment
strengths of a repeated measures design
fewer participants are required
the same participants across conditions reduces the possibility of participant variables
issues of repeated measures design
having to repeat the tasks/conplete 2 tasks might increase the risk of order effects; where participants night lead to boredom
boredom might lead to detoriation in performance on the 2nd task
demand characteristics may feature
independent group design
2 seperate groups of participants experience 2 different conditions
strengths of independent group design
participants are less likely to become bored and give up so order effects are reduced
due to the participant only taking part in one condition there are less likely demand characteristics
issues in independent group design
more participants are required and this increases the time and money spent on recruitment
participant variables are more likely due to the increased individual differences e.g. age, gender - may lead to extraneous variables
matched pairs design
participants are paired together on a variable relevant to the experiment e.g. IQ, age, gender
strengths of matched pairs design
participant variables are reduced -participants are matched closely on their abilities and characteristics
participants only take part in a single condition so order effects and demand characteristics are less of a problem
issues of matched pairs design
participants can never be matched exactly
matching/ranking maybe time consuming and expensive
when do we use counterbalancing
repeated measures design- when the same participants are repeatedly exposed to the conditions
quasi experiments- when there is a lack of random assignment
why do we use counterbalancing
to minimise the impacts of extraneous variables on an experiment
to ensure order effects are balanced out across all experimental conditions
laboratory experiments
concluded under controlled conditions
the researcher manipulates the IV to measure the effect on the DV
the setting is not naturalistic
participants will be aware of the contrived/artificial nature of the situation
strength of laboratory experiments
high degree of control over extraneous variables - high degree of control of internal validity
standardised procedures are used
issues of laboratory experiments
due to the contrived/artificial nature, there's a lack of external validity, specifically ecological validity. this means findings cannot be generalised to the setting beyond the laboratory which lack mundane realism
Amanda characteristics exist because people changed their behavior and act in an unnatural manner
field experiments
are carried out in naturalistic conditions
the researcher manipulates the IV to measure the effect on the DV
typically participants do not know that they are taking part in an investigation
strength of the field experiment
high level of ecological validity and greater mundane realism
demand characteristics are reduced due to participants being unaware that they are taking part in an experiment
issues of field experiments
due to the natural setting goes less control over extremely as variables
ethical issues are associated due to participants not being able to give informed consent to take part
natural experiments
where researcher does not manipulate the IV
strengths of natural experiments
high level of external validity specifically ecological validity given that real world events are studied in natural setting
issues of natural experiments
maybe a lack of mundane realism
natural experiments have no control over the environment - increased extraneous variables
quasi experiments
containing naturally occuring IV but one that already exists
e.g. gender, personality, ethnicity
therefore participants can be randomized between the conditions
can be conducted in a natural or laboratory setting
strengths of quasi experiments
the compare different types of people with pre-existing characteristics easily
issues of quasi experiments
participants cannot be randomly allocated to research conditions
sampling
involves selecting participants from a target population
sample should always be representative of this target population to enable generalisation with the results
random sampling, systematic sampling, stratified sampling, opportunity sampling and volunteer sampling
random sampling
sophisticated, where every member of the target population has an equal transfer being selected
strength of random sampling
largely free from researcher bias
extraneous variables should be divided equally between a different groups, enhancing internal validity
issues of random sampling
difficult and time consuming
some individuals may be unwilling to take part
systematic sampling
involves using predetermined system that selects every nth person
strength of systematic sampling
largely free from researcher bias, therefore objective
quick
issues of systematic sampling
some individuals maybe I'm willing to take part
the samples may not be truly unbiased if every nth person has a particular characteristic in common e.g. all girls or all left-handed
stratified sampling
a sophisticated form of sampling where the composition of the sample reflects the proportions of people in certain subgroups
strengths of stratified sampling
lottery free from researcher bias
representative because it says designed to reflect the composition of the target population
issues of stratified sampling
difficult and time consuming
it is not a perfect process as it cannot possibly reflect all of the individual differences that exist between those in the target population
opportunity sampling
involve selecting anyone who is available and willing
strengths of opportunity sampling
convenient quick and easy and saves money
issues of opportunity sampling
bias
volunteer sampling
involves participants self-selecting through advertisment on a poster/advert
strengths of volunteer sampling
quick and easy
participants are happy and willing to take part
issues of volunteer sampling
volunteer bias - one participant may be more willing
quantitative data
strengths: easy to analyse, more objective, less bias
issues: lacks representativeness and external validity
qualitative data
strengths: rich and detail, provides insight into the unique human experience, enhanced external validity
issues: subjective, investigator effects
primary data
refer to data that is reported by the original researcher e.g. an interview with people with OCD about their experiences
data doesn't already exist, it must be generated
strengths: high level of control
issues: time and effort
secondary data
information that was collected by other researchers for a purpose other than the investigation (third party) e.g. a research assessors how GCSE results of schools in her local area compare with the national average
data that already exists
strengths: less time consuming
issues: concern over accuracy
meta-analysis
combines findings from multiple previously published studies that have the same aims and hypotheses
studies or reviewed together either through qualitative review of previous research or statistical quantitative analysis to test for significance
strengths: , comparisons handy made easily if studies have the same aim and hypotheses
issues: issues of systematic publication bias, inherent differences. although studies are similar, there will exist differences which may mean that studies are not comparable
naturalistic observation
take place in an unaltered setting where the observer does not interfere in any way e.g. shopping centre
strengths: high ecological validity because behavior is naturally occurring
issues: issues with acertaining reliability
controlled observation
take place under strict conditions e.g. laboratory, prison study
often uses a one-way mirror
strengths: can be replicated to check for reliability
issues: lower external (ecological) validity as behavior is observed in an artificial setting
covert observations
consist of observing people without their consent e.g. one way mirror, joining a group as a member
strengths: investigator effects and demand characteristics are less likely as the behavior observed is more likely to be natural - increases the internal validity of the data
issues: ethical issues due to the participants not giving a informed consent
overt observations
where observations are open and participants are aware that they are being observed
strength: more ethical as informed consent can be gained and participants have the right to withdraw
issues: investigator effects and demand characteristics are more likely as the behavior observed is less likely to be natural
participant observations
involve the researcher who is observing, taking part in the activity
strengths: if a rapport can be established participants may behave more naturally, data obtained can be in depth due to the observer being in close proximity
issues: investigator effects and demand characteristics are more likely as the behavior observed is less likely to be natural
non participant observations
were the person conducting the research does not take part in the activity e.g. coaching
strengths: investigator effects and demand characteristics are less likely as behavior observed is more natural
issues: due to the lack of close proximity the research may miss certain behaviors of interest
inter-observer reliability
the extent to which 2 or more observers are observing and recording behaviour in a consistent way
structured observations
the use coded schedules - organises data into behavioral categories
strengths: researchers can compare behavior more easily
issues: problems acertaining high internal validity - some behaviours may be missed
unstructured observations
involves every instance of the observed behavior being recorded and described it is much detail as possible
strengths: richness and data allows for greater internal validity
issues: prone to observer bias due to lack of objective behaviour categories
time sampling
records behavior at prescribed intervals
strength: pure observations make it easier to manage
issues: not every behaviour will be counted which may lead to this being unrepresentative
event sampling
records number of times that the target population occurred e.g. tally
strength: every behavior of interest will be counted
issues: some behavior could be missed if there's too much happening at the same time
content analysis
QUANTITATIVE -> QUALITATIVE
a type of observation which involves studying people indirectly via communications they have produced (artifact) through qualitative data
for example: video or audio recording (interview transcripts), media (social media /books/magazines)
content analysis summary
•familiarize yourself with the artifacts (transcripts)
•identify an operationalize coding units
•include another researcher to discuss categories
•create a tally of the occurrences
•compare to check for reliability (ensure categories on mutually exclusive)
improving reliability of content analysis
-codes should be clearly defined measurable and operationalized
-researchers should be trained
-a pilot study should be used to analyze a smaller data set
-include another researcher to also operationalize artifacts and discuss findings with to increase reliability and prevent researcher buyer
thematic analysis
a form of content analysis but the outcome is qualitative
thematic analysis summary
1.data is collected
2. read the data/artifact first to spot patterns and themes
3. reread data/artifacts looking for emerging themes
4.annotate the artifact
5. using the annotations, categories can be determined
6. in the final part, analysing the artifact, direct quotes can be used
strengths and issues of content analysis
strength: high external validity and high ecological validity due to the conclusions being based on real life behaviour
issues: may be subjective and suffer from researcher bias when researchers interprets the text in a way that supports their pre-existing views
open questions
generates qualitative data
strengths: less chance of researcher bias
issues: participants may answer in a socially desirable way - lack validity
closed questions
generates quantitative data
strengths: easier to analyse and able to look for patterns and trends
issues: unable to pursue and explore responses that are of particular interest - may lack depth and detail
acquiescence bias
when you indicate a positive connotation (agreeing with a statement even when in doubt)
structured interviews
predetermines set of questions asked in the same order for each interviewee (standardisation)
strength: interviewer does not have to be highly trained, quantitative data is easy to analyse statistically
issues: does not allow for additional questions to be asked
unstructured interviews
more like a conversation where the interviewer is facilitating the discussion (not asking set questions)
strengths: generates large amount of qualitative data, investigator effects and demand characteristics are reduced
issues: qualitative data is more difficult to analyze statistically, more time consuming and costly
semi-structured interviews
mostly prepared questions but allows deviation
strengths: open questions help to reduced social desirability bias
issues: highly trained interviewer is required
case studies
strengths: provide rich detailed analysis, generates mostly qualitative data, can be used in circumstances that would ordinarily be considered ethical
issues: personal accounts are probe to inaccuracy and interviews are prone to social desirability bias
case studies vs questionnaires
case studies: longitudinal and observe changes over time, produces rich detailed qualitative data
questionnaires: provides a snapshot of experience, typically produces less detailed information
ethical issues - informed consent
the aims and consequences of the research should be made clear before they agreed to participate
dealing with it: presumptive consent (consent is presumed), prior general consent (before), retrospective consent (after)
ethical issues - deception
when information is deliberately withheld from participants
dealing with it: should be fully debriefed into all the true aim of the research and should be given the right to withdraw
ethical issues - right to withdraw
remove themselves or their data from the study at any stage
dealing with it: should be fully debriefed until the true aim of the research and should be given the right to withdraw
ethical issues - protection from harm
psychologists have the responsibility to protect their participants from physical or psychological harm - participants should leave the research in the same state as they entered in
dealing with it: should be reminded of the right to withdraw, should be debrief that the end, researchers should terminate the experiment if the level of psychological or physical harm is higher than expected
ethical issues - privacy and confidentiality
privacy:
the right to decide how information about them will be communicated to others
dealing with it: should we given the right to withdraw, researcher should explain that their information will be protected and kept confidential
confidentiality:
where a participants personal information is protected by law
dealing with it: participants are provided with a pseudonym, number or initial to protect their identity and assured in anonymity
ethical issues - debriefing
participants should be fully debriefed and told the true aim of the research and given the right to withdraw
peer review
an independent assessment process that takes place before a research study is published and undertaken by other experts in the same field
peer review process
-research proposals/manuscripts are submitted for assessment
-the reviewer provides recommendations on whether the research should be published or suggests improvements
-accept the manuscript
-accept the manuscript with revisions
-suggest the author makes revision
-reject the manuscript without the possibility of resubmission
purpose of peer review
assess the quality of findings, check the validity to avoid misinforming the public, assess work originality, retain the integrity of psychological research
strengths and issues of peer review
strengths: there is less opportunities for plagiarised work and duplications of research, avoids psychologists publishing flawed research that can reduce the public trust
issues: publication bias - researchers only publishing positive results
benefits of research on the economy
a psychologically healthy and well educated population can be more productive, producing more and higher goods and services
those in work will generate tax revenue that pays before public services
those in work have more money to spend on goods and services to help grow the economy
abstract
a summary of key points in the research is typically 150 to 200 words long
gives a general overview of the study - first information a reader will encounter