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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

introduction

justifys the need for conducting research, typically accounts for one third of the overall report

method

this and results account for 1/3 of the report - provides sufficient details so it can be replicated but remain focused

includes:

design, sample. materials, procedure, ethics

results

can only support a hypothesis and not provide or disprove it - summarises and presents the findings typically in graphs and tables

discussion

where the findings and results are interpreted in qualitative form -statistically analysed

referencing

includes fault details of any source material cited in the report

1. in text - fisher et al. (1987)


2. a book - author. initial. (year of publication). book title in italics. place of publication: publishers


3. web references - source (date), title: weblink (date assessed)


4. a journal article - author, initial. (year of publication) article title. journal title in italics, volune number in italics, issue number if available, page range.

objectivity

to be objective means that researchers must not let their personal opinions, judgments or biases interfere with the data

improving objectivity: systematic data collection, control, double blind, peer review

empirical method

the idea that knowledge is gained from direct experiences in an objective systematic and controlled way to produce quantitative data

falsifiability

the idea that a research hypothesis could be proved wrong

paradigm

a set of a shared assumptions and methods with a particular discipline - a free Michael module that shapes how we understand and interpret information and concepts

it encompasses the theories methods and standards that define a particular discipline or field of study

paradigm shift

when a paradigm shifts it can lead to significant changes in understanding

e.g. the earth is flat vs round

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