Psychology - research methods

What is a hypothesis?

• A statement which clearly describes the relationship between variables as stated by the theory (e.g. drinking SevenUp soda causes people to become more talkative)

• Directional hypothesis: researcher clearly states the difference anticipated between two conditions (include words like more, less, higher, faster, etc)

• Non-directional hypothesis: states a difference between conditions but does not specify the nature of this difference

Operationalisation of variables

• ensuring the variables are measurable as possible (e.g. adding units)

• Example of an operationalised hypothesis: After drinking 300ml of SevenUp soda, participants will say more words in the next 5 minutes than participants who drink 300ml of water

Laboratory experiments

• Laboratory experiments are conducted in highly controlled environments where the scientists manipulate the independent variable

• Strength: have high control over extraneous variables so researchers can ensure that any effect of the DV is most likely a result of manipulation of the IV, so lab experiments high internal validity as scientists can demonstrate cause and effect

• Limitation: low mundane realism, environment may not reflect everyday life, so in an unfamiliar context the participant may behave unusually, meaning experiment has low external validity as findings lack generalisability beyond the controlled research setting. Participants might also exhibit demand characteristics due to awareness of being tested.

Field experiments

• Field experiments take place in the participants' usual environment, but the researcher manipulates the IV

• Strength: higher mundane realism as the environment is more natural or typical for the participant, so behaviour produced may be more valid, especially since participants are unaware of being studied so this means they have high external validity.

• Limitation: challenging to obtain fully informed consent as researcher may want to preserve hypothesis to avoid demand characteristics, inducing ethical issues on deception + psychological harm

Natural experiments 

• Natural experiments are when the researcher measures the effect of an IV on a DV but has no control over the IV, the research setting does not necessarily have to be natural (participants may be tested in a lab)

• Strength: provide opportunities for research that could not otherwise be undertaken for practical/ethical reasons (e.g. Rutter's study of institutionalised Romanian adoptees) so have high external validity as they involve studying real-world issues

• Limitation: Naturally occuring events may only happen rarely, reducing the opportunity for researching and limiting the scope for generalising findings to other similar situations

Quasi experiment

• Quasi experiments have an IV based on existing difference between ps (e.g. age, gender) which simply exists and cannot be changed

• Strength: happen in controlled conditions so can be replicated easier due to the high level of control as ps are not randomised, ensuring new extraneous variables are not introduced when repeating the experiment

• Limitation: cannot randomly allocate participants to conditions so leads to selection bias, where results are influenced by pre-existing differences between the groups so cannot determine outcome as solely caused by IV

Extraneous variables

• Any other variables (that are NOT the IV) which could potentially influence the DV

• Usually identified at the start of the study, researcher tries to minimise their impact

Demand characteristics

• Ps attempt to work out aim of experiment by interpreting cues

• Behave how they think they will be expected to act based on experimental situation, either over-perform to please experimenter or under-perform to sabotage results of study

• So ps behaviour not natural, demand characteristics = extraneous variable that may affect DV

Investigator effect

• unwanted influence of investigator on research outcome

• Hugh Coolican (2006) points out can include unconscious cues (e.g. smiling more with certain ps) and expectancy effects

• Leading questions

Randominsation

• Using chance methods to minimise effect of extraneous variables (e.g. researcher’s unconscious biases) on outcome

• E.g. in memory experiment where ps recall words from a list, words should be randomly generated

Standardisation

• ensure ps subject to same environment, information, experience

• list of exactly what will be done in study, e.g. standardised instructions read to ps

Control groups

• Comparison group to determine whether IV had effect on DV

• Both groups have differing IVs

Independent group design (experimental designs)

• All ps experience one level of the IV (Group 1 experiences one IV, group 2 experiences a different IV)

• Strength: order effects not problematic, ps less likely to guess aim of study

• Limitation: Ps who occupy diff groups not same in terms of ps variables - if researcher finds a mean diff between groups on the DV, may be due to ps variables rather than effects of IV - this could be extraneous v which reduces validity of findings

Repeated measures design (experimental designs)

• All ps experience both conditions of the experiment

• Each participant experiences condition A, then they all later experience condition B

• Mean results from both conditions compared to find differences

• Strength: ps variables are controlled, therefore higher internal validity

Matched pairs design (experimental design)

• Ps paired together on similar variables relevant to experiment (e.g. IQ)

• Then one p from each pair allocated to a different experimental condition

• Controls effect of ps variables

• Strength: ps only partake in a single condition so order effects + demand characteristics less of a problem

• Limitation: ps can never be matched exactly, some important differences which act as extraneous variables affecting DV

Random sample

• Obtain a list of all members in target population, randomly assign each p a number

• Use a lottery method (e.g. random number generator) to select ps in sample

• Strength: potentially unbiased, extraneous variables potentially divided equally between groups, enhancing internal validity

• Limitation: although probability suggests random sampling likely to produce more representative sample than methods like opportunity, random sample can still be unrepresentative, e.g. select many ps with the same characteristics

Systematic sample

• Every nth member of a target population selected (e.g. every 3rd house on a street)

• Sampling frame produced where list of target population is organised into

• Sampling system nominated (e.g. every 3rd, 6th person etc) then researcher begins from a randomly determined point (reduces bias) then works through sampling frame until sample complete

• Strength: Objective, once system for selection established researcher has no influence over who is chosen

• Limitation: ps may refuse to take part, resulting in volunteer sample which would be biased

Stratified sample

• Composition of sample reflects proportions of people in subgroups (strata) within target population

• Identify the different strata that make up population, work out proportions needed for sample to be representative

• Select ps that will compose each strata via random sampling

• Strength: representative sample, accurately reflects composition of population so findings can be generalised

• Limitation: identified strata cannot reflect all different subgroups/strata of population, cannot completely represent target population

Opportunity sample

• Selecting anyone who is nearby and available

• Strength: Economical in time and money, does not require list of target population and no need to divide them into strata

• Limitation: Ps all selected from same area so will have a certain demographic, reflecting a specific segment of population and not representative so findings cannot be generalised

Volunteer sample

• Ps select themselves to be part of the sample

• Researcher may advertise experiment, or ps may simply volunteer when researcher asks

• Strength: Ps more engaged and motivated so cooperate more, less likely to drop out

• Limitation: Volunteer bias, may attract a certain ‘profile’ of person who is curious + likely to please researcher + exhibit demand characteristics which affects generalisability of findings

Informed consent (ethical issues)

• Providing ps with a comprehensive outline of the study, including research aims, procedures, risks, benefits, rights (including right to withdraw)

• So ps can make informed judgement without being coerced or feeling obliged

• From researcher POV, informed consent might make study meaningless as ps behaviour will not be natural as they know aims of study

Deception (ethical issues)

• Deliberately misleading or withholding information from ps during investigation

• Ps not received adequate information when agreeing to take part have not given informed consent

• Occasions where deception can be justified if does not cause ps undue distress

Protection from harm (ethical issues)

• Ps should not be placed at more risk than in daily lives, protected from physical and psychological harm (e.g. being embarrassed or in undue stress)

• Ps reminded that they have right to withdraw at any point in investigation

Privacy and confidentiality (ethical issues)

• Ps have right to control personal information

• Confidentiality should be protected (right to have any personal data protected)

BPS code of conduct (ways of dealing with ethical issues)

• British Psychological Society ethical guidelines/code of ethics

• Aim to ensure all ps respected and considered during every reserach phase

• Implemented by ethics committees in research institutions who use a cost-benefit approach to see whether proposals are ethically acceptable

Dealing with informed consent (dealing with ethical issues)

• Ps should be issued a consent letter/form to sign with relevant info which might affect decision to participate

• Ps UNDER 16 require parental consent

Dealing with deception + protection from harm (dealing with ethical issues)

• Ps should be fully debriefed after study

• Made aware of investigation’s actual aims and details not supplied during study (e.g. existence of other groups or experimental conditions)

• Ps informed of what data will be used for, given right to withdraw info before, during, after study + withhold data, crucial if retrospective consent is a feature of the study

Dealing with privacy + confidentiality (dealing with ethical issues)

• If personal details held, must be protected

• If details held must maintain anonymity - researcher refers to. ps using numbers/initials

• During briefing/debriefing, ps reminded that data will be protected and not shared with other researchers

What are pilot studies?

• Small-scale trial run of an intended investigation using a handful of ps instead of the total number

• Checks if the investigation will progress smoothly

• Not just restricted to experimental studies, used for self-report techniques to assess clarity of questions

• Allows researcher to identify any potential issues and to modify the deisgn/procedure of the study

What is a single-blind procedure?

• Ps not told aim of research or experimental conditions at the beginning of the study

• Information that might create expectations not revealed until the end of the study, controls effect of demand characteristics

What is a double-blind procedure?

• Neither ps nor researcher aware of investigation’s aims, a third party (the ‘investigator’) conducts investigation without knowing its main purpose

• Important in drug trials, treatment administered to ps by an individual who does not know which drugs are real or placebos

• This means expectations cannot influence ps behaviour, reducing researcher bias

What is a naturalistic observation?

• Occur in the setting or context where target behaviour would usually occur

What is a controlled observation?

• researcher observes ps in a structured environment, allowing some control over extraneous variables

What is a covert observation?

• Ps are unaware that they are the focus of study, behaviour observed secretly

• Must occur in public for observation to be ethical

What is an overt observation?

• Ps know behaviour is being observed, have given informed consent beforehand

What are participant observations?

• Researcher joins the participants to produce a first-hand account

What are non-participant observations?

• Researcher remains separate from those they are studying, records behaviour in an objective manner

What are behavioural categories?

• List of observable behaviours/target behaviours that are observable and measurable which researcher will study

• Strength: Make data collection more structured and objective as they are observable, measurable and self-evident, improving inter-observer reliability

• Limitation: Categories can be unclear, ambiguous and subjective, requiring further interpretation, risks becoming a ‘dustbin’ category

What is continuous recording?

• All instances of a target behaviour are recorded for a period of time

What is event sampling?

• Counting the number of times a behaviour occurs in a target individual or group

• Strength: Useful when target behaviour/event occurs quite infrequently, time sampling might miss it

• Limitation: If specified event is too complex, observer may overlook important details

What is time sampling?

• Recording behaviour at pre-established time intervals

• Strength: Reduces number of observations required to be made

• Limitation: Instances when behaviour is sampled might be unrepresentative of observation as a whole

What is a structured observation?

• Systematic research method used to observe and record specific behaviours or events according to a predefined framework

• Strength: Produces numerical data, analysis and comparison of behaviour observed between ps is straightforward

• Limitation: Hawthorne effect, ps alter behaviour as they know they are being observed so data is skewed as ps act differently compared to natural setting, decreases validity of findings

What is an unstructured observation?

• Qualitative research method where researchers observe and record behaviour in its natural setting without predetermined categories or frameworks

• Strength: Greater richness and depth of detail in data collected

• Limitation: Greater risk of observer bias as lacks objective behavioural categories so researcher may only record eye-catching behaviours, not necessarily important or useful

What is a questionnaire? (Self-report technique)

• A list of predetermined written questions for ps to respond, usually assessing thoughts/feelings

• Can be used as part of an experiment to assess the DV (e.g. whether views on the use of specific drugs are different in older and younger people)

• Open questions do not have a fixed range of answers, ps can answer in any way (open-ended) and produce qualitative data that is rich in detail but may be difficult to analyse as there are a range of responses

• Closed questions have a fixed number of responses, multiple choice, produce quantitative data which is easy to analyse but lacks depth/detail

What are the different types of interviews? (Self-report technique)

• Structured interviews: pre-determined set of questions asked in a fixed order

• Unstructured interviews: No pre-determined questions, conversational and aims to discuss a certain topic which prompts free-flowing interactions, interviewee encouraged to expand on answers

• Semi-structured interviews: Pre-determined questions but interviewer can ask follow up questions based on ps answers

What are likert scales? (designing questionnaires)

• Respondent indicates agreement with a statement of a scale, ranging from strongly agree to strongly disagree

What are rating scales? (designing questionnaires)

• Respondents identify a value that represents their strength of feeling about a particular topic

What are fixed-choice options? (designing questionnaires)

• List of possible options, multiple choice, respondents required to indicate those that apply

How do you design interviews?

• Interview schedule which includes questions to cover, standardised to reduce contaminating effect of interviewer bias

• Usually involve an interviewer and a single p, although group interviews may be appropriate

• Conduct in a quiet room away from others as will increase likelihood that interviewee will open up

• Begin interview with some neutral questions to make interviewee feel relaxed and comfortable and to establish rapport

• Reminder ps that answers will be confidential

How do you write good questionnaires?

• Avoid overuse of jargon/technical terms only known by specialists, e.g. do you agree that maternal deprivation in early childhood inevitably leads to affectionless psychopathy in later life?

• Avoid emotive language/leading questions as they show researcher’s attitude towards a topic and guides ps towards a particular answer so should be replaced with neutral alternatives, e.g. is it not obvious that student fees should be abolished?

• Avoid double-barrelled questions and double negatives which contain two questions in one, e.g. do you agree with the following statement: footballers are overpaid and should have to give twenty percent of wages to charity or I am not unhappy in my job

What are the different types of correlation?

• Positive: two variables increase move in the same direction

• Negative: one variable increases as the other decreases

• Zero: no relationship between variables

Evaluation of correlations

• Strength: useful preliminary tool for research, assessing strength/direction of a relationship provides precise + quantifiable measure of relationship between variables - strong relationships between variables or interesting patterns suggest ideas for possible future experimental research

• Strength: relatively quick and economical to carry out, does not require controlled environment or deliberate change of variables

• Limitation: Cannot demonstrate cause and effect between variables, unsure what co-variable causes the other to change

• Limitation: Does not account for intervening variables which influence the other variables

What is quantitaive data?

• Data that can be counted, usually numerical in the form of individual scores - open to statistical analysis and straightforward to convert graphically

What is qualitative data?

• Data expressed through words instead of numbers, written description of thoughts, feelings, opinions of ps