AS Level Psychology key facts

The core studies

Biological approach: Dement and Kleitman (sleep and dreams)

• Sample: 9 adults (7 men, 2 women), 5 studied in detail. They avoided alcohol and caffeine on the day of testing.
• Method: laboratory experiment with repeated measures (each sleeper woken in REM and in non-REM), plus a correlation and a short interview after each waking.
• Recall: dreams reported after about 80% of REM awakenings (152 of 191) but only about 7% of non-REM awakenings (11 of 160).
• Length: woken after 5 or 15 minutes of REM, sleepers usually chose the right length (45 of 51 correct for 5 minutes, 47 of 60 for 15 minutes).
• Direction: eye movements fitted the dream, e.g. up and down movements when the dreamer was climbing ladders.
• Strengths: the EEG is objective and the controls were good. Weaknesses: small sample, an unnatural place to sleep, and dream reports that cannot be checked.

Biological approach: Hassett et al. (monkey toy preferences)

• Sample: 34 rhesus monkeys in the analysis (11 males, 23 females), living in one social group at a research centre.
• Toys: 6 wheeled (e.g. truck, wagon) and 7 plush (e.g. teddy bear), one of each kind put out in each of seven 25-minute trials.
• Independent variable: sex of the monkey (naturally occurring, not manipulated). Dependent variable: frequency and duration of contact with each toy type.
• Design: independent measures for the comparison of males with females; data collected by observation.
• Result: males preferred wheeled toys; females showed no significant preference.
• Children were not tested: the monkey results were compared with earlier published data on children.
• Weaknesses: monkeys are not humans, and the toys were labelled masculine or feminine by people, not by the monkeys.

Biological approach: Hölzel et al. (mindfulness and brain scans)

• Sample: 16 adults on the MBSR course and 17 waiting-list controls, all healthy volunteers with little or no experience of meditation.
• Course: 8 weekly group sessions of 2.5 hours, one full day, and daily practice at home with recordings (body scan, yoga, sitting meditation).
• Design: longitudinal, with repeated measures (before and after) and a comparison between the two groups.
• Result: grey matter increased in the left hippocampus, the posterior cingulate cortex, the temporo-parietal junction and the cerebellum.
• Functions: these regions are linked with learning and memory, emotion regulation, thinking about oneself and perspective taking.
• Strengths: objective MRI data and a control group. Weaknesses: small volunteer sample and self-reported practice.

Cognitive approach: Andrade (doodling)

• Sample: 40 adults aged 18 to 55 from a research panel, 20 in the doodling group and 20 in the control group, randomly allocated.
• Method and design: laboratory experiment, independent measures.
• Independent variable: doodling (shading shapes) or not doodling. Dependent variables: names written while listening (monitoring) and items recalled in the surprise test.
• Message: about 2.5 minutes, in a flat voice, with 8 names of party-goers and 8 place names.
• Monitoring: doodlers wrote a mean of 7.8 correct names; controls 7.1.
• Recall: doodlers recalled a mean of 7.5 names and places; controls 5.8.
• Weaknesses: an artificial task, and no measure of how much each person actually daydreamed.

Cognitive approach: Baron-Cohen et al. (eyes test)

• Groups: 15 men with AS or HFA; 122 typical adults from the general population; 103 university students; 14 adults matched for IQ with the AS/HFA group.
• Revised test: 36 items, four choices each, a glossary of the words, and equal numbers of male and female faces.
• Mean Eyes Test scores (out of 36): AS/HFA 21.9; general population 26.2; students 28.0; IQ-matched 30.9.
• Mean AQ scores: AS/HFA 34.4; students 18.3; IQ-matched 18.9.
• Eyes Test and AQ scores were negatively correlated: more autistic traits went with lower Eyes Test scores.
• Control task: the AS/HFA group could judge the sex of each person from the eyes, so the problem was with mental states, not with seeing eyes.
• Weaknesses: still photographs of eyes are unlike real social life, and the AS/HFA group was small and all male.

Cognitive approach: Pozzulo et al. (line-ups)

• Sample: 59 children aged 4 to 7 and 53 adults aged 17 to 30.
• Targets: two familiar cartoon characters (Dora and Diego) and two unfamiliar human faces, each shown in a 6-second clip.
• Line-up: four photographs shown together, with a blank silhouette to point to if the target was not there.
• Independent variables: age group, type of target (cartoon or human), and target-present or target-absent line-up.
• Dependent variable: correct identification in target-present line-ups and correct rejection in target-absent line-ups.
• Target-present, correct identification: cartoons, children 0.99 and adults 0.95; humans, children 0.23 and adults 0.66.
• Target-absent, correct rejection: cartoons, children 0.74 and adults 0.94; humans, children 0.45 and adults 0.70.

Learning approach: Bandura et al. (aggression)

• Sample: 72 children (36 boys, 36 girls) aged about 3 to 6 from the Stanford University nursery school.
• Groups: 24 saw an aggressive model, 24 saw a non-aggressive model, 24 were controls. Groups were matched on ratings of the children's existing aggression.
• Independent variables: behaviour of the model, sex of the model, sex of the child. Dependent variable: aggression shown by the child.
• Observation: a record every 5 seconds for 20 minutes, giving 240 observations per child.
• Result: children who saw the aggressive model showed far more imitative physical and verbal aggression than the other groups.
• Sex differences: boys showed more physical aggression than girls, and boys imitated the male model more than the female model.
• Weaknesses: a Bobo doll is made to be hit, only short-term effects were measured, and young children were shown aggression.

Learning approach: Fagen et al. (elephant learning)

• Sample: 5 female elephants at a stable in Nepal: 4 juveniles and 1 adult. They were trained with their handlers (mahouts) present.
• Primary reinforcer: food, which meets a biological need. Secondary reinforcer: the whistle, which gained its value by being paired with food.
• Capture: reward a behaviour the animal does naturally. Lure: use food to guide the animal into position. Shaping: reward actions that come closer and closer to the target.
• Behavioural chaining: join separately trained actions into one sequence (trunk here, trunk up, bucket, blow, steady).
• Data: structured observation with a behavioural checklist; a behaviour was passed when the elephant did it correctly on at least 80% of test trials.
• Result: the 4 juveniles learned the full trunk wash within the study; the adult did not, possibly because of her age and health.
• Weaknesses: very small sample, no comparison group, possible observer bias.

Learning approach: Saavedra and Silverman (button phobia)

• Method: case study of one boy, using interviews with the boy and his mother, observation and self-report ratings.
• Feelings Thermometer: a 9-point scale from 0 to 8 on which the boy rated his distress.
• Hierarchy: buttons ranked from least to most distressing. Large denim jean buttons were rated lowest (2) and small clear plastic buttons highest (8).
• Stage 1: real-life (in vivo) exposure with positive reinforcement from his mother. He handled more buttons, but his distress ratings went up.
• Stage 2: imagery exposure, in which he imagined how buttons looked, felt and smelled and talked about them. His distress ratings fell.
• Result: the phobia was gone at the 6-month and 12-month follow-ups, and he could wear small clear buttons on his school uniform.
• Weaknesses: one child, so results may not generalise; no comparison; ratings are subjective.

Social approach: Milgram (obedience)

• Aim: to find out how far people would obey an order to give increasingly strong shocks to another person.
• Sample: 40 men aged 20 to 50 from the New Haven area, volunteers who answered a newspaper advertisement or a mailed invitation.
• Shock generator: 30 switches from 15 volts to 450 volts, going up in 15 volt steps. Obedience was measured as the highest shock given.
• No voice-feedback in this version: the learner pounded on the wall at 300 volts and then stopped answering.
• Results: all 40 went to at least 300 volts; 26 of 40 (65%) went to 450 volts. Signs of stress included sweating, trembling, nervous laughter and three seizures.
• Dispositional hypothesis: obedience comes from personality. Situational hypothesis: most people obey in that situation. The results support the situational one.
• Ethics: deception, psychological harm and pressure against the right to withdraw; participants were debriefed afterwards.

Social approach: Perry et al. (personal space)

• Aim: to investigate whether oxytocin affects preferred personal space, and whether the effect depends on empathy.
• Sample: 54 male university students; empathy was measured by a questionnaire (the Interpersonal Reactivity Index).
• Independent variable: oxytocin or placebo (a spray with no active hormone). Each participant had both, about a week apart, in a double-blind procedure.
• Experiment 1: computerised Comfortable Interpersonal Distance Scale. A figure (stranger, authority figure, friend or a ball) approaches and the participant stops it where he would feel uncomfortable.
• Experiment 2: choosing between pairs of pictures of rooms that differed in features such as the distance between two chairs.
• Result: with oxytocin, high empathy participants chose closer distances than with placebo; low empathy participants did not, and in Experiment 1 they preferred more distance.
• Evaluation: good controls and two measures, but screen tasks are artificial and the sample was all male students.

Social approach: Piliavin et al. (subway Samaritans)

• Aim: to investigate bystander helping in a real-life emergency and the factors that affect it.
• Sample: about 4,450 subway passengers, an opportunity sample who did not know they were in a study; 103 trials.
• Independent variables: type of victim (cane or drunk), race of victim (black or white), whether and when a model helped, and the number of bystanders.
• Controls: the victim collapsed 70 seconds after the train left the station, on a journey of about 7.5 minutes with no stops; all victims dressed alike.
• Results: the cane victim got spontaneous help in 62 of 65 trials (95%); the drunk victim in 19 of 38 trials (50%). About 90% of first helpers were men.
• No diffusion of responsibility was found: help was not slower or rarer in larger groups.
• Ethics: no informed consent, no right to withdraw, deception, possible distress and no debrief.

Research methodology

Experiments

• Laboratory experiment: high control and a standard procedure, so reliable and easy to replicate; but artificial, so lower ecological validity and more demand characteristics.
• Field experiment: natural behaviour and higher ecological validity; but less control of extraneous variables, and often no consent or debrief.
• Independent measures: different participants in each condition. No order effects, but participant variables can affect results. Use random allocation.
• Repeated measures: the same participants do all conditions. No participant variables, but order effects and demand characteristics. Use counterbalancing.
• Matched pairs: participants are paired on a relevant variable and one of each pair goes into each condition. Fewer participant variables and no order effects, but matching is slow and never perfect.
• Order effects: practice (getting better) and fatigue (getting tired or bored) in later conditions.
• Counterbalancing: half do condition A then B, half do B then A. A control group or condition gives a baseline for comparison.

Self-reports

• Closed questions: fixed answers (yes/no, rating scales). Quantitative data, easy to analyse and compare, but little detail.
• Open questions: free answers. Qualitative data, rich in detail, but slow to analyse and open to the researcher's interpretation.
• Structured interview: the same fixed questions in the same order for everyone. Reliable and easy to replicate, but not flexible.
• Unstructured interview: a topic but no fixed questions. Detailed and flexible, but hard to compare and to replicate.
• Semi-structured interview: some fixed questions plus follow-up questions.
• Social desirability bias: answering in a way that makes you look good instead of telling the truth.
• Questionnaires reach many people quickly and cheaply, and being anonymous can make answers more honest; interviews allow questions to be explained.

Case studies

• Case study: one individual or unit studied in detail, usually with several methods.
• Data are mostly qualitative and rich, but can include quantitative data such as test scores.
• Strength: depth and detail, high validity, and the chance to study rare cases that would be impossible or unethical to create.
• Strength: can suggest new ideas for later research.
• Weakness: findings cannot be generalised, because one case may be unique.
• Weakness: hard to replicate, and the researcher may become close to the participant and lose objectivity (researcher bias).
• Ethics: confidentiality is hard to protect when a case is unusual, and long, close study can be intrusive.

Observations

• Overt: participants know they are observed. Ethical, but behaviour may change (demand characteristics).
• Covert: participants do not know. Behaviour is natural, but there is no informed consent and privacy may be invaded.
• Participant observer: joins the group and gains insight, but may lose objectivity. Non-participant: stays apart and is more objective.
• Structured: behavioural categories and a tally chart give quantitative data that are easy to compare. Unstructured: detailed qualitative data that are harder to analyse.
• Naturalistic: high ecological validity, little control. Controlled: more control and easier to replicate, less natural.
• Categories must be operationalised (defined clearly) so that observers record the same thing.
• Inter-observer reliability: two or more observers watching the same behaviour produce closely matching records.

Correlations

• Positive correlation: as one co-variable increases, the other increases. Points slope upwards from left to right.
• Negative correlation: as one increases, the other decreases. Points slope downwards from left to right.
• Strength: r runs from −1 to +1. Near +1 or −1 is strong; near 0 is weak or no correlation. The sign shows direction, not strength.
• Co-variables must be operationalised: state exactly how each is measured, with units or a scale.
• No causality: A may cause B, B may cause A, or a third variable may affect both.
• Strength of the method: allows study of variables that cannot be manipulated for practical or ethical reasons, and can suggest ideas for experiments.

Longitudinal studies

• Longitudinal study: the same people are measured repeatedly over an extended time.
• Strength: shows real change and development within individuals, and long-term effects.
• Strength: no participant variables between ages or stages, unlike comparing different groups of different ages at one time.
• Attrition: participants leave the study. The sample gets smaller and may become biased if those who leave differ from those who stay.
• Weakness: takes a long time and costs a lot; results arrive slowly.
• Weakness: repeated testing can cause practice effects, and events in the world during the study may affect results.
• Ethics: consent should be checked again as the study goes on, the right to withdraw must stay open, and data must be kept confidential for years.

Aims and hypotheses

• Aim: the purpose of the study, e.g. "to investigate whether X affects Y".
• Alternative hypothesis: predicts a difference between conditions or a correlation between variables.
• Null hypothesis: predicts no difference or no correlation; any difference is due to chance.
• Directional (one-tailed): states the direction, e.g. higher, lower, faster, a positive correlation.
• Non-directional (two-tailed): says there will be a difference or a correlation but not which way.
• Use a directional hypothesis when earlier research or theory suggests the direction of the result.
• A good hypothesis names both variables in an operationalised (measurable) form.

Variables

• Independent variable (IV): the variable the researcher manipulates; it creates the conditions.
• Dependent variable (DV): the variable the researcher measures.
• The IV is the cause being tested; the DV is the effect.
• Operational definition: a clear statement of how a variable is manipulated or measured.
• An operationalised IV names the conditions, e.g. 200 mg of caffeine or no caffeine.
• An operationalised DV names the measure and its unit, e.g. reaction time in milliseconds.
• A DV can be measured by counts, times, scores on a test, rating scales or physiological measures such as heart rate.

Controlling of variables

• Control: keeping a variable the same in all conditions so it cannot affect the DV.
• Uncontrolled variable: a variable other than the IV that may affect the DV.
• Participant variables: differences between individuals, e.g. age, ability, motivation.
• Situational variables: differences in the environment, e.g. noise, lighting, time of day.
• Standardisation: the same procedure and instructions for every participant.
• Random allocation to conditions reduces the effect of participant variables in independent measures.
• Repeated measures removes participant variables between conditions; counterbalancing deals with order effects.

Types of data

• Quantitative data: numerical, e.g. a score of 14 out of 20.
• Qualitative data: descriptive, in words, e.g. a diary entry about feelings.
• Objective data: based on fact or direct measurement, not affected by opinion.
• Subjective data: based on a personal opinion, feeling or interpretation.
• Quantitative strength: easy to analyse and compare. Weakness: lacks detail.
• Qualitative strength: detailed and in depth. Weakness: hard to compare, open to researcher interpretation.
• Quantitative data are not always objective: a self-rating of mood out of 10 is a number but is subjective.

Sampling of participants

• Population: all the people the study is about. Sample: the people who actually take part.
• Opportunity sampling: uses whoever is available. Quick and easy, but likely to be biased and unrepresentative.
• Random sampling: equal chance for everyone, e.g. names from a hat or a random number generator.
• Random sampling avoids researcher bias but needs a full list of the population and takes time; those chosen may refuse.
• Volunteer (self-selecting) sampling: people respond to an advert or request.
• Volunteers are willing and can come from a wide area, but they may be a certain type of person, so the sample can be biased.
• Generalisation: applying the results from the sample to the population; it needs a representative sample.

Ethics

• Informed consent: participants know what the study involves before they agree; for children, a parent or guardian also consents.
• Right to withdraw: participants can leave at any time and can have their data removed.
• Lack of deception: participants should not be misled about the aim or procedure.
• Confidentiality: data are stored securely and individuals cannot be identified from them.
• Privacy: no observation in private places or of private matters without consent.
• Debriefing: after the study, explain the true aim and make sure participants leave in the state they arrived.
• Animals: replacement, suitable species, smallest numbers, minimal pain and distress, suitable housing and food.

Validity

• Validity: the study tests what it claims to test.
• Ecological validity: how far the findings apply to real-life settings and everyday tasks.
• Demand characteristics: features of a study that let participants guess the aim and change their behaviour.
• Objective measures raise validity; subjective measures can be biased by interpretation.
• Generalisability: how widely the findings apply beyond the sample; low when the sample is small or unrepresentative.
• Good controls and standardisation raise validity by removing uncontrolled variables.
• Single-blind and double-blind designs and hiding the aim reduce demand characteristics.

Reliability and replicability

• Reliability: the consistency of a measure or a procedure.
• Inter-rater / inter-observer reliability: agreement between two or more raters or observers working independently.
• Test-retest reliability: same test, same people, two occasions; similar scores show reliability.
• A strong positive correlation between the two sets of scores shows high reliability.
• Percentage agreement = (number of agreements ÷ total observations) × 100.
• Improve inter-observer reliability with clear operational definitions of behaviours and training of observers.
• Replicability: the study can be repeated exactly; standardisation and controls make this possible.

Data analysis

• Mode: the most frequent score. Median: the middle score in order. Mean: total of scores ÷ number of scores.
• With an even number of scores, the median is halfway between the two middle scores.
• Range = highest score − lowest score.
• Standard deviation: the average spread of scores around the mean; larger means more spread out.
• Bar chart: separate categories or conditions, with gaps between the bars.
• Histogram: continuous data in order on the x-axis, bars touching, frequency on the y-axis.
• Scatter graph: one point per participant for two measured variables; used for correlations.