how to write a hypothesis psychology aqa

Aims And Hypotheses, Directional And Non-Directional

March 7, 2021 - paper 2 psychology in context | research methods.

• Back to Paper 2 - Research Methods

In Psychology, hypotheses are predictions made by the researcher about the outcome of a study. The research can chose to make a specific prediction about what they feel will happen in their research (a directional hypothesis) or they can make a ‘general,’ ‘less specific’ prediction about the outcome of their research (a non-directional hypothesis). The type of prediction that a researcher makes is usually dependent on whether or not any previous research has also investigated their research aim.

Variables Recap:

The  independent variable  (IV)  is the variable that psychologists  manipulate/change  to see if changing this variable has an effect on the  depen dent variable  (DV).

The  dependent variable (DV)  is the variable that the psychologists  measures  (to see if the IV has had an effect).

It is important that the only variable that is changed in research is the  independent variable (IV),   all other variables have to be kept constant across the control condition and the experimental conditions. Only then will researchers be able to observe the true effects of  just  the independent variable (IV) on the dependent variable (DV).

Research/Experimental Aim(S):

An aim is a clear and precise statement of the purpose of the study. It is a statement of why a research study is taking place. This should include what is being studied and what the study is trying to achieve. (e.g. “This study aims to investigate the effects of alcohol on reaction times”.

It is important that aims created in research are realistic and ethical.

Hypotheses:

This is a testable statement that predicts what the researcher expects to happen in their research. The research study itself is therefore a means of testing whether or not the hypothesis is supported by the findings. If the findings do support the hypothesis then the hypothesis can be retained (i.e., accepted), but if not, then it must be rejected.

Three Different Hypotheses:

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AQA A-LEVEL PSYCHOLOGY REVISION NOTES: RESEARCH METHODS

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PSYCHOLOGY AQA  A-LEVEL UNIT 2 (7182)

The syllabus.

METHODS, TECHNIQUES & DESIGN

• Primary and secondary data, and meta-analysis. Quantitative and qualitative data
• Aims, operationalising variables, IV’s and DV’s
• Hypotheses - directional and non-directional
• Experimental design - independent groups, repeated measures, matched pairs
• Validity – internal and external; extraneous and confounding variables; types of validity and improving validity
• Control – random allocation, randomisation, standardisation
• Demand characteristics and investigator effects
• Reliability; types of reliability and improving reliability
• Pilot studies
• Correlation analysis – covariables and hypotheses, positive/negative correlations
• Observational techniques – use of behavioural categories
• Self-report techniques – design of questionnaires and interviews
• Case studies
• Content analysis
• Thematic Analysis

PARTICIPANTS; ETHICS; FEATURES OF SCIENCE & SCIENTIFIC METHOD; THE ECONOMY

• Selecting participants and sampling techniques
• The British Psychological Society (BPS) code of ethics and ways of dealing with ethical issues
• Forms and instructions
• Peer review
• Features of science: objectivity, empirical method, replicability and falsifiability
• Paradigms and paradigm shifts
• Reporting psychological investigations
• The implications of psychological research for the economy

DESCRIPTIVE STATISTICS

• Analysis and interpretation of quantitative data. Measures of central tendency - median, mean, mode. Calculating %’s. Measures of dispersion – range and standard deviation (SD)
• Presentation and interpretation of quantitative data – graphs, histograms, bar charts, scattergrams and tables
• Analysis and interpretation of correlational data; positive and negative correlations and the interpretation of correlation coefficients
• Distributions: normal and skewed

INFERENTIAL STATISTICS

• Factors affecting choice of statistics test: Spearman’s rho, Pearson’s r, Wilcoxon, Mann-Whitney, related t-test, unrelated t-test, Chi-Squared test
• Levels of measurement – nominal, ordinal, interval
• Procedures for statistics tests
• Probability and significance: use of statistical tables and critical values in interpretation of significance; Type I and Type II errors
• Introduction to statistical testing: the sign test

INTRODUCTION

Research Methods is concerned with how psychologists conduct research in an attempt to find evidence for theories . A theory without research support is really just someone’s reasoned opinion, not a proven fact .

Psychologists generally adopt a scientific approach to studying the mind and behaviour. The scientific method is based on empiricism – the belief that one can gain true knowledge of the world through the unbiased observation and measurement of observable, physical phenomena .

Laboratory experimentation is the method most associated with science as it involves the careful manipulation of variables to establish whether there are cause-effect relationships with other variables: for example, will an increase in testosterone cause an increase in aggression?

Psychologists face difficulties, however, in that they are studying highly complex, reactive creatures (humans) who tend not to behave in the predictable way that the objects of study of physics, chemistry and biology do. Equally, people put in an artificial laboratory situation who are aware they are being observed will tend not to behave in a normal, natural way. For this (and various other) reasons, psychologists have developed a variety of other means of research such as field and natural experiments , correlation studies and observations .

A debate exists within Psychology as to what extent it is desirable and/or appropriate to apply scientific methods to the study of humans. Many psychologists have argued that a strictly scientific approach reduces the complexity of human behaviour to an overly reductionist level and that human psychology can be better understood by more detailed and in depth methods such as questionnaires , interviews , case studies and content analysis .

Whereas biological approaches , behaviourism and cognitive psychology tend to favour quantitative , scientific , laboratory based approaches, psychodynamic and humanistic approaches argue for a more qualitative , descriptive approach.

The syllabus focuses on scientific approaches and how to design studies which produce valid (accurate/truthful) findings. There is also an emphasis on the statistical analysis of quantitative data .

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METHODS, TECHNIQUES & DESIGN ( A-level Psychology revision notes)

PRIMARY AND SECONDARY DATA, AND META-ANALYSIS. QUANTITATIVE AND QUALITATIVE DATA

Psychologists conduct research in an attempt to find evidence for theories . Throughout the history of Psychology there has been an on-going debate in regard to what methods of investigation are appropriate to study the mind and behaviour. Whilst some favour a highly scientific, lab-based, experimental approach , others argue that these methods are inappropriate to the study of humans and support more in depth, less scientific, qualitative approaches such as interviews, case studies and observations.

• Laboratory Experiments
• Field Experiments
• Natural & Quasi Experiments
• Correlation Studies
• Observational techniques
• Self-report Questionnaires
• Self-report Interviews
• Case Studies
• Content Analysis

Each of these methodologies uses different research techniques and has associated strengths and limitations .

Data (information produced from a research study) may be

• Quantitative : numerical data that can be statistically analysed . This has the advantage of being more objective , quicker to gather and analyse, and can be presented in ways that are easily and quickly understandable. However, data can be superficial , and lacking depth and detail of participants’ subjective
• Qualitative: written , richly detailed, descriptive accounts of what is being studied. This allows participants to express themselves freely. However, these methods are time consuming , can be costly to collect, difficult to analyse and suffer from problems of subjectivity .

Data gathered by psychologists can be

• Primary – directly collected by the psychologist them self: e.g. questionnaires, interviews, observations, experiments.
• Secondary – data collected by others: e.g. official statistics, the work of other psychologists, media products such as film or documentary.
• Meta-analysis refers to when a psychologist draws together the findings and conclusions of many research studies into 1 single overall conclusion.

LABORATORY EXPERIMENTS ( AQA A-level Psychology revision notes)

Lab experiments are the most complex methodology in terms of their logic and design.

Any experiment begins with an aim .

The aim is a loose, general statement of what we intend to investigate: e.g. does alcohol affect driving performance?

Any experiment looks at the cause-effect relationship between 2 variables . A variable is any factor/thing that can be measured and changes. For example, intelligence, aggression, score on authoritarian personality scale, short-term memory capacity, etc. The two variables in the above example are alcohol and driving performance.

OPERATIONALISING VARIABLES

In psychological research we often want to find a way of expressing a variable numerically. This is referred to as operationalising a variable . Variables can be operationalised in many ways – for example,

• Intelligence can be operationalised through an IQ test
• Authoritarianism can be operationalised through a questionnaire
• STM capacity can be operationalised through a task such as seeing how many digits a participant can remember at once.

INDEPENDENT & DEPENDENT VARIABLES

Of the 2 variables we are testing in an experiment, one is referred to as the Independent Variable (IV) and the other is referred to as the Dependent Variable (DV) .

In an experiment we test 2 conditions of the IV against the DV to see if there is a significant difference between how the 2 conditions of the IV affect the DV .

For example, we could set up an experiment to examine the cause-effect relationship between alcohol and driving performance . To do this we could recruit 100 volunteer participants , randomly split them into 2 groups of 50 , give the 1 st group a measure of alcohol and then let them drive on a driving simulator which would produce a score of x/20 for driving performance. The 2 nd group would be given no alcohol and allowed to drive on the simulator. Therefore, we would end up with 50 scores of x/20 for those who had driven after consuming alcohol, and 50 scores of x/20 for those who had driven and not consumed alcohol.

We could take the mean average score for each group and compare them. For example, we may find that those who had drunk alcohol scored a mean average of 10/20 whereas those who hadn’t consumed alcohol scored an average of 16/20. What we have done in this experiment is to test 2 conditions of the IV (alcohol and no alcohol) against the DV (driving performance) to see if there is a significant difference between how the 2 conditions of the IV affect the DV . If we find a significant difference between how the 2 conditions of the IV affect the DV we have found evidence that there is a cause-effect relationship between alcohol consumption and poor driving performance .  

From the aim of our experiment we formulate our hypotheses.

A hypothesis is an exact, precise, testable prediction of what we expect to find in an experiment.

• The Experimental/Alternative Hypothesis : a statement predicting that we will find a difference between how the 2 conditions of the IV affect the DV: e.g. ‘There will be a significant difference in driving performance between participants who have and have not consumed alcohol’ .

The above hypotheses are non-directional (or 2-tailed) hypotheses. This means that they do not make a prediction about the direction of results : i.e. they don’t predict that 1 of the groups is going to do better or worse than the other, they just predict that some kind of difference will occur.

However, if the experimenter strongly expects that results will go in a certain direction or previous research indicates this he may choose to apply a directional (or 1-tailed) hypothesis. This does make a prediction about the direction of results.

• Experimental Hypothesis (1-tailed): ‘Participants who have consumed alcohol will show significantly poorer driving performance than participants who have not consumed alcohol’.

EXPERIMENTAL DESIGN

In any experiment we always have at least 2 groups of participants performing in at least 2 experimental conditions . There are several different ways in which we can allocate (put) participants to different conditions each with associated strengths and limitations .

1. Independent Groups Design . Participants are split into 2 groups , each group performing in 1 condition only .

The limitations of this design are

• Participant Variables – the fact that individual differences between participants may affect the DV without us being aware of it and thus reduce the validity (accuracy) of our results. For example, we may find that participants in the alcohol condition are all excellent drivers with high alcohol tolerance, whilst participants in the no-alcohol condition are all poor drivers. Thus, the alcohol group may drive better and we might (falsely) conclude that alcohol improves driving performance. The problem of participant variables is reduced with a large sample and by randomly allocating participants to the 2 conditions.
• It requires more participants than a repeated measures design .

The advantage of this design is that we will not encounter Order Effects (see below).

2. Repeated Measures Design . In this design all participants perform in the 1 st condition and then perform in the 2 nd condition . This allows us to directly compare participants’ performance across the 2 conditions.

• Order Effects – when participants perform in condition 1 then condition 2 their performance in the 2 nd condition may either improve due to practise or get worse due to boredom or tiredness . In an attempt to overcome the problem of order effects we can use counterbalancing . This involves ½ the participants performing in condition 1 first, then condition 2, while the other ½ of the participants perform in condition 2 first, then condition 1. (This is thought to balance out the problem of order effects).
• They may also work out the aim of the study and exhibit demand characteristics (see below).

The advantage of this design is that there is no possibility of participant variables threatening the validity of the study.

3. Matched Pairs Design : This design overcomes the problem of order effects and participant variables . Before the study begins we need to find participants who we can match with each other in terms of relevant characteristics such as age, gender, IQ, etc. The study then runs as an independent groups design , however, because each participant is matched with another participant in the other condition participant variables are less of a problem. The disadvantage of this design is it may be costly, time-consuming and difficult to find participants who match precisely .

It is highly important that experiments are well designed and run - otherwise findings may be inaccurate and lead us to draw false conclusions.

Validity generally refers to the truthfulness and accuracy of our findings.

We can distinguish between 2 types of validity.

• INTERNAL/EXPERIMENTAL VALIDITY . This relates to whether we are really measuring what we think we are measuring. In any experiment we are trying to isolate the effect of the IV on the DV . Therefore, we need to ensure that no other unwanted, uncontrolled extraneous variables are affecting the DV without our knowledge. If an extraneous variable does affect our final results, we refer to as a confounding (i.e. confusing) variable.

• Ecological Validity . This relates to the problem of whether studies conducted under highly controlled, artificial, lab situations can produce findings that can be generalised to everyday life, or whether behaviour shown by participants will be artificial . For example, in the drink-driving study, participants use a driving simulator which is not really similar to driving in a real car on a real road.
• Population Validity . If we only use small or biased/unrepresentative samples of participants, we may not be able to generalise findings to human behaviour in general.
• Temporal Validity . If studies were conducted a long time ago, it can be argued that their findings are not relevant to the present day. For example, Asch’s conformity study was conducted in 1950’s America and it has been argued that the climate of America at this time was particularly conformist. Social change since the 50’s has meant that people are now far more non-conformist and independent.

CONTROL OF EXTRANEOUS VARIABLES; RANDOM ALLOCATION, STANDARDISATION

Extraneous variables are variables which the experimenter has failed to eliminate or control which are affecting the DV without us being aware of it. This threatens the validity of the study and the accuracy of our findings.

Extraneous variables must be carefully and systematically controlled . When designing an experiment, researchers should consider the following areas where extraneous variables may arise:

• Random allocation/randomisation of participants to experimental conditions. To avoid any bias on the behalf of the researcher, participants should always be divided into groups randomly.
• Standardisation of instructions and procedures. Participants should be given exactly the same instructions as each other and go through exactly the same procedures as each other to avoid differences in these acting as extraneous variables.
• Participant variables : participants’ age, intelligence, personality and so on should be controlled across the different groups taking part. For example, in the above experiment: gender, driving experience, alcohol tolerance, body mass, etc. Participants could also be pre-tested and put into a matched-pairs design.
• Situational variables : the experimental setting and surrounding environment must be controlled. This may include the time of day, the temperature or noise effects.
• Order effects : participants may improve or get bored performing in different conditions. This can be controlled by using independent groups, matched participants or counter-balancing.
• Demand Characteristics or Investigator Effects (see below).
• A control group is a group of participants from who act as a baseline from which differences in the experimental group are measured. For example, we might compare improvements in mood scores for an experimental group who received therapy against a control group who none.

TYPES OF VALIDITY AND IMPROVING VALIDITY

It is highly important that experiments are well designed and run - otherwise findings may be inaccurate and lead us to draw false conclusions. If studies are to be regarded as credible, they must be valid .

The following techniques are used to check for/achieve/ensure validity .

• Face validity is the extent to which a test is subjectively viewed as being able to measure the concept it claims to measure. In other words, a test can be said to have face validity if it "looks like" it is going to measure what it is supposed to measure.
• Content Validity involves independent experts being asked to assess the validity/accuracy/appropriateness of instruments/tests used to measure a variable: e.g. agreeing that a particular IQ test is a valid measure of intelligence.
• Concurrent Validity involves comparing the validity of a new test/measure against an established test/measure whose validity is already known and trusted. For example, the results of a new form of IQ test could be tested against an old, established IQ test. If scores correlate between the 2 tests they are said to have concurrent validity.

THE RELATIONSHIP BETWEEN RESEARCHER AND PARTICIPANTS

The fact that an experiment is a social situation means that behaviour may be affected by the presence of others (experimenter and other participants) and the expectations that participants have. Thus, we may not be getting a valid picture of how people behave in the real world.

• Demand Characteristics refers to the fact that participants realise they are in an experiment and are being observed and tested. They may, therefore, alter their behaviour either to behave in ways they think the experimenter wants them to behave in or according to how they think they should behave. Participants may try to work out the aim of experiment and modify their behaviour accordingly. They may also show ‘social desirability bias’ – giving responses they believe are correct or moral, rather than answering honestly.
• Investigator Effects refers to the fact that the experimenter may consciously or unconsciously gives hints or clues to research participants about how he wants or expects them to behave.

RELIABILITY

Reliability of a study refers to the issue of if we conduct the study again will the study produce similar results ? Clearly, if a study produces wildly varying results each time it is carried out there is either no real cause-effect relationship between the IV and the DV or the design of the study is invalid . Therefore, repeating a study confirms previous findings.

TYPES OF RELIABILITY

Inter-rater reliability

• If a number of different observers are conducting the same observational study, we need to ensure the observers have inter-rater reliability . This means that observers are all defining behaviours and recording observations in the same way as each other . Thus, before the study begins observers should be trained through the use of, for example, a training video where they learn and are then tested on how to define and categorise behaviours in the same way as each other. We can assess inter-rater reliability by analysing the correlation between different observers score on the same behaviour. This will produce a correlation coefficient (see Correlation Studies and Spearman’s rho test): e.g. +0.96 = a strong positive correlation (they are rating things in the same way as each other).

Test-retest reliability

• Reliability of a test (e.g. IQ test) or questionnaire can be tested by asking a participant to complete the test/questionnaire, then complete it again 2 weeks and a month later. If answers are similar over a period of time, then the test/questionnaire can be said to have reliability. We can assess test-retest reliability by analysing the correlation between different test scores. This will produce a correlation coefficient (see Correlation Studies): e.g. +0.96 = a strong positive correlation (high similarity between different test scores).

PILOT STUDIES

A pilot study is a small scale version of the main study that is conducted in advance to ensure

• The procedures of the study will run smoothly
• That equipment/tests are functioning accurately
• That participants understand instructions
• That all extraneous variables are controlled

  STRENGTHS OF LABORATORY EXPERIMENTS

• High degree of control : experimenters can control all variables in the experiment. The IV and DV can be precisely defined (operationalised) and measured to assess cause-effect relationships - for example, the amount of caffeine given (IV) and reaction time (DV). This leads to greater accuracy and objectivity.
• Replication : other researchers can easily repeat/replicate the experiment and check results for reliability . This is much easier in a controlled laboratory situation as opposed to a field experiment conducted in the real world.

LIMITATIONS OF LABORATORY EXPERIMENTS

• Lack of ecological validity.
• Demand characteristics.

(Explain both these points in full according to above notes.)

FIELD EXPERIMENTS ( Psychology A-level revision)

A field experiment is carried out in the real world rather than under artificial laboratory conditions. Participants are exposed to ‘set-up’ social situation to see how they respond. The ‘naïve’ participants are unaware they are taking part in an experiment.

STRENGTHS OF FIELD EXPERIMENTS

• As the experiment is conducted in the real world levels of ecological validity are increased meaning that we can generalise behaviour to real-life behaviour.
• As participants do not know they are involved in an experiment they will not show demand characteristics .

LIMITATIONS OF FIELD EXPERIMENTS

• As the study is not conducted under tightly controlled laboratory conditions there is a greater chance that extraneous variables will influence the DV without the researcher being aware of this.
• Field experiments often involve breaking ethical guidelines : e.g. failing to get participants consent, deceiving participants, failing to inform them of their right to withdraw or debriefing them, etc.

NATURAL & QUASI EXPERIMENTS ( A-level Psychology revision)

In a natural experiment the psychologist does not manipulate or ‘set up’ a situation to which participants are exposed to, rather they observe a change in the natural world (IV) and assess whether this has an effect on another variable (the DV) . For example, whether the introduction of TV into remote communities (IV = (i) no TV, and (ii) TV) and measuring whether this has had an effect on children’s’ aggressiveness (DV). A quasi-experiment is the same as a normal experiment but participants are not randomly allocated to conditions .

STRENGTHS OF NATURAL/QUASI EXPERIMENTS

• As the experiment is conducted in the real world levels of ecological validity are increased.
• In natural experiments, as participants do not know they are involved in an experiment they will not show demand characteristics.

LIMITATIONS OF NATURAL/QUASI EXPERIMENTS

• Natural experiments may involve breaking ethical guidelines : e.g. failing to get participants consent to be observed, failing to inform them of their right to withdraw or debriefing them.

CORRELATION ANALYSIS ( AQA A-level Psychology revision)

 A correlation study involves measuring the relationship between 2 covariables : e.g. height and weight, stress and illness, ‘A’ Level point score and income aged 30, etc. (However, correlation studies only measure whether there is  some kind of relationship , not whether there is a cause-effect relationship .)

 The relationship may either be

To conduct a correlation study we need to operationalise the 2 co-variables and their relationship can then be plotted on a scattergram for each participant. The general pattern revealed should indicate whether the relationship is positive or negative and how weak or strong the relationship is. However, we can conduct statistical analysis of our data to produce a correlation coefficient : a number somewhere between -1 and +1 which will indicate the exact direction and strength of relationship between the 2 co-variables.

HYPOTHESES FOR CORRELATION STUDIES

Whereas hypotheses for experiments predict there will be a ‘difference’ between how the 2 conditions of the IV affect the DV, hypotheses for correlation studies predict there will be a ‘relationship’ between 2 co-variables.

Hypotheses can be directional or non-directional depending on whether or not past research indicates whether we should expect to find a relationship (either positive or negative).

• 2-Tailed Experimental Hypothesis : ‘There will be a significant correlation between stress and illness’.
• 1-Tailed Experimental Hypothesis : ‘There will be a significant positive correlation between stress and illness’. (This could also be predicting a negative correlation.)

  STRENGTHS OF CORRELATION STUDIES

• Correlation studies allow us to assess the precise direction and strength of relationship between 2 co-variables using correlation coefficients (see above).
• Correlation studies are a valuable preliminary (initial) research tool . They allow us to identify relationships between variables that we may then decide to investigate in more detail through experimentation.

LIMITATIONS OF CORRELATION STUDIES

• Correlation studies only tell us that there is some kind of relationship between 2 variables, they do not tell us about cause-effect relationships , and thus they are a weaker methodology than lab experiments.
• We may sometimes find a correlation between 2 variables by pure chance , even when no real relationship exists between the variables – thus they may be misleading. For example, there is an almost perfect negative correlation between Nigerian iron exports and the UK birth rate between 1870 and 1920 even though these factors are completely unrelated.

OBSERVATIONAL TECHNIQUES ( AQA A-level Psychology revision guide)

Observations simply involve observing behaviour in the natural environment .

Observations may be

• Overt : the psychologist’s presence is made known to the group being studied. This may lead to demand characteristics and participants behaving in unnatural ways.
• Covert : the psychologist’s presence is hidden . Either he appears as a normal member of the public or is his presence is concealed in some way (e.g. CCTV camera). Although this overcomes the problem of demand characteristics , there are ethical issues to do with deception, lack of consent and invasion of privacy.
• Participant : the psychologist joins the group being studied. This may be covert or overt.
• Non-Participant : the psychologist remains outside the group being studied. This may be covert or overt.

Observational studies can be conducted in real life situations (naturalistic observations) or in laboratories (which provide more control – controlled observations ). Behaviours observed can be recorded in a qualitative form or can be counted/quantified .

For example, we may wish to conduct an observational study of gender differences in aggressive behaviours amongst 5-7-year olds. A tally chart can be constructed to record observations and behavioural classifications/categories .

This chart allows us to make statistical statements about behaviours: e.g. boys punch 4 times more than girls do.

One way of recording behavioural categories is event sampling (as in the example above – recording the number of times a particular event occurs); the other is time sampling – recording what is occurring at certain time intervals: e.g. every minute.

If a number of different observers are conducting the same observational study, we need to ensure the observers have inter-rater reliability (see section of Reliability above).

STRENGTHS OF OBSERVATIONAL STUDIES

• During covert observations there are high levels of ecological validity and no demand characteristics . Participants are unaware that they are being observed and they are in a natural environment – thus we are observing behaviour as it naturally occurs.
• With participant observation the psychologist can question participants and get a much more in depth insight into the behaviours, beliefs and motivations of the group being studied . Thus, a much deeper, richer, descriptive picture of behaviour is produced.

  LIMITATIONS OF OBSERVATIONAL STUDIES

• With covert observations ethical issues arise concerning invasion of privacy, lack of consent, deception and lack of right to withdraw.
• With overt observations participants may exhibit demand characteristics and act in socially-appropriate or otherwise unnatural ways.

SELF-REPORT METHODS: QUESTIONNAIRE SURVEYS & INTERVIEWS ( A-level Psychology resources)

 The term self-report simply means that the participant is reporting on their own perception/view of themselves – either using a questionnaire or an interview .

 For either technique:

• Social desirability bias may be an issue in that if a participant knows their answers will be read/heard by someone else they may say what they think is socially acceptable/desirable rather than the truth. To combat this, questionnaires can be kept anonymous and confidential.
• Self-report studies are also subjective in that the individual’s perception of themselves may be quite different from how others view them.

QUESTIONNAIRES

Questionnaires can be:

• Closed ended .

E.g. I intend to vote for Joe Biden.

Closed ended questions allow us to produce quantitative data: e.g. statistical statements such as 45% of participants agreed.

• Open ended .

Produce lengthier answers – richly descriptive, qualitative data.

E.g. Explain why you intend to vote for Joe Biden.

__________________________________________________

When constructing questionnaires, we must try to ensure that the questions we ask are clear , concise , non-ambiguous , and easily understandable, and will be interpreted by all participants in the same way as each other.

We may also want to check the reliability of the questionnaire through test-retest reliability . Open-ended questionnaires can be thematically analysed (see later section on this).

STRENGTHS OF QUESTIONNAIRES

• Closed-ended questionnaires are capable of providing large amounts of information from large amounts of people fairly cheaply and quickly .
• Closed-ended questions can be statistically analysed to allow us to make statements about %’s of people who hold certain beliefs, etc.
• Open-ended questions allow us to gain an in depth insight into participants’ personal opinions and the motives that underlie behaviours and beliefs .

  LIMITATIONS OF QUESTIONNAIRES

• If socially sensitive questions are asked participants may give socially-appropriate responses. E.g. if a questionnaire asks whether someone holds racist beliefs it is unlikely they will admit to this to a researcher. This can be overcome by making questionnaires anonymous and confidential.
• Open-ended questions can be difficult to interpret and analyse as participants may give lengthy answers. This makes it hard to understand broad patterns and trends in participants’ beliefs and behaviours.

Interviews can be conducted with individuals or groups either face-to-face or telephone/internet. The respondent can describe their response in depth and detail (qualitative data) and say what they want to say rather than filling out pre-set answer choices (e.g. questionnaires). Interviews can be thematically analysed (see   later section on this).

Interview questions can be:

• Structured : a pre-set list of questions is asked.
• Unstructured : the interview progresses as more of an on-going conversation between interviewer and interviewee.

STRENGTHS OF INTERVIEWS

• Interviews provide richly detailed qualitative descriptions of participants’ subjective (personal) understanding of their behaviour, beliefs and motivations .
• With open-ended questions , interviewees may be able to suggest and shed light on further areas of research and interest relating to the topic they are being interviewed about.
• Structured interviews allow all participants to be asked the same questions , making general patterns in answers easier to analyse and keep the interview limited to the subject matter the interviewer wants to cover.

LIMITATIONS OF INTERVIEWS

• If socially sensitive questions are asked participants may give socially-appropriate responses. E.g. if an interviewer asks whether someone holds racist beliefs it is unlikely they will admit to this.
• Open-ended questions can be difficult to interpret and analyse as participants may give lengthy, personal answers. This makes it harder to analyse broad patterns and trends in participants’ beliefs and behaviours.

CASE STUDIES ( AQA A-level Psychology resources)

These are longitudinal studies (conducted over a long period of time) which focus in great detail on an individual or a small group . They are often used in the field of psychopathology and child development, and may include a variety of methods such as unstructured interviews and observations .

STRENGTHS OF CASE STUDIES

• Case studies provide richly detailed descriptions of participants’ subjective (personal) understanding of their behaviour, beliefs and motivations .
• Case Studies usually follow the progress and changes an individual goes through over time.

LIMITATIONS OF CASE STUDIES

• Case studies are associated with problems of subjectivity and personal interpretation on the behalf of the psychologist: e.g. the psychologist may be biased in their viewpoint and interpretation of events and behaviour: for example, with the case study of Little Hans, Freud was accused of interpreting Hans’ behaviour to make it support his theory of the Oedipus Complex. Thus, because case studies do not use controlled scientific methods of experimentation, they are thought to lack scientific objectivity and proof.
• For the above reason, and for the fact they are only carried out on one individual, case studies suffer a lack of reliability and generalisability .

CONTENT ANALYSIS ( A-level Psychology notes)

This is a technique where researchers identify themes or behavioural categories and count how many times they occur (see   later section on thematic analysis) . It is often used with written or visual material such as interviews, open-ended questionnaires, diaries, magazines, films, etc.  A coding system of categories will be developed whereby we count certain times a particular piece of content arises.

For example, we might ask mothers with children who have just started primary school to keep a diary of their child’s response to this and then count how many times categories such as ‘child crying’, ‘child showing clingy behaviour’, ‘child showing anger to mother’ occur.

STRENGTHS OF CONTENT ANALYSIS

• It allows qualitative data (writing or visual material) to be put into a quantitative form (counting behaviours) , so that statistical analysis can take place and data can be represented in tables and graphs.

LIMITATIONS OF CONTENT ANALYSIS

• Constructing a coding system involves the risk of an investigator imposing their own meaning on the data. The investigator might choose coding categories they think are important and overlook categories which actually are important. Thus, there may be problems of subjectivity and personal bias .

THEMATIC ANALYSIS ( AQA A-level Psychology notes)

  Interviews, open-ended questionnaires and content analysis (all qualitative research techniques) can be analysed in terms of themes which occur in the content of responses given by participants.  We can count these themes to produce quantitative data . For example, if we interviewed adults who had experienced maternal deprivation as an infant we could analyse what major themes occurred in interviews (e.g. feelings of loss, desire for love, etc.) and count how many times these themes occurred.

STRENGTHS OF THEMATIC ANALYSIS

• We can turn complex qualitative data into quantitative data which can then be statistically analysed. For example, 65% of participants referred to feelings of loss in their interviews.

LIMITATIONS OF THEMATIC ANALYSIS

• If a number of researchers are conducting thematic analysis on the same data they may interpret and count themes in a different way to each other which would lead to a lack of reliability. (This could be overcome through testing for inter-rater reliability.)

PARTICIPANTS & SAMPLING ( A-level Psychology revision notes)

It is important to select participants carefully when conducting research to ensure the study has population validity (see section on Validity above).

The term population refers to all the people within a certain category whom we wish to study: e.g. all schizophrenics, all 5-11 year olds, all pregnant women, etc. From this population we draw a smaller sample . Ideally, we want our sample to be fairly large and to be representative of the population as a whole (i.e. a good cross-section in terms of age, gender, ethnicity, etc.)

With a large , representative, random sample of participants we should be able to generalise (apply) our findings to the population as a whole (i.e. say that what is true of our sample is true of the population as a whole).

There a number of different sampling methods we can employ to select participants each with its own advantages and disadvantages.

• Random sampling . The sample is randomly selected from the population: e.g. picking names at random out of a hat. Although this method is truly random it does not guarantee a representative sample .
• Volunteer (self-selecting) sampling . Participants respond to an advert placed by the researcher: e.g. Milgram’s obedience study. This method is not random and doesn’t guarantee a representative sample as only certain types of people are likely to volunteer. However, volunteers are likely to make motivated and cooperative participants in research.
• Opportunity sampling . Potential participants are approached by the researcher and asked whether they would be willing to take part in a study. This method is not random and doesn’t guarantee a representative sample as only certain types of people are likely to agree to take part. However, those who do are likely to make motivated and cooperative participants in research.
• Systematic sampling . Taking every ‘nth’ person on a list: e.g. every 10 th person on a school register. Not random or guaranteed to be representative .
• Stratified sampling . The population is assessed for what proportion of particular characteristics it contains (e.g. age, gender, ethnicity, social class, etc.) and representative numbers of participants possessing these characteristics are randomly sampled to form the sample.

For example, a school population of 1000 students has 40% boys and 60% girls, and 50% of all students are below the age of 16 and 50% are 16 +.

If we wanted a stratified sample of 100 students we would select

• 40 boys (40% of all students) and 60 girls (60% of all students)
• 20 boys below the age of 16 (50% of the 20 boys)
• 20 boys above the age of 16 (50% of the 20 boys)
• 30 girls below the age of 16 (50% of the 20 girls)
• 30 girls above the age of 16 (50% of the 20 girls)

Stratified sampling is truly representative and random.

ETHICAL ISSUES AND WAYS OF DEALING WITH THEM ( AQA A-level Psychology revision notes)

The British Psychological Society (BPS) publish ethical guidelines which psychologists are supposed to follow when planning and conducting research.

DECEPTION AND INFORMED CONSENT  

Participants should not be deceived (lied to) or involved in experiments unless they have agreed to take part. One way of dealing with this is to make sure that the participant is told precisely what will happen in the experiment before requesting that he or she give voluntary informed consent to take part. In reality, many experiments require some level of deception to avoid demand characteristics, hence it is often difficult to receive fully informed consent.

For example, Milgram got consent to take part in an experiment, but not informed consent as participants did not know the true aim of the study.

Dealing with Deception and Lack of Informed Consent

• At the end of the experiment participants should be informed about the aims, findings and conclusions of the investigation and the researcher should take steps to reduce any distress that may have been caused by the experiment. This may be in the form of counselling . They should also be asked if they have any questions.
• Presumptive Consent . The general public are surveyed and asked whether they believe that the breaking of ethical guidelines in a particular study is justified or not . This solution is often used in relation to experiments where participants cannot be asked for consent as the study requires them to remain naïve: e.g. field experiments such as Hofling.
• Prior General Consent . In this proposed solution, people volunteer to take part in research at some point in the future . Thus, they serve as a pool of participants who may be used at some point in the future.
• Retrospective consent involves asking the participants for consent after they have participated in the study.
• In the case of young children or the mentally ill , parents or guardians can provide consent if they judge a procedure is in the client’s best interests: e.g. whether a child with ADD should be prescribed a drug. Approval could also be obtained after consulting professional colleagues: e.g. psychiatrists debating whether a depressed patient would benefit from a drug treatment.

RIGHT TO WITHDRAW

Participants should have the right to withdraw from an experiment at any time.

They should be informed of this right in the standard briefing instructions given to them before the experiment commences. They have the right to insist that any data they have provided during the experiment should be destroyed.

PROTECTION FROM PHYSICAL AND PSYCHOLOGICAL HARM

Participants should be exposed to no more risk than they would encounter in their normal lives. They should also be protected from any kind of psychological harm such as stress, embarrassment or damage to their self-esteem .  If participants are showing signs of distress they should be reminded of their right to withdraw .

CONFIDENTIALITY

Information about participants’ identities should not be revealed and can be kept confidential by ensuring participants’ identities remain anonymous and confidential. Freud, for example, gave his clients pseudonyms: e.g. Little Hans.

FORMS & INSTRUCTIONS ( Psychology A-level revision)

CONSENT FORM

If asked to write a consent form, to get full marks you must provide sufficient information on both ethical and methodological issues for participants to make an informed decision. You must also write as it would be read out to participants.

The form should contain

• The purpose of the study
• The length of time required of the participants
• Details of any parts of the study that participants might find uncomfortable
• Details about what will be required of them, and what they will have to do
• There is no pressure to take part in the study at all
• Right to withdraw (they can leave at any time, without giving a reason, keep any money they have been paid, and any data collected on them will be destroyed)
• Reassurance about protection from harm
• Reassurance about confidentiality of the data
• They should feel free to ask the researcher any questions at any time
• They will receive a full debrief at the end of the programme

STANDARDISED INSTRUCTION FORM FOR PARTICIPANTS

You need to use the details in the description of the study to write an appropriate set of instructions for participants. The instructions should be clear, concise, use formal language and be as straightforward possible. They must:

• Explain the procedures of this study relevant to participants.
• Include a check of understanding of instructions.

(This is not a consent form so references to ethical issues are not necessary.)

PEER REVIEW ( A-level Psychology revision)

Peer review is the process by which psychological research papers are subjected to independent scrutiny (close examination) by other psychologists working in a similar field who consider the research in terms of its validity and significance . Such people are generally unpaid . Peer review happens before research is published.

Peer review is an important part of this process because it provides a way of checking the validity of the research, making a judgement about the credibility (believability) of the research, and assessing the quality and appropriateness of the design and methodology .  It is a means of prevent incorrect data entering the public domain. This is important to ensure that any funding is being spent correctly .

Peers are also in a position to judge the importance or significance of the research in a wider context .  They can also assess how original the work is and whether it refers to relevant research by other psychologists.  They can then make a recommendation as to whether the research paper should be published in its original form, rejected or revised in some way.  This peer review process helps to ensure that any research paper published in a well-respected journal can be taken seriously by fellow researchers and the public. 

MAJOR FEATURES OF THE SCIENTIFIC METHOD ( AQA A-level Psychology revision)

Science is the unbiased observation and measurement of the natural world. It is the only tool humanity has developed for establishing factual truths about the world. Science allows us to establish the laws of physical world and from this knowledge create technology .

Since the 1700’s the scientific method has been developed, scrutinised and refined.

Major features of the scientific methods are

• Empiricism – Information is gained through direct observation or experiment on physically observable and measurable phenomena rather than by reasoned argument, unfounded beliefs, faith or superstition.
• Objectivity – Scientists should strive to be unbiased and non-interpretative in their observations and measurements. Prior expectations and preconceptions should be put aside. Subjective can be thought of as biased, personal and interpretive.
• Replicability – One way to demonstrate the validity of any observation or experiment is to repeat it. If the outcome is the same, this confirms the truth of the original results, especially if the observations have been made by a different person. In order to achieve such replication it is important for scientists to record their methods carefully so that the same procedures can be followed in the future.
• Control – Scientists seek to demonstrate causal relationships between variables. The experimental method is the only way to do this – where we vary one factor (the independent variable) and observe its effect on a dependent variable. In order for this to be a ‘fair test’ all other conditions must be kept the same, i.e. controlled . This allows us to establish the cause-effect relationships which underlie the laws of nature.
• Theory construction – One aim of science is to record facts, but an additional aim is to use these facts to construct theories to help us understand and predict the natural world. A theory is a collection of general principles that explain observations and facts . Theories should be based a sound body of valid and reliable scientific study.
• Hypothesis Testing – A good theory must be able to generate testable hypotheses . Popper developed the concept of falsification – the only way to really prove a theory correct is to disprove it: if it can’t be disproved it must be correct.

PARADIGMS AND PARADIGM SHIFTS ( AQA A-level Psychology revision guide)

A paradigm refers to the accepted and approved of ways of thinking, understanding, theorising and researching that exist and are shared within any one particular science. For example, biologists all tend to work within a paradigm where they accept basic concepts (evolution and Darwinian theory) as true and agree on how biology should be studied (scientific experimentation).

Psychology is often described as pre-paradigmatic as there is no complete, shared agreement between psychologists about how they should understand and explain human behaviour or what the best methods to study behaviour are. Psychology encompasses a number of conflicting approaches (e.g. behaviourism, biological, cognitive, psychodynamic, evolutionary, etc.) which disagree over what the major influences are on behaviour and what methods should be employed to study behaviour.

A paradigm shift occurs when there is a fundamental change in how scientists in a particular field understand and research subject matter due to evidence proving that the previous paradigm was inadequate/incorrect in some way. For example, in the field of physics, Newton’s laws were the dominant paradigm from the 18 th to early 20 th century before the work of Einstein resulted in a paradigm shift in the way in which physicists understood the physical laws of the natural world.

CONVENTIONS FOR REPORTING PSYCHOLOGICAL INVESTIGATIONS ( A-level Psychology resources)

Psychological investigations are written up/reported in the same way by all psychologists.

Abstract – A summary of the study covering the aims/hypothesis, method/procedures, results and conclusions. Allows a reader to gain a quick overall understanding of a study.

Introduction/Aim/Hypotheses – What the researchers intend to investigate. This often includes a review of previous research (theories and studies), explaining why the researchers intend to conduct this particular study. The researchers may state their research predictions and/or a hypothesis or hypotheses.

Method – A detailed description of what the researchers did , providing enough information for replication of the study. Included in this section is:

• Information about the participants (how they were selected , how many were used, and the experimental design )
• The independent and dependent variables
• The testing environment
• Materials used
• Procedures used to collect data
• Any instructions given to participants before (the brief ) and afterwards (the debrief )

For full marks, the method section should be written clearly , succinctly and in such a way that the study would be replicable . It should be set out in a conventional reporting style, possibly under appropriate headings . The important factor here is whether the study could be replicated.

Results – This section contains statistical data including descriptive statistics (tables, averages and graphs) and inferential statistics (the use of statistical tests to determine how significant the results are).

If you are asked to outline and discuss the results of a study mention the following points

• Write the results out clearly in words: e.g. ‘the mean number of objects remembered for participants listening to music was seven, but for those not listening to music was nine’.
• Refer to the standard deviation or range and explain what they mean, e.g. ‘those listening to music had a higher standard deviation than those not listening to music, meaning that their scores varied more around the mean. So there were more individual differences in participants’ memories when listening to music.’
• Say whether the results were significant and how you know this (refer to the OV, CV and level of significance), and what it means if they were.
• Discuss issues of validity
• Discuss issues of reliability
• The researchers offer explanations of the behaviours they observed and might also consider the implications of the results (how it can be applied to the real world) and make suggestions for future research.
• The researchers must consider their work critically, and evaluate it in terms of validity, reliability, any short-comings or criticisms, etc.
• Discuss how their research relates to the background research discussed in their introduction.

THE IMPLICATIONS OF PSYCHOLOGICAL RESEARCH FOR THE ECONOMY ( AQA A-level Psychology resources)

Although it is difficult to quantify how much psychology contributes to the economy, Psychology university departments receive over £50 million in research grants annually.

Psychological research is used in diverse fields such as medicine, psychiatry, therapy, social work, childcare, advertising, marketing, business, forensic in crime, the army, education, etc.

Apart from direct benefits, Psychology indirectly contributes to the economy: for example, in the UK, 40% of people claiming incapacity benefits are doing so due to anxiety or depression, therefore, psychotherapy may assist the long-term unemployed in returning to work which causes increased tax revenue.

Psychology may also assist in finding solutions to wider social problems relating to crime, aggression, child abuse, etc. This could contribute to the economy by reducing levels of crime (theft and damage to properties), reducing prison population (paid for by the tax-payer) and increased taxation (people working rather than being in prison).

DESCRIPTIVE STATISTICS ( A-level Psychology notes)

Once a study has been conducted that produces quantitative data , patterns and trends can be simply analysed using some of the following techniques.

MEASURES OF CENTRAL TENDENCY

This refers to the 3 forms of average – Mean, Median and Mode – which tell us about the average within a set of data.

For example, a set of scores are produced in a memory test:

5, 7, 8, 8, 10, 11, 14, 15, 45

Add all scores and divide by total number of scores:  123 divided by 9 = 13.67

• An advantage of the mean is that it is the truest form of average because it uses all scores within a set of data.
• A disadvantage is that the mean may be artificially inflated or deflated by extreme scores (outliers) in a set of data (in such a case we can say that the data is skewed ). In the above example the extreme score of 45 artificially inflates the mean to an unrealistically high level .

The median is the middle score in a set of ranked (put in order from low to high) data.

• An advantage of the mode is that It is not affected by extreme scores ( outliers ).
• A disadvantage is that the Mode can be altered a lot by small changes in a set of data.

E.g. 2, 4, 4, 5, 9, 15, 16 Median = 5 (Take mean average if 2 numbers in middle).

       2, 4, 5, 9, 15, 16, 17 Median = 9 (Take mean average if 2 numbers in middle).

The most frequently occurring score in a set of data.

• A disadvantage is that the Mode can be altered a lot by small changes in a set of data. Also, set of scores may have no mode value .

E.g.  2, 2, 4, 5, 9, 15, 16   Mode = 2

         2, 3, 4, 5, 9, 16, 16 Mode = 16

CALCULATING %’s

To calculate how much 1 number is as a percentage of another number divide the 1 st number by the 2 nd and multiple by 100.

For example, if Bob earns £26,060 a year and Nicola earns £137,540 then 

26,060/137,540 x 100 = 18.94

Therefore, Bob earns 18.94% of Nicola’s salary.

MEASURES OF DISPERSION

These tell us about the ‘spread’/‘dispersion’/’variability’ within a set of scores – the range and the standard deviation (SD).

This simply tells us about the range of scores in a set of data . The range is calculated by taking the highest score and subtracting the lowest score.

THE STANDARD DEVIATION (SD)

The standard deviation tells us about the amount of variability from the mean .

For example, 2 classes of students with 2 different psychology teachers gained the following % scores in an end of year test.

GROUP 1: 18, 24, 31, 46, 55, 64, 79, 82, 90, 98.  Mean = 59

GROUP 2: 49, 52, 54, 57, 68, 60, 62, 64, 66, 68.  Mean = 60

Although the 2 groups have very similar mean scores, GROUP 1 have a much larger SD – there is a lot of variability from the mean whereas there is little variation from the mean in GROUP 2.

The SD is a stronger measure of dispersion than the range because

• The SD is a measure of dispersion that is less easily distorted by a single extreme score .
• The SD takes account of the distance of all the scores from the mean.
• The SD d oes not just measure the distance between the highest score and the lowest score .

DISPLAYS OF DATA ( AQA A-level Psychology notes)

Quantitative data can be plotted on a variety of graphs and charts.

GRAPHS are used to display continuous scores ( ordinal data : see Inferential Statistics below). For example, to record participants scores in a memory test (x/20).

HISTOGRAMS are graphs converted to show interval scores (rather than continuous ones). (See Inferential Statistics below.)   

BAR CHARTS are not used to display scores - rather they display categories of information ( nominal data : see Inferential Statistics below). For example, number of participants in a particular category such as: favourite colour, borough of London lived in, participants studied at A Level, etc.

Note: whereas histogram bars join because they display continuous sets of scores, bar chart bars are separate as they show separate categories of information. 

SCATTERGRAMS are used to display data from correlation studies (see previous notes on Correlation Studies).

DISTRIBUTIONS: NORMAL AND SKEWED DISTRIBUTIONS; CHARACTERISTICS OF NORMAL AND SKEWED DISTRIBUTIONS ( A-level Psychology revision notes)

Many characteristics of populations follow a normal distribution: e.g. height, weight, shoe size, etc.

IQ scores are show a ‘normal’ distribution as below: i.e. most scores cluster around the mean average and as scores decrease or increase in either direction, fewer and fewer people possess these high or low scores. 68% of the population have an IQ between 85 and 115, only 2% of the population have an IQ between 130 and 145.

However, distributions of characteristics in populations may be ‘skewed’ ( distorted in one direction of another). For example, salary in the UK is positively skewed : i.e. a small % of the population earn a very large salary. The IQs of children at a school for the gifted would be negatively skewed (i.e. few with a low IQ, lots with a high IQ).

INFERENTIAL STATISTICS ( AQA A-level Psychology revision notes)

Although quantitative data can be analysed in fairly simple ways using measures of central tendency and dispersion, psychologists and scientists employ more complex statistical techniques to analyse results.

Experiments and correlation studies involve assessing whether

• there is a significant difference between how the 2 conditions of the IV affect the DV
• there is a significant correlation between 2 co-variables.

The term ‘significant’ can be thought of as referring to whether there is a real, interesting and important difference or correlation between variables.

For example, in the drink-driving study we may find a mean average score of 16/20 for the sober group and 9/20 for the alcohol group – clearly this is an important ‘significant’ difference. On the other hand if the scores were 14/20 and 11/20 we would be less sure if there was a real ‘significant’ difference between the groups.

At a basic level, statistical analysis is a tool to assess whether we have or have not found a significant difference or correlation in a study.

There are a number of different statistical tests that can be used to analyse data. Which test is appropriate to use is decided by

• Whether the study is an experiment or a correlation study
• Whether the study’s design is an independent groups design or a repeated measures design
• Whether data is at the ordinal , nominal, interval or ratio level (see below)

LEVELS OF DATA

Quantitative data comes in different forms/types.

• Ordinal Data – scores which can be ranked from low to high: e.g. scores in an IQ test, memory test or personality questionnaire.
• Nominal Data – data in the form of categories of information: for example, number of students studying particular participants in college.

For the following examples decide whether data is ordinal or nominal.

Height, eye colour, borough of London lived in, stress score, favourite animal, skill at driving, reaction speed.

• Interval Data – Ordinal data which has either been separated into intervals: e.g. 0-5, 6-10, 11-15, 16-20, etc.

PROCEDURES FOR STATISTICS TESTS 

In the exam you are only required to know about how to conduct inferential statistics using the Sign Test , however all statistics tests follow the basic principles below.

• Data from an experiment or correlation study is processed through a number of statistical/mathematical formulae. This will eventually produce one single number which ‘describes’ the data as a whole – this is referred to as the Calculated/Observed Value (OV)
• The OV is then compared to a Critical Value (CV). This is a number found by cross-referencing certain information on a table of statistical significance .
• Different statistics tests have different rules
• In some tests if the OV > CV then the statistics test shows that we have found a significant difference/correlation and can, therefore, accept the experimental hypothesis . If the OV < CV we reject the experimental hypothesis .
• In other tests the reverse is true: e.g. if OV < CV we accept the experimental and reject the null.
• In the exam you will be told which of the 2 rules above applies to the statistics test concerned.
• At a basic level, therefore, statistical analysis of data is a way of establishing whether we have or haven’t found significant results.

LEVELS OF STATISTICAL SIGNIFICANCE AND PROBABILITY (P)

In theory, psychologists/scientists never say that their findings are 100% accurate and true – there is always a probability that although results seem to indicate particular findings they are incorrect and findings have occurred by chance .

The concept of level of significance is used to indicate to readers to what percentage probability we can say that a particular set of findings are accurate and true, and to what extent results may have simply occurred due to chance .

For most pieces of psychological research a significance level of P < 0.05 is used. This indicates a 95% probability that results are accurate and true and a <5% probability that results occurred due to chance.

Higher levels of significance can be set when the accuracy of research findings is more important: e.g. in trials of a new drug. Thus findings which are significant at P < 0.01 mean that researchers are 99% confident results are true and there is only a 1% probability they occurred due to chance.

< m eans ‘the same as or less than’.

Depending on the results of statistical analysis of data we may find that results are significant at any one of the above levels of probability. The higher the level of probability – the more significant, and therefore stronger, our results are.

TYPE 1 & TYPE 2 ERRORS

Type 1 errors – calling something true when it’s false.

When a statistics test indicates that the experimental hypothesis should be accepted, but in fact, the results are due to chance random factors . If the level of significance is set at 5%, there will always be a 1/20 chance of a type 1 error.

Clearly, the higher the level of significance (e.g. P < 0.1), the greater the chance that a type 1 error will occur (in this case 10%).

Type 2 errors – calling something false when it’s true.

When a statistics test indicates that the experimental hypothesis should be rejected, but in fact, the results are significant .

Clearly, the lower the level of significance (e.g. P < 0.005), the greater the chance that a type 2 error will occur.

 >>>>>>>>

THE SIGN TEST ( Psychology A-level revision)

The Sign Test is the 1 statistics test you do need to know how to fully conduct .

Signs tests are used in experiments with a repeated measures design and nominal data .

Example and procedures

We could conduct a study into whether there is a difference in people’s memory for a list of 10 words they’ve been read (DV = memory score x/10) depending on whether they heard the words in quiet conditions (1 st condition of the IV) or noisy conditions (2 nd condition of the IV). We would use a 1-tailed hypothesis for this study as previous research indicate that noise would disrupt memory ability

Once the experiment is conducted data (results from participants) is put into a results table .

Steps to calculate Sign Test

• Subtract the score for the experimental condition from the control condition . If the result is negative add a minus – sign; if it’s positive add a + sign; if there’s no difference add a 0
• Count the number of times the less frequent sign occurs . In the above example, the + sign is the least frequent. Call this value S . Therefore, S = 2
• Count the total number of + and – signs . Call this value Therefore, N = 7
• Decide whether a 1 or 2-tailed hypothesis was used . In the above example, we used a 1-tailed hypothesis.
• Consult the table of statistical significance (below) for the Sign Test to find the critical value (CV).
• Look down the left hand column marked N until you get to the total number of + and – In the case described N = 7 .
• Cross reference N with the columns for either 1 or 2-tailed test (depending on whether your hypothesis is 1 or 2-tailed) and the Level of Significance value 05 (this is your Level of Significance – P < 0.05 ). In the case above this gives a value of 0 . Call this value the critical value (CV) . Therefore, CV = 0.
• If the critical value ≥ S then we have found a significant difference between how the 2 conditions of the IV affected the DV: i.e. there is a significant difference in how noisy and quiet conditions affect memory ability. In the example above the critical value (CV = 0) is not greater than S (S = 2) therefore, we have not found a significant difference.

  Table of Critical Values for the Sign Test

Research Methods: Scientific Method & Techniques

Scientific processes.

Aims: The aim of a study is what the purpose is of a piece of research. For example- to investigate if age affects memory.

Hypothesis: The prediction of what the results will be. This can be directional, in which the expected effect of a variable is stated, or non-directional, where a difference is predicted, but not the nature of the difference. For example:

• Directional: young people will do better in a memory test than older people
• Non-directional: there will be a difference between young and older people in performance on a memory test

The above hypotheses are known as the experimental/alternative hypothesis. There is also the null hypothesis , which predicts that there will be no difference between the conditions, for example ‘there will be no difference between young and older people in performance on a memory test’.

Directional hypotheses are used when previous research indicates what the results will be, for example if other studies have found that young people have better memories than older people, we can predict that the result will go the same way. If there is no previous research, or previous research is contradictory, and a non-directional hypothesis would be used.

Independent and dependent variables: In an experiment, the variable manipulated or changed by the researcher is the independent variable (IV). The result, which should be affected by the change in IV, is the dependent variable (DV). All other variables should be controlled as far as possible, so that it is the IV that affects the DV and nothing else. For the purposes of experiments, IVs and DVs must be operationalised - put into a form which is measurable. For example, ‘Age’ (the IV) could be operationalised as ‘participants between 20 and 25 years of age and participants between 60 and 65 years of age’. ‘Memory ability’ (the DV) could be operationalised as ‘the score on a test of memory’ or ‘the number of words successfully recalled’. This can be used in a hypothesis as follows:

‘Participants between 20 and 25 years of age will score more highly on a memory test than participants between 60 and 65 years of age’.

This is an operationalised hypothesis, and it is directional, in this case.

Variables & Control

As well as the IV and DV, other variables exist which potentially affect the results of experiments.

Extraneous variables: Variables other than the IV which may have an effect on the DV if not controlled for. For example, in the memory experiment, the intelligence and motivation levels of the participants may have an impact on their score on the memory test. The researcher should take steps to minimise the impact of these, for example by giving participants an IQ test beforehand and eliminating any particularly high or low scores from the sample.

Confounding variables: Variables other than the IV that have (or almost certainly have) had an effect on the DV. We know they have had an effect because they vary systematically with the IV. For example, in the memory experiment, if all of the young participants are given the memory test at 9am, and all of the older participants are given the test at 7pm, the time of day has acted as a confounding variable, as it has varied systematically with the IV. Therefore, any difference in the results of the two groups may be due to the difference in time of day, rather than the difference in age. The effect of this can be reduced or eliminated by testing both age groups at the same time of day.

Demand characteristics: These are clues which participants respond to when in an experimental situation, in which they try to guess the aim or intended outcome of a study and therefore change their behaviour accordingly. They are a form of participant reactivity (people not behaving naturally as they know they are being studied). The effect of these can be reduced by not revealing the aim of the study to the participants, or by using an independent measures design, so that participants only take part in one of the experimental conditions. For example, if participants are told the aim of the memory study, the young participants may try really hard on the memory test, as they may guess that this is the predicted outcome of the study. They act in ways that they think will please the experimenter. Alternatively, the older participants may try really hard on the test in order to prove the prediction wrong. Either way, the participants do not act naturally, so reducing the validity (correctness) of the results.

Investigator effects: These are any unwanted influences that the investigator/experimenter communicates to the participants which affects their behaviour. For example, being more encouraging towards the young participants in the memory test, as this is the expected result. These can be minimised by the use of standardised instructions, or the double-blind procedure.

Randomisation: This is a way of controlling for the effects of extraneous/confounding variables. Allocating participants to tasks, selecting samples of participants, and so on, should be left to chance as far as possible, to reduce the investigator’s influence on a study.

Standardisation: This is where the experience of an experiment is (as far as possible) kept identical for every participant, for example using standardised instructions. This reduces the effect of extraneous/confounding variables.

Single and double-blind: The single-blind procedure is when the participant does not know the aim of the study. This helps reduce the possibility of demand characteristics from affecting the results. Double-blind is when where the investigator who deals with the participants also does not know the aim of the study. This helps reduce the chance of investigator effects, as the investigator will not unconsciously communicate the aim to the participants.

Control groups: These are used for the purpose of comparison, often when testing the effects of a drug, for example. One group of participants (the ‘experimental group’) will be given the real drug, another group a placebo (fake drug). This can allow the researcher to directly compare the results of the two groups. If the experimental group improves then it is likely that this is because of the drug.

In a study, the population is the target group of people the researcher is studying (e.g. ‘males in their 20s’). The sample is the group of people selected to take part in the study, drawn from the target population. In order to select a sample, a sampling technique will be used:

Random: Each member of the target population has an equal chance of being selected. For example, using a random name or number generator, or picking names out of a hat.

• Evaluation : The researcher cannot influence the selection of participants, but the sample could, by chance, end up being unrepresentative.

Systematic: A participant is selected in a systematic way, for example, selecting every 10 th person from the electoral roll. This is decided through a sampling frame, where a list of the target population is put in order.

• Evaluation : The researcher cannot influence the selection of participants, and it is likely to be representative.

Stratified: The make-up of the sample reflects the make-up of the target population. For example, if studying teachers, as there are more female than male teachers, there should be more female participants. If 60% of teachers are female, this means that in a sample of 20, there should be 12 female and 8 male teachers. Once these quotas are identified, the participants to fill them are selected at random from the target population.

• Evaluation : random techniques are used, so the researcher can’t influence the selection. The sample produced is representative of the target population, as it has been designed to be so. However, it is hard to represent all the ways in which people are different.

Opportunity: Participants are selected from whoever is most easily available. For example, standing in the street one afternoon and approaching passers-by to see if they want to take part.

• Evaluation : this is convenient, as it is much less time-consuming and costly than some of the other methods. However, there is a high chance of obtaining an unrepresentative sample, as large groups of the population have no chance of being involved. Also the researcher controls which participants are selected, which could lead to bias.

Volunteer: Participants put themselves forward to take part in a study. For example, a newspaper or internet advert is placed asking for volunteers, and people respond agreeing to take part.

• Evaluation : this is easy and convenient for the researcher, but it is open to volunteer bias, whereby only certain types of people (the type that put themselves forward) take part. This reduces the representativeness of the sample.

Pilot Studies

These are small-scale trial runs of an experiment. The purpose is to check that the procedure works smoothly and that there are no misconceptions. Any problems can be addressed and the procedures amended for the real study.

Experimental Design

This refers to how participants are allocated to experimental conditions.

Independent groups: There are different participants in each condition. This would be appropriate for the memory experiment, as the participants need to be different ages in each condition.

• Advantages : participants are less likely to guess the aim of the study, and there are no order effects - effects arising from having completed two tasks, for example becoming more practised and doing better in the second condition, or getting bored/fatigued and doing worse in the second condition
• Disadvantages : there may be differences between the two groups of people- e.g. intelligence, age, gender, which may cause differences in the results. Twice as many participants are needed.

Repeated measures: One group of participants completes both/all of the conditions of the experiment. For example, to test the effect of listening to music on problem-solving ability, participants are given problems to solve whilst listening to music, then another set of problems to solve in silence.

• Advantages : there are no participant variables between the conditions, and fewer participants are needed
• Disadvantages : there are order effects which may influence the results. This can be addressed by counterbalancing- half the participants do one task followed by the second (A followed by B) and the other does the opposite (B followed by A). Also, participants may work out the aim of the study, like in the music example, and may change their behaviour.

Matched pairs: As independent groups, but participants are ‘matched’ on qualities relevant to the experiment. For example, in the music study, one participant is allocated to the ‘music’ condition, and another who is similar in terms of age, IQ and occupation is allocated to the ‘silence’ condition. This involves pre-testing participants on certain measures in order to match them up.

• Advantages : order effects and demand characteristics are less likely to have an impact, and participant variables are reduced
• Disadvantages : participants can never be matched perfectly, so there might still be some participant variables. Matched pairs is the most time-consuming and expensive design to use.

Observational Design

Structured or unstructured: The researcher may decide to focus on particular behaviours or actions when conducting the observation, and only record these- this is the structured method (more likely with several participants). Alternatively, they may just record everything that is going on- this is the unstructured method (more likely with fewer participants).

• Evaluation: Structured- the data is much easier to analyse to spot trends and make conclusions (it is likely to be quantitative). But, the data is in less detail as only certain things have been recorded. Unstructured- data is much harder to analyse, and there is more risk of observer bias (only recording things that fit with the observer’s preconceived ideas). But, the data in in more detail and is much ‘richer’.

Behavioural categories: This is the process of making a target behaviour measurable, by breaking it down into observable components. ‘Aggression’ could be broken down into shouting, hitting, punching and so on. This allows different observers to use the same checklist of behaviours, as they are not (or, should not be) subjective.

• Evaluation: To be useful, categories should be unambiguous and objective, as far as possible, and should cover all possible behaviours. Categories should not overlap (e.g. ‘hitting’ and ‘striking’ would be too similar).

Sampling methods: In unstructured observations, continuous recording is often used, where everything that happens is recorded. Because this is often not feasible, researchers usually use one of two sampling methods to record data. Event sampling is when a record is made of each example of a particular behaviour during the observation (e.g. counting the number of times someone shouts out). Time sampling is when behaviours are recorded in a specific timeframe (e.g. recording the behaviours shown during a one-minute time frame every five minutes).

• Evaluation: Event sampling- good for recording infrequent behaviours that may be missed otherwise. But, other important behaviours may be missed. Time sampling- reduces the number of observations needed, but the behaviour recorded may be less representative of the whole observation.

Inter-observer reliability: Usually there will be more than one person observing behaviours, to lessen the risk of observer bias affecting the results. Observers will use the same behavioural categories, and will observe the same behaviours in a pilot study, comparing their findings with the other observer(s). The results are compared, and the level of reliability is worked out by correlating the pairs of observations made. If necessary, behavioural categories can then be modified if inter-observer reliability is low.

Self-Report Design

Questionnaires: Can be designed with open or closed questions. In addition, questionnaires can use Likert scales , where the responder indicates their depth of feeling (‘1= strongly agree, 5= strongly disagree’); rating scales , where a number is chosen to indicate strength of opinion (‘how important do you think respect for authority is- 1=not important at all, 5= extremely important’); and fixed-choice options where the responder has to select from a pre-determined response which matches their opinion (‘why do people obey orders? (a) Uniform (b) Location (c) Proximity (d) Personality’)

Interviews: Most of these will be one-to-one with just the interviewer and interviewee, although sometimes they take place in groups. The list of questions to be asked will be drawn up, and the interview can be unstructured, structured or semi-structured. The interviewer aims to establish a rapport with the interviewee and make them feel comfortable.

Writing questions: To work effectively, questions should:

• Be free of technical language (jargon) and unfamiliar terms (‘do you think the agentic state is a valid explanation for obedience?’) as most people will not know what they mean
• Avoid emotive language and leading questions (‘do you think the disgusting habit of smoking should be banned?’) which guide participants towards the answer you are hoping for
• Not be ‘double-barrelled’- meaning two questions in one (‘do you think that smoking should be banned and anyone caught smoking sent to prison?’) as participants may agree with one half but not the other
• Avoid double negatives (‘are you not unhappy?’) as these can be confusing

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Directional Hypothesis

A directional hypothesis is a one-tailed hypothesis that states the direction of the difference or relationship (e.g. boys are more helpful than girls).

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• How to Write a Strong Hypothesis | Steps & Examples

How to Write a Strong Hypothesis | Steps & Examples

Published on May 6, 2022 by Shona McCombes . Revised on November 20, 2023.

A hypothesis is a statement that can be tested by scientific research. If you want to test a relationship between two or more variables, you need to write hypotheses before you start your experiment or data collection .

Example: Hypothesis

Daily apple consumption leads to fewer doctor’s visits.

Table of contents

What is a hypothesis, developing a hypothesis (with example), hypothesis examples, other interesting articles, frequently asked questions about writing hypotheses.

A hypothesis states your predictions about what your research will find. It is a tentative answer to your research question that has not yet been tested. For some research projects, you might have to write several hypotheses that address different aspects of your research question.

A hypothesis is not just a guess – it should be based on existing theories and knowledge. It also has to be testable, which means you can support or refute it through scientific research methods (such as experiments, observations and statistical analysis of data).

Variables in hypotheses

Hypotheses propose a relationship between two or more types of variables .

• An independent variable is something the researcher changes or controls.
• A dependent variable is something the researcher observes and measures.

If there are any control variables , extraneous variables , or confounding variables , be sure to jot those down as you go to minimize the chances that research bias  will affect your results.

In this example, the independent variable is exposure to the sun – the assumed cause . The dependent variable is the level of happiness – the assumed effect .

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Step 1. Ask a question

Writing a hypothesis begins with a research question that you want to answer. The question should be focused, specific, and researchable within the constraints of your project.

Step 2. Do some preliminary research

Your initial answer to the question should be based on what is already known about the topic. Look for theories and previous studies to help you form educated assumptions about what your research will find.

At this stage, you might construct a conceptual framework to ensure that you’re embarking on a relevant topic . This can also help you identify which variables you will study and what you think the relationships are between them. Sometimes, you’ll have to operationalize more complex constructs.

Step 3. Formulate your hypothesis

Now you should have some idea of what you expect to find. Write your initial answer to the question in a clear, concise sentence.

4. Refine your hypothesis

You need to make sure your hypothesis is specific and testable. There are various ways of phrasing a hypothesis, but all the terms you use should have clear definitions, and the hypothesis should contain:

• The relevant variables
• The specific group being studied
• The predicted outcome of the experiment or analysis

5. Phrase your hypothesis in three ways

To identify the variables, you can write a simple prediction in  if…then form. The first part of the sentence states the independent variable and the second part states the dependent variable.

In academic research, hypotheses are more commonly phrased in terms of correlations or effects, where you directly state the predicted relationship between variables.

If you are comparing two groups, the hypothesis can state what difference you expect to find between them.

6. Write a null hypothesis

If your research involves statistical hypothesis testing , you will also have to write a null hypothesis . The null hypothesis is the default position that there is no association between the variables. The null hypothesis is written as H 0 , while the alternative hypothesis is H 1 or H a .

• H 0 : The number of lectures attended by first-year students has no effect on their final exam scores.
• H 1 : The number of lectures attended by first-year students has a positive effect on their final exam scores.

If you want to know more about the research process , methodology , research bias , or statistics , make sure to check out some of our other articles with explanations and examples.

• Sampling methods
• Simple random sampling
• Stratified sampling
• Cluster sampling
• Likert scales
• Reproducibility

 Statistics

• Null hypothesis
• Statistical power
• Probability distribution
• Effect size
• Poisson distribution

Research bias

• Optimism bias
• Cognitive bias
• Implicit bias
• Hawthorne effect
• Anchoring bias
• Explicit bias

A hypothesis is not just a guess — it should be based on existing theories and knowledge. It also has to be testable, which means you can support or refute it through scientific research methods (such as experiments, observations and statistical analysis of data).

Null and alternative hypotheses are used in statistical hypothesis testing . The null hypothesis of a test always predicts no effect or no relationship between variables, while the alternative hypothesis states your research prediction of an effect or relationship.

Hypothesis testing is a formal procedure for investigating our ideas about the world using statistics. It is used by scientists to test specific predictions, called hypotheses , by calculating how likely it is that a pattern or relationship between variables could have arisen by chance.

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McCombes, S. (2023, November 20). How to Write a Strong Hypothesis | Steps & Examples. Scribbr. Retrieved March 12, 2024, from https://www.scribbr.com/methodology/hypothesis/

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AQA A-level Psychology Hypothesis Writing Frame

Subject: Psychology

Age range: 16+

Resource type: Worksheet/Activity

Last updated

21 January 2022

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Students often struggled to write a hypothesis, particularly if the exam question demands that this hypothesis is for a repeated or independent measures design. This Hypothesis Writing Frame is perfect for guiding students through the process of writing a hypothesis, outlining exactly what they should write with spaces to substitute the independent and dependent variable. It also includes a writing frame for a correlation hypothesis: this has yet to be examined but is a possibility for future exam questions.

This A4 handout comes complete with definitions for key terms: Hypothesis, Directional Hypothesis, Non-direction Hypothesis and Operationalisation; including when a non-directional or directional hypothesis should be used.

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Schizophrenia A-level Revisions Notes

Bruce Johnson

A-level Psychology Teacher

B.A., Educational Psychology, University of Exeter

Bruce Johnson is an A-level psychology teacher, and head of the sixth form at Caterham High School.

Learn about our Editorial Process

Saul Mcleod, PhD

Editor-in-Chief for Simply Psychology

BSc (Hons) Psychology, MRes, PhD, University of Manchester

Saul Mcleod, Ph.D., is a qualified psychology teacher with over 18 years experience of working in further and higher education. He has been published in peer-reviewed journals, including the Journal of Clinical Psychology.

On This Page:

What do the examiners look for?

• Accurate and detailed knowledge
• Clear, coherent, and focused answers
• Effective use of terminology (use the “technical terms”)

In application questions, examiners look for “effective application to the scenario” which means that you need to describe the theory and explain the scenario using the theory making the links between the two very clear. If there is more than one individual in the scenario you must mention all of the characters to get to the top band.

Difference between AS and A level answers

The descriptions follow the same criteria; however you have to use the issues and debates effectively in your answers. “Effectively” means that it needs to be clearly linked and explained in the context of the answer.

Read the model answers to get a clearer idea of what is needed.

Exam Advice

You MUST revise everything – because the exam board could choose any question, however, it does make sense to spend more time on those topics which have not appeared for a while.

With these particular questions there is a sizeable risk that people don’t understand the difference between the questions, and then write about the wrong thing.

Make sure you know which is which, for example do you understand the difference between “genetic explanation” and “neural correlates explanation”, and do you have a model essay for each?

Schizophrenia is a severe mental illness where contact with reality and insight are impaired, an example of psychosis.

Section 1: Diagnosis and Classification of Schizophrenia

Classification is the process of organising symptoms into categories based on which symptoms cluster together in sufferers. Psychologists use the DSM and ICD to diagnose a patient with schizophrenia.

Diagnosis refers to the assigning of a label of a disorder to a patient. The ICD-10 (only negative symptoms need to be present) is used worldwide and the DSM-5 (only positive symptoms need to be present) is used in America.

In order to diagnose Schizophrenia the Mental Health Profession developed the DSM (Diagnostic and Statistical Manual) still used today as a method of classifying mental disorders (particularly in the USA).

It is also used as a basis for the ICD (International Classification of Diseases) used by the World Health Organisation in classifying all disorders (mental and physical).

Note: you may come across the terms DSM-IV and ICD-10. These refer to the latest editions of the two classification systems.

Positive Symptoms

an excess or distortion of normal functions: including hallucinations and delusions.

Positive symptoms are an excess or distortion of normal functions, for example hallucinations, delusions and thought disturbances such as thought insertion.

• Hallucinations are usually auditory or visual perceptions of things that are not present. Imagined stimuli could involve any of the senses. Voices are usually heard coming from outside the person’s head giving instructions on how to behave. • Delusions are false beliefs. Usually the person has convinced him/herself that he/she is someone powerful or important, such as Jesus Christ, the Queen (e.g. Delusions of Grandeur). There are also delusions of being paranoid, worrying that people are out to get them. • Psychomotor Disturbances: Stereotypyical – Rocking backwards and forwards, twitches, & repetitive behaviors. Catatonia- staying in position for hours/days on end, cut off from the world.

Negative Symptoms

where normal functions are limited: including speech poverty and avolition.

Negative symptoms are a diminution or loss of normal functions such as psychomotor disturbances, avolition (the reduction of goal-directed behavior), disturbances of mood and thought disorders.

• Thought disorder in which there are breaks in the train of thought and the person appears to make illogical jumps from one topic to another (loose association). Words may become confused and sentences incoherent (so called ‘word salad). Broadcasting is a thought disorder whereby a person believes their thoughts are being broadcast to others, for example over the radio or through TV. Alogia – aka speech poverty – is a thought disorder were correct words are used but with little meaning. • Avolition: Lack of volition (i.e. desire): in which a person becomes totally apathetic and sits around waiting for things to happen. They engage in no self motivated behavior. Their get up and go has got up and gone!

Classification

Slater & Roth (1969) say that hallucinations are the least important of all the symptoms, as they are not exclusive to schizophrenic people.

Classification and diagnosis does have advantages as it allows doctors to communicate more effectively about a patient and use similar terminology when discussing them. In addition, they can then predict the outcome of the disorder and suggest related treatment to help the patient.

Scheff (1966) points out that diagnosis classification labels the individual, and this can have many adverse effects, such as a self-fulfilling prophecy (patients may begin to act how they are expected to act), and lower self-esteem.

Ethics – do the benefits of classification (care, treatment, safety) outweigh the costs (possible misdiagnosis, mistreatment, loss of rights and responsibility, prejudice due to labelling).

Reliability and Validity in Diagnosis and Classification of Schizophrenia

with reference to co-morbidity, culture and gender bias and symptom overlap.

Reliability

For the classification system to be reliable, differfent clinicians using the same system (e.g. DSM) should arrive at the same diagnosis for the same individual.

Reliability is the level of agreement on the diagnosis by different psychiatrists across time and cultures; stability of diagnosis over time given no change in symptoms.

Diagnosis of schizophrenia is difficult as the practitioner has no physical signs but only symptoms (what the patient reports) to make a decision on.

Jakobsen et al. (2005) tested the reliability of the ICD-10 classification system in diagnosing schizophrenia. A hundred Danish patients with a history of psychosis were assessed using operational criteria, and a concordance rate of 98% was obtained. This demonstrates the high reliability of the clinical diagnosis of schizophrenia using up-to-date classification.

Comorbidity describes people who suffer from two or more mental disorders. For example, schizophrenia and depression are often found together. This makes it more difficult to confidently diagnose schizophrenia. Comorbidity occurs because the symptoms of different disorders overlap. For example, major depression and schizophrenia both involve very low levels of motivation. This creates problems of reliability. Does the low motivation reflect depression or schizophrenia, or both?

Gender bias: Loring and Powell (1988) found that some behavior which was regarded as psychotic in males was not regarded as psychotic in females.

Validity – the extent to which schizophrenia is a unique syndrome with characteristics, signs and symptoms.

For the classification system to be valid it should be meaningful and classify a real pattern of symptoms, which result from a real underlying cause.

The validity of schizophrenia as a single disorder is questioned by many. This is a useful point to emphasise in any essay on the disorder. There is no such thing as a ‘normal’ schizophrenic exhibiting the usual symptoms.

Since their are problems with the validity of diagnois classification, unsuitable treatment may be administered, sometimes on an involuntary basis. This raises practical and ethical issues when selecting different types of tretment.

Problems of validity: Are we really testing what we think we are testing? In the USA only 20% of psychiatric patients were classed as having schizophrenia in the 1930s but this rose to 80% in the 1950s . In London the rate remained at 20%, suggesting neither group had a valid definition of schizophrenia.

Neuropsychologist Michael Foster Green suggests that neurocognitive deficits in basic functions such as memory, attention, central executive and problem solving skills may combine to have an outcome which we are labelling “Schizophrenia” as if it was the cause when in fact it is simply an umbrella term for a set of effects.

Predictive validity. If diagnosis leads to successful treatment, the diagnosis can be seen as valid. But in fact some Schizophrenics are successfully treated whereas others are not. Heather (1976) there is only a 50% chance of predicting what treatment a patient will receive based on diagnosis, suggesting that diagnosis is not valid.

Aetiological validity – for a diagnosis to be valid, all patients diagnosed as schizophrenic should have the same cause for their disorder. This is not the case with schizophrenia: The causes may be one of biological or psychological or both.

David Rosenhan (1973) famous experiment involving Pseudopatients led to 8 normal people being kept in hospital despite behaving normally. This suggests the doctors had no valid method for detecting schizophrenia. They assumed the bogus patients were schizophrenic with no real evidence. In a follow up study they rejected genuine patients whom they assumed were part of the deception.

Culture – One of the biggest controversies in relation to classification and diagnosis is to do with cultural relativism and variations in diagnosis. For example in some Asian countries people are not expected to show emotional expression, whereas in certain Arabic cultures public emotion is encouraged and understood. Without this knowledge a person displaying overt emotional behavior in a Western culture might be regarded as abnormal. Cochrane (1977) reported that the incidence of schizophrenia in the West Indies and the UK is 1 %, but that people of Afro-Caribbean origin are seven times more likely to be diagnosed as schizophrenic when living in the UK.

Cultural bias – African Americans and those of Afro-carribean descent are more likely to be diagnosed than their white counterparts but diagnostic rates in Africa and the West Indies is low – Western over diagnosis is a result of cultural norms and the diagnosis lacks validity.

Section 2: Biological Explanations for Schizophrenia

Family studies find individuals who have schizophrenia and determine whether their biological relatives are similarly affected more often than non-biological relatives.

There are two types of twins – identical (monozygotic) and fraternal (dizygotic). To form identical twins, one fertilised egg (ovum) splits and develops two babies with exactly the same genetic information.

• Gottesman (1991) found that MZ twins have a 48% risk of getting schizophrenia whereas DZ twins have a 17% risk rate. This is evidence that the higher the degree of genetic relativeness, the higher the risk of getting schizophrenia. • Benzel et al. (2007) three genes: COMT, DRD4, AKT1 – have all been associated with excess dopamine in specific D2 receptors, leading to acute episodes, positive symptoms which include delusions, hallucinations, strange attitudes. • Research by Miyakawa et al. (2003) studied DNA from human families affected by schizophrenia and found that those with the disease were more likely to have a defective version of a gene, called PPP3CC which is associated with the production of calcineurin which regulates the immune system. Also, research by Sherrington et al. (1988) has found a gene located on chromosome 5 which has been linked in a small number of extended families where they have the disorder. • Evidence suggests that the closer the biological relationship, the greater the risk of developing schizophrenia. Kendler (1985) has shown that first-degree relatives of those with schizophrenia are 18 times more at risk than the general population. Gottesman (1991) has found that schizophrenia is more common in the biological relatives of a schizophrenic, and that the closer the degree of genetic relatedness, the greater the risk.

Very important to note genetics are only partly responsible, otherwise identical twins would have 100% concordance rates.

One weakness of the genetic explanation of schizophrenia is that there are methodological problems. Family, twin and adoption studies must be considered cautiously because they are retrospective, and diagnosis may be biased by knowledge that other family members who may have been diagnosed. This suggests that there may be problems of demand characteristics.

A second weakness is the problem of nature-v-Nurture. It is very difficult to separate out the influence of nature-v-nurture. The fact that the concordance rates are not 100% means that schizophrenia cannot wholly be explained by genes and it could be that the individual has a pre-disposition to schizophrenia and simply makes the individual more at risk of developing the disorder. This suggests that the biological account cannot give a full explanation of the disorder.

A final weakness of the genetic explanation of schizophrenia is that it is biologically reductionist. The Genome Project has increased understanding of the complexity of the gene. Given that a much lower number of genes exist than anticipated, it is now recognised that genes have multiple functions and that many genes behavior.

Schizophrenia is a multi-factorial trait as it is the result of multiple genes and environmental factors. This suggests that the research into gene mapping is oversimplistic as schizophrenia is not due to a single gene.

The Dopamine Hypothesis

• Dopamine is a neurotransmitter. It is one of the chemicals in the brain which causes neurons to fire. The original dopamine hypothesis stated that schizophrenia suffered from an excessive amount of dopamine. This causes the neurons that use dopamine to fire too often and transmit too many messages. • High dopamine activity leads to acute episodes, and positive symptoms which include: delusions, hallucinations, confused thinking. • Evidence for this comes from that fact that amphetamines increase the amounts of dopamine . Large doses of amphetamine given to people with no history of psychological disorders produce behavior which is very similar to paranoid schizophrenia. Small doses given to people already suffering from schizophrenia tend to worsen their symptoms. • A second explanation developed, which suggests that it is not excessive dopamine but that fact that there are more dopamine receptors. More receptors lead to more firing and an over production of messages. Autopsies have found that there are generally a large number of dopamine receptors (Owen et al., 1987) and there was an increase in the amount of dopamine in the left amygdale (falkai et al. 1988) and increased dopamine in the caudate nucleus and putamen (Owen et al, 1978).

One criticism of the dopamine hypothesis is there is a problem with the chicken and egg. Is the raised dopamine levels the cause of the schizophrenia, or is it the raised dopamine level the result of schizophrenia?

It is not clear which comes first. This suggests that one needs to be careful when establishing cause and effect relationships in schizophrenic patients.

One of the biggest criticisms of the dopamine hypothesis came when Farde et al found no difference between schizophrenics’ levels of dopamine compared with ‘healthy’ individuals in 1990.

Noll (2009) also argues around one third of patients do not respond to drugs which block dopamine so other neurotransmitters may be involved.

A final weakness of the dopamine hypothesis is that it is biologically deterministic. The reason for this is because if the individual does have excessive amounts of dopamine then does it really mean that thy ey will develop schizophrenia? This suggests that the dopamine hypothesis does not account for freewill.

Neural Correlates

• Neural correlates are patterns of structure or activity in the brain that occur in conjunction with schizophrenia • People with schizophrenia have abnormally large ventricles in the brain . Ventricles are fluid filled cavities (i.e. holes) in the brain that supply nutrients and remove waste. This means that the brains of schizophrenics are lighter than normal. The ventricles of a person with schizophrenia are on average about 15% bigger than normal (Torrey, 2002).

A strength is that the research into enlarged ventricles and neurotransmitter levels have high reliability. The reason for this is because the research is carried out in highly controlled environments, which specialist, high tech equipment such as MRI and PET scans.

These machines take accurate readings of brain regions such as the frontal and pre-frontal cortex, the basil ganglia, the hippocampus and the amygdale. This suggests that if this research was tested and re-tested the same results would be achieved.

Supporting evidence for the brain structure explanation comes from further empirical support from Suddath et al. (1990). He used MRI (magnetic resonance imaging) to obtain pictures of the brain structure of MZ twins in which one twin was schizophrenic.

The schizophrenic twin generally had more enlarged ventricles and a reduced anterior hypothalamus. The differences were so large the schizophrenic twins could be easily identified from the brain images in 12 out of 15 pairs.

This suggests that there is wider academic credibility for enlarged ventricles determining the likelihood of schizophrenia developing.

A second weakness of the neuroanatomical explanations is that it is biologically deterministic. The reason for this is because if the individual does have large ventricles then does it really mean that they will develop schizophrenia? This suggests that the dopamine hypothesis does not account for freewill.

Section 3: Psychological Explanations for Schizophrenia

Family dysfunction.

Family Dysfunction refers to any forms of abnormal processes within a family such as conflict, communication problems, cold parenting, criticism, control and high levels of expressed emotions. These may be risk factors for the development and maintenance of schizophrenia.

• Laing and others rejected the medical / biological explanation of mental disorders. They did not believe that schizophrenia was a disease. They believed that schizophrenia was a result of social pressures from life. Laing believed that schizophrenia was a result of the interactions between people, especially in families. • Bateson et al. (1956) suggested the double bind theory, which suggests that children who frequently receive contradictory messages from their parents are more likely to develop schizophrenia. For example parents who say they care whilst appearing critical or who express love whilst appearing angry. They did not believe that schizophrenia was a disease. They believed that schizophrenia was a result of social pressures from life. • Prolonged exposure to such interactions prevents the development of an internally coherent construction of reality; in the long run, this manifests itself as typically schizophrenic symptoms such as flattening affect, delusions and hallucinations, incoherent thinking and speaking, and in some cases paranoia. • Another family variable associated with schizophrenia is a negative emotional climate, or more generally a high degree of expressed emotion (EE). EE is a family communication style that involves criticism, hostility and emotional over-involvement. The researchers concluded that this is more important in maintaining schizophrenia than in causing it in the first place, (Brown et al 1958). Schizophrenics returning to such a family were more likely to relapse into the disorder than those returning to a family low in EE. The rate of relapse was particularly high if returning to a high EE family was coupled with no medication.

One strength of the double bind explanation comes from further empirical support provided by Berger (1965). They found that schizophrenics reported a higher recall of double bind statements by their mothers than non-schizophrenics.

However, evidence may not be reliable as patient’s recall may be affected by their schizophrenia. This suggests that there is wider academic credibility for the idea of contradictory messages causing schizophrenia.

A second strength of the research into expressed emotion (EE) is that it has practical applications. For example Hogarty (1991) produced a type of therapy session, which reduced social conflicts between parents and their children which reduced EE and thus relapse rates.

This suggests that gaining an insight into family relationships allows psychiatric professionals to help improve the quality of patient’s lives.

Individual differences – EE is associated with relapse but not all patients who live in high EE families relapse and not all patients in low EE families avoid relapse – Family dysfunction is an incomplete explanation for schizophrenia.

A weakness of the family relationsships appraoch is that there is a problem of cause and effect. Mischler & Waxler (1968) found significant differences in the way mothers spoke to their schizophrenic daughters compared to their normal daughters, which suggests that dysfunctional communication may be a result of living with the schizophrenic rather than the cause of the disorder.

This suggests that there is a problem of the chicken and egg scenario in relation to expressed emotion causing schizophrenia.

A second weakness of the double bind theory is that there are ethical issues. There are serious ethical concerns in blaming the family, particularly as there is little evidence upon which to base this.

Gender bias is also an issue as the mother tends to be blamed the most, which means such research is highly socially sensitive. This suggests that the research therefore does not protect individuals from harm.

Cause and effect – It remains unclear whether cognitive factors cause schizophrenia or if schizophrenia causes these cognitions – Family dysfunction may not be a valid explanation for schizophrenia.

Cognitive explanations

including dysfunctional thought processing.

Cognitive approaches examine how people think, how they process information. Researchers have focused on two factors which appear to be related to some of the experiences and behaviors of people diagnosed with schizophrenia.

First, cognitive deficits which are impairments in thought processes such as perception, memory and attention. Second, cognitive biases are present when people notice, pay attention to, or remember certain types of information better than other.

Cognitive Deficits

• There is evidence that people diagnosed as schizophrenic have difficulties in processing various types of information, for example visual and auditory information. Research indicates their attention skills may be deficient – they often appear easily distracted. • A number of researchers have suggested that difficulties in understanding other people’s behavior might explain some of the experiences of those diagnosed as schizophrenic. Social behavior depends, in part, on using other people’s actions as clues for understanding what they might be thinking. Some people who have been diagnosed as schizophrenic appear to have difficulties with this skill. • Cognitive deficits have been suggested as possible explanations for a range of behaviors associated with schizophrenia. These include reduced levels of emotional expression, disorganised speech and delusions.

Cognitive Biases

• Cognitive biases refer to selective attention. The idea of cognitive biases has been used to explain some of the behaviors which have been traditionally regarded as ‘symptoms’ of ‘schizophrenia’. • Delusions: The most common delusion that people diagnosed with schizophrenia report is that others are trying to harm or kill them – delusions of persecution. Research suggests that these delusions are associated with specific biases in reasoning about and explaining social situations. Many people who experience feelings of persecution have a general tendency to assume that other people cause the things that go wrong with their lives.

A strength of the cognitive explanation is that it has practical applications. Yellowless et al. (2002) developed a machine that produced virtual hallucinations, such as hearing the television telling you to kill yourself or one person’s face morphing into another’s.

The intention is to show schizophrenics that their hallucinations are not real. This suggests that understanding the effects of cognitive deficits allows psychologists to create new initiatives for schizophrenics and improve the quality of their lives.

A final strength is that it takes on board the nurture approach to the development of schizophrenia. For example, it suggests that schizophrenic behavior is the cause of environmental factors such as cognitive factors.

One weakness of the cognitive explanation is that there are problems with cause and effect. Cognitive approaches do not explain the causes of cognitive deficits – where they come from in the first place.

Is it the cognitive deficits which causes the schizophrenic behavior or is the schizophrenia that causes the cognitive deficits? This suggests that there are problems with the chicken and egg problem.

A second weakness of the cognitive model is that it is reductionist. The reason for this is because the approach does not consider other factors such as genes.

It could be that the problems caused by low neurotransmitters creates the cognitive deficits. This suggests that the cognitive approach is oversimplistic when consider the explanation of schizophrenia.

Section 4: Drug Therapy: typical and atypical antipsychotics

Drug therapy is a biological treatment for schizophrenia. Antipsychotic drugs are used to reduce the intensity of symptoms (particularly positive symptoms).

Typical Antipsychotics

• First generation Antipsychotics are called “Typical Antipsychotics” Eg. Chlorpromazine and Haloperidol. • Typical antipsychotic drugs are used to reduce the intensity of positive symptoms, blocking dopamine receptors in the synapses of the brain and thus reducing the action of dopamine. • They arrest dopamine production by blocking the D2 receptors in synapses that absorb dopamine, in the mesolimbic pathway thus reducing positive symptoms, such as auditory hallucinations. • But they tended to block ALL types of dopamine activity, (in other parts of the brain as well) and this caused side effects and may have been harmful.

Atypical Antipsychotics

• Newer drugs, called “atypical antipsychotics” attempt to target D2 dopamine activity in the limbic system but not D3 receptors in other parts of the brain. • Atypical antipsychotics such as Clozapine bind to dopamine, serotonin and glutamate receptors. • Atypical antipsychotic drugs work on negative symptoms, improving mood, cognitive functions and reducing depression and anxiety. • They also have some effect on other neurotransmitters such as serotonin . They generally have fewer side effects eg. less effect on movement Eg. Clozapine, Olazapine and Risperidone.

Since the mid-1950s antipsychotic medications have greatly improved treatment. Medications reduce positive symptoms particularly hallucinations and delusions; and usually allow the patient to function more effectively and appropriately.

Antipsychotic drugs are highly effective as they are relatively cheap to produce, easy to administer and have a positive effect on many sufferers. However they do not “cure” schizophrenia, rather they dampen symptoms down so that patients can live fairly normal lives in the community.

Kahn et al. (2008) found that antipsychotics are generally effective for at least one year, but second- generation drugs were no more effective than first-generation ones.

Some sufferers only take a course of antipsychotics once, while others have to take a regular dose in order to prevent symptoms from reappearing.

There is a sizeable minority who do not respond to drug treatment. Pills are not as helpful with other symptoms, especially emotional problems.

Older antipsychotics like haloperidol or chlorpromazine may produce side effects Sometimes when people with schizophrenia become depressed, so it is common to prescribe anti-depressants at the same time as the anti-psychotics.

All patients are in danger of relapsing but without medication the relapses are more common and more severe which suggests the drugs are effective.

Clozapine targets multiple neurotransmitters, not just dopamine, and has been shown to be more effective than other antipsychotics, although the possibility of severe side effects – in particular, loss of the white blood cells that fight infection.

Even newer antipsychotic drugs, such as risperidone and olanzapine are safer, and they also may be better tolerated. They may or may not treat the illness as well as clozapine, however.

Meta–analysis by Crossley Et Al (2010) suggested that Atypical antipsychotics are no more effective, but do have less side effects.

Recovery may be due to psychological factors – The placebo effect is when patients’ symptoms are reduced because they believe that it should.

However, Thornley et al carried out a meta-analysis comparing the effects of Chlorpromazine to placebo conditions and found Chlorpromazine to be associated with better overall functioning – Drug therapy is an effective treatment for SZ.

RWA – Offering drugs can lead to an enhanced quality of life as patients are given independence – Positive impact on the economy as patients can return to work and no longer need to be provided with institutional care.

Ethical issues – Antipsychotics have been used in hospitals to calm patients and make them easier for staff to work with rather than for the patients’ benefit – Can lead to the abuse of the Human Rights Act (no one should be subject to degrading treatment).

Severe side effects – Long term use can result in tardive dyskinesia which manifests as involuntary facial movements such as blinking and lip smacking – While they may be effective, the severity of the side effects mean the costs outweigh the benefits therefore they are not an appropriate treatment.

In most cases the original “typical antipsychotics” have more side effects, so if the exam paper asks for two biological therapies you can write about typical anti-psychotics and emphasise the side effects, then you can write about the atypical antipsychotics and give them credit for having less side effects.

Section 5: Psychological Therapies for Schizophrenia

Family therapy.

Family therapy is a form of therapy carried out with members of the family with the aim of improving their communication and reducing the stress of living as a family.

Family Therapy aims to reduce levels of expressed emotion, and reduced the likelihood of relapse.

Aims of Family Therapy

• To educate relatives about schizophrenia. • To stabilize the social authority of the doctor and the family. • To improve how the family communicated and handled the situation. • To teach patients and carers more effective stress management techniques.

Methods used in Family Therapy

• Pharoah identified examples of how family therapy works: It helps family members achieve a balance between caring for the individual and maintaining their own lives, it reduces anger and guilt, it improves their ability to anticipate and solve problems and forms a therapeutic alliance. • Families taught to have weekly family meetings solving problems on family and individual goals, resolve conflict between members, and pinpoint stressors. • Preliminary analysis: Through interviews and observation the therapist identifies strengths and weaknesses of family members and identifies problem behaviors. • Information transfer – teaching the patient and the family the actual facts about the illness, it’s causes, the influence of drug abuse, and the effect of stress and guilt. • Communication skills training – teach family to listen, to express emotions and to discuss things. Additional communication skills are taught, such as “compromise and negotiation,” and “requesting a time out” . This is mainly aimed at lowering expressed emotion.

A study by Anderson et al. (1991) found a relapse rate of almost 40% when patients had drugs only, compared to only 20 % when Family Therapy or Social Skills training were used and the relapse rate was less than 5% when both were used together with the medication.

Pharaoh et al. (2003) meta – analysis found family interventions help the patient to understand their illness and to live with it, developing emotional strength and coping skills, thus reducing rates of relapse.

Pharoah identified examples of how family therapy works: It helps family members achieve a balance between caring for the individual and maintaining their own lives, it reduces anger and guilt, it improves their ability to anticipate and solve problems and forms a therapeutic alliance.

Economic Benefits: Family therapy is highly cost effective because it reduces relapse rates, so the patients are less likely to take up hospital beds and resources. The NICE review of family therapy studies demonstrated that it was associated with significant cost savings when offered to patients alongside the standard care – Relapse rates are also lower which suggests the savings could be even higher.

Lobban (2013) reports that other family members felt they were able to cope better thanks to family therapy. In more extreme cases the patient might be unable to cope with the pressures of having to discuss their ideas and feelings and could become stressed by the therapy, or over-fixated with the details of their illness.

Token Economy

• Token economies aim to manage schizophrenia rather than treat it. • They are a form of behavioral therapy where desirable behaviors are encouraged by the use of selective reinforcement and is based on operant conditioning. • When desired behavior is displayed eg. Getting dressed, tokens (in the form of coloured discs) are given immediately as secondary reinforcers which can be exchanged for rewards eg. Sweets and cigarettes. • This manages schizophrenia because it maintains desirable behavior and no longer reinforces undesirable behavior. • The focus of a token economy is on shaping and positively reinforcing desired behaviors and NOT on punishing undesirable behaviors. The technique alleviates negative symptoms such as poor motivation, and nurses subsequently view patients more positively, which raises staff morale and has beneficial outcomes for patients. • It can also reduce positive symptoms by not rewarding them, but rewarding desirable behavior instead. Desirable behavior includes self-care, taking medication, work skills, and treatment participation.

Paul and Lentz (1977) Token economy led to better overall patient functioning and less behavioral disturbance, More cost-effective (lower hospital costs)

Upper and Newton (1971) found that the weight gain associated with taking antipsychotics was addressed with token economy regimes. Chronic schizophrenics achieved 3lbs of weight loss a week.

McMonagle and Sultana (2000) reviewed token economy regimes over a 15-year period, finding that they did reduce negative symptoms, though it was unclear if behavioral changes were maintained beyond the treatment programme.

It is difficult to keep this treatment going once the patients are back at home in the community. Kazdin et al. Found that changes in behavior achieved through token economies do not remain when tokens are with¬drawn, suggesting that such treatments address effects of schizophrenia rather than causes. It is not a cure.

There have also been ethical concerns as such a process is seen to be dehumanising, subjecting the patient to a regime which takes away their right to make choices.

In the 1950s and 60s nurses often “rewarded” patients with cigarettes. Due to the pivotal role of dopamine in schizophrenia this led to a culture of heavy smoking an nicotine addiction in psychiatric hospitals of the era.

Ethical issues – Severely ill patients can’t get privileges because they are less able to comply with desirable behaviors than moderately ill patients – They may suffer from discrimination

Cognitive Behavioral Therapy

In CBT, patients may be taught to recognise examples of dysfunctional or delusional thinking, then may receive help on how to avoid acting on these thoughts. This will not get rid of the symptoms of schizophrenia but it can make patients better able to cope with them.

Central idea: Patients problems are based on incorrect beliefs and expectations. CBT aims to identify and alter irrational thinking including regarding:

• General beliefs.
• Self image.
• Beliefs about what others think.
• Expectations of how others will act.
• Methods of coping with problems.

In theory, when the misunderstandings have been swept away, emotional attitudes will also improve.

Assessment : The therapist encourages the patient to explain their concerns.

• describing delusions • reflecting on relationships • laying out what they hope to achieve through the therapy.

Engagement :

The therapist wins the trust of the patient, so they can work together. This requires honesty, patience and unconditional acceptance. The therapist needs to accept that the illusions may seem real to the patient at the time and should be dealt with accordingly.

ABC : Get the patients to understand what is really happening in their life:

A: Antecedent – what is triggering your problem ? B: behavior – how do you react in these situations ? C: Consequences – what impact does that have on your relationships with others?

Normalisation :

Help the patient realise it is normal to have negative thoughts in certain situations. Therefore there is no need to feel stressed or ashamed about them.

Critical Collaborative Analysis :

Carrying on a logical discussion till the patient begins to see where their ideas are going wrong and why they developed. Work out ways to recognise negative thoughts and test faulty beliefs when they arise, and then challenge and re-think them.

Developing Alternative Explanations :

Helping the patient to find logical reasons for the things which trouble them Let the patient develop their own alternatives to their previous maladaptive behavior by looking at coping strategies and alternative explanations.

Another form of CBT: Coping Strategy Enhancement (CSE)

• Tarrier (1987) used detailed interview techniques, and found that people with schizophrenia can often identify triggers to the onset of their psychotic symptoms, and then develop their own methods of coping with the distress caused. These might include things as simple as turning up the TV to drown out the voices they were hearing! • At least 73% of his sample reported that these strategies were successful in managing their symptoms. • CSE aims to teach individuals to develop and apply effective coping strategies which will reduce the frequency, intensity and duration of psychotic symptoms and alleviate the accompanying distress. There are two components: 1. Education and rapport training: therapist and client work together to improve the effectiveness of the client’s own coping strategies and develop new ones. 2. Symptom targeting: a specific symptom is selected for which a particular coping strategy can be devised Strategies are practised within a session and the client is helped through any problems in applying it. They are then given homework tasks to practice, and keep a record of how it worked.

CBT does seem to reduce relapses and readmissions to hospital (NICE 2014). However, the fact that these people were on medication and having regular meetings with doctors would be expected to have that effect anyway.

Turkington et al. (2006) CBT is highly effective and should be used as a mainstream treatment for schizophrenia wherever possible.

Tarrier (2005) reviewed trials of CBT, finding evidence of reduced symptoms, especially positive ones, and lower relapse rates.

Requires self-awareness and willingness to engage – Held back by the symptoms schizophrenics encounter – It is an ineffective treatment likely to lead to disengagement.

Lengthy – It takes months compared to drug therapy that takes weeks which leads to disengaged treatment as they don’t see immediate effects – A patient who is very distressed and perhaps suicidal may benefit better in the short term from antipsychotics.

Addington and Addington (2005) claim that CBT is of little use in the early stages of an acute schizophrenic episode, but perhaps more useful when the patient is more calm and beginning to worry about how life will be after they recover. In other words, it doesn’t cure schizophrenia, it just helps people get over it.

Research in Hampshire, by Kingdon and Kirschen (2006) found that CBT is not suitable for all patients, especially those who are too thought disorientated or agitated, who refuse medication, or who are too paranoid to form trusting alliances with practitioners.

As there is strong evidence that relapse is related to stress and expressed emotion within the family, it seems likely that CBT should be employed alongside family therapy in order to reduce the pressures on the individual patient.

Section 6: Interactionist Approach

The Interactionist approach acknowledges that there are a range of factors (including biological and psychological) which are involved in the development of schizophrenia.

The Diathesis-stress Model

• The diathesis-stress model states that both a vulnerability to SZ and a stress trigger are necessary to develop the condition. • Zubin and Spring suggest that a person may be born with a predisposition towards schizophrenia which is then triggered by stress in everyday life. But if they have a supportive environment and/or good coping skills the illness may not develop. • Concordance rates are never 100% which suggests that environmental factors must also play a role in the development of SZ. MZ twins may have the same genetic vulnerability but can be triggered by different stressors. • Tienari Et. A. (2004): Adopted children from families with schizophrenia had more chance of developing the illness than children from normal families. This supports a genetic link. However, those children from families schizophrenia were less likely to develop the illness if placed in a “good” family with kind relationships, empathy, security, etc. So environment does play a part in triggering the illness.

Holistic – Identifies that patients have different triggers, genes etc. – Patients can receive different treatments for their SZ which will be more effective.

Falloon et al (1996) stress – such as divorce or bereavement, causes the brain to be flooded with neurotransmitters which brings on the acute episode.

Brown and Birley (1968) 50% people who had an acute schizophrenic episode had experienced a major life event in 3 weeks prior.

Substance abuse: Amphetamine and Cannabis and other drugs have also been identified as triggers as they affect serotonin and glutamate levels.

Vasos (2012) Found the risk of schizophrenia was 2.37 times greater in cities than it was in the countryside, probably due to stress levels. Hickling (1999) the stress of urban living made African-Carribean immigrants in Britain 8 to 10 times more likely to experience schizophrenia.

Faris and Dunham (1939) found clear pattern of correlation between inner city environments and levels of psychosis. Pederson and Mortensen (Denmark 2001) found Scandanavian villages have very LOW levels of psychosis, but 15 years of living in a city increased risk.

Fox (1990): It is more likely that factors associated with living in poorer conditions (e.g. stress) may trigger the onset of schizophrenia, rather than individuals with schizophrenia moving down in social status.

Bentall’s meta-analysis (2012) shows that stress arising from abuse in childhood increases the risk of developing schizophrenia.

Toyokawa, Et. Al (2011) suggest many aspects of urban living – ranging from life stressors to the use of drugs, can have an effect on human epigenetics. So the stressors of modern living could cause increased schizophrenia in future generations.

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Specifications that use this resource:

• GCSE Psychology 8182

Lesson plan: The Sapir-Whorf hypothesis: Paper 2 Section B Language, thought and communication

This is a sample lesson plan to help teachers to structure a one hour lesson on the Sapir-Whorf hypothesis in the 'Language, thought and communication' topic on Paper 2 of our GCSE Psychology specification (8182). It's a guide only and can be amended to suit teachers and their students’ needs.

Learning objectives

• All students should be able to understand and evaluate the Sapir-Whorf hypothesis.
• Some students will be able to give a more detailed evaluation of the Sapir-Whorf hypothesis.
• All students should be aware of some psychological evidence suggesting that there are variations in recall of events and recognition of colours.
• All students should be able to draw on knowledge and understanding of the entire course of study to show a deeper understanding of the theories about language and thought.

Prior knowledge needed

Students don't need prior knowledge but will benefit from having studied Piaget's theory that language depends on thought (also in the 'Language, thought and communication topic' of this specification).

Resources and preparation

• Differentiated study sheets that provide method, results etc for relevant studies
• Relevant textbook pages for the topic
• YouTube: The Sapir-Whorf hypothesis
• What is the Sapir-Whorf hypothesis?
• Whodunnit? Cross-linguistic differences in eye-witness memory

Further work and reading

Students to write an answer to a 9 mark exam question in the 'Memory' section of SAMS for 81821.

Preparation for next lesson

Complete homework.

Document URL https://www.aqa.org.uk/resources/psychology/gcse/psychology/teach/lesson-plan-the-sapir-whorf-hypothesis

Last updated 25 Apr 2019