Psychological Research Methods

Front 1

Define validity.

Back 1

Validity is the extent to which a study measures what it intends to measure (internal) and the extent to which the findings can be generalises beyond the research settings they were found (external).

Front 2

Define face validity.

Back 2

Whether a test, scale or measure appear on 'the face of it' to measure what it intends to measure.

Front 3

How can you determine face validity?

Back 3

'Eyeballing' the measuring instrument or passing it onto an expert to check.

Front 4

Define concurrent validity.

Back 4

Demonstrated when the results obtained are very close to those obtained on another recognisable scale/test.

Front 5

Give an example of concurrent validity.

Back 5

If a new IQ test was administered and the IQ scores they achieve may be compared with their performance on another IQ test such as the Standford-Binet test. Close agreement between the two sets of data indicate that the new test has concurrent validity (+0.8).

Front 6

In an experimental piece of research, what validity issues may arise?

Back 6

Demand characteristics

Investigator effects

Front 7

In an experimental piece of research, how could you resolve any validity issues?

Back 7

Use a control group

Standardised procedures

Single/double blind procedures

Front 8

In a questionnaire, what validity issues may arise?

Back 8

Social desirability bias

Leading questions

Front 9

In a questionnaire, how may you resolve any validity issues that may arise?

Back 9

Respondents remain anonymous

Using a lie scale

Front 10

In an observation, what validity issues may arise?

Back 10

Demand characteristics

Investigator effects (overt)

Broad/overlapping behavioural categories

Front 11

In an observation, how may you resolve any validity issues that may arise?

Back 11

Operationalised behavioural categories

Control group

Use a covert observation instead

Front 12

When using qualitative methods, what validity issues may arise?

Back 12

Population validity (case studies)

Researcher bias

Open to interpretation (subjective)

Front 13

When using qualitative methods, how can you resolve any validity issues that may arise?

Back 13

Coherence of researchers reporting

Use of direct quotes

Triangulation

Front 14

Define reliability.

Back 14

When a psychological measure can be used multiple times within the same results; it is said to be reliable.

Front 15

How can you assess reliability?

Back 15

Test-retest method

Inter-rater reliability

Front 16

Describe the test-restest method.

Back 16

- Commonly applied when assessing the relaibility of psychological tests; e.g. personality, IQ or questionnaires.

- The test is administered twice to the same participant and the results are compared

- If scores are obtained then a correlation can be calculated (correlation co-efficient).

- A reliable result is one that is +0.8.

Front 17

Name a problem with using the test-retest method.

Back 17

- Deciding on the time-lapse between tests.

- There must be sufficient time in case the attitude or ability being tested actually changes.

Front 18

Describe inter-rater reliability.

Back 18

- Involves checking the consistency of ratings that two or more independent researchers have completed.

- The two observers will apply the behavioural categories to a test run (also known as pilot study) and the consistency of the results will be assessed.

Front 19

When using a questionnaire, what reliability issues may arise?

Back 19

- Questions may be too complex/ambiguous

- Questions may be interpreted differently by the same person on a different occasion.

Front 20

When using a questionnaire, how can the reliability be improved?

Back 20

- Test retest

- Create a correlation co-efficient

- Pilot study to rewrite/improve

- Poorly written questions can be replaced with closed questions

Front 21

When using an interview, what reliability issues may arise?

Back 21

- Questions may be leading or too ambiguous

- The participant could waffle on (qualitative data)

- Interviewer bias

Front 22

When using an interview, how can the reliability be improved?

Back 22

- Use the same interviewer each time

- Ensure interviewers are trained

- Use a structured interview method

Front 23

When using an experiment, what reliability issues may arise?

Back 23

Participants may be tested under slightly different conditions each time

Front 24

When using an experiment, how can the reliability be improved?

Back 24

- Use the same instructions for each participant (standardised)

- Use the same conditions for each participants

Front 25

When using an observation, what reliability issues may arise?

Back 25

- Different observes have different opinions/judgements

- Observer bias

- Might not have operationalised behaviour categories

Front 26

When using an observation, how can the reliability be improved?

Back 26

- All behavioural categories are correctly operationalised

- All possible behaviours included in the checklist

- Train the observers

Front 27

Define content analysis.

Back 27

A research technique that allows qualitative data to be placed into categories or themes.

Front 28

Define the different methods of content analysis.

Back 28

1. Coding

2. Thematic analysis

Front 29

Describe coding as a method of content analysis.

Back 29

The stage of a content analysis in which the communication to be studied is analysed by identifying each instance of the chosen categories (which may be words, phrases or even sentences).

Front 30

Describe thematic analysis as a method of content analysis.

Back 30

An inductive and qualitative approach to analysis to involves identifying or explicit ideas within the data. Theories will often emerge once the data has been coded.

Front 31

What two ways can you deal with and analyse qualitative data?

Back 31

- Turn it into qualitative data by coding and categorising it. Then use statistical tests to analyse it.

- Analyse each sentence and identify or seek out theme in the content.

Front 32

How can a researcher review and amend themes in a content analysis?

Back 32

1. Researcher makes themselves familiar with the data.

2. Categorise the information into meaningful units.

3. Count/label each time this theme occurs in the information.

Front 33

Evaluate content analysis.

Back 33

+ Flexibility (in terms of analysing and representing the data according to the aims of the research)

+ Ethical and valid nature (already in the public domain - consent/mundane realism)

- Lack of objectivity (reflexivity - used in descriptive forms of analysis)

- Risk of researcher bias

Front 34

Explain why case studies are examples of an idiographic approach.

Back 34

- Often observing a single participants or a group of similar participants.

- Focus on the individual rather than developing a set of laws.

Front 35

What do case studies allow a researcher to do that a nomothetic approach does not?

Back 35

Allow a researcher to investigate into a topic in much more detail than if the researcher was trying to generalise a large number of participants.

Front 36

What kind of qualitative techniques lend themselves to generating material suitable for a case study?

Back 36

- Semi-structured interviews

- Participant observation

- Personal notes; diaries, letters, notes

- Official documents; clinical notes, appraised reports

Front 37

Describe an intrinsic case study.

Back 37

- Only represent themselves

- Knowledge from them is pursued for the sake of knowing rather than a general problem

Front 38

Describe an instrumental case study.

Back 38

- Examples of general phenomenon

- Provides the researcher with an opportunity to study the phenomenon by:

Identifying it

Explaining it

Front 39

Name 5 examples of what 'case' could refer to.

Back 39

1. Person - study of a single individual

2. Group - study of a distinctive set of people

3. Location - study of place

4. Organisation - study of a single organisation

5. Event - study of a particular social/cultural event

Front 40

Outline the case study of Koluchova (1976).

Back 40

- Czechoslovakian, male, identified twins

- Mother died during birth

- Father was of low intelligence

- Boys were never allowed out of the house

- Kept in a small untreated closet

- Discovered at age 7

- Could hardly walk, had acute rickets, fearful, poor speech

- After having lived in a foster home, as adults they appear well adjusted and cognitively able

Front 41

Outline the case study of Curtiss (1977).

Back 41

- Genie was found aged 13

- History of isolation, neglect and physical resistant

- Kept strapped to a child's potty in the attic

- On discover her appearance was of a 6/7 year old child

- Unsocialised, primitive and 'hardly human'

- Made virtually no sound and couldn't walk

- Hasn't achieved full social adjustment or language despite intervention

Front 42

Outline the case study of Corkin (1984).

Back 42

- HM (27 year old male)

- Operated on his brain to relieve extreme epilepsy which influenced his memory

- Could recall most experiences before the operation

- Couldn't remember new experiences for more than 15 minutes

- Declarative memories (memories of facts/events) vanished

- With practise he could acquire new skills like playing tennis

- Now in his 70's he cannot recognise a photo of himself

Front 43

Outline the case study of Freud (1909).

Back 43

- Analysis of a phobia of horse in a 5 year old boy (Hans)

- Family lived opposite a coaching inn so Hans was afraid to leave the house

- Scared of the noise they made with their feet

- Symptomatic of his Oedipus complex

- Horses represented his dad/allowed him to stay at home with his mother

- Freud considered that this represented a disguised form of castration threat anxiety

Front 44

Define a case study.

Back 44

An event, problem, process, activity or programme of a single person or several similar people.

Front 45

Define a bounded system of a case study.

Back 45

Boundaries of the case; usually time and/or space.

Front 46

How many forms of data do case studies use?

Back 46

Multiple sources (almost every kind of qualitative data).

Front 47

What three types of case study are there?

Back 47

Single instrumental case study

Collective/multiple case study

Intrinsic case study

Front 48

Define a single, instrumental case study.

Back 48

Researcher focuses on an issue/concern and then selects a bounded case to illustrate that issue/concern.

Front 49

Define a collective case study.

Back 49

Researcher focuses on an issue/concerns and then selects several bounded cases to illustrate that issue.

Front 50

Describe the method of a case study.

Back 50

1. Determine if a case study will answer your research question

2. Identify the case and what types of case study will be used

3. After collecting data, the researcher analyses the data to determine common themes between all of the cases (cross-case analysis)

4. Assertions, when the researcher makes interpretations of the meaning of the case/themes. Researcher makes statements about the lessons learned from the case )what should be learned from the meaning of the data)

Front 51

Describe the strengths of the case study.

Back 51

+ Can stimulate new research into extraordinary behaviour that may be unlikely to be investigated otherwise (due to ethics)

+ Can challenge established theories

+ Rich, detailed in-depth data is produced

+ Can allow access to investigations which cannot be manipulated in research labs

Front 52

Describe the weaknesses of the case study.

Back 52

- Challenging to determine the case or find an issue/cause and then find a case to illustrate it or study the case itself

- Challenging to determine whether to study/multiple cases

- Challenging to define the boundaries of the case (time consuming)

- Replication and generalisation not possible due to the uniqueness of the situation

- Risk of researcher bias

- Memory distortion when reconstructing case history can mean that memory events are subject to influence

Front 53

Define an aim.

Back 53

A general statement of purpose (what the researcher intends to investigate, the purpose of the study).

Front 54

Define a hypothesis.

Back 54

Prediction or relationship (a clear, precise, testable statement).

Front 55

Define directional hypothesis (one tailed).

Back 55

States the direction of the difference or relationship, these tend to be used when the findings of the previous research studies suggest a particular outcome.

Front 56

Define a non-directional hypothesis (two tailed).

Back 56

Does not state the direction, these tend to be used when there is no previous research, or findings from previous research are contradictory.

Front 57

Define a variable.

Back 57

Anything that can vary or change within the investigation.

Front 58

Define an independent variable.

Back 58

An aspect of the experimental situation which is manipulated by the researcher or changes naturally so that the DV can be measured.

Front 59

Define a dependent variable.

Back 59

The variable that is measured by the researcher.

Front 60

Define an extraneous variable.

Back 60

Any variable other than the independent variable that may have an effect on the dependent variable if it is not controlled.

Front 61

Give an example of an extraneous variable.

Back 61

Participant variables - e.g. age, personality

Situational variables - e.g. noise, temperature

Confounding variables - have already impacted the results

Front 62

Define a target population.

Back 62

A group of people who are the focus of the researcher's interest from which a smaller sample is drawn.

Front 63

Define a sample.

Back 63

A group of people who take part in a research investigation. The sample is drawn from a target population and is presumed to be a representative of that population.

Front 64

Describe random sampling.

Back 64

All members of the target population have an equal chance of being selected.

A list of all members of the target population is obtained, all are then assigned a number.

The sample is then generated through a lottery methods (a computer based randomiser).

Front 65

Describe systematic sampling.

Back 65

A type of probability sampling in which sample methods from a larger population are selected according to a random starting point and a fixed periodic interval.

The researcher first randomly picks the first item from the population, then they will select each nth subject from the list.

Front 66

Describe stratified sampling.

Back 66

When the entire population is divided into subgroups (strata) based on members shared attributes.

Then the population is randomly selected within each category.

Front 67

Describe opportunity sampling.

Back 67

Consists of taking the sample from people who are available at the time the study was carried out and fits the criteria you are looking for.

Based on convince.

Front 68

Describe opportunity sampling.

Back 68

A volunteer selecting participants selecting themselves to be part of the sample; hence it is self-selection.

To select a volunteer sample, a researcher may place an advert in a newspaper or in a common room notice board.

Front 69

Define bias.

Back 69

When certain groups may be over to under-represented within the sample selected. This limits the extent to which generalisations can be made to the target population.

Front 70

Define generalisation.

Back 70

The extent to which findings and conclusions from a particular investigation can be broadly applied to the population. This is made possible if the sample of participants is representative of the population.

Front 71

Define a pilot study.

Back 71

A small scale version of an investigation that takes place before the real investigation.

Front 72

Describe the process of a pilot study.

Back 72

- Carried out before the main study.

- Often changes are made to the design as a result.

- Pilot study data will not be included in the final data.

- Piloting potentially saves time and money because it helps avoid flawed designs.

Front 73

Describe a lab experiment.

Back 73

- Conducted in a well controlled environment.

- Allows accurate measurements to be made.

- Researchers decides where, how and when the experiment takes place and which participants.

Front 74

Describe a field experiment.

Back 74

- Conducted in the 'real world'.

- More naturalistic setting in a lab.

- Experiments carried out in this method are more representative of everyday life.

Front 75

Describe a natural experiment.

Back 75

- External

- The researcher takes advantage of a pre-existing independent variable.

- Called natural because the variable would have changes even if the experiment tried to stop it.

- Conditions created naturally.

- Can be tested in a lab.

Front 76

Describe a quasi experiment.

Back 76

- Internal

- An IV that is based on an existing difference between people (e.g age or gender).

- No one can manipulate this variable, it simply exists.

Front 77

Evaluate lab experiments.

Back 77

+ Easy to replicate

+ Precise control of EV/IV allowing cause-effect to be established

- Artificial setting (ecological validity)

- Demand characteristics may bias results

Front 78

Evaluate field experiments.

Back 78

+ More likely to reflect real life

+ Less demand characteristics

- Less control over EVs

- Difficult to replicate

Front 79

Evaluate natural experiments.

Back 79

+ Can be used in situations which would be ethically unacceptable to manipulate IV

- More expensive and time consuming

- No control over EV

- Difficult to replicate

Front 80

Define ecological validity.

Back 80

The extent to which findings of a research study are able to be generalised to real life settings.

Front 81

Define mundane realism.

Back 81

The extent to which an activity or the entire study itself is similar to an activity or process one would complete in day to day life. Measure of ecological validity.

Front 82

Define demand characteristics.

Back 82

Any cue from the researcher or from the research situation that may be interpreted by participants as revealing the purpose of the investigation. This may lead to the participants changing their behaviour within the research situation.

Front 83

Define social desirability.

Back 83

A bias that describes the tendency of survey respondents to answer questions in a manner which will be viewed favourably by others.

Front 84

Define the 'screw-you' effect.

Back 84

When a participant actively goes out of their way to do everything wrong in an experiment.

Front 85

Define descriptive statistics.

Back 85

The term given to the analysis of data that helps to describe the numerical results of a piece of research (e.g. graphs, measures of central tendency and measures of dispersion).

Front 86

Define measures of central tendency.

Back 86

Mean

Mode

Median

Front 87

Define biomodel.

Back 87

Some data sets have two modes (two numbers that appear the most)

Front 88

How do you overcome biomodel?

Back 88

Use different measures of central tendency.

Front 89

Define the mean.

Back 89

Add up all the results, divide by the number of results.

Front 90

Define the median.

Back 90

Place results numerically, find the central number.

Front 91

Define the mode.

Back 91

Number that appears the most frequently in a set of data.

Front 92

Evaluate the mean.

Back 92

Can't be identified within categorised data

Affected by outliers (anonymous results)

Front 93

Evaluate the median.

Back 93

Doesn't acknowledge average.

Front 94

Evaluate the mode.

Back 94

Not representative of the whole

Risk of bimodal

Front 95

Define measures of dispersion.

Back 95

Describes how widely the scores vary and are spread from one another:

Range

Standard deviation

Front 96

Evaluate the mean.

Back 96

+ The only MCT that includes all values/scores and is the most sensitive.

+ Provides the most representative score.

- Easily distorted by extreme scores.

Front 97

Evaluate the median.

Back 97

+ Middle value is set

- Unrepresentative of all the data

+ Not effected by extreme scores

Front 98

Evaluate the mode.

Back 98

- Can be bimodel.

- Unrepresentative of all the data

+ When the data is categorical, this is the only MCT that can be used.

+ Not affected by extreme scoresE

Front 99

Describe the range.

Back 99

Calculates the spread of scores.

Can be calculated by subtracting the lowest value from the highest.

Front 100

Describe standard deviation.

Back 100

Calculates the spread of scores around the mean value.

Larger the standard deviation, the greater the dispersion and spread of scores.

Front 101

What does a large SD suggest?

Back 101

Not all the participants are effected by the IV in the same way because the scores are widely spread. Whereas a small standard deviation would suggest that most participants responded in the same way and that the scores are all tightly packed.

Front 102

Identify three characteristics of presenting data using a scatter graph.

Back 102

- To show correlation

- To show a direction (positive/negative)

- No manipulation of 1 variable

Front 103

How can raw data be presented in a report?

Back 103

Table of descriptive statistics

Descriptive summary paragraph

Presentative of data in a graph

Front 104

How do you create a table of descriptive statistics?

Back 104

- All tables must have a title

- The table mist only display 1 MCT and 1 MD

- Describe the key findings, you must only describe the data reported in the table, you can't make any suggestions about why these results may have been found.

Front 105

Define a graph.

Back 105

A visual aid that help make sense of quantitative data, they provide an overall picture that helps summarise the results and show patterns within the data.

Front 106

What type of graph would you use for discrete/nominal data?

Back 106

Bar chart

Front 107

What type of graph would you use for correlational data?

Back 107

Scattergraphs

Front 108

What type of graph would you use for frequency/interval data?

Back 108

Distributions

Front 109

Define a distribution.

Back 109

A visual way of examining how frequency data falls within a graph.

Front 110

Describe a normal distribution curve.

Back 110

When there is a large amount of frequency data, the distributions prevents a symmetrical 'bell curve'. Most people fall in the middle with very few people falling in the extreme ends. The ends of the tail never touch the axis and therefore never reaches 0 as more extreme scores are always possible.

Front 111

Where do mean, median and mode fall on a normal distribution curve?

Back 111

All occupy the same middle point of the curve because they are all very similar in value.

Front 112

Describe a positive skew on a distribution curve.

Back 112

When most of the distribution is concentrated towards the left of the graph and there is a long tail on the right.

Front 113

Give an example of a positive skew on a distribution curve.

Back 113

Most students in an example got a really low score on an exam.

Front 114

Describe a negative skew on a distribution curve.

Back 114

When most of the distribution is concentrated towards the right of the graph meaning there is a long tail on the left.

Front 115

Give an example of a negative skew on a distribution curve.

Back 115

Most of the students in a class score really highly on an exam.

Front 116

Where do mean, median and mode fall on a skewed distribution curve?

Back 116

The measures of central tendency are not all positioned in the centre; mode remains the highest point in the peak, median always comes second (this is because the median and mode are not effected by extreme scores in the data). Mean is always positioned further way from the mid-point because it is affected by extreme scores.

Front 117

Define investigator effects.

Back 117

Any effect of the investigators behaviour (conscious or unconscious) on the research outcome (DV).

Front 118

Give an example of investigator effects.

Back 118

Presence of a researcher

Way in which the researcher asks the questions

Researchers expectations of what the findings may be

Gender/age of the researcher

Front 119

Give an example of demand characteristics.

Back 119

What the participants may have heard from other participants

Verbal communication

Setting of the study

Characteristics of the researcher

Front 120

Define randomisation.

Back 120

The use of chance in order to control for the effects of bias when designing a study.

Front 121

Define standardisation.

Back 121

Using exactly the same formalised procedures and instructions for all participants in a research study.

Front 122

Give an example of randomisation.

Back 122

A memory experiment that involves recalling words from a list. The list must be randomised through a computer so there is no researcher influence.

Front 123

Give an example of standardisation.

Back 123

A standardised set of instructions.

Front 124

Define an independent group as an experimental design.

Back 124

One group of participants for the control condition. Another (separate) group of participants for the experimental condition.

Front 125

Define repeated measures as an experimental design.

Back 125

One group of participants take part in both conditions. They repeat their participation.

Front 126

Define matched pairs as an experimental design.

Back 126

One group pf participants for control condition. Another (separate) group of participants for the experimental condition. But each participants is matched to another.

Front 127

Evaluate an independent group as an experimental design.

Back 127

+ Avoids order effects (such as practise or boredom)

- More people are needed than with the repeated measures design

- More time consuming

- Individual differences between participants (such as age, gender)

Front 128

Evaluate repeated measures as an experimental design.

Back 128

+ More statistical power because they control EV's

+ Fewer subjects required

+ Quicker and cheaper

+ Assess an effect over time

- Increased likelihood of order effects

Front 129

Evaluate matched pairs as an experimental design.

Back 129

+ Reduces participant variables

+ Avoids order effects

- Very time consuming trying to match participants

- Impossible to match people entirely

Front 130

Define a naturalistic observation.

Back 130

Watching and recording behaviour in the setting within which it would normally occur.

Front 131

Define a controlled observation.

Back 131

Watching and recording behaviour within a structured environment; i.e where some variables are managed

Front 132

Define a covert observation.

Back 132

Participants' behaviour is watched and recorded without their knowledge or consent

Front 133

Define an overt observation.

Back 133

Participants' behaviour is watched and recorded with their knowledge or consent.

Front 134

Define a participant observation.

Back 134

The researcher becomes a member of the group whose behaviour they are watching and recording

Front 135

Define a non-participant observation.

Back 135

The researcher remains outside of the group whose behaviour they are watching and recording.

Front 136

Define observational techniques.

Back 136

Types of observations; can be naturalistic, controlled, covert, overt or involve participants

Front 137

Define open questions.

Back 137

An open question doesn't have a pre-set, fixed range of answers. It allows participants to expand and answer freely in any way they wish to. These questions often answer 'why' people think/behave in certain ways.

Front 138

Define closed questions.

Back 138

A closed question has a fixed choice of response, determined by the researcher.

Front 139

Evaluate observations.

Back 139

+ Naturalistic observations have a high ecological validity

+ Observations allow researchers to investigate usually unethical topics

+ Can develop new hypothesis for further research

- If participants know they are being observed then their behaviour becomes unnatural

- Ethical issues (consent, confidentiality, right to withdraw)

- Low reliability (inter-rater etc)

Front 140

Define a questionnaire.

Back 140

A set of written questions given to participants without the need for a researcher to be present.

Front 141

Define the Likert scale.

Back 141

When the respondent indicates their agreement with a statement using a scale of usually 5 points.

Front 142

Give an example of the likert scale

Back 142

Zombie films have a educational value.

1 - strongly agree

2 - agree

3 - neutral

4 - disagree

5 - strongly disagree

Front 143

Define a rating scale.

Back 143

Gets respondents to identify a value that represents their strength or feeling about a particular topic.

Front 144

Give an example of a rating scale.

Back 144

How entertaining do you find zombie films?

Very entertaining Not at all entertaining

5 4 3 2 1

Front 145

Define a fixed choice option in a questionnaire.

Back 145

Includes a list of possible options and respondents are required to indicate those that apply to them.

Front 146

Give an example of a fixed choice option in a questionnaire.

Back 146

Why do you watch zombie films?

Entertaining

Amusing

Front 147

Define acquiescence bias.

Back 147

A tendency for a person to respond to any questionnaire/interview item with agreement regardless of the actual content.

Front 148

What makes a good questionnaire?

Back 148

Do not include:

Ambiguity

Double negatives

Double barrelled questions

Emotive language

Leading questions

Use of jargon

Front 149

Evaluate the likert scale.

Back 149

+ Easy to answer

+ Easy analysis

- Social desirability bias

Front 150

Evaluate the rating scale.

Back 150

+ Easy to answer

+ Easy analysis

- Social desirability bias

Front 151

Evaluate the fixed choice answer for questionnaires.

Back 151

+ Easy to answer

+ Easy to analyse

- Restricted choice of answers

Front 152

Describe Jason & Messick's (1961) f-scale used to measure authoritarian personality (case of acquiescence bias).

Back 152

- Used the f-scale to measure authoritarian personality.

- Created the reversed f-scale (items were opposite to the original)

- Gave both questionnaires to the same group of respondents and found a strong positive correlation between two sets of results.

- Showed a tendency to agree with items on a questionnaire regardless of if the content of the question was true.

Front 153

Evaluate questionnaires.

Back 153

- Demand characteristics

- Social desirability bias

- Response bias & acquiescent bias

- No clarification

+ Cost effective

+ Straightforward to analyse

+ Easy to gather large amounts of data

+ Easy to replicate

Front 154

Define the interview schedule as part of designing an interview.

Back 154

This is the list of questions that the researcher will ask in a structured/semi-structured interview.

Front 155

Define the environment as part of designing an interview.

Back 155

Interviews should be conducted in a quiet room, away from other people to increase the likelihood that the interviewee will open up.

Front 156

Define rapport as part of designing an interview.

Back 156

In one-one interviews it is good to practise to start with neutral questions to make interviewees feel relaxed and comfortable as a way of establishing a rapport with them.

Front 157

Define ethical consideration as part of designing an interview.

Back 157

Interviewees must give consent to take part, be told that their answers/identity will remain anonymous and that they have the right to withdraw.

Front 158

Define recording as part of designing an interview.

Back 158

Notes can be taken at the time or recorded and analysed later.

Front 159

Describe the process of designing an interview.

Back 159

Interview schedule

Standardisation

Environment

Rapport

Ethical considerations

Recordings

Front 160

What makes a good interview?

Back 160

Do not include;

Ambiguity

Double negatives

Use of jargon

Double barrelled questions

Emotive language

Leading questions

Front 161

Define a structured interview.

Back 161

- Follows a precise list of questions that are asked in a fixed order

- Similar to a questionnaire but conducted by an interviewer

- The interviewer asks the question and wait for a response to record before moving on to the next set of questions on the list

Front 162

Define a semi-structured interview.

Back 162

- Has a list of questions but can be changed according to responses

- Sort of interview that is likely to have in an everyday life such as job interview

Front 163

Define an unstructured interview.

Back 163

- No set questions

- Similar to a conversation

- Interviewee is strongly encouraged to elaborate and expand on their answers to develop their conversation

Front 164

Evaluate interviews.

Back 164

+ Reduced demand characteristics (more likely to be honest in front of someone)

+ Easy to replicate

+ More control over responses

+ Respondents can elaborate

+ More ethical

- Social desirability

- Difficult to analyse

- More costly and time consuming

- Can create a rapport

Front 165

Define a correlation.

Back 165

Relationships between two co-variables.

Front 166

How can correlations be investigated?

Back 166

Using non-experimental methods that are looking for a relationship/connections such as self-report methods, observations and case studies.

Front 167

How can you present the data gained from a correlational study?

Back 167

In terms of STRENGTH and DIRECTION

Front 168

How can direction be presented in a correlational study?

Back 168

Direction is expressed as 'positive' or 'negative' (or zero correlation if there is no relationship/ or curvilinear if the relationship is more complex than just one direction.

Front 169

How can strength be presented in a correlational study?

Back 169

Strength is indicated numerically as a 'correlation co-efficient' that ranges from +1 through 0 to -1.

Front 170

Define one direction relationships as a correlation.

Back 170

One direction relationships are either negative or positive. However if they change direction over time they are known as 'curvilinear'.

Front 171

Describe a negative correlation.

Back 171

As X increases, Y decreases.

Front 172

Describe a positive correlation.

Back 172

As X increases so does Y.

Front 173

Describe a zero correlation.

Back 173

There is no pattern; it is neither positive or negative, this shows no relationship between X and Y.

Front 174

Why are scatter graphs correlational relationships rather than experimental design?

Back 174

There is not 'cause and effect' relationship between two co-variables.

Front 175

What's the difference between an experimental hypothesis and a correlational hypothesis?

Back 175

An experimental hypothesis predicts a difference between conditions of IV and effect on DV and can predict a direction (more/less etc) for the effect of the IV on DV whereas a correlational hypothesis predicts a relationship between two co-variables and can predict the direction (positive/negative).

Front 176

What's the difference between an experiment and a correlation?

Back 176

An experiment aims to establish a cause and effect relationship between the IV and DV whereas a correlation only shows the relationship between the co-variables, it doesn't show that one variable effects the other.

Front 177

Give an example of a correlational hypothesis.

Back 177

There will be a relationship between people who drink coffee and levels of anxiety.

Front 178

Evaluate correlations.

Back 178

+ Useful preliminary tool as a starting point for further research.

+ Economical and less time consuming

- Cause and effect relationship cannot be established

- May be an EV responsible for the correlation

Front 179

Who published ethical guidelines?

Back 179

The British Psychological Society - code of ethics

Front 180

What's the difference between ethical issues and ethical guidelines?

Back 180

The Ethical guidelines are a quasi-legal document produced by BPS whereas ethical issues are issues that arise when a conflict exist between the rights of participants in research and the goals of the research.

Front 181

Describe the BPS Code of Ethics.

Back 181

A quasi-legal document that instructs psychologists about what behaviour is not acceptable when dealing with participants. It is built around 4 major principles:

Respect

Competence

Responsibility

Integrity

Front 182

Define informed consent.

Back 182

Making participants aware of the aims of their research, their procedures, their rights and also what the data will be used for.

Front 183

Define deception.

Back 183

Deliberately misleading or withholding information from participants at any stage of the investigation.

Front 184

Define protection from harm.

Back 184

Participants should not be placed at any more risk than they would be in their daily lives and should be protected from physical and psychological harm. Participants should not be exposed to more risk than they would expect to experience in everyday life.

Front 185

Define confidentiality.

Back 185

Keeping information private; participants should feel confident that the study's report won't reveal information or data which makes it possible for individual participants to be identified, f for their data to be linked to them.

Front 186

Define right to withdraw.

Back 186

Participants should be allowed to leave at any point during the study if they decide they no longer want to take part, including retrospectively after the study has finished (their data would be removed from the research and destroyed).

Front 187

What types of consent are there?

Back 187

Prior-general

Presumptive

Retrospective

Front 188

Define prior-general consent.

Back 188

Participants give their permission to take part in a number of different studies - including one that will involve deception. By consenting; participants are effectively consenting to be deceived.

Front 189

Define presumptive consent.

Back 189

Rather than getting consent from the participants themselves, a similar group of people are asked if the study is acceptable. If this group agree then consent of the original participants is 'presumed'.

Front 190

Define retrospective consent.

Back 190

Participants are asked for their consent (during debriefing) having already taken part in the study. They may not have been aware of their participation or they may've been subject to deception.

Front 191

How do psychologists deal with protection from harm?

Back 191

Psychologists can ask ethics committees to check their research proposals, to help spot any potential problems. At the start of the study they could ask their pp's about any pre-existing problems and at any point in the study they can stop the research at the first sign of any harm occurring. After the study they can debrief all pp's and offer aftercare.

Front 192

How do psychologists deal with uninformed consent?

Back 192

Psychologists will ask pp's to read and sign a consent form and will ask the parents of children under 16 years to give consent on their behalf. The carers/specialists of an adult with communication/understanding difficulties will be consulted if they feel they are unable to make an informed decision on their own. Retrospective consent can be gained during the debrief.

Front 193

How do psychologists deal with deception?

Back 193

Debriefing should be used to explain the real aim and rationale for the deception, as well as to reassure the participant and allow them to ask any questions they may have. The right to withdraw should be emphasised throughout and retrospective right to withdraw via destruction of data should be offered.

Front 194

How do psychologists deal with confidentiality?

Back 194

Psychologists should allocate numbers, letters or codes to each pp to ensure they're kept anonymous, as well as keeping the local of the study as general as possible. Consent must be gained from pp's for their data to used in situations where it is impossible to offer confidentiality.

Front 195

How do psychologists deal with right to withdraw?

Back 195

Pp's should be informed of their right at the beginning of the research, and should be reminded of this right at suitable points during and after the research. If they choose to exercise their right, pressure should not be put on them to stay and payment should not be used to coerce pp's. Task avoidance should be taken as a wish to withdraw in child pp's.

Front 196

Define peer review.

Back 196

Peer review is the process of subjecting a piece of research, before publication to independent scrutiny by other psychologists in a similar field, who consider the research in terms of its validity, significance and originality.

Front 197

What is the purpose of peer review?

Back 197

1. To allocate research funding

2. To validate the quality and the relevance of the research

3. To suggest amendments and improvements

Front 198

What is the process of peer review?

Back 198

1. The study is written up by the researchers

2. It is submitted to a journal for publication

3. Editorial board selects articles for relevance and quality

4. The report is read by anonymous reviewers and returned to the journal with comments suggesting they should either accept or revise it before publication. They often recommend rejection with amendments or improvements.

Front 199

Evaluate peer review.

Back 199

- Anonymity of the reviewer can be used as a way to criticise rival researchers who are in competition for research funding

- Publication bias; favour research that has a positive rather than negative or non-significant results

- Peer reviewers try to maintain the status quo by being critical of any research that contradicts the current research; it can slow down research in that area

Front 200

Why is peer review important in psychological research?

Back 200

- Checks the validity of the research

- It is difficult for authors and researchers to spot every mistake in a piece of work

- Prevents the dissemination of irrelevant findings, unwarranted claims, unacceptable interpretations, personal views and deliberate fraud

- Can also judge the quality and significance of the research in a wider context

Front 201

Describe the mental health statistics for the UK.

Back 201

- 1 in 4 people will experience some kind of mental health problem in the course of a year

- Depression affects 1 in 5 older people

- British men are 3x more likely than women to commit suicide

- Self harm rates for the UK are the highest in Europe; 400 per 100,000 population

Front 202

Describe the economic implications for mental health in the UK.

Back 202

- Mental illness in the UK costs over £105.2 billion a year through costs of medical or social care

- Sickness absence in work due to mental health costs around £8 billion per year (70 million working days are lost)

- 43% of unemployed people will have a primary mental health issue

Front 203

Explain why statistical testing is used in psychological research.

Back 203

Researchers use statistical testing to determine the likelihood that the effect/difference/relationship they have found has occurred due to chance.

Front 204

Why must we carry out statistical testing even if we have calculated the mean?

Back 204

Although there appears to be a difference in the mean scores of two conditions we do not know yet whether this is a significant difference. It could be that the difference in the scores was just a coincidence and therefore occurred through chance.

Front 205

Give an example of a statistical test.

Back 205

Sign test

Front 206

What conditions must be in place before conducting a sign test?

Back 206

1. The researcher must be looking for a difference not a relationship.

2. The experiment must have used a repeated measures design.

3. The data collected must be nominal, i.e. organised into categories.

Front 207

Define a level of significance.

Back 207

This is the point where the researcher is able to accept the experimental hypothesis and show statistically that there is a significant difference between two conditions.

Front 208

Define a 0.05 level of significance.

Back 208

This means that there is less than 5% probability that the results occurred by chance and that is is more likely that the difference can be explained through the manipulation of the independent variable.

Front 209

What conditions must be in place before using a critical values table?

Back 209

- The desired level of significance.

- The number of participants.

- Whether the hypothesis is one tailed (directional) or two tailed (non-directional)

The observed value (the value that is calculated once the statistical test has been completed.

Front 210

How do researchers determine whether or not the results are significant at the level of 0.05?

Back 210

Critical values table.

Front 211

How do you conduct a sign test?

Back 211

1. Convert the data to nominal; to do this you subtract the Pp's score from the control condition. If the answer is negative put a - sign and if the answer is positive put a + sign.

2. Add up the - & +, if there are any that get the same score then this data is ignored and the total number is adjusted.

3. Take the less frequent sign (s)

4. Compare the s value with the critical value; the s value must be equal to or less than the critical value at the 0.05 level of significance.

Front 212

What would you include in the design if you were designing a study?

Back 212

IV

DV (and how you're going to measure it)

Type of method

Type of design

Front 213

What would you include in the sample if you were designing a study?

Back 213

Age

Gender

Size

Technique (e.g. opportunity sample)

Front 214

What would you include in the controls if you were designing a study?

Back 214

Counterbalancing/randomisation

Standardisation

Front 215

What details do you include when designing a study?

Back 215

Design

Sample

Controls

Materials

Procedure

Ethical issues

Front 216

Define an abstract to a scientific report.

Back 216

- First section of a journal article

- Short summary that includes all major elements (A, H, M, R, C)

- Psychologists often read to abstract in order to identify if this study is worth further reading

Front 217

Define an introduction to a scientific report.

Back 217

- A literature review of the general area of investigation

- Research review should follow a logical progression - beginning broadly and gradually becoming more specific until the aims and hypothesis are presented

Front 218

Define a method of a scientific report.

Back 218

- Should include sufficient detail so that other researchers are able to precisely replicate the study

- Design of the study must be clearly stated and reasons for choice

- Sample must include size, target population and sampling method

- Materials must be included

- Controls (e.g. random allocation)

- Procedure

- Ethics (and how they were addressed

Front 219

Define the results of a scientific report.

Back 219

- Summary of key findings

- Can include descriptive statistics and inferential statistics

- Must include final outcome (was the hypothesis accepted or rejected)

- If the results are qualitative then the results should include categories/themes

Front 220

Define a discussion at the end of a scientific report.

Back 220

- Summary of the results/findings verbally rather than statistically

- Must be presented in the context of the evidence presented in the introduction

- Researcher should be mindful of the limitations of the investigation and discuss them here

- Wider implications of the research are considered

Front 221

Define referencing at the end of a scientific study.

Back 221

- Full details of any source material that the researcher used or cited in the report

Front 222

Give an example of referencing.

Back 222

Author (year). Title of chapter. Title of book/journal. Publisher/volume no. & page no.

Front 223

What materials are used within psychological research?

Back 223

- Standardised instructions: Details are the same for each pp - purpose: to reduce EV's

- Informed consent: Requirement of the study and must remain anonymous - purpose: to make the study ethically acceptable

- Debriefing form: Reveals the true aims of the research and provides contact details in case the pp's withdraws - purpose: to make the study ethically acceptable

Front 224

Why is statistical testing used in psychological research?

Back 224

To determine whether a result is due to chance or due to the manipulation of the IV.

Front 225

What is the accepted level of probability in psychology?

Back 225

P ≤ 0.05

Front 226

What does P ≤ 0.05 mean?

Back 226

That the findings are less than 5% due to chance.

Front 227

Why do we need significance levels?

Back 227

Statistical tests work on a basis of probability rather than certainty. All statistical tests employ a level of significance. The usual level of significance is P ≤ 0.05. This means that there is up to a 5% possibility that the observed effect occurred due to chance.

Front 228

Why can't we used a P ≤ 0.5?

Back 228

50% likelihood that the results have occurred due to chance.

50% confidence that the results have occurred due to the manipulation of the IV.

Too lenient - Type 1 error

Front 229

Why can't we used a P ≤ 0.2?

Back 229

20% likelihood that the results have occurred due to chance.

80% confidence that the results have occurred due to the manipulation of the IV.

Too lenient - Type 1 error

Front 230

Why can't we used a P ≤ 0.2?

Back 230

10% likelihood that the results have occurred due to chance.

90% confidence that the results have occurred due to the manipulation of the IV.

Too lenient - Type 1 error

Front 231

Why can't we used a P ≤ 0.01?

Back 231

1% likelihood that the results have occurred due to chance.

99% confidence that the results have occurred due to the manipulation of the IV.

Too stringent - Type 2 error

Front 232

Define a type 1 error.

Back 232

When a researcher says that the results are significant when in fact they're not . The null hypothesis is rejected and experimental/alternative hypothesis is accepted incorrectly.

AKA false positive/optimistic error

Most likely to happen if the significant level is too lenient.

Front 233

Define a type 2 error.

Back 233

When a researcher says that the results are not significant when in fact they're. The null hypothesis is accepted and experimental/alternative hypothesis is rejected incorrectly.

AKA false negative/pessimistic error

Most likely to happen if the significant level is too stringent

Front 234

Why do psychologists use P ≤ 0.05 level of significance?

Back 234

It best balances the risk of making a type 1 or type 2 error.

Front 235

Define statistical testing.

Back 235

- Used to determine whether any difference found between variables is statistically significant.

Front 236

What three pieces of information are needed to conduct a statistical test?

Back 236

- Testing for a difference or relationship

- Research design used

- Level of measurement

Front 237

Define level of measurement.

Back 237

The type of quantitative data that is collected from the research.

Front 238

Define nominal data.

Back 238

- Data is represented in the form of categories.

Front 239

Give an example of nominal data.

Back 239

Are you a smoker or a non-smoker?

Front 240

Define ordinal data.

Back 240

- Data can be ranked or ordered in some way

- Doesn't have equal intervals between the numbers

- Can often be represented on a scale of 1-10 and may involve some interpretation

Front 241

Give an example of ordinal data.

Back 241

On a scale of 1-10 (1=minimal, 10=a lot), how much do you feel you have improved since your last assessment?

Front 242

Define interval data.

Back 242

- Data is based on a numerical scales with equal intervals.

- They use accepted units of measure and so are more objective than ordinal data.

Front 243

Give an example of interval data.

Back 243

Time

Speed

Height

Front 244

What measure of central tendency do you need to use when looking at nominal data?

Back 244

Mode

Front 245

What measure of central tendency do you need to use when looking at ordinal data?

Back 245

Median

Front 246

What measure of central tendency do you need to use when looking at interval data?

Back 246

Mean

Front 247

What measure of dispersion do you need to use when looking at nominal data?

Back 247

N/A

Front 248

What measure of dispersion do you need to use when looking at ordinal data?

Back 248

Range

Front 249

What measure of dispersion do you need to use when looking at interval data?

Back 249

Standard deviation

Front 250

What does N stand for?

Back 250

Total number of participants

Front 251

What test do you use when its an experiment, using a repeated measures design and uses nominal data?

Back 251

Sign test

Front 252

What test do you use when its an experiment, using a independent groups design and uses ordinal data?

Back 252

Mann-Whitney

Front 253

What test do you use when its an experiment, using a repeated measures design and uses ordinal data?

Back 253

Wilcoxon

Front 254

What test do you use when its an experiment, using a repeated measures design and uses interval data?

Back 254

Related t-test

Front 255

What test do you use when its an experiment, using an independent group design and uses interval data?

Back 255

Unrelated t-test

Front 256

What test do you use when its an correlation and uses ordinal data?

Back 256

Spearman's Rho

Front 257

What test do you use when its an correlation and uses interval data?

Back 257

Pearson's r

Front 258

What test do you use when its an experiment, using an independent group design and uses interval data?

Back 258

Chi-squared

Front 259

In statistical tests, if there is an r in the title, how do you know if the results are significant?

Back 259

Results are significant if the calculated/observed value is equal to or more than the critical value at P ≤ 0.05, therefore the experimental/alternative hypothesis would be accepted and the null rejected.

Front 260

In statistical tests, if there isn't an r in the title, how do you know if the results are significant?

Back 260

Results are significant if the calculated/observed value is equal to or less than the critical value at P ≤ 0.05, therefore the experimental/alternative hypothesis would be rejected and the null accepted.

Front 261

How do you write a statement of significance?

Back 261

The calculated value of (whichever test you have conducted) is ...

The critical value of (whichever test you have conducted) for a one/two tailed test at P ≤ 0.05 where N/df is ..., is....

As the calculated value of (whichever test you have conducted) is greater than/less than the critical value, the result is/not significant at P ≤ 0.05 and therefore we must reject experimental/alternative/null hypothesis and accept the experimental/alternative/null hypothesis; WRITE THE HYPOTHESIS YOU ACCEPT

Front 262

What three pieces of information do you need to find out if a statistical test is significant or not?

Back 262

1. Is the hypothesis directional (one tailed) or non-directional (two tailed)?

2. What is the sample size/degrees of freedom?

3. Level of probability? (always assume this is P ≤ 0.05 unless told otherwise).

Front 263

Which statistical tests require you to know the full number of participants (N)?

Back 263

Sign test, Wilcoxon, Spearmans Rho

Front 264

Which statistical tests require you to know the full number of participants per condition (NaNb)?

Back 264

Mann Witney

Front 265

What is important to remember about the full number of participants when using a sign test or a wilcoxon?

Back 265

Sample size can be reduced where there is no difference between the scores. Any score that is the same in both conditions is ignored and sample size is reduced accordingly.

Front 266

Which statistical tests require you to know the degrees of freedom (df)?

Back 266

Unrelated t-test, Related t-test, Pearson's r, Chi-squared

Front 267

Define degrees of freedom?

Back 267

The number of values in the final calculation that are free to vary

Front 268

How do you calculate degrees of freedom in an unrelated t-test?

Back 268

(Na + Nb) - 2

Front 269

How do you calculate degrees of freedom in anrelated t-test?

Back 269

N-1

Front 270

How do you calculate degrees of freedom in a pearson's r test?

Back 270

N-2

Front 271

How do you calculate degrees of freedom in a chi-squared test?

Back 271

(Rows - 1) x (columns -1)

Front 272

What 8 features of science are there?

Back 272

Objectivity

Empirical method

Replicability

Falsifiability

Theory construction

Hypothesis testing

Paradigms

Paradigm shift

Front 273

Define objectivity.

Back 273

- Opposite of subjectivity

- Must not allow personal opinion/biases to distort data

- Researchers must keep a critical distance during research

- Objectivity is the basis of the empirical method

- Lab experiments tend to have the highest level of objectivity

Front 274

Define the empirical method.

Back 274

- Emphasise the importance of data collection based on direct, sensory experience

- Experimental method and observational method are good examples of the empirical method

- Theory cannot claim to be scientific unless it has been empirically tested

Front 275

Define theory construction.

Back 275

- Theory is a general set of laws or principles that have the ability to explain particular events of behaviours

- Theory construction occurs through gathering evidence via direct observation

- Then a series of experiments reveal a connection to the observation

- Provides understanding by explaining regularities in behaviour

Front 276

Define hypothesis testing.

Back 276

- To make clear and precise predictions on the basis of theory

- An essential component of a theory is that it can be scientifically tested

- Theories should suggests a number of possible hypothesis

- A hypothesis can then be tested using systematic and objective methods to determine whether or not it will be rejected/accepted

- The process of deriving new hypothesis from an existing theory is known as a deduction

Front 277

Define replicability.

Back 277

- Popper (1934) argued that if a scientific theory is to be 'trusted' the findings from it must be shown to be repeatable across a number of different contexts/circumstances

- Replication has an important role in determining the validity of the findings

- Used to see the extent to which the findings can be generalised

- In order for replicability to become possible, it is vital for researchers to report their investigations with as much precision and detail as possible

Front 278

Define falsifiability.

Back 278

- Popper (1934) argued that a key criteria of scientific theory is its falsifiability

- Genuine scientific theory should hold itself up for hypothesis testing and the possibility of being proven wrong

- Even when a scientific principle has been successfully and repeatedly tested it was not necessarily true instead it has simply not been proven to be false - theory of falsification

- Clear line between good science in which theories are constantly challenged and pseudosciences which can't be falsified

Front 279

Define paradigms .

Back 279

- Kuhn (1962) argued that the difference between scientific disciplines from non-scientific disciplines is a shared set of assumptions and methods (paradigm)

- Psychology lacks a universally accepted paradigm (seen as a pre-science) there are too many contradicting approaches to qualify as a science

- Natural sciences are characterised by having a number of principles as their core such as the theory of evolution

Front 280

Define a paradigm shift.

Back 280

- Kuhn (1962) suggested that this is the process when an established science has a scientific revolution

- A handful of researchers begin to questions the accepted paradigm and as the critique begins to gather popularity and pace a paradigm shift occurs when there is too much contradictory evidence to ignore.

Front 281

Give an example of a paradigm shift.

Back 281

The change from a Newtonian paradigm in physics towards Einsteins theory of relativity.

Front 282

Write a debrief that the psychologist could read out to the participants?

Back 282

Thank you for taking part for in this investigation. The aim of the study was...

To ensure you are fully debriefed you must know...

I'd like to remind you that your data and any personal details will remain confidential and anonymous.