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The Person and its Measurement - Coggle Diagram
The Person and its Measurement
Defining features of personality
Emphasis on Individual uniqueness
Defining characteristics of an individual
Comprehensive: Comprises ABC (affect, behaviour, and cognition)
Patterns: Organised and enduring points to the existence of a structure
Mechanisms: Processes such as self-regulation
Interactions and adaptation: Functional adaptation to the environment. Personality has consequences in everyday life
Theoretical perspectives
Dispositional-Trait Approach: Focus on the way individuals differ from one another and how these differences can be conceptualised and measured (the big 5)
Biological Approach
Psychophysiology: The biological bases for ABC
Behaviour genetics: Nature vs nurture
Evolutionary influences: Gender
Psychodynamic: Internal dynamics of psychic energy and mental processes in the unconscious
Sigmund Freud: Humans have two drives for sex and aggression and are always being suppressed, leading to internal conflict
Humanistic Approach: Human nature is positive and growth-oriented. People have the free will to strive toward self-actualisation. Special emphasis on people's subjective experiences.
Social Cognitive Approach: Understand the situational and contextual influences on personality and the dynamic psychological processes. Understand what we do with our personalities rather than what we have.
Data types
S data: Self-judgements
Structured questions: Self-report questionnaires
Unstructured questions: Personal strivings (open ended questions and have to translate answers to codes), The Twenty Statements Test ("I am....." 20 times)
Advantages: People are the best experts on themselves, privileged access to inner experiences, easy and simple to connect
Disadvantages: Intentional distortion/concealment, unaware or lack of insight, danger of being overused
I data: Informant-judgements
Getting knowledgeable informants to judge person's personality, expert opinions
Advantages: Independent information from S data, observables from a variety of situations, have contextual information in judgement
Disadvantages: Subjective and error-prone, limited knowledge about a person, circumscribed perspective of the person
L data: Life outcomes
Life or archival records, person's environment.
Residue or consequence of person's personality rather than personality itself
Advantages: Quantifiable, objective, verifiable, intrinsic real-life importance, relevant to psychological constructs
Disadvantages: Multidetermination of outcomes
B data: Behaviours
Direct observations, experiments, physiological data, personality tests that require further interpretation (MMPI, and projective tests)
B data tests are different from S data tests because the psychologist sees how you will answer rather than taking what you answer at face value
Projective tests: Rorschach inkblot tests and thematic apperception test (TAT) (ambiguous picture and ask participants to interpret)
Experience sampling or diary-based methodology: Asking people to report their experiences
Advantages: Objective and quantifiable, experimental manipulations and controls
Disadvantages: Ambiguity in determination (behaviours could indicate something else)
Triangulation: Employ a variety of data types to see if they converge on similar results
Research designs
Case studies: Detailed insights but lacks generalisability
Experiments: Can infer causality, but no ecological validity and it may be impossible to manipulate variables
Correlational studies: Ecological validity (generalisable to real life) but cannot infer causality
Effect size (correlation coefficient): Look at the magnitude of the correlation coefficient rather than just the significance of it
r=0.10 is small
r=0.30 is moderate
r=0.50 is large
Using r squared is no longer recommended
Limitations of null-hypothesis significance testing (NHST): Ignores the strength of relation, and is highly influenced by sample size (r is almost always significant for large sample sizes)
Binomial Effect Size Display (BESD):
Reliability: Consistency of the scores
Test-restest reliability: Correlation between test scores of the same test taken at different points in time; interval about 4-8 weeks (the construct being measured must be stable)
Parallel forms reliability: Administer two different test forms and calculate correlation
Inter-rater reliability: Similar ratings across different raters, take average of ratings or 1 rater's ratings for analysis
Internal consistency reliability: Correlation between multiple items on the same test that measures the same construct
Satisfactory reliability > 0.70
Good reliability > 0.80
Most widely used estimate of reliability because it's easier and less time-consuming
Sources of unreliability
Low precision of measurement: Being careless in recording and scoring data
Participant: Random participant error
Experimenter: Participants respond differently depending on the experimenter
Environment: Unexpected situations
Enhancing Reliability: Standardisation, ensure no mistakes, have more items and measurements, aggregation (averaging repeated measurements so that random errors cancel out)
Validity: Degree to which evidence and theory support the interpretations of test scores entailed by the proposed uses of tests
Ways to establish validity (NOT different TYPES of validity)
Content validation: Whether the items that make up a measure have been adequately sampled from the universe of behaviours that represents relevant aspects of the construct in question
Criterion-related validation: The extent to which the measure predicts some external variable that is distinct from the construct in question
Construct validation: The extent the measure of the construct in question exhibits theoretically expected relations with measures of other constructs
Convergent validity: The measure correlates with other measures that it should correlate with
Discriminant validity: Measure does not correlate with other measures that it should not be correlated with
Nomological network