Personality Psychology: Definitions, Approaches, and Data Types

Personality (Definition)

An individual's characteristic patterns of thought, emotion, and behavior, plus the mechanisms behind them.

Personality Psychology Mission

To explain whole, functioning persons and appreciate individual uniqueness in real environments.

Psychological Triad

The three core topics of psychology: how people Feel (affect), Think (cognition), and Behave (action).

Triad Conflicts

Inconsistencies where feelings, thoughts, and actions clash (e.g., attracted to someone you know is bad for you).

Pigeonholing vs. Uniqueness

Labeling categorizes people, but personality psychology is uniquely sensitive to human individual differences.

One Big Theory (OBT)

A hypothetical theory explaining all of personality; flawed because a theory covering everything explains nothing best.

Engineering Trade-off (Toaster-Radio)

A device that does one thing well does little else; an all-in-one appliance does nothing particularly well.

Complementary Approaches

The basic approaches are not mutually exclusive competitors; each answers distinct questions best.

Funder's First Law

Great strengths are usually great weaknesses, and surprisingly often the reverse is true as well.

Trait Approach (Focus)

Conceptualizes, measures, and tracks stable psychological individual differences over time.

Biological Approach (Focus)

Explains individual differences via anatomy, physiology, genetics/heredity, and evolution.

Psychoanalytic Approach (Focus)

Investigates the unconscious mind, internal mental conflicts, and defenses (Freud).

Phenomenological Approach (Focus)

Emphasizes conscious awareness, free will, humanistic growth, and cross-cultural reality.

Learning & Cognitive Approaches (Focus)

Examines behavior change via rewards/punishments, observational learning, and cognitive processing.

Applied Value of Personality Psych

Not purely theoretical; widely applied in clinical therapy, career counseling, health, and leadership.

Scientific Education

Teaches students to explore the unknown, gather data, and question existing knowledge (Ph.D.).

Technical Training

Teaches practitioners to memorize and apply already established facts to practical tasks (M.D.).

Funder's Second Law

There are no perfect indicators of personality; there are only clues, and clues are always ambiguous.

Funder's Third Law

Something beats nothing, two times out of three.

S Data (Definition)

Self-judgments provided directly by the individual about their own traits and behaviors.

Face Validity

When assessment items directly and transparently measure what they appear to measure on their face.

S Data Advantage: Information Volume

You are the only person present across every single situation and context in your life.

S Data Advantage: Private Access

Provides unique, direct access to your own inner fantasies, fears, hopes, and intentions.

S Data Advantage: Definitional Truth

Certain attributes (like self-esteem) are true by definition simply because you believe them.

S Data Advantage: Causal Force

Beliefs alter reality through self-efficacy (setting goals) and self-verification (prompting others to confirm self-views).

S Data Advantage: Cost-Effective

Extremely simple, inexpensive, and fast to collect from large groups online.

S Data Disadvantage: Bias

People distort self-views to look socially desirable (self-enhancement, narcissism) or deliberately fake answers.

S Data Disadvantage: Fish-and-Water Effect

Being so accustomed to your own chronic traits that they become invisible and feel completely normal.

S Data Disadvantage: Cognitive Errors

Distortions caused by lack of insight, psychological repression of painful memories, or careless responding.

S Data Disadvantage: Overuse

Because S data is cheap and simple, researchers rely on it excessively, ignoring other data sources.

I Data (Definition)

Judgments made by knowledgeable informants (friends, coworkers, clinicians) about a person's traits.

I Data Advantage: Information Volume

Informants observe hundreds of daily behaviors across diverse real-world settings.

I Data Advantage: Real-World Basis

Grounded in natural social interactions rather than artificial, contrived laboratory setups.

I Data Advantage: Common Sense & Context

Informants automatically interpret behaviors within their situational context and baseline history.

I Data Advantage: Definitional Truth

Socially perceived traits (like charm, likability, or obnoxiousness) exist entirely in the eyes of others.

I Data Advantage: Causal Force (Reputation)

Reputation shapes social/job opportunities and produces behavioral confirmation (expectancy effects).

I Data Disadvantage: Compartmentalization

People inhabit separate life compartments (William James); informants only see the persona tied to their setting.

I Data Disadvantage: No Private Access

Informants cannot observe private inner mental life, secret fears, or unvoiced motives.

I Data Disadvantage: Extreme Event Error

Informants disproportionately recall vivid, rare, or emotionally shocking incidents over routine habits.

I Data Disadvantage: Bias & Letter of Rec Effect

Distorted by prejudices or the tendency of participants to nominate informants who view them favorably.

L Data (Definition)

Verifiable, concrete, archival facts and real-life outcomes that hold psychological significance.

L Data Examples

Arrest records, marriage status, GPA, salary, medical history, or the physical neatness of a bedroom.

Residue of Personality

Physical living spaces reflect traits (e.g., tidy rooms indicate high conscientiousness).

L Data Advantage: Objective & Verifiable

Provides concrete, verifiable outcomes often recorded in precise numerical records.

L Data Advantage: Intrinsic Importance

Reflects real-world consequences that applied psychologists actively seek to predict and improve.

L Data Disadvantage: Multidetermination

Life outcomes are caused by many non-psychological factors (e.g., economic recessions, luck, false arrest).

L Data Prediction Constraint

Personality predicts life outcomes only to the modest degree that those outcomes were psychologically caused.

B Data (Definition)

Direct observations and numerical recordings of what a participant actually does in a testing situation.

Natural B Data

Objective tracking in daily life: behavioral diaries, EAR audio recordings, wearable cameras, and social media.

Laboratory B Data

Direct observations in controlled rooms: emergency tests (smoke in room), avatar choices, and game reactions.

Physiological B Data

Autonomic and biological measures: blood pressure, galvanic skin response (sweating), heart rate, and brain scans.

B Data Advantage: Context Range

Allows researchers to artificially trigger rare, latent, or crisis events without waiting for nature.

B Data Advantage: Objectivity

Researchers record direct actions themselves rather than trusting the participant's or informant's word.

B Data Disadvantage: Cost & Effort

Highly expensive, labor-intensive, and demanding to set up, monitor, and code.

B Data Disadvantage: Uncertain Meaning

Raw behaviors and physiological spikes do not interpret themselves; psychological meaning is ambiguous.

Reliability (Definition)

The consistency and repeatability of measurements; the degree to which data are free of measurement error.

Measurement Error (Error Variance)

The cumulative variation of a score around its true mean caused by uncontrolled random influences.

State vs. Trait

A state is a temporary, momentary psychological event; a trait is a stable, persistent personality attribute.

Threats to Reliability

Low instrument precision, fluctuating participant states (illness, fatigue), experimenter mood, and environmental noise.

How to Improve Reliability

Standardize experimental scripts, measure important traits, and use aggregation.

Aggregation (Principle)

Averaging multiple items or observations cancels out random errors because random influences sum to zero.

Spearman-Brown Formula

A mathematical formula predicting the gain in test reliability achieved by adding equivalent items.

Validity (Definition)

The degree to which an instrument actually measures the psychological construct it claims to assess.

Reliability vs. Validity

Reliability is necessary for validity, but reliability alone is not sufficient (a test can be reliably wrong).

Psychological Construct

An unobservable theoretical attribute (like intelligence or sociability) known only through its visible effects.

Construct Validation

Verifying a measure's validity by showing that diverse tests, informant ratings, and behaviors correlate together.

Generalizability

A broad psychometric concept subsuming reliability and validity; asks to what other people, times, and settings results apply.

WEIRD Samples Threat

Over-generalizing findings derived primarily from Western, Educated, Industrialized, Rich, and Democratic participants.

Gender Gap in Experiments

Women volunteer and show up to psychology studies at much higher rates, making recruited male samples unusual.

Shows vs. No-Shows

Participants who fail to appear score lower on conventional morality/assertiveness and higher on narcissism.

Case Study Method

An intensive, in-depth investigation of a single person, patient, or real-world disaster.

Case Study Pros & Cons

Pro: Treats the whole person and generates rich hypotheses; Con: Findings cannot be generalized or used to test causality.

Experimental Method

Manipulates an independent variable (IV) with random assignment to measure its effect on a dependent variable (DV).

Experimental Causality

The only design that definitively establishes causal direction because the researcher controls the IV.

Experimental Limitations

Creates artificial situations, frequently requires deception, and carries operational ambiguity of the construct.

Correlational Method

Measures naturally occurring variables in participants without intervention to assess their statistical relationship.

Third-Variable Problem

When an unmeasured confounding factor is the true underlying cause of the association between two correlated variables.

Reverse Directionality

The inability of correlational data to determine whether variable X caused Y, Y caused X, or both influence each other.

Scatter Plot Basics

Plots paired scores on x and y axes; downward slopes indicate negative correlation, upward slopes indicate positive correlation.

Correlation Strength on Plots

Data points clustering tightly around the regression line indicate a stronger correlation than widely scattered points.

Omnibus vs. Single-Trait Inventories

Omnibus tests measure a wide range of traits (e.g., NEO-PI, MMPI); single-trait tests measure one trait (e.g., Shyness).

S-Data Personality Tests

Self-report inventories where items ask directly about personal traits and are interpreted literally.

B-Data Personality Tests

Performance-based tests where indirect responses, task behaviors, or latency patterns are scored (MMPI, IQ, IAT).

Projective Hypothesis

Ambiguous, meaningless stimuli elicit interpretations that reflect the test-taker's unconscious needs and conflicts.

Rorschach Inkblot Test

A projective B-data test using symmetric inkblots; scored via Exner's Comprehensive System or Klopfer's method.

Rorschach Predictive Validity

Achieves modest validity (r ≈ .33); predicts psychiatric hospital commitment and suicide better than self-reports.

Thematic Apperception Test (TAT / PSE)

Participants tell stories about ambiguous pictures; accurately assesses implicit motives (achievement, power, affiliation).

Draw-A-Person Test

A projective technique interpreting bodily exaggerations or omissions in client drawings; possesses dubious validity.

Projective Test Drawbacks

Extremely expensive, time-consuming, highly vulnerable to subjective interpreter bias, and lacks incremental validity.

Objective Tests (Definition)

Inventories consisting of structured, forced-choice questions (True/False, Yes/No, Likert rating scales).

Objective Item Ambiguity

Items require subjective interpretation by the test-taker so that individual differences in personality can emerge.

Gough's Commonality Scale

A CPI scale of items answered identically by 95% of people; catches illiterate individuals, saboteurs, or random guessing.

Why Objective Tests Have Many Items

Single items are unreliable; aggregating many items cancels random errors and maximizes scale reliability.

Rational Test Construction

Writing items that seem directly, logically, and transparently connected to the trait being assessed (e.g., WPDS).

Rational Condition 1: Clarity

Each item must mean the exact same thing to the test-taker as it does to the psychologist who wrote it.

Rational Condition 2: Self-Awareness

The person completing the test must have the capacity to make an accurate, observant self-assessment.

Rational Condition 3: Truthfulness

The test-taker must be willing to report their self-assessment honestly without faking or distortion.

Rational Condition 4: Valid Indicator

Every item must actually be a genuine, valid indicator of the underlying psychological attribute.

Factor Analytic Test Construction

Using factor analysis to find clusters of correlated items that tap into a common underlying factor.

Factor Analytic Steps

Administer a huge item pool, compute item correlations, extract clusters, and label the shared factor (e.g., Cattell 16, Big Five).