Comprehensive Study Notes on Human Intelligence: Intelligence Models, Trajectories, and Correlates

Defining Intelligence and the Psychometric Approach

• The Consensus Definition of Intelligence     * Intelligence is defined as a very general mental capability.     * This capability involves several core abilities, including:         * Reasoning         * Planning         * Solving problems         * Thinking abstractly         * Comprehending complex ideas         * Learning quickly         * Learning from experience     * While this is widely referred to as "the consensus definition," it remains a subject of controversy within the field.

• The Psychometric Approach     * This approach characterizes intelligence based on what is measured by standardized tests.     * Edwin Boring (1923) famously stated: "Intelligence is what the tests test."     * The psychometric approach is currently the dominant methodology in intelligence research, focusing on the statistical relationships between different cognitive tasks.

Historical Models: Spearman and the G-Factor

• The G-Factor Model (Spearman, 1904, 1927)     * Charles Spearman compiled results from numerous different tests of cognitive ability.     * He observed a phenomenon of universal positive intercorrelation: individuals who performed well on one type of mental test tended to perform well on others.     * Based on this correlation, Spearman proposed an underlying factor called "general intelligence," or the $g$-factor.     * The Two-Factor Theory Equation:         * Performance ($P$) on any given task is a product of general intelligence plus specific abilities related to that task.         * $P = g + s$     * In this model, general intelligence is defined primarily through statistical relationships rather than specific biological mechanisms.

The Cattell-Horn Theory of Intelligence

• Theory Overview (Horn & Cattell, 1966)     * This model was developed using factor analysis on a large, age-diverse sample of $N = 327$ participants, ranging in age from $11$ to $63$ years.     * It rejects the idea of a single $g$-factor, proposing instead that cognitive performance measures consist of two distinct factors: Fluid Intelligence and Crystallized Intelligence.

• Fluid Intelligence ($G_f$)     * This represents the ability to solve new problems, use logic in new situations, and identify patterns.     * Fluid intelligence is believed to be converted into crystallized intelligence through life experience.

• Crystallized Intelligence ($G_c$)     * This represents the ability to use learned knowledge and experience.     * Examples of crystallized intelligence tasks include:         * Vocabulary/Word Definitions: Defining words such as "Chair," "Hesitant," or "Presumptuous."         * General Knowledge: Answering questions such as "What is the capital of France?" (Paris), "Name three oceans?" (e.g., Atlantic, Pacific, Indian), or "Who wrote the Iliad?" (Homer).

• Investment Theory and Age Divergence     * Investment Theory: Asserted that individuals "invest" their fluid intelligence to acquire crystallized knowledge over time.     * Age Trajectory: Fluid and crystallized intelligence diverge as people age. While crystallized intelligence tends to remain stable or increase with experience, fluid intelligence often declines.

The Cattell-Horn-Carroll (CHC) Theory

• The Unified Model (Carroll, 1993; McGrew, 2009)     * The CHC theory is currently considered the "theoretical champion" and serves as the foundation for modern intelligence tests.     * It was developed through sophisticated factor analysis of $461$ datasets, covering a $60$-year timespan ($1927$-$1987$) and involving over $130,000$ participants.

• The Three-Stratum Model     * Stratum III (Top): General Intelligence ($g$). This represents the highest level of cognitive abstraction.     * Stratum II (Middle): Broad General Abilities ($∼ 18$ abilities). This includes Fluid Intelligence ($G_f$) and Crystallized Intelligence ($G_c$).     * Stratum I (Bottom): Narrow Specific Abilities ($∼ 80$ abilities). These are highly specialized cognitive skills.

Intelligence Stability and Change Across the Lifespan

• Temporal Stability (Deary, 2020)     * General intelligence is partially stable across a lifetime. Test performance at age $11$ correlates with performance at age $70+$ at approximately $0.7$.

• Age-Related Decline     * General intelligence typically declines with age.     * On average, IQ scores decline by approximately $7.5$ points per decade between the ages of $35$ and $85$.     * Broad general abilities (Stratum II) decline at different rates depending on the specific ability.     * There are large individual differences in the trajectory of this decline; not everyone loses cognitive function at the same rate.

• Overlap with General Intelligence ($g$)     * As people age, individual changes in specific cognitive abilities become more closely related to general intelligence.     * At age $35$, there is a $45\%$ overlap between specific cognitive abilities and $g$.     * By age $85$, this overlap increases to $70\%$.

Critiques of Alternative Intelligence Models

• Gardner’s Theory of Multiple Intelligences     * Proposes distinct types: Visual-spatial, Linguistic-verbal, Logical-mathematical, Body-kinesthetic, Musical, Interpersonal, Intrapersonal, and Naturalistic.     * Critique: Research by Waterhouse (2006) indicates this theory lacks any empirical basis. It also suffers from issues with internal consistency.

• Sternberg’s Triarchic Theory of Intelligence     * Proposes three types of intelligence: Practical, Analytical, and Creative.     * Critique: Evidence suggesting these are separate types is weak; Chooi et al. (2014) argue that Sternberg’s data is better described by a standard $g$-based statistical model.

Genetic and Environmental Influences

• The Gene-Environment Interaction     * Intelligence is determined by the interaction between genetics and environmental factors.     * Genetics become increasingly influential on intelligence as an individual ages (Haworth et al., 2010).

• Genetic Factors     * Intelligence is a polygenetic trait, meaning it is influenced by many genes rather than a single "intelligence gene" (Davies et al., 2011).     * At least $148$ genes have been identified as contributing to intelligence.

• Environmental and Socioeconomic Factors     * Socioeconomic Status (SES): Low SES may amplify differences in early developmental stages (Stumm & Polmin, 2014).     * Enrichment: Factors such as access to books and preschool attendance can attenuate (reduce) the performance gaps associated with SES (Christensen et al., 2014).     * Education: Formal education is a significant predictor; each year of education adds approximately $3$ IQ points (Ritchie & Tucker-Drob, 2018).

Practical Significance: Why Intelligence Matters

• Predictive Validity of Intelligence ($g$)     * Educational Success: Predicts achievement and duration of schooling (Deary et al., 2007).     * Professional Performance: Predicts job performance and career success (Kuncel and Hezlett, 2010).     * Health Outcomes: Correlates with better health and longevity (Batty et al., 2008). Higher IQ is associated with a lower risk of being murdered or dying in an accident.     * Creativity: Higher $g$ correlates with higher creative potential (Nusbaum and Silvia, 2011).     * Belief Systems: Intelligence is a predictor of political and religious beliefs (Deary et al., 2008; Zuckerman et al., 2013).

Neural Correlates of Intelligence

• Biological Foundations (Deary, 2020)     * Intelligence is correlated with several brain characteristics:         1. Brain size         2. Cortical thickness         3. White matter integrity         4. Absence of non-clinical damage     * The correlation magnitude between these physical neural factors and IQ scores generally ranges between $0.2$ and $0.3$.

Cross-Generational Stability: The Flynn Effect

• The Phenomenon     * Globally, IQ scores have been rising with every generation since the early $1900$s.     * These increases are occurring faster in developing countries.

• Proposed Causes     * Diverse factors have been suggested, including cultural shifts, improved nutrition, better education, genetics, reduced lead exposure, and increased exposure to technology.

• Interpretation and Trends     * Most experts believe the Flynn effect does not reflect a true change in underlying general intelligence ($g$), but rather improvements in test-taking factors or environment-specific skills.     * Recent evidence (Bratsberg & Rogeberg, 2018) suggests a reversal of the Flynn effect (declining IQ scores) in some Western countries.     * This reversal is attributed to environmental causes rather than factors like immigration or assortative mating.