Dag vanintelligentie

2018Donald H. Saklofske, Ph.D.Department of PsychologyUniversity of Western Ontario, Canada

dsaklofs@uwo.ca

The influences of culture and societal context on intelligence

Research Program (Intelligence): Fundamental Questions

on its definition and measurement?

–How robust/universal is the structure of intelligence across countries/cultures?

–How well do intelligence tests ‘travel’?

–What is the kind and extent of within country similarities/differences on intelligence tests?

–While genetics may explain much of the variance in intelligence, what are key ‘external’ factors that would account for differences observed between groups and individuals?

–Can changes in these ‘demographic’ influences in turn, impact intelligence?

The study and measurement of intelligence are a cornerstone of psychology’s contribution to individual differences research. Concurrent with the development of models leading the construction of intelligence measures, intelligence has been examined from various causal and correlational perspectives including the role of genetic and environmental foundations such as race, country, and demographic (e.g., SES, education) factors.

However, while scientific study has been extensive, the interpretation and application of these findings, including the very tests that are used to measure intelligence, has also led to controversy within and outside of psychology. The ongoing development of the Wechsler intelligence tests starting with the 3rd editions of the WISC and WAIS, has provided opportunity to examine some of the key factors that may further our understanding of both individual and group as well as country differences. In several recent publications together with Larry Weiss et al., we have examined the Wechsler standardization test data to determine the impact of societal context (e.g., education, income) on intelligence test scores. I will present some of these findings and challenges to the view that ‘demographics are destiny’.

To first comment on some fundamental criticisms regarding the study and

measurement of intelligence:

• There is no agreement on what is intelligence

• Intelligence and intelligence tests are devoid of theory which is necessary to define, study and use the results

• Psychological tests are really not that good… and IQ tests are worse, their use leading to misclassifying persons, bias in job selection, social stigmatizing, etc

Intelligence Tests and Assessment: Some longstanding controversy

• In spite of their widespread use, the Wechsler scales and other intelligence tests, have not been without their critics. Intelligence tests have weathered many storms ranging from their dismissal by radical behaviorists of the 1960’s and the famous court challenges of the 1970’s and 1980’s, to those who advocate an exclusive social constructivist view of human behavior. There are others who argue that the very ‘idea’ of intelligence is irrelevant as is the need to assess cognitive abilities. Some would criticize intelligence tests and their clinical use from an ethical or moral perspective while others ‘believe’ that there is not sufficient empirical support to continue using intelligence tests in applied settings for diagnosis, intervention planning, or any kind of predictive purpose.

• Of course, it is possible that success may generate criticism, rejection, or a cavalier attitude of indifference.

• What is so remarkable about all of this contention and controversy is that the construct of intelligence is one of the most studied and measured of all individual differences variables in psychology. In fact, intelligence represented by a collection of cognitively complex tasks or ‘g’ is correlated with more human behaviors and outcomes than any other factor studied by psychologists.

• Gottfredson (2008) succinctly states: “perhaps in no other applied setting is construct validity more important than for clinicians who are asked to diagnose individuals and intervene in their lives … arguably, a battery of cognitive tests is the most important single tool in sketching that portrait”

Psychological testing and psychological assessment: A review of evidence and issues.

Meyer, Gregory J.; Finn, Stephen E.; Eyde, Lorraine D.; Kay, Gary G.; Moreland, Kevin L.; Dies, Robert R.; Eisman, Elena J.; Kubiszyn, Tom W.; Reed, Geoffrey M.

American Psychologist, Vol 56(2), Feb 2001, 128-165.

• This article summarizes evidence and issues associated with psychological assessment. Data from more than 125 meta-analyses on test validity and 800 samples examining multimethod assessment suggest 4 general conclusions: (a) Psychological test validity is strong and compelling, (b) psychological test validity is comparable to medical test validity, (c) distinct assessment methods provide unique sources of information, and (d) clinicians who rely exclusively on interviews are prone to incomplete understandings.

• Following principles for optimal nomothetic research, the authors suggest that a multimethod assessment battery provides a structured means for skilled clinicians to maximize the validity of individualized assessments. Future investigations should move beyond an examination of test scales to focus more on the role of psychologists who use tests as helpful tools to furnish patients and referral sources with professional consultation.

Early Mental Test: J. Mck.Cattell

Alfred Binet

• Developer of an innovative approach to assessing intelligence (Stanford-Binet tests).

• Developer of innovative memory tests.

• Ideas for the measurement of cognitive functioning developed after observing his daughters.

• Founder of the first French psychology journal.

• Extremely prolific with diverse publications.

David Wechsler (1896-1981)

In 1934 he began construction of the WB followed by the most widely used intelligence tests: WISC, WAIS, WPPSI

Above all, Wechsler was a clinician, and his goal was to create a practical measure that would reflect his view of intelligence: “the global capacity of the individual to act purposefully, to think rationally, and to deal more effectively with his environment” (Wechsler, 1944, p.3).

Wechsler Scales and Revisions

W-B 1939

WAIS 1955

WAIS-R 1981

WAIS-III 1997

WAIS-IV 2008

WAIS-V 2019

W-B II 1946

WISC 1949

WISC-R 1974

WISC-III 1991

WISC-IV 2003

WISC-V 2014

WPPSI 1967

WPPSI-R 1989

WPPSI-III 2002

WPPSI-IV 2012

Theory and Models: Various ways of classifying intelligence tests

• General ‘g’ and specific mental abilites: Spearman: ‘g’ and ‘s’; Burt-Vernon; Wechsler (WISC/WAIS ‘g’, VIQ/PIQ;4 factors), Stanford-Binet (SB-IV/V)

• Intelligence A,B,C; Gf – Gc (Hebb, Vernon; Cattell, Horn• Multiple Abilities: Thorndike , Thurstone (PMA) • CHC (WJ-III): Cattell, Horn, Carroll• Neuropsychology-based intelligence: Luria/Das PASS (planning, attention, sequential

and simultaneous processing). CAS, KABC-II• Sternberg: triarchic• Gardner: multiple intelligences (e.g, kinesthetic, musical, verbal)• Neo-Piagetian/ Dynamic: Feuerstein• Single measure tests (RPM, NNVT)• Self report, lexicon, • Culture Fair (SOMPA; Cattell Culture Fair)• Emotional intelligence

Cognitive Ability Tests and the Name Given to the Global Score

Test Name of Global Score

Cognitive Assessment System Full Scale

Differential Ability Scales–II General Conceptual Ability

Insight Insight Ability Index

Kaufman Assessment Battery for Children–II Fluid Crystallized or Mental Processing Index

Kaufman Brief Intelligence Test–II IQ Composite

Leiter International Performance Scale–R Full Scale Quotient

Reynolds Intellectual Assessment Scales Composite Intelligence Index

Stanford Binet–5 Full Scale IQ

Wechsler Scales Full Scale IQ

Woodcock-Johnson III General Intellectual Ability

CHC BROAD ABILITIES:•Comprehension-Knowledge (Gc): breadth and depth of a person's acquired knowledge, ability to communicate one's knowledge, ability to reason using previously learned experiences or procedures.•Fluid reasoning (Gf): broad ability to reason, form concepts, solve problems using unfamiliar information or novel procedures.•Quantitative knowledge (Gq): ability to comprehend quantitative concepts and relationships and to manipulate numerical symbols.•Reading & Writing Ability (Grw): basic reading and writing skills.•Short-Term Memory (Gsm): ability to apprehend and hold information in immediate awareness and then use it within a few seconds.•Long-Term Storage and Retrieval (Glr): ability to store information and fluently retrieve it later in the process of thinking.•Visual Processing (Gv): ability to perceive, analyze, synthesize, and think with visual patterns, ability to store and recall visual representations.•Auditory Processing (Ga): ability to analyze, synthesize, and discriminate auditory stimuli, ability to process and discriminate speech sounds that may be presented under distorted conditions.•Processing Speed (Gs): ability to perform automatic cognitive tasks, particularly when measured under pressure to maintain focused attention.

Number of Subtests Measuring Each CHC Ability in Frequently Used Individual

Tests of Cognitive Ability

CHC Ability WJ III DAS II WISC-IV KABC-II SB-V

Fluid Intelligence 3 4 3 2 5

(Gf)

Crystallized

Intelligence (Gc)2 4 5 3 3

Short-Term Memory

(Gsm)2 3 3 3 4

Visual Processing

(Gv)4 5 2 6 3

Auditory Processing

(Ga)4 1

4(Voc/lns/

Inf/WR0 0

Long-Term Retrieval

(Glr)4 2 3+ (VC 4 0

Processing Speed

(Gs)5 2 3 0 0

Using the WISC III, IV, V and WAIS-IV as the data for this presentation “Are demographics destiny”?

Wechsler Model: WISC-IV

Full scale

Verbal Visual

Fluid

Working

Precessing

comprehension spatial reasoning memory speed

Similarities Block design Matrix reasoning Digit span Coding

Vocabulary Visual puzzles Figure weights Picture span Symbol search

Information Picture concepts

Comprehension Arithmetic

Letter-number

sequencing

Cancellation

Primary index scales

Verbal

comprehension

Similarities

Vocabulary

Visual

spatial

Block design

Visual puzzles

Fluid

reasoning

Matrix reasoning

Figure weights

Working

memory

Digit span

Picture span

Processing

speed

Coding

Symbol search

Ancillary index scales

Quantitative

reasoning

Figure weights

Arithmetic

Auditory

working memory

Digit span

Letter-number

sequending

Nonverbal Block

design Visual

puzzles Matrix

reasoning Figure

weights Picture

span

Coding

General

ability

Similarities

Vocabulary

Block design

Matrix reasoning

Figure weights

Cognitive

proficiency

Digit span

Picture span

Coding

Symbol search

Complementary index scales

Naming

speed

Naming

speed literacy

Naming

speed quantity

Symbol

translation

Immediate

symbol

translation

Delayed

symbol

translation

Recongnition

symbol

translation

Storage

and retrieval

Naming

speed index

Symbol

translation

index

FIGURE 1.1 Structure of the WISC-V as defined by basic composition of the FSIQ, the five

primary index scores, the five ancillary index scores, and the three complementary index scores.

Subtest descriptions are reused with permission from the WISC-V Manual (Wechsler, 2014).

Test Structure – WAIS-IV

Working Memory Scale

Core Subtests Digit

Span Arithmetic

Supplemental Subtests Letter-

Number Sequencing (16-69 only)

Verbal Comprehension Scale

Core Subtests Similarities

Vocabulary Information

Supplemental Subtests Comprehension

Processing Speed Scale

Core Subtests Symbol

Search Coding

Supplemental Subtests Cancellation

(16-69 only)

Perceptual Reasoning Scale

Core Subtests Block

Design Matrix

Reasoning Visual Puzzles

Supplemental Subtests Picture

Completion Figure Weights

(16-69) only

FSIQ

New!

New!

New!

Genetics -- Environment

(Not to minimize the significance of Genetics)…Effects of Environment, Culture, SES, Education etc. on Intelligence

• Itard… Wild Boy

• Skodak & Skeels

• Spitz et al.

• Dennis, McGraw, Najarian et al.

• Bayley et al.

• Rosensweig’s animal studies

• Saklofske, D. H.,van de Vijver, F., Oakland, T., Mpofu, E., & Suzuki, L. (2015).

Intelligence and culture. In In S. Goldstein et al. (Eds), Handbook of intelligence:

Evolutionary theory, historical perspectives, and current concepts. NY: Springer.

• Yan, G. , Saklofske, D. H., & T. Oakland (2009) . Contrasting views of

intelligence: Chinese and North American perspectives. School Psychology

International, 30,456-473.

Returning to these Fundamental Questions: What can my colleagues and I add…

–How robust/universal is the structure of intelligence across countries/cultures?

–How well do intelligence tests ‘travel’?

–What is the kind and extent of country similarities/differences on intelligence tests?

–While genetics may explain much of the variance in intelligence, what are key ‘external’ factors that would account for differences observed between groups and individuals?

–Can changes in these ‘demographic’ influences in turn, impact intelligence?

Outline

WISC-III/IV/V Equivalence–Country test adaptations–Robustness of intelligence –Equivalence across countries

WISC-IV/V USA Group Comparisons–Hispanic, African-American, Caucasian–Home factors, expectation

WAIS-IV USA Group Comparisons

–Hispanic, African-American, Caucasian

Thanks also to our publisher: Academic Press/ Elsevier

WISC-III: Countries Participating• 16 countries: WISC-III standardization studies:

–Canada (n = 1,100);

–Germany, Austria and German-speaking Switzerland (n = 1,570);

–France and French-speaking Belgium (n = 1,120);

–Greece (n = 956);

–Japan (n = 1,125);

–Lithuania (n = 452);

–The Netherlands and Dutch-speaking Belgium (n = 1,229);

–Slovenia (n = 1,080);

–South Korea (n = 2,231);

–Sweden (n = 1,036);

–Taiwan (n = 1,100);

–United States (n = 2,200)

1a. Test Adaptations

•USA WISC-III; model and subtests

• Tests in each country modified/developed by local expert teams to address the issue of ‘bias’ in test content and structure

•While there are standardization and norming studies from other countries, only those that met ‘criteria’ were used in this analysis.

• CURRENT studies even more rigorous in following the The

International Test Commission Guidelines (ITC) for Translating and

Adapting Tests: Second Edition (ITC, 2016).

Number of Items Changed (VIQ)Inf Sim Ari Voc Com DS

Canada

France 10 3 2 23 10

German 5 2 10 11 3

Greece 11 2 10 2

Japan 17 7 2 28 5

South Korea 6 1 4 7 3

Lithuania 4 7

The Netherlands 9 4 6 22 9

Slovenia 5 1 7

Sweden 13 2 13

Taiwan 3 9 1

United Kingdom 2 1

Total 85 20 26 137 34 0

Results

• No items changed in Canada and very few in Britain (English speaking)

• Most items changed in Japan

• Most items changed in Vocabulary, followed by Information

• More items changed in ‘verbal’ subtests (although almost no changes in Digit Span) than in ‘performance’ subtests (latter changes with Japanese scale)

1b. One- and Two-Factor Solution

One

factor

Subtest

Picture Completion 0.61 0.46 0.25

Information 0.76 0.84 -0.04

Coding 0.46 -0.14 0.80

Similarities 0.75 0.84 -0.06

Picture Arrangement 0.60 0.32 0.41

Arithmetic 0.69 0.59 0.19

Block Design 0.69 0.31 0.54

Vocabulary 0.76 0.88 -0.09

Object Assembly 0.60 0.23 0.51

Comprehension 0.68 0.79 -0.08

Symbol Search 0.56 -0.05 0.81

Digit Span 0.52 0.37 0.23

Correlations of factors 1.00 0.47

0.47 1.00

Two factorsa

Factor 1 Factor 1 Factor 2

Three-Factor Solution

Subtest

Picture Completion 0.16 -0.14 0.69

Information 0.79 -0.05 0.09

Coding -0.01 0.86 0.01

Similarities 0.79 -0.06 0.08

Picture Arrangement 0.10 0.09 0.59

Arithmetic 0.58 0.18 0.10

Block Design 0.05 0.15 0.71

Vocabulary 0.87 -0.05 0.01

Object Assembly -0.11 0.03 0.86

Comprehension 0.77 -0.05 0.01

Symbol Search -0.01 0.76 0.19

Digit Span 0.47 0.34 -0.11

Correlations of factors 1.00 0.33 0.51

0.33 1.00 0.30

0.51 0.30 1.00

Factor 1 Factor 2 Factor 3

Four-Factor Solution

Subtest

Picture Completion 0.22 -0.09 0.67 -0.10

Information 0.74 -0.03 0.08 0.14

Coding 0.00 0.91 -0.09 0.00

Similarities 0.78 -0.01 0.05 0.05

Picture Arrangement 0.20 0.19 0.52 -0.19

Arithmetic 0.38 0.07 0.14 0.45

Block Design -0.03 0.09 0.73 0.20

Vocabulary 0.87 0.02 -0.03 0.04

Object Assembly -0.13 -0.01 0.87 0.07

Comprehension 0.83 0.05 -0.05 -0.08

Symbol Search -0.01 0.80 0.11 0.03

Digit Span 0.07 0.05 0.01 0.87

Correlations of factors 1.00 0.33 0.50 0.29

0.33 1.00 0.35 0.22

0.50 0.35 1.00 0.23

0.29 0.22 0.23 1.00

Perceptual

Organization

FD/WMVerbal

Comp.

Processing

Speed

1c. Equivalence

•Evaluated by means of factorial agreement, comparing all countries in a pairwise manner (Tucker’s phi)

•One-, two-, and three-factor solutions were very stable across countries same factors measured in all countries

•First three factors in four-factor solution stable, but fourth factor less stable: Place of Arithmetic varies

Subtest and IQ Mean Differences: Effect Sizes

Dependent variable h2

Subtest h2 IQ scores h

2

Picture Completion 0.01 Verbal IQ 0.01

Information 0.01 Performanc 0.05

Coding 0.02 Full Scale

IQ

0.03

Similarities 0.03

Picture Arrangement 0.01

Arithmetic 0.02

Block Design 0.01

Vocabulary 0.02

Object Assembly 0.03

Comprehension 0.02

In cells: proportion of

variance accounted

for by country in an

Analysis of

Variance with country

as independent

variable and (sub)test

score as dependent

variable

Results

• Country differences are statistically significant for subtests and subtest-based indices

• However, the country differences tend to be small in terms of effect size (eta squared); all below Cohen’s metric of .05 as lower threshold for medium-sized effects (subtests .01 to.03; VIQ .01; PIQ .05; FSIQ .03)

1c. Country-Level Indicators

• Affluence

–Combination of energy use per capita (in kg of oil equivalent), percent of labor force in agriculture, electricity consumption per capita (in KWh), national electricity consumption (in KWh) (weighted for population variations), Gross Domestic Product per capita (in USD), etc.

• Education

–Combination of Pupil-teacher ratio in pre-primary education, in primary education, and in secondary education, percentage enrolling in tertiary education, etc.

Correlations of IQ/Index scores and Country-Level Variables

IQ Scores Affluence Education

Verbal IQ 0.43 0.55*

Performance IQ 0.43 0.63*

Full Scale IQ 0.49 0.68*

SUMMARY

• Factorial composition of WISC-III stable across countries (replicated in several of our studies with WISC-IV, WAIS-IV)

• Tests can be adapted to minimize ‘test bias’

• Country mean differences tend to be small

• Mean FSIQ for countries varied systematically with level of affluence and education as indicated by key economic indicators such as GNP and percent of GNP spent on education,

• Wechsler intelligence tests well suited for cross-cultural comparisons

WISC-IV / WAIS-III

The four-factor structure of the WISC-IV has also been supported by international

adaptations across Australia/New Zealand, Canada, Europe, UK and in Asian regions.

Within each region, confirmatory factor analyses supported the four factor structure

(e.g. Wechsler, 2004; Chen et al., 2010).

Factor invariance has also been shown with the Wechsler Adult Intelligence Scale:

Third Edition (WAIS-III) between U.S. and Canada (Bowden, Lange, Weiss & Saklofske,

2008) and other countries

WISC-V Data (van de Vijver, Weiss, Saklofske et al. 2019)

• Data from the following samples: Australia and New Zealand, English-speaking Canada, French-speaking Canada, France, Germany, Dutch-speaking regions (Netherlands and Flanders), Spain, Scandinavia (Sweden, Norway, and Denmark), United Kingdom, and the United States.

• The main conclusions are threefold: (1) there is strong support for the identical structure of intelligence in the Western countries of the study (4 and 5-factor structure); (2) the country differences in mean scores are small; (3) these differences are not related to social indicators that are derived from educational and economic level of a country.

• With the exception of the last conclusion, similar results were obtained in a cross-cultural study involving the WISC-III.

WISC-V cont.

• The present study implies that careful instrument design and adequate sampling frames can go a long way to debunk myths about cross-cultural intelligence and country differences. While our study cannot speak to the controversial issue of the relative contributions of genes and cultural factors to group differences in intelligence, it would appear that many studies that employed the combination of Western tests administered to convenience samples may erroneously lead to an overestimation of group differences due to confounding factors.

• BUT…. Some exceptions!!!!

WISC-V cont.

• The main global conclusion from our analysis is that country differences in cognitive test scores in these Western samples are small and in many cases negligible from a practical perspective; for example, global IQ differences account for less than 1% of the variance. Individual differences within countries are much larger than country differences.

• In the present study no significant correlations between cognitive test scores and social indicators were found.

• The discrepancy with our WISC-III research may be due to the limited cultural variation in the present study: mainly involved WEIRD countries: Western, Educated, Industrialized, Rich, and Democratic (Henrich, Heine, & Norenzayan, 2010), whereas the WISC-III study showed a larger cultural variation.

• Also more detailed and sensitive social indicators: 1. Human Development Index, which is a composite of the level of economic development, life expectancy, and years of schooling (all at country level); 2. Gross Domestic Product (per capita); 3. educational expenditure (per capita), which refers to the number of dollars spent on education (per capita) in a country.

However while we can measure/assess intelligence and address the ‘bias’ issue in tests…

• Differences within countries/cultures > differences between countries.

• Other unique characteristics within and between country groups, based on ‘demographic’ factors, may impact the development and expression of cognitive abilities

2. WISC-IV/V in Societal Context

• “The examiner should take into account other factors such as the child’s educational, medical, cultural, and family history…” (Prifitera, Saklofske,Weiss, 2005;Weiss, Saklofske, Prifitera, 2006)

• Disproportionate representation of minorities in special education

• Differential risk for learning problems

• A question of: test bias vs. ‘group’ differences …and the effects of SES, poverty and other demographic differences?

Demographic Differences Between USA Groups: A ‘Natural Laboratory’ Study

Group Differences

3 largest Racial- Ethnic Groups in USA: AA, Hispanic, White:

-mental health

-physical health

-income

-education

-home environment

Racial/ethnic group differences: Mental Health status and services

• -controlling for SES, rate of psychological disorders among AA and Whites about same…BUT AA much higher proportion in Low SES. Higher MI amongst homeless, incarcerated, foster care… AA higher in all categories. AA not accessing MH services about 2.5x less than Whites.

•Hispanic … differences between 1st/2nd generation

Racial/ethnic group differences: Physical Health status and services

•AA more physical health problems than either White or Hispanic (infant mortality, diabetes, heart disease, prostate cancer, HIV/AIDS, Sickle cell anemia

•Hispanic, varies Cuban/Puerto Rican/Mexican/Central America

Racial/ethnic group differences: Income

• Income of parents directly impacts the SES of families which relates to IQ test scores of children (huge issue re. discrimination, unfair pay, access to health care, education, language…

•While 17% of all US children live below poverty level, 30.% Hispanic children; also 3x more AA than White live in severe poverty

Racial/ethnic group differences: Education

• parent education and children’s IQ… r=.43;

20 point difference in mean FSIQ of children whose parents dropped out of HS vs. those who completed college.

HS droput rate College Entrance Rate

• White 5.9 67.0

• AA 19.3 46.7

• Hispanic* 47.0 26.0

• Asian 15.5 73.3

• * Hispanic… heterogeneous group

• From WISC-IV Standardization study (2003)

Home environment influences on children’s cognitive development

• AA children: home environment ratings typically add significant information to the prediction of IQ scores from SES and the variance explained is often larger than for White Children

• Mexican-American children: Neither SES nor family size contributes significantly to the prediction of cognitive ability beyond that accounted for by home environment.

• Growing evidence over more than 60 years of research that home environment is an important predictor of cognitive development and academic achievement across cultures. Enriching, cognitively stimulating environments enhance intellectual development and skill acquisition in children whereas impoverishing environments inhibit it. (parallel in Rosenzweig’s studies: acetylcholine and cerebral cortex volume)

The role of the child in cognitive development

• Beyond genetics and the critical role that parents and educators play in the cognitive development and achievements of children, there are non-cognitive characteristics of the developing child that mediate the actualization of cognitive potential including:

• Temperament (e.g. enhancing vs. preserving trait)

• Conative factors including motivation, volition, self efficacy, self concept , perfectionism

Factors influencing intelligence test scores between Race/Ethnic Groups within the USA.

• Given the previous description of individual, group and also demographic differences as a context for exploring group differences, we now examine patterns of IQ score differences across racial/ethnic groups using the USA as ‘natural laboratory’

• For purposes of this discussion, only focus on African American, Hispanic and White groupings

• Groups based on national standardization using parent education (SES), race/ethnicity, age, gender, region of country.

Race/Ethnicity

• IQ/INDEX African American Hispanic White

• FSIQ 91.7* 93.1 103.2

• VCI 91.9 91.5 102.9

• PRI 91.4 95.7 102.8

• WMI 96.1 94.2 101.3

• PSI 95.0 97.7 101.4

* WISC-III FSIQ = 88.6 ( a Flynn effect or improved test or…?)

Age trends and Race/Ethnicity

Af. Amer – White Hispanic-WhiteIQ/INDEX 6-11 yr 12-16 yr 6-11yr 12-16 yr

FSIQ 6.0 11.8 1.3 8.0VCI 5.6 12.2 3.7 8.5PRI 6.8 10.5 -.2 3.9 WMI 1.9 5.9 2.4 5.5PSI 3.5 5.6 -1.5 3.4

Child FSIQ by Parent Education

• Education Level FSIQ

• 8th grade or less 88.2

• 9th to 11th grade 87.2

• High School 94.5

• Some College 102.4

• College grad 108.7

Mean FSIQ by Family Status

Single Parent Dual Parent

Families Families

AA 89.4 95.

Hispanic 92.7 93.3

White 99.3 104.7

•Differences related to income, etc

SES Mediators of difference between African American and White FSIQ

R2 R2 % Mean

diff diff

Model 1

Race .047 10.4

Model 2

PED .188

PED, Race .214 .026 44.5% 7.8

Model 3

PED .188

PED, income .223 .035

PED, income, race .239 .016 65.4% 6.3

SES Mediators of difference between Hispanic and White FSIQ

R2 R2 % Meandiff diff

Model 1Race .014 6.3

Model 2PED .175PED, Race .175 .000 99.0% 0.5

Model 3PED .175PED, income .205 .035PED, income, race .205 .000 99.0% 0.5

Race and IQ

• There are no known biological or genetic markers of race.

• Race is a socially created construct

• Race is not a valid independent variable because group membership can not be defined in any scientifically acceptable manner.

• Psychologists should seriously question using race as an independent variable in psychological research (Helms, 2005)

BUT… to the point…RACE/ETHNIC differences in intelligence can be largely accounted for by key factors such as PED and other ‘proxy’ variables

Two qualifiers

• PED, Income etc. are ‘distal’ resources and exert their effects ‘indirectly’ (Bronfenbrenner & Ceci, 1994) vs. ‘proximal processes describing the reciprocal interactions between developing child and significant others. Distal resources can place limits on the efficiency of the proximal processes

• THUS… while findings such as those just presented provide invaluable information about ‘group’ characteristics, psychology is committed to understanding individual differences.

• So we must turn our attention to proximal mediators of children’s cognitive development (e.g. what occurs between parent-child at home)

Parental Expectations (PEX) of Children’s Academic Success

• …is a good predictor of the child’s academic success

• …is a good predictor of the child’s attained level of cognitive ability

• …are communicated to the child in a myriad of subtle and not so subtle ways

• … PEX is correlated with Parent Education and FSIQ level

Parental Expectations (PEX) as mediator of FSIQ across groups

R2 R2 % MediatedModel 1

PED, Income .213Model 2

PEX .307PEX, PED, Income .372 .065 69.5%

Model 3PED, Income .213

PED, Income, PEX .372 .159 48.2%

Mean FSIQ of children by Parent Expectation Level

Parent Expectations FSIQ

Low 78.5

Medium 96.5

High 107.4

PEX

• PED and Income combined explain approx. 21% of the variance in children’s FSIQ; PEX alone explains about 30%.

• Effect of PEX is only partially accounted for by PED and Income

• PEX accounts for similar amounts of variance in children’s FSIQ in AA/White and Hispanic/White comparisons

• Although PEX varies across PED levels, and many other factors may account for the covariation of PEX and FSIQ, PEX predicts substantial variance in children’s measured IQ within each level of PED

Home Environment & Ability

• Enriching, cognitively stimulating environments enhance intellectual development and skill acquisition, whereas cognitively impoverished environments inhibit it.

• The positive effects of:– Reading to children– Computer use– Limiting television – learning opportunities, modeling learning

• Parental expectations alone explain more variance in children’s cognitive ability scores than parent education and income combined (many examples of parent ‘sacrifices’ to ensure their children’s education and future)

Take Away Points

•Racial/ethnic differences NOT due to item/test bias but likely a proxy for other variables (eg. low SES, parent expectation)

• SES estimated by parent education and income accounts for a large portion of the variance in children’s intelligence test scores between racial/ethnic groups.

•AND drawing for the research literature and our studies of Home Environment:

*What parents do at home is more important than what they are.

*Demographics is not destiny!

3. ADULT intelligence and Social Context

Examining differences in mean scores across groups is a relatively simple but flawed procedure for assessing cultural bias in tests (Gottfredson & Saklofske, 2009). A more sophisticated approach is to examine how the relationship of intelligence test scores to ‘important criterion variables’ differs across groups:

• Demographic Differences in Various Areas of Life (group disparities in education, mental health, physical heatlh

• Role of Cognitive Stimulation in Intellectual Development

• Home Environment Influences on Cognitive Development

Education of 16-90 year olds

HS drop outCollege Entrance

White 14.7 51.2

AA 25.7 40.1

Hispanic 43.8 29.1

Asian 15.5 73.3

Race/Ethnicity & WAIS-IV

IQ/INDEX African American Hispanic White

• (N= 260) (N=289) (N=1540)

• FSIQ 88.67 91.63 103.21

• VCI 91.15 91.41 102.92

• PRI 88.33 94.10 102.87

• WMI 92.12 91.76 102.68

• PSI 91.89 95.75 101.86

(SD’s 13.6 - 15.1)

WAIS-IV mean difference scores between racial/ethnic groups by birth cohort

AGE

65-90 45-64 30-44 20-29 16-19

AA/W 19.3 17.2 13.1 13.4 10.0

H/W 17.9 13.62 14.2 7.3 9.3

SES mediators of FSIQ Differences between Groups: AA-White, 20-90 yr.

R2 R2 Diff % Mediated Mn diff.Model 1

Race .15 14.88 Model 2

Ed .29Model 3

Ed, Income,region .35 .061Occupation, Sex

Model 4 Ed, Income,region .44 .092 38.4% 11.23

Occupation,Sex,Race

SES mediators of FSIQ Differences between Groups: AA-

White,16-19 yr.

R2 R2 Diff % Mediated Mn diff.Model 1

Race .05 7.89 Model 2

Ed .15Model 3

Ed, Income,region .22 .072Occupation, Sex

Model 4 Ed, Income,region .24 .014 72.8% 3.87

Occupation,Sex,Race

SES mediators of FSIQ Differences between Groups: Hispanic-White, 20-90 yr.

R2 R2 Diff % Mediated Mn diff.Model 1

Race .11 11.95 Model 2

Ed .31Model 3

Ed, Income,region .37 .060Occupation, Sex

Model 4 Ed, Income,region .41 .037 66.1% 6.56

Occupation,Sex,Race

SES mediators of FSIQ Differences between Groups: Hispanic-White, 16-19 yr.

R2 R2 Diff % Mediated Mn diff.Model 1

Race .12 11.96 Model 2

Ed .25Model 3

Ed, Income,region .29 .039Occupation, Sex

Model 4 Ed, Income,region .31 .018 84.3% 3.95

Occupation,Sex,Race

General Review

• There are multiple theories and definitions of intelligence

• Opinions vary widely on how to measure and assess intelligence

• There are strong and divergent views on the relevance and importance of intelligence and its usefulness as an individual differences construct

• Genetics and environment are both important ‘causal’ agents

• There is a cross-cultural robustness to the underlying structure of intelligence and how intelligence is expressed is influenced by culture

• What we do know is that intelligence is correlated with more aspects of individual differences than any other psychological construct.

• Intelligence is impacted by the world we live in… demographics are influential determiners of the development and expression of intelligence

• Demographics are also modifiable!!

Summary

• There is both an intersection and overlap of factors that impact the development of intelligence and cognitive processes, including one’s capability/opportunity to demonstrate those abilities. As well this includes both proximal and distal resources and social norms.

• Intelligence is malleable, within limits, by environmental factors that mediate opportunities for cognitive growth and maintenance of cognitive abilities… and the effects of these mediators is cumulative across the lifespan.

• Our data suggests racial-ethnic IQ differences may be decreasing with successive generations

• Racial-ethnic differences are likely to be proxies for other key variables such as personal factors.

• Personal factors account for significant variance in intelligence

• Demographics are not destiny.

Thank you