Transcript Aging and Intelligence PS277 – Lecture 9 Cognitive Aging – The Far Side.

Aging and Intelligence
PS277 – Lecture 9
Cognitive Aging – The Far
Side
Outline
 Definitions of Intelligence – A Short
History
 Everyday Conceptions of Intelligence
 Aging and Patterns of Change in
Intelligence
 Factors Involved in These Changes
Baltes’ Framework on
Intelligence Over the Lifespan
 Intelligence as multi-dimensional
concept?
 Multi-directionality in change
 Plasticity and training
 Interindividual variability in patterns
I. History of Intelligence as a
Construct
 Early Single-Factor Theories:
 Binet’s Test – diagnose children unable to cope
with regular schooling in Paris system –
focused on performance on reasoning tasks
and gave a single score (M = 100)
 Spearman’s g – general factor theory = all
tests correlated positively, a single general
factor or “thing” called intelligence, on which
everybody can be ranked
Multiple Factor Theories
 Thurstone’s Original 7 Primary Mental
Abilities
 Verbal meaning
 Perceptual speed
 Reasoning
 Number
 Associative memory
 Word fluency
 Spatial orientation
Secondary Mental Abilities
 Interactions and structures that combine these primary
abilities (6 studied so far)
 Fluid vs. Crystallized Intelligence – two most widely
studied developmentally
 Fluid = seeing patterns and relationships in novel
situations, abstracting information – letter series (d f i m r
x e ?)
 Crystallized = incorporated the knowledge and
information of the culture (what word is associated with
bathtub, prizefighting and wedding?)
Howard Gardner’s Theory of
Multiple Intelligences
II. Everyday Intelligence:
What’s Your View?
 List behaviors that you think are
characteristic of young adults who are
highly intelligent vs. those who aren’t?
 Anything special about older people
who are highly intelligent vs. those who
are not?
Everyday Conceptions of
Intelligence
 Sternberg’s research on lay people vs. experts’ conceptions of
intelligence
 122 Lay Persons: 3 factors found were labeled practical
problem-solving ability, verbal ability, social competence
 140 Experts: 3 factors found were labeled verbal intelligence,
problem-solving ability, practical intelligence
 Pretty similar in having multiple factors, but more emphasis on
social competence by lay persons, recent emphasis on
“emotional intelligence” in field may reflect need to get more at
this in standard measures
Predictability from Standard IQ
Tests
 Scholastic performance: correlations show that prediction of
school performance in kids is about .50 with various IQ tests –
good but not great. Same sort of findings with respect to
university performance and standardized tests (e.g., GREs)
 Occupational performance: some predictability, but this may
depend on relations with level of school attainment... practical
intelligence measures do just as well as standard IQ tests
 Adjustment: some weak associations for children, but
generally not much, emotional and social intelligence might
predict better
 Not such a great record for such a big business!
III. Patterns of Test Performance
and Aging – Fluid vs. Crystallized
IQ
Baltes’ Framework on Types
of Intelligence
 Mechanics of Intelligence – biologically based
development, influenced by how the brain
works, skills needed for schooling, develops
most in early life – somewhat parallel to fluid
intelligence
 Pragmatics of Intelligence – everyday
knowledge and skills for solving problems,
wisdom, verbal knowledge, more growth into
later life – very close to crystallized
intelligence
IV. Factors Moderating Patterns of
Change in Intelligence Performance in
Later Life
 Age is not really a meaningful explanation of
anything – why?
 Cohort Differences – the Flynn Effect
 Health Status and Terminal Drop
 Information Processing Factors
 Social and Lifestyle Variables
Cohort Factors in Intelligence
– The Flynn Effect
 IQ test actual scores
have increased on
average for last 50 years.
Why?
 Technology, nutrition,
education of parents,
other ideas?
 Maybe intelligence really
is not fixed
Cohort Differences in Aging and
Intelligence? – Seattle Longitudinal Study
Health and Terminal Drop
 Lindenberger and Baltes’ findings on sensory
function and fluid intelligence
 Biological age and primary abilities in Victoria
Study – book shows that a lot of the variation in
primary abilities is predictable from biological
age measures
 Terminal drop as a phenomenon in all of these
data sets
Victoria Study Data on Biological Age
as Predictor of Cognitive Change
Information Processing and Intelligence
Tests – Componential Analyses
 Earl Hunt’s work: performance on IQ tests seems to be
substantially a function of individual differences in information
processing – one component of this is speed
 Example: Hi vs. lo verbal test performers differed in speed of
reaction to (A, a) vs. (A, A) stimulus sets when have to respond
“same” if each letter has same name, “different” if they don’t (A,
B)
 Task componential analysis: In order to solve the (A, a)
problem, must also retrieve the names of the two letters, so this
is how much longer this takes over the (A, A) case
 Speed of processing and working memory declines may
account for much of aging losses in later life intelligence test
performance
Occupational Effects on
Intelligence in Adulthood
 Schooler’s work on occupational complexity and
intelligence
 Male workers (and some wives) interviewed and tested in
1964, 1974, 1994 – mean age was 57 in 1994
 Work complexity was rated, cognitive tests like recall,
PMA verbal meaning, etc.
 Used SEM to test a model of reciprocal influence
between work and IQ, separated for older and younger
worker groups
Schooler et al.’s Model of Effects
for Young vs. Older Workers
Training Intelligence – Schaie
and Willis Work
 Seattle Longitudinal
Study
 Trained Spatial
Orientation or Inductive
Reasoning skills,
depending on problems
 Clear benefits in 65% of
older adults
 Persisted over 7 to 14
years in follow-ups
Schaie & Baltes