Cognitive Perspective
 Mental representations of objects and their significance
 Consider the simplicity of an image vs. events/people etc.
 Each is idiosyncratically defined with a great deal of complexity
 Evolution has moved the environment into the brain (perception vs.
“reality”) – No direct experience of the environment (e.g., eye).
 Mediated by perception of the environment, and this is decidedly a
cognitive event (mediated by expectancies, motivation, etc.)
 This perspective can more easily explain complex behaviors (most
human action) and does not deny the presence of cognitive
processes (thoughts & feelings)
 For example, when considering approach/avoidance conflicts, it is
possible to examine individual differences in how one cognitively
construes the same event (e.g., Is a test as a potential for success
or failure?)
Less variability for the semi-starved rat considering food/shock
Cognitive revolution (1950s forward)
How do we think, perceive, remember, solve, etc.?
Tolman’s latent learning
When learning is not immediately evident or behaviorally observable
Learning occurs in the absence of reinforcement for the behavior or
any associative learning (learning from temporal association)
Research on hungry rats with 3 conditions: 1) food when they reach
the end of the maze, 2) no food after running the maze, or 3) initially
no reinforcement, but later reinforced for running the maze
Dramatic improvement for rats in condition 3 after reinforced and did
better than those in condition 1
So they were learning in earlier trials, despite not being reinforced or
showing it behaviorally (forming cognitive maps)
Later replicated in other animals and humans
Chomsky’s “preparedness” for learning in children
Linguistics movement (a readiness to learn/acquire speech)
Thought processes are intermediaries between stimulus and response
Cognitive Revolution
 George Miller work with human memory
memory is critical to learning as it accounts for whether we remember
and how we recall it.
e.g., learning by chunks: issue of capacity for learning (7+-2), the role
of perception in learning (chess pieces for novices & experts), etc.
Considers the computer as a metaphor for the mind
 Von Neumann & McCullough’s use of binary mathematical
relations among symbols to reflect the mind
Artificial intelligence, bottom-up and top-down metacognitions
e.g., Deep Blue as a model for human thinking in chess
 In addition to memory, behavior & cognitions are influenced by:
information processing (e.g., heuristics and biases),
pattern recognition (prototypes),
schema (less agreeable people are more likely to see others as hostile)
George Kelly (1955)
Construct theory
Humans as scientists
Where did your “experiments” begin?
Personal theories = constructs
Used to explain the present and predict the
future
“Ask them, they might just tell you.” (credible
approach that emphasizes the subjective
appraisals of individuals
Fundamental Postulate and Corollaries
 How you represent the environment is affected by the
anticipation of events
 assume replication; oriented to the future
 uniqueness of your construct system
 finite number of dichotomous constructs
 range of convenience for any construct
If events can’t be explained by any construct, this leads to
anxiety
 choice of constructs and their ordinal association (you
can have any theories, but the theories you choose limit
what you’ll find)
Kelly’s cognitive complexity
 Kelly defined cognitive complexity as having many
superordinate (or core) constructs (initiated the cognitive
movement)
Patient with single core construct of “Army – not Army”
 Greater cognitive complexity is associated with better
adaptiveness as it means you have more ways of
interpreting events (vs. being very limited in how you view
things)
 Tetlock & Suedfeld have studied the cognitive complexity
of communications and how it predicts conflict. Lower
complexity = maladaptive (conflict)
e.g., examined UN communications between countries and could
predict times of conflict
Social learning/cognitive theory
 Behavior potential = Behavioral expectancy (regardless
of the reinforcing or punishing contingencies, do you
expect the consequence?) X reward value (idiosyncratic
value one places on the reinforcer or punisher)
Julian Rotter, 1970s
 Because previous experience necessarily influences
expectancy, Rotter’s model necessarily considers the
person & situation
Putting cognitive theory to the
test, part 1
Can learning occur from modeling in animals?
 Modeling/imitation: learning in the absence of
reinforcement for either the target or the model
 Modeling occurs in species within the great ape lineage
e.g., fear of snakes in monkeys reared in captivity after exposure
to monkeys reared in wild
Can modeling occur in species outside the great ape lineage?
 Rhesus monkeys ranging in age from 1 to 14 days
exposed to human models engaging in simple behaviors
like tongue protrusions, mouth opening, lip smacking, etc.
 Greater learning for “older” monkeys, and some behaviors acquired more
easily (also evidenced individual differences in acquisition)
 Evidence for mirror neurons (cells that fire when others perform an action
to promote mimicry)
Modeling in humans
 Bandura’s social learning theory suggests that modeling
requires:
Attention – notice and attend to the behavior
Retention – defining features of the behavior have to be encoded,
retained, and recalled
Reproduction – more complex tasks may require rehearsal
Motivation – incentives are typically needed, but they may be
internal, or in some cases, absent (highly variable factor)
 The bulk of the human data on modeling/imitation is nonexperimental in nature and has focused on areas of great
concern (Is violence in our society due to modeling? – see
school shootings such as Sandy Hook, 2012; James Holmes,
2012, etc.)
Effects of violent/aggressive models
Media coverage as a source of modeling?
 Reviews literature on violent TV viewing in childhood (survey
research). Huston & Cofer, 1986; also Bushman & Huesmann, 2014
Prospectively predicts adult aggression. Confounds?
Findings persist after controlling for SES, level of supervision, and
aggression as a child.
Effects are growing since 1975
Effects are strongest when individuals can identify with the models
Less overt effect for adults; a readiness to aggress
Weaker modeling effects for pro-social behavior
 Conclusions regarding violent video games: strongest effects
when looking at aggression in the lab vs. violence outside the
lab
FYI - Violent crimes decrease when violent films are showing (Dahl &
Vigna, 2009); Those who like violence are busy!
Putting cognitive theory to the
test, part 2
Is there experimental evidence for modeling in humans?
 Effects of aggressive models on children (see Bobo doll
experiment; Bandura et al., 1961)
Children randomly assigned to one of 3 conditions: 1) aggressive
adult, passive adult, a group with no adult model
Aggressive adult model punched and struck the doll with mallet
Children exposed to the aggressive model engaged in significantly
more aggressive behavior with the bobo doll
Males showed more physical aggression, but no gender difference on
verbal aggression
Modeling is most effective when it is a similar model
 Follow-up study to test effects of reward and punishment
Minimal change in aggression if model was punished
Double the effect if model was rewarded (Bandura et al., 1963)
How durable are the effects?
Self-efficacy and reciprocal
determinism (Bandura)
 Self-efficacy – the belief in one’s ability to succeed
(mastery, competency, effectiveness)
This belief appears important to expectations for favorable
outcomes, and this in turn, impacts motivation, effort, etc.
Can be domain-specific (e.g., work vs. relationships)
 Reciprocal determinism (causality) – behavior is
predicted by the person (internal cognitions), their
behavior, and the environment
Each factor influences the other
Note: Psychodynamic was fully focused on internal motives and
behavioral perspective was fully focused on the environment
Self-regulatory theory (Mischel)
 1. Reward value – differential value for certain rewards
& punishers (different between individuals & over time)
 2. Expectancies – typically based on previous experience
 3. Encoding strategies – how information is interpreted
by the individual (exam feedback), framing effects, etc.
 4. Competencies – actual ability mediates these
processes (self-efficacy beliefs – see also Bandura)
 5. Self-regulation – how goals influence/regulate all of
the previous four factors
research by Kunda (1990) examining motivated reasoning - an
event with a 60% likelihood of occurring can be described as
“not very likely” (get cancer) to “somewhat likely” (get an “A”)
e.g., how goals influence the interpretation of a test grade
Seeing what you want to see
 Study 1: Participants doing a randomly determined “taste test”
and a briefly presented ambiguous video image (either a “B”
or “13”) would determine what they tasted (fresh OJ or
gelatinous substance). - Balcetis & Dunning, 2006
Image presented for 400ms then computer “crashed”
Participants were more likely (82%) to see the image that would result
in the preferred substance (OJ)
 We see desirable objects (those fulfilling immediate goals—a
drink for the thirsty, money, favorable feedback) as physically
closer than less desirable objects. Biased distance perception
revealed through actions (e.g., under-throwing a beanbag at a
desirable object). - Balcetis & Dunning, 2009
 Seeing desirable objects as closer than less desirable objects serves
the self‐regulatory function of energizing the perceiver to approach
objects that fulfill needs/goals (“wishful seeing;” Dunning & Balcetis, 2013)
Cognitive perspectives on depression
 Maladaptive cognitions & attributions e.g., learned
helplessness in a dog restrained (failure to acquire new
learning) – Seligman, 1978
 Cognitive triad of well rehearsed thoughts (Beck et al., 1979)
1. Negative thoughts about the self (“I suck”)
- internal vs. external attributions
2. Negative thoughts about the everyone else (“no one loves me”)
– general vs. specific conclusions
3. Negative thoughts about the future (“things will never change”)
– stable vs. changing
 Interdependence of mood and personality
Neur - overreaction to events - sad mood - stronger neg view - Neur
 Arbitrary inferences: drawing specific conclusions without
evidence, selective abstraction (details taken out of context),
magnification and minimization, etc.)
Cognitive models for depression
 A. Ellis: ignoring positive things in life, exaggerating the
negative, and over-generalizing (irrational thoughts)
“I should act like this” (tyranny of the “shoulds”)
Note: Cognitive interventions are one of the most effective
treatments for depression (equal to medications)
 Confirmation bias – looking for information that confirms
negative schemas (“I will never amount to anything”) and
ignoring/minimizing disconfirming information
Consequently, we seek self-verification vs. self-enhancement
See Swann et al., 1992 computer game study on experts and novices
See De La Ronde & Swann, 1998 for research on commitment in relationships
These effects are seen as automated vs. intentional
 Linehan’s biosocial model of personality where genetic
predispositions for emotional problems and the reinforcing
social environment causes personality disorders
Assessment tools from the cognitive
perspective
Repetory Grid (Kelly): Class assignment
P. 1: Identify the important people in your life
P.2: Think about the three individuals and how
two are alike on some trait and yet different
from the third person on the same trait.
e.g., 2 of the 3 are really organized while the
third person is really disorganized
Measures of affect & other
cognitive structures
 BDI-II: 21-item measure matched to DSM-IV (clinical)
 CES-D: 20-item measure for general population
 Hamilton Rating Scale for Depression: for clinical use
 BAI: 21-items for use in clinical and non-clinical settings
 State-Trait Anxiety: Addresses the stable and more
transient aspects of anxiety (trait and state)
 IAT – Implicit measure to contrast most measures which
are self-report. Uses reaction times to get at cognitive
associations.
Does it measure knowledge of something or actual beliefs?
 Possible selves – identifying possible selves that
individuals have at any one time to capture cognitive
appraisals about the self
Sociobiological theory
 Consider how males and females differ in their
personalities as they are expressed in relationships
 Evolutionary pressures differ by gender
Microevolution: changes within a population; short time period
 Females have high investment in children so should be
more selective (they seek resource-related traits)
Why is there a need to ensure paternal certainty?
 Males have relatively short temporal investment so no
need to be selective (they seek fertility/youth), but this
breeds increased competition for the limited resource
 What might “physical attractiveness” represent in
addition to beauty?
 Health (i.e., reproductive potential)
Sociobiological theory - p.2
 Various species demonstrate increased sexual potency
(shorter refractory period) for males when new females
are introduced (vs. repeated copulation with the same
female); quantity
Known as the “Coolidge Effect”
 Females need to have paternal certainty (access to
resources) and must be selective based on parental
investment theory (more time required & less fertile
time across the lifespan)
Sociobiological theory - p.3
 Are there different search criteria employed for short and
long term relationships?
 For males it’s sexual availability and fertility, respectively
 For females, it’s sexual availability and ambition/earning
potential, respectively
 Note: Promiscuity is seen as desirable by both genders
for short-, but not for long-, term relationships
 Men will consider short term relationships with almost
anyone, but women are much less likely to do so.
 Men desire to have sig more sex partners v. women
Schmitt et al, 2003: > 20 vs. 2-3 for women
Putting Sociobiological theory to
the test
Over 10,000 individuals from 33 countries (Buss, 1992)
 Among the top traits for both men and women in short term
relationships was promiscuity (sexual availability)
 For long term relationships the top trait for both groups is physical
attractiveness
 For females, earning potential was consistently rated high
(noteworthy, given the population sampled)
Examination of personal ads (Kenrick & Keefe, 1992)
 Females seek males who are older than themselves and are
economically established. Their own ads emphasize their beauty.
 Males emphasize their own economic achievements and seek
younger attractive women (Note: Youth is a proxy for reproductive
potential, as shown by the fact that teen boys prefer older women)
120 Personal Ads
- Baize & Schroeder, 1995
NY Times examples:
 A BEAUTY
SWF in 30s, slim, gym-fit and shapely works in Manhattan.
Sweet, earthy, free-spirited (azure eyes, long locks, leftist
politics) seeks male in 40s, accomplished, passionate,
reliable, gentle genius to adore.
 A KNOCK OUT
Gorgeous blond, 20s, great figure, sensuous, sincere, fun,
looking for love of my life: tall, established, 30s-40s.
 A GOOD MAN
DJM, 60, successful, attractive, professional, seeks
attractive, open, sensitive, caring/sharing, in 50's, Long
Island.
 ARCHITECT/ARTIST
Living in theater district. Latte drinking, Sushi eating, NY
Times addicted, professional in his 30s. Seeks 20-30s,
attractive, fun-loving female. Long hair a plus.
Jealousy by gender
“Would you experience more distress over sexual infidelity
or emotional infidelity?” - Buss et al., 1999
Imagine partner falling in love with someone else vs. Imagine
partner trying different sexual positions with someone else.
 83% of females more jealous of emotional infidelity vs.
40% of males
 Males show greater physiological arousal to imagined sex
of partner with someone else
 Why are females more jealous of emotional infidelity?
Because it threatens access to resources
 Why are males more jealous about sexual infidelity?
Because it threatens paternal certainty
More Recent Research
 Sperm competition following significant absences in
response to female infidelity
Shackelford & Goetz (2007)
 The “Florida Study” (2008) examined response rates to
3 requests by gender
Go on a date, go to my place, have sex
 As seen in other mammals, maternal aggression in
lactating mothers is higher relative to bottle feeding
mothers (competition with the winner administering a
loud unpleasant noise to the loser). Lactating mothers
did a longer noise relative to bottle feeders who did not
differ from women who were never pregnant

Hahn-Holbrook et al., 2011
Critique of sociobiological theory
 Studied almost exclusively in college students
 Do dating and mating involve the same motives?
 Sociobiological theory (like evolutionary theory) does not
predict specific future behavior, it explains events post
hoc
this is a major weakness (recall that Freud could likewise
explain anything after the fact)
e.g., long vs. short-necked giraffes
 Evolutionary drift - some events are a consequence of
adaptive behavior but are not themselves adaptive
Ch. 8: A Trait Approach
 Traits as building blocks to describe behavior
 Linking traits to behavior
 Organizing traits (factors)
Big Three (Eysenck)
Big Five (Costa & McCrae)
 Person-Situation Debate
 Supplementing traits with other approaches
Goals
Act-Frequency
 Assessing traits
Traits over time: A review
 Recall the traits forwarded by Humoral Theory (Hippocrates
& Galen)
Sanguine
Choleric
Melancholic
Phlegmatic
 Carl Jung
Introversion-Extraversion
 Gordon Allport’s trait hierarchy
Cardinal traits
Central traits
Secondary traits
Trait approaches based on body
morphology
 Palm readings
 Criminality (Lombroso) - physical features predict criminality
L’uomo delinquente
 Phrenology (Gall) - skull morphology; advances due to:
Localization
Quantification
Standardization
Example morphological assessment
Phrenology
Trait approaches based on body types
 Sheldon’s body types (1950); Photos of incoming freshmen 1930s
Endomorph – jolly/happy, lazy (BMI is inversely corr. with suicide
rates, but only for men; “jolly & fat” Mukamal, 2007)
Mesomorph – dominant, athletic
Ectomorph – smart, shy
Based on physical stereotypes. Can stereotypes affect personality?
 Not theoretically derived; (cf. pelvic distance & hormonal
release during adolescence as it relates to masculine and
feminine traits; Schlegal, 1982).
Sheldon’s body morphology
The “success” of trait methods based
on morphology
 Barnum effect - broad and slightly positive statements;
Most non-standardized, unreliable, and non-validated
procedures rely on the Barnum effect
Stock statements - true in all circumstances
Fishing statements – general statements that can be interpreted
in many ways (“you’ve experienced a loss”)
 Research (Glick, 1985) suggests that people are more
likely to believe Barnum-type false feedback vs. real
personality FB
 Research (Wyman et al., 2008) suggests that people
can differentiate real from bogus personality
assessments, but they can’t differentiate real personality
readings from bogus astrological readings (likely due to
Barnum effect).
Traits emerging from linguistic
assessments
 Analysis of language (Allport)
Approx. 18,000 words describing human behavior (subsumed by
over 4,000 trait descriptors)
Lexical hypothesis: By examining the adjectives used to describe
human behavior we can determine:
What is the minimum number of groupings (factors) needed to
organize all of these adjectives, and
What are the best labels for these groupings (factors)
 Statistical approach to organizing the adjectives and traits
(Cattell)
Factor analysis used to reduce the data
e.g., Consider your lecture notes or a further summary of the
class and how they summarize all the material.
Number of factors, labels for them, and how they relate to one
another
Organizing traits
 From 450 B.C. to present
 Organizing structure for personality
 Eysenck’s three personality “factors” to describe all
relevant personality traits
1. extraversion/introversion -ARAS
2. neuroticism/emotional stability -limbic system
3. psychoticism (abnormal personality) /ego
strength (tolerate stress, reality focus)
* Only the 1st two factors apply to non-clinical
population
- Circumplex model (for the normal population)
The construction of personality factors from everyday
experiences (higher level factors are the least modifiable)
4. Type/Factor
Extraversion
Sociability
Going out
Impulsivity
Smiling
Smiled at Mary
yesterday
Waving
Smiled at person
seated next to you
Liveliness
3. Trait
2. Habitual
behavior
1. Individual
behavior
Putting trait theory to the test, part 1
 Are there measurable differences in neuroticism (emotional instability)
and what does this predict?
 Neuroticism:
Modestly higher in females and this differences is seen across cultures
N increases with age and peaks in late adolescence & declines throughout adulthood
SES is inversely related to N (high SES = lower N)
N predicts mental health outcomes like risk for major depression, personality disorders,
higher rates of cardio-vascular problems and mortality (regardless of cause)
 Peer rated traits are better predictors of mortality (your friends know how long you’ll
live!  Jackson et al., 2015). Likely due to the fact that multiple peers are used to
assess vs. only a single source for self-rated personality.
 High heritability (.6)




 Should we be treating neuroticism, given the fact that we can
successfully treat anxiety, which is a transient version of N? (Barlow et
al., 2013). Lowering susceptibilities?
Other ways of organizing traits
 Cattell’s 16 PFs
 The Big Five (Costa & McCrae, 1985)
Neuroticism - emotional stability/instability (highly heritable)
Extraversion - sensation seeking/pos. emotions (highly heritable)
Extraverts work better when experiencing stimulation; ARAS
Openness - to new experience (creativity)
Intellectually curious, more liberal views, more tolerant of diversity
Agreeableness - quality of interactions
More likely to engage in prosocial activity, altruism, cooperativeness, fewer
problems with mental health
Conscientiousness – responsibility, hard work, self-disciplined
More successful in work and school, predicts effort, fewer problems with
mental and physical health, are happier and live longer.
Big Five traits & everyday life
 NEO profile that best predicts school/work performance?
High C, N, and O (adaptive application of N)
 O is related to productivity as a function of the structure of the
setting (high O works best in less structured settings)
 Low C and low A generally predict poor productivity in a variety of
school and work-related settings
 High N is a general predictor for psychological problems
(depression, anxiety, etc.), and the more extreme the score, the
more likely the problems
 Costa & McCrae suggest that psychopathology is defined by
extreme scores on the NEO
Some research suggests that these traits are observed across
species such as dogs, chimps, & hyenas (Gosling & John, 1999)
Big Five & Culture & Lifespan
 Big Five Factors are generally replicated in other cultures and other
languages, even when data comes from peer ratings
 One exception is agreeableness is sometimes better explained as two
factors of humility and honesty (Ashton et al., 2004).
 High heritability for the big five factors, especially for neuroticism
and extraversion (approximately .6)
 Big Five factors increase in stability over the lifespan, and highest
for extraversion and conscientiousness & lowest for neuroticism
(Note: This does not match the heritability data)
 Cumulative continuity hypothesis: Continuity of personality is
strengthened as we get older because we have more choice over our
environments (and we pick environments that reinforce/strengthen
existing traits)
e.g., the extravert chooses environments that value extraverted
behavior
Putting trait theory to the test, part 2:
Can we alter traits (experiments)?
 Locus of Control (LOC; Rotter) – under the conscientiousness
factor
Internal - control over one’s own destiny
External - fatalistic, chance outcomes
 Most individuals are internal LOC in North America.
 This is more adaptive as well.
Survey research summary:
 Implications for school/work re: effort
 Relationships
 Health
- continued; Experimentally
manipulating control/predictability
 Glass & Singer 1972
 Uncontrollable and aversive noise and its effects on performance
Two conditions: one with “control button” and one without
Assessed persistence with anagrams, and performance in a
follow-up task
 Benefits reflected in sustained effortful behavior and outcomes
 None of the participants ever actually pushed the button, so there
were no differences in exposure to the loud aversive sounds
Emphasis is perceived rather than real control
 Ultimately, the researchers stopped hooking up the button (dummy
switch)
 What if the participants had tried to push the button?
 Higher cost for thinking you have control then realizing you don’t
vs. never thinking you had it (we rarely have the opportunity to
assess control beliefs in everyday life; that’s why perception is key)
- continued; Experimental research on
control
 Studies in old age homes (Langer, 1983; Rodin, 1986)
to assess the effects of predictability and control
3 conditions (control, predictability, neither)
equal time in all visits, and everyone does so within
regular visiting hours
predicted health and mortality within the next year
implications/applications?
Strengths/limitations of this study relative to Glass &
Singer (1972) and other survey studies?
 Similar research in work settings involving control over
how to do tasks; in prisons involving control over TV
programming, chair locations (Ruback et al., 1986;
Wener et al., 1987), health fears (Lecci & Cohen, 2007)
The person situation debate
 Mischel shock (Personality and Assessment; Mischel, 1968)
1. Traits account for only 9% of behavior (correlations of .30)
Personality vs. situation debate (data on school children in
different settings – predicting behaviors like lying)
2. Traits are just labels.
 Attempts to address the 1st critique with new measures, but more
difficult to counter the 2nd critique
 Modern personality inventories can go beyond 9% (see NEO-PI)
 * Problematic to predict a single instance of behavior from general
trends (S. Epstein), but we can predict behavioral tendencies
 Traits predict best in situations without clear “situational scripts.”
Situational strength: refers to the clarity of the situational script.
e.g., first date behavior vs. seventh date behavior
More specific traits also predict better
e.g., work LOC vs. relationship LOC
Supplementing the Big Five
 Act-frequency approach (Buss & Craik, 1983)
Identify actions that reflect the trait of interest
Rate the extent to which each represents the prototype for that
trait (prototypicality ratings)
 Personal goal assessment: An idiographic approach
The idiosyncratic expression of basic motives (hunger vs.
“truffles for the wedding”)
Traits in context (LOC vs. control over the relevant experiences
in your life; e.g., goal to “get married” or “get a degree”)
Gordon Allport (1930)
 Consider how traits and motivation (goals) each assess different
(unique) aspects of personality
 “Havings” and “Doings” of personality (Allport, 1930; Cantor, 1990)
stable features (traits) and more dynamic features (goals)
 Traits (havings) can reflect biological predispositions that may limit
the opportunities for what one can do.
 Goals can determine how their traits manifest in their actions (goals
are the doings of personality)
 Both predict behavior: Traits predict about 20% of university
grades and goals relating to both school and non-school activities
can account for an additional 10-20% (Little, Lecci, & Wadkinson,
1992)
Example assessments: Goal constructs
 From more fleeting/transient experiences to life long
pursuits
Current Concerns (Klinger, 1977)
Personal Projects Analysis (Little, 1983)
Personal Strivings (Emmons, 1986)
Life Tasks (Cantor, 1987)
Goal Systems Assessment Battery (Karoly &
Ruehlman, 1995)
 Intersection of motivational and cognitive perspectives;
“Hot Cognitions”
Illustration of the PPA approach
 PPA = Personal projects Analysis (Little, 1983)
 Adults average about 14 personal goals
 Content may be significant
e.g., Health goals for hypochondriacs
Most common goal across settings & populations: “lose weight”
5 factors used to interpret the PPA
 Meaningfulness (importance, enjoyment)
 Efficacy (progress, outcome, skills)
 Structure (control, initiation, time adequacy)
 Stress (stress, difficulty, challenge)
 Social Support (visibility, other’s view)
Meaning-Efficacy trade-off
 Molecular goals (time focused & concrete)
high efficacy but low meaningfulness
 Molar goals (broad, life long pursuits)
low efficacy but high meaningfulness
 Anxiety can be predicted from goals with high meaning & low efficacy
 Research on college students and their goals shows that depression is
marked by low efficacy & low meaningfulness (Lecci et al., 1994)
 Depression can also be marked by the failure to disengage (Kuhl,
1986) from unsuccessful projects - depression as “information”
Ipsative scoring for the PPA
 Ipsative scoring refers to comparisons within the individual (no
need for a norm group, though normative scoring can be done)
 Goals can be scored by comparing your own score at one time to
scores from obtained from another time
Only meaningful if scores can change (traits are supposed to be
stable, so any changes on the NEO are considered error in
measurement)
Your goals, however, can change.
 Goals can also be scored by comparing ratings across different
content domains (e.g., social vs. academic) – look at your scores
 Most clinical work and counseling interventions with goals adopt the
ipsative scoring procedures (goal of intervention can be perceived
changes in the goal system)
 Goals can also be scored normatively (see next slide)
Normative scoring for the PPA
academic vs leisure goals (skip this)
 Academic goals
Importance:
High = 10
Low = 5 or <
Enjoyment
High = 7 or >
Low = 2 or <
Stress
High = 9 or >
Low = 3 or <
Other’s view of importance
High = 10
Low = 4 or <
e.g.,
 Leisure goals
Importance:
High = 9 or >
Low = 4 or <
Enjoyment
High = 9 or >
Low = 6 or <
Stress
High = 5 or >
Low = 1 or <
Other’s view of importance
High = 8 or >
Low = 1 or <
Putting trait theory to the test, part 3
 Personality traits and mortality: 3 studies
Study 1: 1,812 males from one of the early MMPI samples (MMPI
assessed in adolescents); Trumbetta et al., 2010
By age 75, factors that predicted mortality were:
social introversion (higher scores are protective) and
psychopathic deviance/antisocial tendencies (hi scores = hji risk)
No control for demographic factors, health behaviors, health
Study 2: >4,000 middle-aged Vietnam era veterans tracked for 15
yrs; Weiss et al., 2013
Statistically controlled for demographics, health behaviors, and
premorbid physical and mental health (still a homogeneous sample)
Neuroticism, paranoia, and antisocial tendencies were risk factors
Study 3: 1,035 men & women in Scotland; Taylor et al., 2009
For men, O and C were protective. No sig effects for women.
* Neg emotion words in tweets predict heart disease mortality better
than demographics, SES & health factors (Eichstaedt et al., 2015)
Personality Measures
 NEO-PI-R (Costa & McCrae, 1992)
 NEO-FFI (Costa & McCrae, 1989)
 Complete for class
 The Big five Inventory
 Available on-line
 The HEXACO
 Big Five + 1 (honesty & humility instead of A)




Eysenck’s Personality Questionnaire (EPQ)
Cattell’s 16 PF
MBTI
See also various goal assessments
Self vs. Peer Ratings – include in class notes
 High degree of consistency between self ratings and the ratings of
others even after only a brief interaction
Almost as accurate as assessments from those who know you
very well
 How does social desirability effect ratings? Social constraints? The
short time period of the assessment?
 Which traits will show the greatest discrepancies?
 Do discrepancies necessarily reflect problems with the self-report?
Real differences between internal and external presentation may
be meaningful
 FUNDAMENTAL ATTRIBUTION ERROR
When evaluating others, people tend to attribute behavior to
traits
When evaluating our own behavior, we tend to attribute it to
the situation (Why? - baserates)
Descargar

Unconscious priming Klinger & Greenwald, 1995