Advanced Developmental - PowerPoint Presentation

Slide1

Advanced Developmental Psychology

PSY

620PSlide2

Bronfenbrenner

; ClennanSlide3

Adversity, support, & resilienceSocial equity theory & racial-ethnic achievement gapsSupportive family environments ameliorate the link between racial discrimination and epigenetic aging

Chen 1

College

completion predicts lower depression but higher metabolic syndrome among young

disadvantaged

minorities

Chen 2

Loosening the link between childhood poverty and adolescent smoking and obesity: The protective effects of social capital.

The resilience conundrumSlide4

Social Equity Theory and Racial-Ethnic Achievement GapsClark

McKown

2013

N. Sun-

SuslowSlide5

Introduction School readiness + academic achievement

Asian Americans > White Americans > Black and Latinos

(

Jencks & Phillips, 1998; Lee, 2002; Reardon & Galindo, 2009)

Black-White achievement gaps

Gap appears to grow over time

(

Farkas

, 2003; Fryer & Levitt, 2004, 2005; Phillips, Crouse, & Ralph, 1998

)

Influences SES, future jobs, health (Levin, 2009; Reardon & Robinson, 2007; Adler, Boyce, Chesney, & Cohen, 1994)What causes racial differences?Genetics (Jensen, 1969)SES and family (Brooks-Gunn, et al. 2003)Academic stereotypes (Steele & Aronson, 1995)Degree of match between home and school environment (Brice-Heath, 1983)

N. Sun-

SuslowSlide6

Social Equity Theory (SET)makes specific proposals about social processes that are relevant to understanding the achievement gap

offers casual explanatory framework to explain racial-ethnic achievement gap

generates specific, falsifiable hypotheses

N. Sun-

SuslowSlide7

Social Processes Transactions between individuals (verbal and nonverbal communication)

Communications between individuals and social settings

Communicates something of social consequence

(apart

from interpersonal interactions)

Civil rights poster

N. Sun-

SuslowSlide8

SET propositions : origins of racial-ethnic achievement gaps 2 classes of social processes influence racial-ethnic achievement gaps:

Direct influences

– social processes that support achievement.

Signal influences

– cues that communicate negative expectations about a child’s racial-ethnic group.

N. Sun-

SuslowSlide9

2 classes of social processes influence racial-ethnic achievement gaps:

Social

processes affecting achievement gap operate across a limited range of key developmental settings.

Relevant

settings change lawfully with age.

Signal influences

depend on children’s ability to detect cues of stereotyped expectation.

Increases during elementary grades.

N. Sun-

SuslowSlide10

Direct influencesSocial processes that promote academic achievement similarly for all children in all racial-ethnic groups. SES

 unequal distribution  gapSlide11

Direct Influences (parenting)SES accounts for some, but not all, of the Black-White test score gap among children. Maternal warmth and engagement accounted for much of the gap after SES was accounted for (Brooks-Gunn et al., 1996)Slide12

Direct influences (parenting)

HOME

WHITES

: “authoritative” parenting (high supportiveness

+ high demandingness)

 better academic, social, and emotional outcomes

(

Baumrind

& Black, 1967)

BLACKS

: Higher overall neighborhood distress + strict parenting = positive academic outcomes

(Baldwin et al., 1990)N. Sun-Suslow

optimal parenting for the development of academic outcomes may be different for children from different racial-ethnic

groups and in different contexts. Slide13

Direct Influences (School)High-quality instruction and positive student-teacher relationships are more available for White than Black students.

Between Schools:

Black students attend schools where instructional quality and teacher skills are, on average, lower (

Clotfelter

et al., 2004).

Within Schools

: Black students are assigned to less experienced teachers than White and Asian peers (

Lett

&

Burkam

, 2002).

N. Sun-SuslowSlide14

Direct Influences (Peers)Stigma associated with academic ambition and White culture can contribute to Black underachievement

(Austen-Smith & Fryer, 2005).

Black students are more likely than White peers to report withholding academic effort because of concern about how others might view them

(Ferguson 2008).

Some minority students value low-performing peers more than high-performing peers

(

Grahm

, 2001).

N. Sun-

SuslowSlide15

Direct Influence (neighborhood)Higher neighborhood cohesion, better students performed in school (Cook et al., 2002).

N. Sun-

SuslowSlide16

Signal Influences Social events that signal to members of negatively stereotyped groups that are devalued because of their group membership(

Inzlict

& Ben-

Zeev

, 2000).

N. Sun-

SuslowSlide17

Signal Influences (Routine signal events)Characterizing a test as diagnostic of natural ability

(

McKown

&

Strambler

, 2009)

Telling participants directly that members of their group routinely perform worse than other members of other

gouprs

(Aronson et al. 1999)

Teacher expectations

– expect more from Whites and Asians  better academic performance N. Sun-SuslowSlide18

Signal Influences and Interpretive SkillWhite teacher who is nervous interacting with Black student example.

Cultural stereotypes.

N. Sun-

SuslowSlide19

N. Sun-

Suslow

Hypothesized ratio of achievement

gap

due to direct & signal influencesSlide20

N. Sun-

Suslow

Hypothesized proportion of

gap

influenced

by different contextsSlide21

Brown, 2017Slide22

Social inequity and healthAfrican Americans vs. other racial groups

 aging-related diseases

 severity

 more serious health consequences

Developmental perspective:

“weathering” hypothesis:

Brown, 2017Slide23

Social inequity and healthBrown, 2017

Racial discrimination in African Americans

98% of African American adults

Stress, frustration, depression, and anxiety

Physiological health markers

Poor birth outcomes

Elevated glucocorticoids

Pro-inflammatory cytokines

C-reactive protein

A

nticipation

of discriminationSlide24

Stress-coping modelBrown, 2017

Individual differences in biological response to high levels of interpersonal discrimination

Stress-coping model

D

iscrimination depletes coping resources

Contextual supports may serve as protective factor

Supportive family environments

Low levels of conflict

Organized & predictable home environmentSlide25

AdolescenceBrown, 2017

African American youth become increasingly cognizant of systemic discrimination in adolescence

Heterogeneity of experience of interpersonal discrimination

Trajectory of exposure to discrimination as characterized by relevant literature:

Low

high

High  stable

High  high

Low  low

Low  stable Slide26

Present study hypothesesBrown, 2017

In African American youth, supportive family environments will reduce the likelihood of cellular aging

This effect will replicate across 2 independent samplesSlide27

MethodsBrown, 2017

SHAPE (Brody et al., 2013)

N = 322

138 men / 184

women

 poverty

46.3% below poverty line

 unemployment

AIM (Brody et al., 2012)

N=294

107 men / 187

women poverty40.2% below poverty lineSlide28

MethodsBrown, 2017

SHAPE (Brody et al., 2013)

16-18 years old

20 years old

AIM (Brody et al., 2012)

17-19 years old

22 years old

Racial discrimination, family environment

Antecubital blood samples (epigenetic aging)

Schedule of Racist Events (self-report)

Various measures of emotional support (Carver Support Scale; Family Support Inventory)

Parent-child conflict on Ineffective Arguing Inventory

Disorganization in home (Confusion, Hubbub, and Order Scale)Slide29

MethodsBrown, 2017

Cellular aging:

e

pigenetic biomarker from DNA methylation pattern of immune-system cells

Epigenetics:

modifications in DNA (e.g.,

methylation

) that do not involve changes in DNA sequence

Methylation as measure of cellular aging:

Epigenetic Aging IndexSlide30

MethodsBrown, 2017

Epigenetic aging (

Hannum

et

Predictive model of aging in immune cells

71 methylation values

Provides residuals along a continuum reflecting discrepancy between cellular and chronological age

al., 2013)Slide31

AnalysesBrown, 2017

Latent growth curve models: model growth of perceived racial discrimination over time

Latent growth mixture modeling (LGMM): identify distinct groups based on levels of exposure to racial discrimination

Linear regression

PBMC epigenetic aging on racial discrimination and family support

Interaction effects (discrimination x support)

Control variables: SES, gender, life stress, depression, BMISlide32

Racial discrimination trajectoriesBrown, 2017

LGMM

78.5%

65.6%Slide33

ResultsBrown, 2017

Regression analyses: SHAPE

1. Discrimination & support

2. + control variables

3. + interactionSlide34

ResultsBrown, 2017

Regression analyses: AIM

1. Discrimination & support

2. + control variables

3. + interactionSlide35

Interaction effectsBrown, 2017Slide36

DiscussionBrown, 2017

Hypotheses supported

Racial discrimination ~ epigenetic aging

Family environment support as protective factor

Parallels research on low SES and adult health problems, with maternal warmth as buffer (Chen et al., 2011)

*Emotion

regulation?

Next steps:

mechanisms

*Role of anger/

hostility?

*Adiposity?

*Gender?Slide37
Slide38

IntroductionEducation is the strongest predictor of long term health outcomes.

About a 10 year difference between those with and without college degrees

Even after controlling for SES, blacks and Hispanics still have poorer health outcomes compared to whites.

Patel/AltamiranoSlide39

Skin-deep resilienceAfrican Americans who are severely disadvantaged:High levels of self control  better mental health & school outcomes

However:

Comprised health

e.g. allostatic load,

cardiometabolic

risk, etc.

Do these findings generalize?

AltamiranoSlide40

AimUpward social mobility may have poor consequences for minorities Used Add Health data (National Longitudinal Study of Adolescent to Adult

Health)

Cohort from adolescence into adulthood

L

ongitudinal data set spanning 14 years

Are there racial disparities in mental and physical health benefits of a college degree?

PatelSlide41

MethodsMental health: DepressionSelf-report measure of depressive symptoms (CES-D)

Physical health: Metabolic Syndrome

Cluster of symptoms (e.g. high BP, cholesterol) common in midlife that predicts later diabetes, heart attack, stroke

Biomarkers: waste circumference, dx of hypertension, etc.

Disadvantage background

22 binary indicators (e.g., sin family household, welfare)

summed to make a standard score

Analysis focused on adolescence (12-18) and early adulthood (24-32)

n=13,009, depressive

sx

sample n=10,786, metabolic sx samplePatel/AltamiranoSlide42

Results: DepressionAcross race



completed college

 fewer depressive symptoms

Blacks: interaction with disadvantage. College is associated with even fewer depressive

sx

for those from more disadvantaged backgrounds (p<0.05).

Patel/ Altamirano

Depressive

sx

stratified by race, college completion,

disadvantage, in

adolescence.Slide43

Results: Metabolic SyndromeWhites

: College completion is protective. No matter how disadvantaged you were, a college degree means lower odds of MS

Blacks and Hispanics

:

Privileged



college is protective against MS

More disadvantaged

at adolescence

 odds of MS are higher than if you did not complete collegePatel/ AltamiranoLogistic regression to find predicted probability of metabolic syndrome. Slide44

ConclusionsDepression

College is good for everyone’s

mental

health

.

Metabolic Syndrome

Not everyone benefits uniformly

Minorities

from

more disadvantaged backgrounds

that

completed college have greater odds for physical health problems than those that did not complete collegeSocially mobile youth are “psychologically hardy” “…higher-status environment may differ…can lead to isolation and lack of social support.”New environment may be hostile, given discriminatory social structures Inds may “deploy strategies that are effective in alleviating mental strife but are harmful to physical health”PatelSlide45

Not a conclusion

U

pward

mobility is bad for youth

AltamiranoSlide46

DiscussionGeneral thoughts on article?Strengths/weaknesses

What about completing college?

Moving away from family and collectivism?

Major? Type of degree?

After college? Across life course? Do effects remain?

First generation college graduates?

Thoughts on depression as a measure for mental health?

What about Anxiety?

The article mentioned policy implications. Implications for clinical care or at-school interventions?

AltamiranoSlide47

Loosening the Link Between Childhood Poverty & Adolescent Smoking & Obesity:

Protective Effects of Social Capital

(Evans & Kutcher, 2010)

(Evans & Kutcher, 2010)Slide48

Background Information

What We Know

Pervasive, lifelong inequalities in physical health begin in childhood

Health risk factors reflect SES gradients: (1) Smoking, (2) Obesity

BUT,

not all low-SES youth smoke or develop food-energy imbalance

SOCIAL CAPITAL

= Multidimensional construct:

Community cohesion

Social control in the community

Social relationships between community members

Social capital has direct effects on well-being (psychological & physical)Slide49

Communities with rich social capital can loosen the link between

childhood

poverty &

adolescent

smoking and obesity

Protective effects of community youth resources will be most potent among individuals at greatest risk for unhealthy behaviors

HypothesisSlide50

Low-income households are more widely dispersed among middle- and upper-income areas in rural communities

Rural poverty is more prevalent & growing faster

Effect of childhood poverty on health risks will be weakened among low-income, rural youth living in communities with greater social capital

Individual and community-level risks and resources are highly collinear in urban settings

Tests of social capital in low-income

urban

populations may be insensitive

Why rural populations?Slide51
Slide52
Slide53

PARTICIPANTS

196 adolescents (

mean age

= 17.42)

Initially recruited at age 9

Male = Female

Rural counties in upstate New York

Income-to-Needs Ratio

: Federal per capita index comparing household income vs. estimated minimal expenditures

½ sample was ≤1 (below poverty line)

Average = 2.80

MethodsSlide54

Procedure

Smoking

Frequency of cigarette use: 0 (none) – 7 (more than once/day)

BMI

Height & weight measured by experimenter; BMI = Kg/m

2

 Growth Charts

Social Capital

Community Cohesion

Maternal rating of social ties & community interdependence

“People in this community share the same values

”

Social Control

Maternal rating of informal adult supervision & willingness to intervene

“One of my neighbors would do something if…”

Relationship with Adults

Youth ratings of supportive relationships with adults

“There are adults at my school I could talk with...”Slide55

Higher social capital attenuated smoking among youth from lower-income households

Figure 1.

Adolescent smoking frequency as a function of childhood income-to-needs ratio & community level of social capital, controlling for gender & community income level Slide56

Higher social capital attenuated income effects on BMI among youth from lower-income households

Figure 1.

Adolescent BMI as a function of childhood income-to-needs ratio & community level of social capital, controlling for gender & community income level Slide57

Results:

Additional Analyses

Additional covariates yielded

same pattern of results

:

Parental education

Maternal marital status

Maternal mental health

Residential relocation

Two other community resources (school quality & extracurricular activities)

did not moderate

income effects on health risk factors

Only social capital total index moderated the relationship (not separate domains)

Additional Findings

% Hispanic

% foreign born

% owner-occupied households

% high school grads

% college grads

% unemployedSlide58

SummaryAdolescents from low-income households smoke more and have greater BMI

Extends prior research findings from urban to rural

Impact of social capital

Policy perspectiveSlide59

Discussion QuestionsHow might the authors’ operationalization for social capital be improved? What additional factors should be accounted for?To what extent might racial differences explain the authors’ findings?

What about the sampling of communities?

How would you explain the “buffering effects” of social capital? Can you think of examples of how it might reduce smoking and obesity?

Do you feel these results would translate to other rural communities?

Do you think there is a time period in which social capital is most influential?

What would a social capital intervention look like?

What other variables could be moderating this relationship?Slide60

Results:

Additional Analyses

A

dditional covariates yielded

same pattern of results

:

Parental education

Maternal marital status

Maternal mental health

Residential relocation

2 other community resources (School quality & Extracurricular activities)

did not moderate

income effects on health risk factors

Only Social Capital total index moderated (not separate domains)

Protective Effects of Social Capital

(Evans &

Kutcher

, 2010)

% Hispanic

% foreign born

% owner-occupied households

% high school grads

% college grads

% unemployedSlide61

Moving Out of High-Risk Neighborhoods(Clampet-Lundquist et al., 2011)

Experimental study

Low-income residents in public housing located in extremely poor neighborhoods randomly assigned to receive vouchers to move to middle-class, low poverty neighborhoods (vs. voucher and no geographic restriction or no voucher)

Findings: Remained in lower poverty areas over time, improved educational and health outcomes for childrenSlide62

Some beneficial effects (for girls)Slide63

Moving Out of High-Risk Neighborhoods(Clampet-Lundquist et al., 2011)

In-depth interviews with subsample to explore processes underlying gender differences in treatment effects

Control vs. treatment “compliers”

Gender differences in

Where/how “hang out” with friends

Degree of acceptance in new neighborhood

Ability to navigate neighborhood environments

Effect of father figure

Interview themes:

Views and experiences of neighborhoods

Perceptions of relative social status

Experiences at schoolDaily routinesAdult and peer networksMental and physical healthSlide64

The problem of resilience….

A

multimodal approach to resiliency asks how individual, dyadic, and social factors contribute to developmental adaption within the context of adversity (

Luthar

et al., 2000; Sheinkopf et al., 2007)Slide65

Life-span perspective is necessaryDevelopment includes content of emotions and social relationships, as well as

capacities

Timing of experience will influence impact

Effects of neural structure/function

Psychological sensitivities and vulnerabilities emerging at that time (e.g., separation)

Non-normative times (e.g., teen pregnancy)

Biological perspective on intrinsic

and

experiential influences (e.g., puberty)Slide66

Key principles and concepts Continuities and discontinuities are to be expected

How are

change

and

levels

related?

Abnormal and normal development have dissimilarities

and

similarities (e.g., heavy drinking & schizophrenia)

Heterotypic and

homotypic

continuitiesHow are form and process related?Transitions occur during the course of development What transitions are important now?What factors of negotiation should we look at?Slide67

Key principles and concepts Individual differences in meaning of/response to transitionsRisk and protective factors (and their interactions; e.g., the great depression)

Importance of indirect as well as direct effects

Processes and mechanisms involved in indirect/direct effects

How

does self-esteem develop?

Age is an ambiguous variableSlide68

Possible Mediating Factors for C/DGenetics (e.g., autism)Altered biological development (e.g., pregnancy/birth complications



schiz

.)

Behavior/experiences in childhood shape environment experienced in adult life

Selection of environments and relationships

Elicitation of interactions with others

Elicitation of societal/cultural responsesSlide69

Psychosocial pathwaysSlide70

Focus on both risk and protective factors

Adolescent

planful

competence

predicts positive outcomes

occupational success

marital

successSlide71

Shyness: Mediating factors?Slide72

What are the mechanisms?Direct

and indirect effects on development

Idea of chains of events or cascading effectsSlide73

Identification of mechanisms promoting continuity (or discontinuity)Direct

and indirect effects on development

Idea of chains of events or cascading effectsSlide74

Mechanisms promoting continuity into adulthood = Mediating factorsGenetics

Altered biological development

Shaping of environment

Selection of environments and relationships

Elicitation of interactions with others

Elicitation of societal/cultural responsesSlide75

Beyond Childhood…..Development depends on a person’s interactions and transactions with many levels of environmentThese interactions continue throughout the lifespan Slide76

Development

Individual change over

time

Reorganizes

Multiple systems (entire person)

Successive, sequential

Crawl

before you

walk

Non-reversible (stable)

You

can’t go back

Normative

Everyone’s doing it --

but what if everyone’s not doing it?

Continued education (or earlier employment)

m

arriage, divorce, childrearing,

immigration

Continues over

lifespan?