Psychology

Research Article

The Role of Chaos in Poverty and Children’s Socioemotional Adjustment Gary W. Evans, Carrie Gonnella, Lyscha A. Marcynyszyn, Lauren Gentile, and Nicholas Salpekar

Cornell University

ABSTRACT—There are growing levels of chaos in the lives

of American children, youth, and families. Increasingly,

children grow up in households lacking in structure and

routine, inundated by background stimulation from noise

and crowding, and forced to contend with the frenetic pace

of modern life. Although widespread, chaos does not occur

randomly in the population. We document that low-income

adolescents face higher levels of chaos than their more af-

fluent counterparts and provide longitudinal evidence that

some of the adverse effects of poverty on socioemotional

adjustment are mediated by exposure to chaotic living

conditions.

There is widespread evidence of growing levels of chaos in

the lives of American children and youth (Bronfenbrenner,

McClelland, Wethington, Moen, & Ceci, 1996). The amount of

time parents can devote directly to their children is declining

precipitously as more hours are spent away from home, working,

commuting, and delivering children to and from child care,

school,andotheractivities;familiesarelesslikelytosharemeals

and otherritualstogetherasdomestic time becomes compressed;

more and more children live in crowded, noisy, and substandard

housing; and increasingly, family members characterize home

life as hectic, unstructured, unpredictable, and, at times, simply

out of control. Although such trends are ubiquitous, chaos is not

evenly distributed in the population. Low-income families are

more likely to face chaotic living conditions than are their mid-

dle- and upper-income counterparts. In this article, we bring

together two strands of thinking about risk factors in human de-

velopment to examine the role of chaos in poverty’s adverse im-

pacts on children’s socioemotional adjustment.

In the bioecological model of human development, Bronfen-

brenner (Bronfenbrenner & Evans, 2000) offers the following

proposition:

Throughout the life course, human development takes place

through processes of progressively more complex reciprocal in-

teractions between an active, evolving biopsychological human

organism and the persons, objects, and symbols in its immediate

externalenvironment.Tobeeffective,theinteractionmustoccuron

a fairly regular basis over extended periods of time. Such enduring

formsofinteractionintheimmediateenvironmentarereferredtoas

proximal processes. (p. 117)

Chaosmayinterferewiththedevelopmentandsustainabilityof

proximal processes because it shortens their duration and in-

creases interruptions, rendering exchanges of energy between

thedevelopingchildandherorhissurroundingslesspredictable.

Chaos may also lower the intensity of proximal processes, given

stress and fatigue in parents and other caregivers who must also

contend with chaos. Frenetic activity, lack of structure, and un-

predictability, in conjunction with intense background stimula-

tion, take their toll by depriving the developing organism of the

kinds of well-structured, predictable, and sustained exchanges

of energy with the persons, objects, and symbols in the immedi-

ate environment critical to fostering and sustaining healthy

development (Bronfenbrenner & Evans, 2000; Bronfenbrenner

& Morris, 1998).

Chaotic living conditions might also interfere with the devel-

opment of competency, the belief that one is an effective agent in

coping with one’s surroundings (White, 1959). Unpredictable,

nonroutine, inconsistent, and noncontingent physical and social

surroundings can interfere with a sense of mastery and lead to

helplessness in the developing person. Lack of routines and

structureandlargelyintractablestimulationmayalsoundermine

the child’s ability to self-regulate and manage his or her own

behaviors and emotions.

Address correspondence to Gary Evans, Departments of Design & Environmental Analysis and of Human Development, Cornell Uni- versity, Ithaca, NY 14853-4401; e-mail: [email protected].

PSYCHOLOGICAL SCIENCE

560 Volume 16—Number 7Copyright r 2005 American Psychological Society

Lack of routines, structure, and rituals in the home has been

shown tobe negatively associated withpsychological adjustment

in children and adolescents, parental competency ratings, sat-

isfaction with family, and school achievement (Fiese et al., 2002;

Repetti, Taylor, & Seeman, 2002). Noise, crowding, and poor

housing quality are positively associated with children’s psy-

chological distress (Evans, 2001; Evans, Wells, & Moch, 2003;

Wachs & Corapci, in press), as well as learned helplessness

(Cohen, 1980; Evans & Stecker, 2004).

POVERTY, CHAOS, AND SOCIOEMOTIONAL ADJUSTMENT

The immediate living environment of many low-income families

can be fairly characterized as chaotic, consisting of numerous

intractable and unpredictable conditions (Bronfenbrenner et al.,

1996; Evans, 2004; McLoyd, 1998; Repetti et al., 2002; Sher-

man, 1994; Taylor, Repetti, & Seeman, 1997). Low-income

children and youth face a bewildering array of suboptimal,

chaotic living conditions. Relative to their more affluent coun-

terparts, they reside inmorecrowded, noisier,and poorer-quality

housing (Evans, 2004; Saegert & Evans, 2003). Poor children

must also contend with less structure, routine, and predictability

in their daily home life (Brody & Flor, 1997; Jensen, James,

Boyce, & Hartnett, 1983; Matheny, Wachs, Ludwig, & Phillips,

1995). Thus, chaos is a plausible mechanism to account for the

adverse impacts of poverty on socioemotional adjustment.

Numerous studies have documented negative relations be-

tween household income and psychological distress in children

and adolescents (Bradley & Corwyn, 2002; Duncan & Brooks-

Gunn, 1997; Grant et al., 2003; Luthar, 1999; McLoyd, 1998).

Grant et al. found an average effect size of .22 for internalizing

symptoms and .17 for externalizing symptoms across 46 studies

of children and poverty. Cross-sectional and longitudinal results

converged. Moreover, the longer the duration of exposure to

poverty, particularly in early childhood, the greater the adverse

impact (Bradley & Corwyn, 2002; Duncan & Brooks-Gunn,

1997; Luthar, 1999; McLoyd, 1998).

Although no researchers have directly investigated poverty

and learned helplessness, a few have shown that lower socio-

economic status (SES) is associated with diminished mastery

beliefs in children (Bandura, Barbaranelli, Caprara, & Pastor-

elli, 2001; Battle & Rotter, 1963). Low-SES parents discourage

self-directedness in their children (Kohn, 1977) and are more

restrictive than high-SES parents (Luster, Rhoades, & Haas,

1989); these trends, in turn, lead to lower self-efficacy among

low-SES adolescents (Whitbeck et al., 1997).

Children’sself-regulatoryabilitymay beinfluencedbypoverty

as well. Studies have shown that income is positively associated

with maternal and teacher ratings of self-regulatory behavior

among 6- through 9-year-olds (Brody, Flor, & Morgan Gibson,

1999) and with delay of gratification among third through fifth

graders(Evans&English,2002).Moreover,Lengua(2003)found

that self-regulatory ability in third through fifth graders buffered

some of the ill effects of multiple risk exposure on psychological

distress.

Three studies provide more direct evidence that chaos may

account for some of the ill effects of poverty on children. In a

study of inner-city 8- to 12-year-olds, Kliewer and Kluger (1998)

discovered that children with regular and predictable house-

holdroutineswere buffered from theharmfuleffects ofhassles on

adjustment. Bresnahan and Blum (1972) studied concept for-

mation in low- and middle-SES 7-year-olds who were asked to

discover what combination of color and form was correct (e.g.,

triangle on green background). The children initially received

either 0, 6, or 12 trials of random feedback (acquisition phase)

and then received accurate, contingent feedback on each test

trial. When there was no initial random feedback, low-SES

children had a 15% error rate on test trials, and high-SES chil-

dren had a 5% error rate. However, when noncontingent, random

feedback (6 or 12 trials) was given during the acquisition phase,

low- and high-SES children had the same error rate, 15%, at test.

In a third investigation, parenting practices (a latent construct

including mother-child harmony, maternal involvement in

school, and maintenance of household routines) significantly

mediated the effects of poverty on cognitive and emotional

competency (Brodyetal., 1999).These three studies suggestthat

chaos could convey some of the harm associated with childhood

poverty.

SUMMARYAND HYPOTHESES

There are growing levels of chaos in the lives of many children.

Chaos, however, is not randomly distributed in the population.

Low-income households experience a disproportionate share of

chaotic living environments characterized by high levels of am-

bient stimulation (e.g., noise, crowding), minimal structure and

routine,andconsiderableunpredictabilityandconfusionindaily

activities. Such conditions have been linked to psychological

distress in the developing person. Furthermore, poverty is neg-

atively associated with good adjustment in children.

Thus, we hypothesized that compared with middle-income

adolescents, low-income adolescents experience greater chaos

and manifest more socioemotional distress. Moreover, we hy-

pothesized that exposure to chaos accounts for some of the

elevation in socioemotional distress among lower-income ado-

lescents. To assess these two hypotheses, we incorporated mul-

tiple indicators of socioemotional distress into a longitudinal

study.

METHOD

Participants

Three hundredthirty-ninechildrenparticipatedinWave1ofthis

study when they were in Grades 3 through 5 (M 5 9.2 years, 51%

male). Three to 4 years later, 223 of these same children were

Volume 16—Number 7 561

G.W. Evans et al.

reevaluated(Wave2)whentheywereinGrades7and8(M513.1

years, 52% male). All of the families in the sample lived in rural

areas in upstate New York. They were recruited from public

schools, New York State Co-Operative Extension programs, and

variousantipovertyprograms(refusalrateinWave1waslessthan

5%).Low-income families were oversampled (53%) because this

research program focuses on rural poverty. The mean income-to-

needs ratio was1.66atWave1and2.34atWave2.Thisratioisan

annually adjusted, per capita index, comparing household in-

come with federal estimates of minimally required expenditures

for maintaining a household. Only one child per household par-

ticipated in the study. The sample was predominantly White

(94%), reflecting the demographics of rural upstate New York.

The mean income-to-needs ratio at Wave 1 was 1.81 for chil-

drenwhoremainedinthesampleatWave2and1.41forthosewho

did not participate in the second wave, t(338) 5 3.24, p < .01.

ChildrenwholeftthesamplebythetimeofWave2datacollection

were disproportionately from low-income families. None of the

outcome measures, however, were related to attrition.

Procedure

All data were collected with a standardized protocol in partici-

pants’ residences (see Evans, 2003, for more details).

Chaos

Chaos was assessed with a standard scale that possesses excel-

lent reliability and converges with independent ratings of noise,

crowding, foot traffic, and confusion in the home (Matheny et al.,

1995). We added items to increase coverage of routines and rit-

uals in the home (a for revised chaos scale 5 .77). These addi- tional items came from the Family Ritual Questionnaire (Fiese &

Kline, 1993) and the Family Routines Inventory (Jensen et al.,

1983). For this measure of chaos, the mother answered ‘‘true’’ or

‘‘false’’ to statements describing environmental stimulation

(‘‘Youcan’thearyourselfthinkinourhome’’),confusion(‘‘Wecan

usuallyfindthingswhenweneedthem’’),andritualsandroutines

(‘‘[Target child] does his[her] homework at the same time each

day’’). Chaos, unlike all other measures we report here, was as-

sessed only at Wave 2.

Learned Helplessness

In Wave 2, learned helplessness was evaluated with a standard

behavioral protocol (Glass & Singer, 1972) adapted for children

(Bullinger,Hygge,Evans,Meis,&vanMackensen,1999;Cohen,

Evans,Stokols,&Krantz,1986).Thechildwasshownapictureof

a tangram and instructed to reproduce the illustration with

multiple plastic pieces that fit into a rectangular frame. The child

could work on the puzzle until it was solved or until he or she felt

unabletosolveit.Atthatpoint,thechildcouldmoveontoanother

tangrampuzzle.Oncethechildmovedontothesecondpuzzle,he

or she could not return to the first puzzle. The child received the

first test puzzle after the experimenter ensured that he or she

comprehended the task. Unbeknownst to the child, this first

problem was unsolvable. The second puzzle was solvable. A total

of 15 min was available for the two test puzzles. The number of

seconds the child persisted on the first puzzle was the index of

learned helplessness. This learned-helplessness measure is re-

lated to beliefs about personal control, experimental manipula-

tions of control, and chronic exposure to uncontrollable stressors

(Cohen, 1980; Cohen et al., 1986; Evans & Stecker, 2004; Glass

&Singer,1972).LearnedhelplessnesswasassessedinWave1by

giving children 10 min to draw linkages between familiar pic-

tures without doubling back or lifting their pencil. Time spent

working on the first problem, which could not be solved, was the

measure of learned helplessness. Children were also given a

second, solvable problem to work on (Evans, 2003).

Psychological Distress

Psychological distress was measured in Wave 1 using the Rutter

Child Behavior Questionnaire (Rutter, Tizzard, & Whitmore,

1970) and in Wave 2 using the Youth Self Report instrument. The

Youth Self Report has excellent reliability and has undergone

extensive validation across a wide range of samples, 11 through

18 years of age (Achenbach, 1991). On a scale from 0 (not true) to

2 (very true or often true), participants answer whether symptoms

describethem.Thesesymptomsinclude‘‘Ifeellonely,’’ ‘‘Iworrya

lot,’’ and ‘‘I get in many fights.’’ We combined internalization and

externalization symptoms into one scale because the overall

scale was reliable (a 5 .93), the two subscales were intercorre- lated (r 5 .70), and the Rutter Child Behavior Questionnaire

combines both types of symptoms.

Self-Regulatory Behavior

For Wave 1, a behavioral measure of delayed gratification was

used to assess self-regulatory behavior (Evans, 2003). Self-reg-

ulation was assessed in Wave 2 with the Children’s Self-Control

Scale (Humphrey, 1982). The children’s English teachers rated

their behaviors on a 5-point rating scale (from never through al-

most always true). Examplesof itemson this scale are ‘‘This child

thinksaheadoftimeabouttheconsequencesofhisorheractions’’

and ‘‘This child sticks to what he or she is doing, even on long,

unpleasant tasks, until finished.’’ The scale has excellent relia-

bility (a 5 .91 in the present study) and has been validated against multiple criteria (Humphrey, 1982).

RESULTS

Cross-Sectional and Longitudinal Analyses

Longitudinal analyses regressed socioemotional outcomes onto

income-to-needs ratios at Wave 2 (Grades 7–8), controlling for

the respective Wave 1 (Grades 3–5) outcome. In addition to these

longitudinal results, we report cross-sectional data from Wave 1.

For descriptive purposes, Table 1 reports means and standard

errors for the Wave 2 sample split into poverty and middle-in-

562 Volume 16—Number 7

Chaos and Children’s Socioemotional Adjustment

come groups. However, all inferential analyses maintained the

continuous nature of the income-to-needs variable.

Income predicted learned helplessness among the middle

school youth when learned helplessness at Wave 1 was statisti-

cally controlled, b 5 31.03, t(219) 5 2.33, p < .02, f 2 5 .02.

These longitudinal findings replicate the cross-sectional asso-

ciation between income-to-needs ratio and learned helplessness

at Wave 1, b 5 22.91, t(276) 5 2.35, p < .02, f 2 5 .03.

The youths’ self-report of psychological distress was signifi-

cantly affected by income, statistically controlling for Wave I

distress, b 5 �0.86, t(220) 5 2.50, p < .01, f 2 5 .03. At Wave 1, income-to-needs ratio was also significantly related to psycho-

logical distress, b 5 �1.99, t(337) 5 6.55, p < .01, f 2 5 .14. Teachers’ ratings of self-regulatory behavior were also signif-

icantly related to income when Wave 1 self-regulatory behavior

was controlled statistically, b 5 1.14, t(120) 5 2.70, p < .01,

f 2 5 .05.

1 There was also a significant relation between income

and self-regulatory behavior at Wave 1, b 5 112.35, t(199) 5

3.41, p < .01, f 2 5 .07.

Chaos as a Mediator of the Relation Between Poverty and

Socioemotional Development

In order to examine whether each of the longitudinal effects of

income-to-needs ratio on socioemotional development was me-

diated by chaos, we conducted a series of hierarchical regression

equations. As shown in Table 2, the first equation regressed

learnedhelplessnessontoincome-to-needsratioatWave2.(Note

that in all the analyses reported in Tables 2 through 4, the re-

spective Wave 1 outcome measure was included as a statistical

control.)ThesecondlineofTable2showstheresultsofregressing

learned helplessness onto chaos, the hypothetical mediator, and

thethirdlineshowstheresultsofregressinglearnedhelplessness

onto income-to-needs ratio after controlling for chaos. Of par-

ticularinteresttothemediationalhypothesisisthechangeinDR2

from row 1 (DR2 5 .02) to row 3 (DR2 5 .01). The significant DR2

for income-to-needs ratio in row 1 becomes statistically nonsig-

nificant in row 3, after chaos is partialed out. Note also the 26%

shrinkage in the beta weight ( p < .05) for income-to-needs ratio

after chaos waspartialedout(row 1:b 531.03,row3:b522.88).

Thus, the significant effect of income on learned helplessness

was attenuated once chaos was controlled for. Income levels

were significantly related to chaos, b 5 �0.85, t(223) 5 4.65, p < .0001.

Table 3 depicts the parallel set of hierarchical regression

equations for psychological distress. As in the analysis for

learned helplessness, the statistically significant, longitudinal

effect of income-to-needs ratio on psychological distress be-

came nonsignificant, and the beta weight shrank significantly

( p < .05), after chaos was partialedout.The longitudinalrelation

between income and psychological distress was mediated

by chaos.

The results for teachers’ ratings of self-regulatory behavior

(Table 4) are similar. The statistically significant longitudinal

effect of income on self-regulatory behaviors was significantly

attenuated ( p < .01) when chaos was partialed out.

DISCUSSION

A healthy childhood environment requires regularity, consis-

tency, predictability, and controllability. In order for proximal

TABLE 1

Chaos, Learned Helplessness, Psychological Distress, and Self-

Regulatory Behavior in Relation to Poverty at Wave 2

Measure

Group

Poverty Middle-income

M SE M SE

Chaos (22–44) 29.56 0.63 27.46 0.27

Helplessness (persistence

in seconds) 443.34 24.28 547.23 22.84

Psychological distress

(0–114) 15.28 0.86 12.37 0.56

Teacher ratings of self-regulatory

behavior (8–40) 28.51 0.67 29.85 0.64

Note. In this table, the sample is divided into a poverty group (income-to-needs ratio � 1.0) and a middle-income group (income-to-needs ratio > 1.0) for de- scriptive purposes only. All inferential analyses maintained the continuous nature of the income-to-needs variable.

TABLE 2

Longitudinal Mediational Analysis of Learned Helplessness and

Income-to-Needs Ratio at Wave 2, Statistically Controlling for

Wave 1 Learned Helplessness

Predictor Total R 2 DR2 FDR2 b (SE)

Income-to-needs ratio .04n .02n 5.42n 31.03n (13.32)

Chaos .04nn .03nn 6.92nn �12.27nn (4.66) Income-to-needs ratio

controlling for chaos .05nn .01 2.72 22.88 (13.86)

np < .05. nnp < .01.

TABLE 3

Longitudinal Mediational Analysis of Psychological Distress and

Income-to-Needs Ratio at Wave 2, Statistically Controlling for

Wave 1 Psychological Distress

Predictor Total R 2 DR2 FDR2 b (SE)

Income-to-needs ratio .14nn .03n 6.27nn �0.86nn (0.35) Chaos .16nn .05nn 13.46nn 0.44nn (0.12)

Income-to-needs ratio

controlling for chaos .18nn .01 3.24 �0.63 (0.35) np < .05. nnp < .01.

1 The sample size is much smaller for self-regulatory behaviors at Wave 2 than

for the other outcome measures because we were dependent on the cooperation of teachers to provide this information.

Volume 16—Number 7 563

G.W. Evans et al.

processes to be effective, they need to occur in a predictable

manner, with some intensity over time, and with minimal inter-

ruption (Bronfenbrenner & Evans, 2000; Bronfenbrenner &

Morris, 1998). The immediate surroundings of low-income ado-

lescents are more chaotic, consisting of noisier, more crowded,

more frenetic, and less structured and predictable routines of

dailyliving,thanarethehouseholdsofwealthieradolescents(see

Table 1). Moreover, these chaotic conditions convey some of the

adverse, longitudinal effects of poverty on children’s socioemo-

tional development (Tables 2–4). The longitudinal research de-

sign of this study, coupled with the cross-sectional replications

plus multiple measures of socioemotional adjustment, lend

confidence to these conclusions.

Study Limitations

More low-income children than middle-income children left the

sample between the first and second waves. Although none of the

socioemotional outcomes showed selective attrition, concerns

remain. For example, perhaps selective attrition biased our re-

sultsbecausefamilieswhomovedorcouldnotbecontactedagain

dealt with more chaos than those who remained in the sample. A

related drawback is the absence of a chaos measure in Wave 1.

Because we learned of the chaos index following Wave 1, we

could not examine whether greater chaos was associated with an

increased likelihood of dropping out of the sample. The absence

ofaWave1chaosmeasurealsoprecludedourexaminingwhether

changes in chaos over time explain changes in the outcome

measures, which would have provided a more rigorous media-

tional test. Furthermore, although it is valuable to study rural

poverty given researchers’ nearly exclusive focus on inner-city

deprivation, there may be critical aspects of inner-city chaos not

captured in this study.

Poverty, Self-Regulatory Behavior, and Learned

Helplessness

In addition to showing that poverty is directly related to chaos,

which, in turn, conveys some of poverty’s impact on socioemo-

tional development, the present study broadens the literature on

chaos. Prior studies have relied primarily on self-reported out-

comes, whereas we included a behavioral measure and teachers’

ratings. Also, this is the only longitudinal study of household

chaos and children’s well-being (Fiese et al., 2002; Repetti et al.,

2002; Wachs & Corapci, in press). Furthermore, we have

broadened the measurement of chaos by employing a multidi-

mensionalindexthatincorporatesassessmentofnoise,crowding,

confusion, and lack of structure and routinesin the households of

children and youth.

The learned-helplessness and poverty data are also notewor-

thy, given prior work showing negative associations between

parentalSES and children’scontrol beliefs (Bandura etal.,2001;

Battle & Rotter, 1963), as well as parenting practices that en-

courage self-directedness (Kohn, 1977; Luster et al., 1989). We

build on this literature in two respects. First, our findings are

longitudinal, and second, we demonstrate a link between poverty

and an overt, behavioral index of learned helplessness rather

than strictly subjective ratings. The present findings are also

noteworthy in light of previous research showing that exposure to

uncontrollableenvironmentalstressorssuchasnoiseorcrowding

induces learned helplessness in humans (Cohen, 1980; Evans &

Stecker, 2004).

Thereiswidespreadevidenceofchaosanddisarrayinthelives

of contemporary American children and youth, particularly

among economically disadvantaged families. Levels of chaos are

accelerating and pushing beyond the confines of poverty into

middle- and upper-income families. Scholars and policymakers

alike need to attend to these trends and contemplate their im-

plications for future generations.

Acknowledgments—We are grateful to the families and chil-

dren who have participated in our research. This work has ben-

efited enormously from the sage counsel of Urie Bronfenbrenner.

WethankJana Cooperman, Kim English, Missy Globerman, Tina

Merrilees,ChanelleRichards,AdamRokhsar,andAmySchreier

for assistance with data collection. Cindy Hazan, Steve Lepore,

andLorraineMaxwellprovidedcriticalfeedbackonearlierdrafts

ofthisarticle.PartialsupportforthisresearchcamefromtheW.T.

Grant Foundation, the John D. and Catherine T. Mac Arthur

Foundation Network on Socioeconomic Status and Health, the

National Institute of Child Health and Human Development (1

F33 HD08473-01), the National Institute of Mental Health (1

F31 MH68089-01A1), and the Cornell University Agricultural

Experiment Station (Project Nos. NYC 327404, 327407).

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Longitudinal Mediational Analysis of Self-Regulatory Behavior

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