Bio-behavioral Resilience: Examining Protective Factors forChild Psychopathology

Angela Zamora1, Donna Hockey1, Kathryn Lemery-Chalfant1, & H. Hill Goldsmith2

1Department of Psychology, Arizona State University, Tempe 2Department of Psychology, University of Wisconsin-Madison

Our sample consisted of 120 monozygotic and dizygotic twin pairs who were between the ages of 5 and 11 (M = 8.1 years) and participated in the Wisconsin Twin Project.

The present study included twin pairs where at least one twin was diagnosed with an internalizing or externalizing disorder using DSM-IV criteria.

Procedure A novel coding system of resilient measures was created by

observing children’s behavior while participating in various tasks during a videotaped four hour home visit.

Two research assistants were trained on the observational coding system, and reached high inter-coder reliability (Kappa > .70).

Using principal component analysis with varimax rotation, 5 factors summarized the observational data and reduced the overall number of variables (see Table 1 for description of measures).

Method

Analysis Plan 2 hierarchical regressions were performed to explore which

resilience variables uniquely predict psychopathology symptoms while controlling for risk variables.

1 multinomial logistic regression was performed to test whether the resilience variables predict psychopathology diagnosis.

Variables that were significantly correlated or approached significance with internalizing or externalizing symptoms were included in the regression models.

Our hypothesis was partially confirmed such that children with higher levels of emotion regulation were less likely to have internalizing and externalizing symptoms, and children with higher levels of positive affect were less likely to have internalizing symptoms after controlling for risk variables. The proportion of the variance (11% and 46%) explained uniquely by the established resilience predictors was significant.

Furthermore, children who were more creative were less likely to have internalizing symptoms after controlling for all risk and resilience variables. The proportion of the variance (3%) explained uniquely by the predictor, creativity, was significant.

Contrary to our hypothesis, none of the hypothesized observed resilience variables predicted externalizing symptoms.

Results

Resilience factors may protect at risk children, especially from anxiety-related symptoms and disorders. Our analyses replicated previous findings that emotion regulation and intelligence protected children from externalizing or comorbid behaviors. However, both emotion regulation and

intelligence were not associated with internalizing behaviors, suggesting that there are different processes going on for children with externalizing vs. internalizing. Exploration of hypothesized observed resilience factors showed that creativity was a strong and consistent predictor for internalizing disorder, and a trend appeared for options thinking.

By teaching children resilience thinking (e.g., how to find alternative solutions to a problem), how to play in a creative way, and how to manage and cope with undesirable events may lower symptoms and diagnosis of internalizing disorders.

Notably, findings indicate the behaviorally coded resilience factors (e.g., creativity, options thinking, see Table 1) were not associated with externalizing disorders, which could be attributed to the fact that they were tapping internal thought processes. Creativity is imagining outside of reality, and options thinking is the process of assessing different outcomes when given one choice.

By better understanding resilience factors, parents, teachers, and practitioners may be able to teach children strategies that may help them live up to their potential and protect them from developing psychopathology.Limitations of Study

The assumption of subject independence is a limitation of the study due to the sample including twins. Direction of effects could not be assessed given the correlational nature of the study. The bio-behavioral observed resilience measures had low variability given coder responses were typically yes / no. Low measurement variability could partly explain why effects were not

found for the other three resilient measures (i.e., adaptability, expression of feelings, and decisiveness).

Discussion & Conclusion

Some children develop psychopathologies such as depression (1-2%, Costellow et al., 1996), anxiety (10%, Shafer et al., 1996), conduct disorder, and attention deficit hyperactivity disorder (ADHD; 2-9%, AACAP, 1997) that decrease their ability to accomplish their goals and lead productive lives.

Many of these children may develop clinical depression, anxiety, or other psychopathology in adulthood that may result in a lower quality of life for them and their families (Harrington, Fudge, Rutter, Pickles, & Hill, 1990).

Emotional and behavioral problems can be classified in two categories:

Internalizing = over-controlled behaviors such as anxiety and depression.

Externalizing = overt behaviors such as aggression and delinquency (Achenbach & Edelbrock, 1978).

Much research has been conducted on identifying risk factors that predict child problem behaviors or psychopathology, but less research has investigated and defined resilience factors. Masten and colleagues (1990) defined resilience as:

“the process of, the capacity for, or outcome of successful adaptation despite challenging or threatening

circumstances.” (p. 426).

In order to gain a deeper understanding of the developmental process of child psychopathology, protective factors and resilience need to be examined as possible contributors to etiology.

Introduction

Children with higher resilience (e.g., creativity, options thinking, emotion regulation, positive affect) will be less likely to have symptoms and diagnosis of internalizing and externalizing disorders.

Hypothesis

The present study examined the relationship among internalizing and externalizing behaviors with established resilience factors, (e.g., IQ, positive affect, and emotion regulation) with eight year old children.

Additionally, we attempted to identify new resilient factors such as adaptability, options thinking, creativity, expression of feelings, and decisiveness (see Table 1), which have been infrequently investigated in the resilience literature.

Purpose of Study

Resilience Factors

Definition Task Measure

Creativity Ability to

Imagine

beyond what

is there

1. Playdoh (Twins must share playdoh and playdoh machine)

2. Snacktime (Twins must choose one cookie and one juice to share)

3. Freethrow (Child given 3 balls to throw in cups for a prize, but task is impossible)

While waiting, child’s creativity is measured.

e.g., child pretends the playdoh is a snake

Options Thinking

Ability to see

other

possible

solutions

1. Picture Ripping

(Child shown experimenter’s favorite photo and asked to rip it up)

Does child rip photo immediately or think of other options.

e.g., child is asked to rip experimenter’s favorite photo, instead of complying with request fully, child makes a very small tear at corner of photo

Adaptability Ability to

change with

circumstances

1. Wrong Prize

(Child receives the wrong prize from his previously rated choice)

Does child play with the wrong prize, and if so, does he/she enjoy it.

e.g., child may be disappointed about getting a prize that he/she did not pick, but the child adjusts to the situation and plays with toy

Expression

of Feelings

Ability to

express one's

feelings to

another person

1. Candy

(Experimenter divides candy evenly, but then gives herself all the candy in the end)

2. Wrong Prize

3. Picture Ripping

Child expresses his/her emotions

e.g., after seeing the experimenter take her candy, child tells the experimenter that it is ‘not fair’ and explains why

Decisiveness Ability to make

decisions easily

when no risk is

involved

1. Free Throw

2. Rated Prize

(After receiving a wrong prize, the child gets to pick a prize again)

Latency measure: number of seconds to choose a prize

Table 1: Resilience Factors Coded From Observed Behavior

Variables Assessments Description of Measure

SES A composite of family income, mother’s and father’s education.

Family conflict Family Conflict Scale

A 10 item measure was used to assess how often marital hostility was expressed in front of the child (Porter & O’Leary, 1980).

Controlling mother Child-rearing Practices Report (CRPR)

A 91 item measure was used to assess mother and father’s report on which parenting methods and ideals are most important to them (Block, 1965). This report was used to assess maternal and paternal warmth and control. For example, “I believe that children should be seen and not heard” were rated on a scale ranging from 1-6.

Warm father

Intelligence

PPVT

Block Design

The Peabody Picture Vocabulary Test (PPVT-R; Dunn & Dunn, 1997), a short test of vocabulary, was administered as a measure of receptive language maturity. The dependent measure used was an age-based standard score. The Block Design, a subtest of the Weschler Intelligence Scale for Children, version three (WISC-III; Weschler, 1991), was administered as a measure of spatial ability and correlated strongly with the performance IQ component of the WISC. Each child was tested separately in the home. The dependent measure used was the final sum score. A composite of the PPVT-R and Block Design was formed.

Positive affect Child Behavior Questionnaire (CBQ)

The CBQ is a parent-report measure of temperament for children from three to eight years of age (Rothbart et al., 2001). Parents rated the child’s behavior over the past six months on a 7-point Likert scale ranging from “extremely untrue of your child” to “extremely true of your child”. Both mothers and fathers completed the CBQ. For the purpose of this study, a composite of mother and father report on child’s Smiling and Laughter was formed.

Emotion regulation Bayley Rating Scale- revised (BRS) and CBQ

A composite of BRS observed regulation, CBQ mother and father reports on child’s Attentional Focusing and Inhibitory Control was formed. The revised BRS (Bayley, 1993) provided an observer report measure of state regulation reported by two trained experimenters who conducted the home visit.

Internalizing and Externalizing Disorder (dependent variables)

Diagnositc Interview Schedule for Children Version IV (DISC-IV)

Primary caregivers completed the computerized version of the NIMH DISC-IV (add reference), that is a structured psychiatric interview for children six and older. For the purpose of the study, internalizing and externalizing symptom composites were created, as well as presence of a diagnosis.

Table 3Summary of Hierarchical Regression Analyses Predicting Child Internalizing and Externalizing Symptoms in 8 Year Olds (N = 240)_________________________________________________________________________________________________________________________________________________________________________________________

Internalizing symptoms Externalizing symptoms_____________________ ____________________

Predictors B SE B β B SE B β____________________________________________________________________________________________Step 1: Risk variables SES -2.04 0.84 -0.16* -0.31 0.74 -0.03 Family conflict 2.47 1.20 0.13* 2.18 1.04 0.14* Controlling mother 0.98 1.05 0.06 1.55 0.93 0.11† Warm father -3.07 1.57 -0.12† -3.05 1.37 -0.14*R2 for Step 1 0.07** 0.05*

Step 2: Established resilience variables Intelligence -0.36 0.76 -0.03 -0.54 0.51 -0.05 Positive affect -1.51 0.74 -0.13* -0.13 0.49 -0.01 Emotion regulation -4.10 0.85 -0.30*** -8.12 0.57 -0.69***ΔR2 for Step 2 0.11*** 0.47***

Step 3: Hypothesized resilience factor Creativity -1.77 0.60 -0.17** 0.16 0.41 0.02ΔR2 for Step 3 0.03** 0.00

FModel 7.66*** 31.10***____________________________________________________________________________________________†p < .10. *p < .05. **p < .01. ***p < .001.

The overall multinomial logistic regression model for the full sample was significant, 2 (15, N = 240) = 106.36, p < .001.

The likelihood ratio tests on the individual variables revealed that creativity, emotion regulation, and intelligence were significant predictors of childhood psychopathology diagnosis.

The odds ratio (OR) is the ratio of the odds that an outcome will be a diagnosis to the odds of no diagnosis meaning an OR less than 1.00 indicates reduced odds for diagnosis, and an OR greater than 1.00 indicates increase odds of having diagnosis.

The odds for having internalizing diagnosis was reduced when children were more creative and displayed greater ability to think of other options during at home tasks.

The odds of having an externalizing diagnosis was reduced when children had greater ability to regulate their emotions.

The odds of having comorbid diagnoses was reduced when children had higher intelligence and when they were able to regulate their emotions.Table 2: Risk and Resilience Measures

Results

Table 4Summary of Multinomial Logistic Regression Analysis Predicting Child Psychopathology Diagnosis in 8 Year Olds (N = 240) ________________________________________________________________________________________

Likelihood of Diagnosis Relative to No Diagnosis

Internalizing Externalizing Comorbid ________________ ________________ _________________

Predictors Odds ratio 95% CI Odds ratio 95% CI Odds ratio 95% CI ________________________________________________________________________________________

Intelligence 1.04 0.69-1.57 0.68 0.41-1.16 0.43** 0.24-0.79

Positive affect 1.10 0.74-1.62 1.49† 0.91-2.44 1.36 0.77-2.37

Emotion regulation 0.75 0.43-1.30 0.11*** 0.05-0.22 0.09*** 0.04-0.20

Creativity 0.59** 0.41-0.85 0.84 0.56-1.23 0.83 0.52-1.31

Options Thinking 0.73† 0.52-1.01 0.94 0.63-1.41 0.85 0.53-1.37

Subsample N 81 57 35________________________________________________________________________________________†p < .10. *p < .05. **p < .01. ***p < .001.Note: Reference group is children with no disorders. The risk variables did not significantly predict psychopathology diagnosis, so they were removed from the final model.