Child and Family Factors that Ameliorate Risk between 4 and 13 Years of Age RONALD SEIFER, PH.D., ARNOLD J. SAMEROFF, PH.D., CLARA P. BALDWIN, PH.D., AND ALFRED BALDWIN, PH.D.

Abstract. Protective processes in at-risk children between 4 and 13 years of age were examined in a longitudinal study. A multiple risk index was used at 4 years to identify 50 high-risk children and 102 who were at low risk. Cognitive and social-emotional status were measured at each time point. The following indicators of protective processes were related to positive change in cognitive and/or social-emotional function in the high-risk children between 4 and 13 years: mother-child interaction; child perceived competence, locus of control, life events, and social support; and maternal parenting values, social support, depression, and expressed emotion. Many of these factors were also related to improvement in the low-risk children. Some variables showed an interaction effect, where impact was substantially higher in the high-risk group compared with the low-risk group. The utility of multiple risk constructs and process oriented approaches to protective factors are discussed. J. Am. Acad. Child Adolesc. Psychiatry, 1992,31,5:893-903. Key Words: high risk, protective factors, personality dispositions, social support, family cohesion. Children at risk for behavioral, adjustment, and psychiatric problems represent a large portion of contemporary youth. Identifying the factors that might protect these children against the deleterious effects of risk is of great practical importance (Luthar and Zigler, 1991; Rolf et al., 1990). The cumulative effects of multiple risks (including parental psychopathology, low socioeconomic status, minority status, large family size, many life events, father absence, maternal anxiety, and rigid parenting) have been demonstrated to have serious impact of cognitive and social-emotional outcomes in children (Sameroff et aI., 1987a; Werner and Smith, 1982). This paper describes a longitudinal study of children identified as at risk when they were 4 years of age and reexamined when they were 13 years old. Their families had a wide range on presence of the multiple risk factors described above. We measured change in the children's cognitive and social-emotional status between 4 and 13 years, as well as many individual and contextual factors that may have buffered their risk. This study was conducted from the perspective of developmental psychopathology (Sroufe and Rutter, 1984), which suggests the following: (1) intergenerational risks are not necessarily specific in nature (i.e., the area of functioning that will be affected by a risk condition is uncertain); (2) risks may occur simultaneously from several sources to affect individual adaptation; and, (3) context and family sysAccepted November 7, 1991. Dr. Seifer is Assistant Professor of Psychiatry and Human Behavior, Brown University Program in Medicine and E.P. Bradley Hospital, East Providence, Rhode Island. Dr. Sameroff is Professor of Psychology, University ofMichigan, Ann Arbor, Michigan. Dr. Clara Baldwin is Associate Professor ofPsychology and Dr. Alfred Baldwin is Professor of Psychology, University of Rochester, New York. This research was supported by grants from the National Institute of Mental Health and the W.T. Grant Foundation. Portions of the paper were presented at the Society for Research in Child Development meeting, Kansas City, 1989. Reprint requests to Dr. Seifer, E.P. Bradley Hospital, 1011 Veterans Memorial Parkway, East Providence, R102915. 0890-8567/92/3105-0893$03.00/0© 1992 by the American Academy of Child and Adolescent Psychiatry. J. Am. Acad. Child Adolesc. Psychiatry, 3 J:5, September J992

tems affect individual adaptation, which may exacerbate or ameliorate the impact of risk factors on individual children. This approach led us to examine the richness and diversity of risk in developing children, and to search for other aspects of their contexts that might buffer them against the deleterious effects of the risk conditions.

Theoretical Approaches to Risk and Protection Translation of the general theoretical principles articulated above into specific research methods involves many decisions. These include the approach to risk in terms of the uniqueness and breadth of the construct as well as the specific domains of function identified as potentially protective in buffering the risk within individuals. Specificity and Multiplicity of Risk Many characteristics of children, families, and social contexts have been identified as placing children at risk for serious problems later in life (such as psychopathology or criminal behavior) (Rutter, 1987). This risk is often presented as specific and linear in nature. For example, parental depression places children at risk for developing depression themselves (Beardslee et aI., 1983). However, while there is some specificity in the nature of risk, the majority of negative outcomes are not directly related to individual risk factors (Sameroff et aI., 1987a; Watt et al., 1984). For example, children of schizophrenic mothers run a lO-fold increased risk for developing schizophrenia compared with the general population, but they are also at risk for many other problems: about 40% of these children will develop psychopathology that is not along the schizophrenic spectrum (Mednick and McNeil, 1968). In areas outside the realm of individual psychiatric disorders, there is even less specificity in the relation of risk to outcome (e.g., low social status is related to psychopathology, substance abuse, delinquency, and behavior problems). In sum, while there is some . specificity, especially in the transmission of serious mental disorders, there is also a substantial lack of specificity associated with risk factors in childhood. The lack of specificity of risk factors must be considered 893

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simultaneously with the fact that risk factors do not occur in isolation from one another. The effects of multiple, nonspecific risk factors may be cumulative in the sense that the presence of more risk factors is related to a higher certainty of negative outcome. Multiple social and family risk factors make a major contribution to predicting cognitive and socialemotional outcomes in 4-year-old (Sameroff et al., 1987a; b) and 13-year-old children (Sameroff et al., 1989). At each age, 10 risk factors were defined: mental illness, high anxiety, low education, low occupation, father absence, rigid parenting values, poor interaction style, many negative life events, minority racial status, and large family size. The total risk score was the number of these risk factors present. Analysis of the type of risk present indicated that the specific risk factors were far less important than the total number of factors present. Other studies of medical phenomena such as heart disease (Kannel and Schatzkin, 1983) and studies of behavioral development (Rubenstein et al., 1989; Rutter, 1979; Williams et al., 1990) have been consistent with this view. Protective Factors

Another important feature of this lack of specificity is that not every individual with a risk condition will have a negative outcome. One approach to risk research would be attempting to improve the precision with which the prediction of negative outcomes could be made. In contrast, Garmezy (1985) has emphasized the study of factors that might protect individuals at risk from having a negative outcome. The investigation of protective factors involves two main components. First is the unambiguous identification of individuals at risk. Risk may be subdivided into external risk factors (such as poverty) and internal vulnerabilities (such as genetic disorders). The second component is the identification of potential mediators above and beyond the simple absence of risk factors. Qualities are assumed to be protective if their presence is associated with better than expected outcomes in the risk population. Analogous to the dichotomy for risk factors, one may conceive of external protective factors and more constitutional stress-resistance or resiliency (Masten and Garmezy, 1985). Although there is heuristic value in identifying components of risk and protection, Rutter (1987) has emphasized the interactive nature of risk, protection, vulnerability, and resilience (see also Werner and Smith, 1982). He asserts that they should not be viewed as static qualities of individuals, but as expressions that vary with specific contexts. For example, the protective factors of most interest are those whose effects are most salient when risk is highest, but have less impact when risk is minimal (Jenkins and Smith, 1990; Rutter, 1987, 1991). Where Masten and Garmezy focus on internal versus external location of the factors, Rutter emphasizes vulnerability and protection as a single dimension of how an individual responds to risk, with an emphasis on the process of functional adaptation, rather than the variable or factor (see also Masten, 1989). This view is consistent with the perspective of developmental psychopathology (Cicchetti, 1990; Sroufe and Rutter, 1984), which views outcomes as a range of developmental paths rather than

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the expression of discreet illnesses based on specific causal factors. . In sum, there is a large portion of the relation of risk to outcome that is nonspecific: individual risks are not uniformly related to individual negative outcomes, and not everyone with a risk factor has a negative outcome. Risk is also cumulative. Having more risk factors increases the likelihood of having a negative outcome. In addition to risk factors, one may identify protective factors that ameliorate the effects of risk. Thus, hypothesized protective factors may be examined in a group of children at the highest risk (defined by simultaneous presence of many risk factors) to examine whether the putative protective factors do, in fact, improve the outcomes of the children. In this study we defined risk using multiple criteria, concentrating on the amount (rather than specific type) of risk. Protective factors, identified in the domains of personality, social support, and family cohesion, were examined in the context of multiple risk with respect to child outcomes.

Studies of Protective Factors Many factors have been identified as possibly having protective quality in children at risk. Garmezy (1985) emphasizes three classes of variables ranging from stable individual traits to dynamic contextual interactions: personality dispositions, social support, and family cohesion. He summarizes four domains of outcomes where these protective factors may operate: persistent antisocial disorders; biological, genetic, or psychosocial disadvantage; schizophrenia; and major affective disorders. Personality Dispositions

There has been speculation that individual cognitive and behavioral styles of children (such as temperament, locus of control, or perceived competence) will protect them from risk (Rae-Gant et al., 1989; Rutter, 1987). The issue of locus of control has traditionally been formulated in terms of internal versus external attributions (Rotter, 1966). More recently, Connell (1985) and Peterson and Seligman (1984) have expanded the construct to include features such as unknown locus (where the child cannot attribute cause to either internal or external sources); or including instability, globality, specificity, and helplessness with the internal-external attributions. These recent formulations may be more relevant to the study of stress-resistance because they differentiate between those children who have a focused view of what controls their lives versus those who have no such perspective. Social Support

Pellegrini and colleagues (1986) identified the importance of child social support for offspring of depressed parents. The importance of social support for parents of children with handicaps, or for preterm infants, has been well documented also (Crnic et al., 1983; Greenberg and Crnic, 1988). Family Cohesion

Family interaction styles, particularly expressed emotion (Vaughn and Leff, 1972) have been strongly implicated in J. Am. Acad. Child Adolesc. Psychiatry, 31..5, September 1992

RISK AND PROTECTIVE FACTORS

relapse rates for those at highest risk for serious mental disorder as well as for initial onset of a variety of emotional disorders (Doane et al., 1981; Rae-Gant et al., 1989). Specific patterns of social interaction are also important. Sigel's (1972) theory of distancing in parent-child teaching interactions is one scheme for quantifying interactions early in life that may have long-lasting significance. This theory posits that mothers who employ strategies that require more complex cognitive functions, i.e., those that require children to cognitively distance themselves from the immediate task at hand, will have children who develop more representational competence. Such strategies may have long-term implications for children's ability to seek adaptive alternatives when under duress.

became worse? From our literature review, we chose child, family, and context constructs as potential indicators of protective processes. We hypothesized that the following protective factors would be related to the better outcomes in the face of high levels of risk: children who had high perceived competence, more social support, and low levels of unknown locus of control; families where mother-child interactions had low levels of expressed emotion or required sophisticated cognitive operations by the children; and contexts with high social support. Further, we hypothesized that many of the relations would be characterized by interaction effects where impact was greater in high-risk individuals.

Assessment of Child Status and Change Over Time

Data presented here are from the 4-year and 13-year assessments of the Rochester Longitudinal Study (RLS) (Baldwin et al., 1990; Sameroff et al., 1982). These 152 families have been studied since the mothers were pregnant with the study children. The original purpose of the study was to examine the transmission of serious mental disorder across generations. Pregnant women were identified at obstetric sites (both public clinics and private physicians) and were approached about participation in the study. Women identified in a county-wide psychiatric registry as having mental illness were targeted for recruitment, and about half of the families in the final sample appeared in this registry. These mental illness classifications were further documented by two psychiatric interviews conducted with all subjects by project staff (Current and Past Psychopathology Scales done prenatally and when the child was 2Y2 years old). About half of the families were from poor social circumstances and a third were minority racial status (all but a few of the minority families were black). At the time their children were born, mothers' average age was 24.5 (SD = 4.8). All mothers were recruited from obstetric services, so there were no families who did not receive prenatal care. The index child in the family was chosen based on the current pregnancy when the family entered the study. This sample, which was recruited between 1970 and 1974, had few mothers with substance abuse problems.

One ultimate goal of risk studies is to identify those individuals who eventually succumb to their risk and exhibit significant pathology. However, in most cases it is only possible to study intermediate outcomes, because of the time required to follow children through the entire risk period for pathology. At our 13-year assessment, we wished to examine the wide range of variation from competent behavior to maladjustment. Ikle et al. (1983) developed a structured interview that emphasized both strengths and weaknesses of young adolescents. This dual emphasis is an important feature when studying risk-protection models. One important choice when assessing children and adolescents is the source of information regarding behavioral adjustment. There is a growing literature that suggests a large degree of discrepancy among different informants (e.g., mothers, fathers, children, teachers, or observers), perhaps with some systematic bias associated with every category of informants, and with no source identified as providing the most accurate information (Achenbach et al., 1987). In this study, we chose to gather information about adjustment from both the mother and child, so that interpretation problems would be minimized. When examining protective factors, one strategy would be to use final outcome levels as the criteria to identify those factors that ameliorate risk. However, this approach may obscure positive effects by failing to consider that children at risk often have initial levels of function well below established norms. Therefore, their outcome scores, even after improvement, could be below average. It is more appropriate to examine the relation of protective factors to the change in status between the time risk is identified and final assessments are made. As Werner (1989) noted, protection is not a static phenomenon, but one that may occur even after poor interim outcomes have been attained.

Research Plan To examine outcomes in our sample of children, we looked at the relation of protective factors to change in cognitive status and change in social-emotional status during the period from 4 through 13 years of age. Given their functioning at 4 years, what factors differentiated high-risk children and their families who improved most between 4 or 13 years of age from those who did not improve or J. Am.Acad. Child Adolesc.Psychiatry, 31:5, September1992

Method

History of RLS Sample

The original RLS sample included 337 families assessed during the prenatal period. About 20% of these families dropped out of the study by the time their children were 4 months of age. Another 20% were lost to the study between I and 4 years of age, leaving a group of 214 families at the 4-year assessment. Nine years later at the 13-year assessment, 152 families were available for this report. We compared the families in the study (N = 152) with those who dropped out between 4 and 13 years (N = 62) and those who dropped out before 4 years (N = 123). There were no significant differences in socioeconomic status, proportion of minority families, father absence, family size, or severity of maternal illness. Thus, although many of these high-risk families were lost to follow-up over a 13-year period, the families who dropped out were not a select group of the highest risk families.

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1. Demographic Characteristics of Low-Risk and High-Risk Groups

Assessment of Child Status

TABLE

High-Risk Group (N = 50)

Low-Risk Group (N = 102)

Sex

52% Male

50% Male

Family size

3.0 Children 14% Firstborn

2.0 Children 39% Firstborn

Family composition

42% Single 18% Separated

3% Single 3% Separated

Race

80% Black

12% Black

SES

0% SES I-III 68% SES IV 32% SES V

52% SES I-III 40% SES IV 8% SES V

Severity of mental illness

36% None 14% Low 24% Moderate 26% Severe

63% None 15% Low 14% Moderate 9% Severe

Number of risk factors

5.22 (SD

At 4 and 13 years of age the children's cognitive and social-emotional competence were assessed. Cognitive Competence

A shortened version of the age-appropriate Wechsler intelligence scale was used (Wechsler, 1967; 1974). At 4 years, the Wechsler Preschool and Primary Scale of Intelligence verbal scales of similarities, comprehension, information, and vocabulary were used to compute a prorated IQ score (X = 103.2; SD = 18.4). At 13 years, the Wechsler Intelligence Scale for Children-Revised scales of information, similarities, picture arrangement, and block design were used to determine the prorated IQ (X = 102.0; SD = 18.7). Social-Emotional Competence

SES

= socioeconomic

= 1.20)

1.13 (SD

= 1.11)

status.

Assessment of Risk The risk status of families was evaluated within the framework of nonspecific multiple risk factors. At the 4-year assessment we examined 10 individual risk factors (Sameroff et aI., 1987). Each family was assigned a score of 0 if no risk was present, or a score of 1 if a risk was present, determined by the following criteria: (1) presence of a diagnosed DSM-ll maternal mental illness (36% of the sample met this criterion); (2) a mother's score of 6 or higher on Rutter's (1976) anxiety/malaise scale (23%); (3) 20 or more stressful life events during the previous 4 years (23%); (4) mothers who had not completed high school (33%); (5) head of household had no more than a semiskilled occupation (27%); (6) father not present in household (24%); (7) four or more children in the family (16%); (8) disadvantaged minority ethnic background (35%); (9) rigid parenting values (23%); and (10) poor quality of mother-child interaction in a laboratory teaching task (14%). Those children whose families had a total risk score of 4 or higher were considered the high-risk sample. There were 50 such children in the RLS sample who were followed through 13 years of age. The remaining 102 children were considered low-risk. The characteristics of the selected low- and high-risk samples are described in Table 1. The high-risk children were from modest circumstances, with ill mothers, and predominantly black. There were about equal numbers of boys and girls, and the average number of children per family was three. The majority of the families did not have a father present in the household. On average, each family had more than five risk factors present. The mothers in the high-risk group were, on average, about 2 years younger than in the low risk group (23.1 versus 25.2; t = 2.55; p < 0.05).

896

At each assessment the mother was interviewed about her child's social-emotional competence. At 4 years the Rochester Adaptive Behavior Inventory (RABI) was employed (Seifer et aI., 1981). After a 90-minute behaviorally oriented interview (with 134 scored items) the interviewer assigned a score on the 5-point Global Rating scale: above average adjustment, no significant problems, subclinically disturbed, clinically disturbed, and seriously disturbed. The validity of this measure was demonstrated in normal and clinical populations (Krafchuk, 1989). At 13 years, the mother and child were interviewed separately using the 88item Ikle et aI. (1983) Community Mental Health Interview (CMHI). Subscales for school productivity, aggression, family conflict, impulsiveness, emotional distress, and conduct problems were derived from 4-point responses to individual interview items. These subscales were used to form a composite adjustment score. A separate adjustment score was derived for the mother report and for the child report. Protective Factor Assessment Protective factors were assessed at 4 and 13 years of age in three domains: personality dispositions, social support, and family cohesion. Personality Dispositions

When the children were 4 years of age, we examined behavioral characteristics of the child. The behavioral style of the child was observed in the laboratory during developmental testing using the Infant Behavior Record of the Bayley (1969) Scales of Infant Development. A summary factor indicative of cooperative behavior during the examination was used. We also obtained a maternal report of temperament using a questionnaire developed by Thomas and Chess (1977). Scale scores were derived from 63 4-point items. A summary score of temperamental difficulty was computed from scales of adaptability, approach, intensity, mood, and rhythmicity. At 13 years of age we measured several qualities of the children. Perceived competence was assessed using Harter's (1982) questionnaire to obtain scores for school, social, and total summary self-esteem. Scales were aggregates of J. Am.Acad. ChildAdolesc.Psychiatry, 31:5, September1992

RISK AND PROTECTIVE FACTORS

4-point scales from the 36-item questionnaire. Locus of control was assessed using Connell's (1985) instrument to obtain scores for internal, external, and unknown (i.e., no source of control). Scale scores were derived from the 48 4point items. Mothers' personality was also assessed in the area of depression, using the 21-item Beck (1967) scale. Social Support

Furman and Buhrmester's (1985) Social Support Inventory provided a general score, which emphasized the social network of the child. The scales were derived from 42 items scored on a 5-point scale. Life events during the past year were indexed using the child form of the Project Competence Life Events Questionnaire (Garmezy et al., 1985), containing 28 events that could be scored yes or no. The mothers also reported about their own social support (tangible, behavioral, confidant, self-esteem) on the Cohen and Hoberman (Cohen et al., 1985) instrument, which emphasizes the mother's perceptions of available support. The scales were derived from 34 true-false items. Life events during the past year were indexed using the mother form of the Project Competence Life Events Questionnaire (Garmezy et al., 1985), with 28 yes-no items. Family Cohesion

Measures of parent-child interaction, parenting values, and expressed emotion were used to index family cohesion. A maternal teaching interaction was videotaped (Barocas et al., 1991), and the cognitive sophistication of the mothers' teaching strategies were categorized according to Sigel's concept of mental operational demands (MODs) (Flaugher and Sigel, 1980). Higher MODs are thought to be predictive of better future cognitive growth in the children. Parenting values of self-direction (versus conformity) were obtained using Kohn's (1977) Parental Values scale. TABLE

The summary score was derived from 13 items rank ordered in terms of the degree to which the parent valued that item for his or her child. Expressed emotion was indexed using the Camberwell Family Interview (Brown and Rutter, 1966) and scales of positive, dissatisfaction, critical, and concerns were used in the analyses. The interview elicits comments about the child that are scored for presence of the positive and negative qualities noted above. Statistical Analysis Plan .

Data analysis was designed to examine whether hypothesized protective factors were related to change in cognitive and social-emotional outcome status from 4 to 13 years of age. The relation of change in status to protective factors was examined in the 50 high-risk families (risk scores of 4 or greater) and 102 low-risk families (risk scores of 3 or lower). Multiple Regression

Sets of variables were examined simultaneously to determine if potential protective factors were related to changes in child status. We examined hierarchical multiple regressions (with entry orders determined by the investigators) for each of the outcomes for the 10 child variables (listed in Table 2) and for the 12 mother variables (listed in Table 3). In these hierarchical regressions with 13-year outcome as the dependent variable, initial level of function was entered as the first step (which results in covarying the effects of initial level when variance explained on subsequent steps is examined). This hierarchical strategy is equivalent to the analysis of residualized change scores, which are independent of the initial level of function. These regressions were done within the high-risk group and within the low-risk group, on the sets of 10 child variables and 12 mother variables. Because there were 50 cases in the high-risk group, it was not feasible to examine the entire set of protective factors in a single

2. Correlation of Change in Cognitive and Social-Emotional Functioning with Potential Protective Factors in Low-Risk and High-Risk Groups

Measures 4-year child measures Easy-difficult temperament Behavioral style summary 13-year child measures Perceived competence School Social Total Locus of control Unknown External Internal Social support Stressful life events

4-13 Year Cognitive Change Low-Risk High-Risk

4-13 Year Mother Report Social Emotional Change Low-Risk High-Risk

4-13 Year Child Report Social Emotional Change Low-Risk High-Risk

-0.03 0.03

0.12 -0.10

-0.11 -0.Q1

-0.13 0.03

-0.Q1 -0.14 -0.07

0.30*" 0.37*" 0.23

0.09 0.10 0.00 -0.09 0.01

-0.29*" -0.07 0.18 0.39**" -0.07

0.32** 0.20* 0.24* 0.03 -0.05 -0.07 0.19 -0.22*

0.09 0.05 0.09 0.13 0.08 -0.29* -0.08 -0.14 -0.18 -0.38**

0.54** 0.26* 0.56** -0.37** -0.26* 0.11 0.17 -0.36**

0.10 0.22

0.25 0.28* 0.30* -0.50** -0.32* 0.13 0.16 -0.40**

Note: Number of cases in Low-Risk Group is 102, in High-Risk Group is 50. "Risk status by protective factor interaction term also significant, p < 0.05. *p < 0.05, **p < 0.Q1. J.Am. Acad. Child Adolesc. Psychiatry, 31:5, September 1992

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SEIFER ET AL. TABLE

3. Correlation of Change in Cognitive and Social-Emotional Functioning with Potential Protective Factors in

Low-Risk and High-Risk Groups

Measures 4-year mother measures Teaching style MOD score 13-year mother measures Stressful life events Depression Beck Scale Social support Tangible Behavioral Confidant Self-esteem Kohn parental values Self-direction Expressed emotion Positive Dissatisfaction Critical Concerns

4-13 Year Cognitive Change Low-Risk High-Risk

4-13 Year Mother Report Social Emotional Change Low-Risk High-Risk

0.36**"

-0.06

-0.04

0.16

-0.08 0.23* -0.02 0.06 -0.10

0.09

0.12

om 0.03 -0.02 0.07

4-13 Year Child Report Social Emotional Change Low-Risk High-Risk

0.23

0.14

0.08

-0.23*

-0.04

-0.05

-0.12

-0.06

-0.29**

-0.35*

-0.09

0.07

0.06 0.05 0.29* -0.18

0.04 0.00 -0.04 0.17

0.04 0.12 -0.15 -0.04

-0.06 0.02 0.11 0.20*

0.14 0.04 0.02 -0.15

0.33*

-0.18

-0.12

0.19

-0.05

0.07 -0.26* -0.41 ** -0.D7

0.28* -0.44** -0.30* -0.39**"

-0.20 0.08 0.05 -0.14

-0.12 -0.25** -0.17 -0.02

-om -0.36* -0.11 -0.36*"

Note: Number of cases in Low-Risk Group is 102, in High-Risk Group is 50. "Risk status by protective factor interaction term also significant, p < 0.05. *p < 0.05, **p < om.

multiple regression (even separating into mother and child variables still left 12 and 10 predictors respectively, which is more than the optimal number with 50 cases). Thus, the multiple regressions conducted in the high-risk group should be considered with some caution because of low power and a high predictor-to-subject ratio. Correlation Analyses

The data analysis strategy included examination of correlations between residualized change scores, using covariance techniques, and the hypothesized protective factors in the high-risk children and in the low-risk children (Cohen and Cohen, 1983). Specifically, the partial correlation between the 13-year outcome scores and the protective factor, with the corresponding 4-year outcome measure covaried, was examined. This covariance of initial level of function from final level of function produces a change score that is uncorrelated with the initial level of function. Three outcome change scores were examined: cognitive competence (using child IQ measured at 4 and 13 years), mother's report of child social-emotional competence (using the RABI at 4 years and CMHI mother report at 13 years), and child selfreport of social-emotional competence (using the RABI at 4 years and CMHI child report at 13 years). Note that the child-report change score uses the 4-year mother report as its base since self-reports were not obtained from these young children. Interaction Effects

To determine whether there was a greater impact of protective factors in the high-risk group, interaction effects

898

were examined. Since the protective factor variables were continuous, interaction terms were computed as described by Cohen and Cohen (1983). The interaction term is defined as the product of predictors with the direct effects covaried. We examined the partial correlation of the 13-year outcome with the product term (i.e., the product of the protective factor and risk status), while covarying the corresponding 4-year outcome level and the direct effects of risk status and protective factor in question. As in the correlations described above, this creates a residualized change that is the final level of function with the initial level covaried. Results Multiple Regressions

We first examined whether the sets of child and mother variables were related to change in cognitive and socialemotional status. There were significant relations when social-emotional outcomes derived from child report were examined. In the low-risk group, R2 = 0.43 (p < 0.01) for the child protective factors and R 2 = 0.16 (p < 0.12) for the mother protective factor variables. In the high-risk group, R2 = 0.32 (p < 0.05) for the child protective factor measures and R2 = 0.23 (p < 0.41) for the mother protective factors. Multiple regression of protective factors with change in social-emotional status derived from maternal report also explained substantial portions of variance, particularly for protective factors associated with mother variables. In the low-risk group, R2 = 0.16 (p < 0.02) for the child variables and R2 = 0.26 (p < 0.01) for the mother variables. In the high-risk group R2 = 0.22 (p < 0.35) for the child variables and R2 = 0.45 (p < 0.01) for the mother variables. J.Am.Acad. Child Adolesc.Psychiatry,31:5, September1992

RISK AND PROTECTIVE FACTORS

Multiple regressions of mother and child measures with cognitive outcomes were not significant. Within the low risk group, R2 = 0.02 (p < 0.98) for child measures and R2 = 0.10 (p < 0.11) for the mother measures. In the high-risk group, R2 = 0.16 (p < 0.32) for the child measures and R2 = 0.26 (p < 0.08) for the mother measures. It should be noted that substantial portions of variance are explained in the high-risk group analyses, but they may fail to reach significance because of the low power of these tests.

Correlations with Individual Protective Factors Since most of the multiple regressions indicated meaningfullevels of variance explained, individual protective factors were examined for their relations to change in cognitive and social-emotional outcomes. Tables 2 and 3 list the partial correlations for the relations of potential protective factors with cognitive and social-emotional change scores. These data are presented within high- and low-risk group families. 4-Year Child Variable Results

At 4 years of age, neither of the child variables : observed behavior style measure nor the mother-report temperament measure, had any predictive value as a protective factor for cognitive or social-emotional competence (Table 2). 4-Year Mother Variable Results

For the mother variables , high-risk group mothers who used higher MODs in their instructions had children whose cognitive competence had improved the most during the subsequent 9 years (Table 3). 13-Year Child Variabl e Results

At 13 years of age, measures of the eight child characteristics were related to change in child competence. Child personality dispositions were related to cognitive and socialemotional competence in the high-risk families (Table 2). Those high-risk children with more perceived competence in school and social arenas had the greatest gains in cognitive competence. Low-risk children had no relations between perceived competence and cognitive change. With respect to social-emotional outcomes , higher perceived competence was related to positive change scores in both low- and highrisk groups, and the relations were of greater magnitude for the child reports of social-emotional competence compared with the mother reports. Children who had lower unknown locus of control made greater gains in both the social-emotional and cognitive realms, primarily in the high-risk group (although child reported social emotional change was related to unknown locus of control in the low-risk group). For external locus of control , the significant effects were smaller than for unknown locus of control, and were restricted to the child reports of social-emotional status in the low- and high-risk groups. No relations with internal locus of control were found. For the social support measures, child social support was related to more improvement in cognitive functioning in the high-risk group. No relations with social-emotional change J. Am.Acad.ChildAdolesc. Psychiatry, 3 J:5, SeptemberJ992

were found. Those children who reported fewer life events tended to have more positive social-emotional change, whether in the low-risk or the high-risk groups, and regardless of whether the mother or child was reporting about the social-emotional status. No relations with cognitive status were found. l S-Year Mother Variable Results

The 11 potential protective factor measures obtained from the mothers are summarized in Table 3. Among the personality disposition measures, mothers who had more self-directing, less conforming values for their children had high-risk children who made more gains in cognitive status. Mothers with lower Beck depression scores had low-risk and high-risk children who gained more on social-emotional competence. These scores were generally unrelated to social-emotional change scores as reported by the children . For social support measures, mothers who had more perceived social support via having a confidante had high-risk children who improved most in the cognitive arena, while mother tangible support was related to improvement in the low-risk children . Mother-reported life events were related to social-emotional (but not cognitive) change scores in the low-risk group. In the family cohesion domain, several variables from the Camberwell interview, which taps expressed emotion by the parent about the child, were related to social-emotional change. Those mothers who expressed more positive comments, and fewer dissatisfactions, criticisms , and concerns had children who improved the most on social-emotional competence. Statistically significant relations were generally higher in the high-risk group, and slightly more frequent for the mother reports than for the child reports of socialemotional status.

Interaction Effects An important consideration in protective factors research is whether relations among putative protective factors and outcomes are general across high-risk and low-risk individuals, or whether they are more apparent in higher-risk groups. We examined interaction effects between risk status and protective factors in the prediction of change in cognitive or social-emotional status for the variables listed in Tables 2 and 3. As indicated on Tables 2 and 3, many of the protective factor variables had significant interaction terms. All interaction terms were for variables that had larger positive impact on the outcome in the high-risk group compared with the low-risk group. For the 13-year child protective factors , perceived competence in school (t = 2.06; p < 0.05) and social (t = 3.09; p < 0.01) domains, unknown locus of control (t = 2.23; p < 0.03), and social support (t = 2.68; P < 0.01) related to cognitive change . No interaction effects with social-emotional change were noted. The 4-year mother teaching style had an interaction effect with cognitive change (t = 2.17; P < 0.05). For the l3-year mother protective factors, expressed emotion concerns had interaction effects with both mother- and child-reported social-emotional

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change (t tively).

=

1.99; p < 0.05 and t

= 2.00; p < 0.05 respec-

obtained relations between contexts and outcomes are not artifacts of the data collection strategy (Patterson, 1986).

Sex Differences

Protective Factors and Individual Families

We examined differences in the pattern of correlations within males and females in low-risk and high-risk groups. There are 132 correlations reported on Tables 2 and 3. Tests on the difference between males and females for each of these correlations revealed five significant effects, slightly below the level expected by chance. Thus, there is no evidence that sex differences are important when considering the patterns of relations observed in this study.

When studies are successful in identifying protective factors, the issue is raised of identification on an individual basis of resilient (or protected) individuals. The analysis strategy of this study obscured the absolute level of functioning at the last assessment. Ideally, one would like to identify a substantial subset of children who by any measure of competence are doing better than average, despite the adversity they face in daily life. Unfortunately, there were only three of the 50 high-risk children who were above the total sample mean on our three 13-year outcome measures; all three had been in the highest risk category at 4 years of age, but by 13 years were scoring better on our risk index. Thus, it is unclear whether the more favorable outcomes in these children were due to protective factors or to a lessening of risk. Few individuals were identified using this categorical approach that emphasized the identification of specific protective variables. A potentially more fruitful approach is process oriented, with relative balances among factors that enhance or inhibit development of competence interpreted with respect to adaptation of individuals. The questions as currently posed in the field are whether factors like socioeconomic status, parental expressed emotion, or child locus of control should be categorized as risk factors, protective factors, child vulnerabilities, or child resiliency, and whether there is empirical support for such categorization. From a more dynamic perspective, questions may be rephrased to ask how multiple factors acting in concert serve to inhibit or enhance the competence of individuals in cognitive or social-emotional domains, where neither individuals nor variables are classified(Luthar and Zigler, 1991).

Discussion The results of this study conform to expectations built over the past decade about the types of processes that should mediate risk. Many of the hypothesized protective factors proved to be associated with change in child status from 4 to 13 years of age. Helpful qualities included individual child characteristics such as self-esteem, social support, and low external or unknown locus of control; family characteristics such as self-directing parental values, good parent teaching strategies, and low rates of parental criticism and maternal depressed mood; and contextual characteristics of good social support and few life events. Conversely, little self-worth, unknown locus of control, parental criticism, conforming values, poor parenting styles, many life events, and little social support predicted less than optimal outcomes. Some of these findings were strong indicators of protective factors in the sense that interaction effects of protective factor and risk status were observed in the prediction of change in outcome status, indicating a greater positive impact of the protective factor in the high-risk group (Jenkins and Smith, 1990; Rutter, 1991). To summarize, many factors hypothesized to be protective did show a relation with positive change in cognitive and/or social-emotional risk. There is strong evidence that many individual and family factors mediate the impact of risk on children between 4 and 13 years of age. Sources of Information about Outcomes Whether information about child functioning was obtained from the parent versus the child proved to be important (Achenbach et al., 1987; Kashani et al., 1985). When considering characteristics of the child (such as self-esteem or locus of control) as protective factors, there were stronger effects with child-reported social-emotional outcomes than with mother-reported outcomes (Table 2). When mother characteristics (such as values or expressed emotion) were considered as protective, the relations were strongest with the mother-reported, rather than child-reported, outcomes (Table 3). Those protective factor measures with relations to outcomes across informants in the high-risk families may be interpreted with greater certainty, i.e., unknown locus of control, child reported stressful life events, and expressed emotion (dissatisfaction and concerns). Future studies must continue to explicitly collect information about child and adolescent outcomes from multiple informants to ensure that

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Categorizing and Defining Protective Factors Although the protective factors identified in this study all index individual and family processes, they may operate in different ways (Rutter, 1987). Altering the risk occurs when individuals variably behave in or appraise the same context in ways that differentially affect adaptation. Unknown locus of control, poor perceived competence, or little social support may indicate individual processes that interfere with successful adaptation. Altering exposure to risk may occur when families enforce restrictions in dangerous contexts or behave differentially toward family members (e.g., when children's temperaments enable them to avoid becoming a family scapegoat). In this study, we speculate that exposure to high negative expressed emotion toward a specific child may be one way that psychopathology is exacerbated for some, but not all, children in a family. In another report from this study, Baldwin et al. (1989) reported that restrictiveness in different socioeconomic groups had different protective implications depending on the dangerousness of one's neighborhood. Protection in the Context of Risk

These protective factors were identified in a group where J. Am.Acad. ChildAdolesc.Psychiatry,31:5, September1992

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risk was defined by multiple factors. Most previous efforts have defined risk using single variables (e.g., Rae-Gant et al., 1989; Watt et al., 1984), which are minimally predictive (Sameroff et al., 1987 a, b; Williams et al., 1990). Thus, the documented protective influence of the variables studied is strong evidence that these are important factors even when there are few resources in the children's developmental context. Some protective factors were restricted to those at the highest risk. From the prevention perspective, it is necessary to distinguish those factors that have competence-promoting influence in the general population, but no special effect in those at highest risk, from those that have their strongest effect among high-risk children (the strongest protective factors). This distinction does not imply that the effects found only in the low-risk group are unimportant (any factor associated with enhanced competence in any group is of interest), only that such effects are less useful when considering the issue of protection in high-risk individuals . Methodological Considerations Cautions in Interpreting Results

There are two areas where the reader should be careful in interpreting the findings presented. The first is in the correlation analyses. There were 132 correlations examined and no correction for error rate was made, so the interpretation of a significant result for any individual variable should be made cautiously. The overall pattern of results, rather than the impact of any individual protective factor, has been emphasized throughout. The second caution concerns the multiple regression analyses, particularly within the high-risk group. Since 10 and 12 predictors were used in the multiple regression equations, these tests had very low power. Therefore, the nonsignificant findings (especially those with high R 2) may result from type II error, especially those where several of the individual variables were related to change in outcome status. Time of Assessment

Assessment of protective factors was conducted at two points in time: 4 years and 13 years. Only the 4-year assessment occurred temporally prior ·to the final assessment of child status at 13 years of age. We have used the term prediction to describe the relation of protective factors to change in outcome status, even though the variables were measured simultaneously. Prediction is used in this context in its statistical sense (i.e., a variable as a predictor in a regression equation), not to indicate that a temporally prior measure predicts later adjustment . Mediation models of protection are tenable even if the mediator variables are measured at the same timepoint as the outcome variables. Since the measures of protective factors as well as cognitive or social-emotional status will have some stability over time, the reciprocal influences of these variables may be estimated by taking snapshots of them at different points in development (even if those time points are simultaneous). Since longitudinal studies cannot measure all of the variables at all of the timepoints that J. Am .Acad. Chiid Adolesc. Psychiatry, 31:5, September 1992

would be desirable on theoretical grounds, interpretation is (unfortunately) always based on less than optimal information. Potential Confounding Factors

Although many protective and risk factors were examined in this study (resulting in some of the cautions noted above), there were many variables that were not examined that may have substantial impact. Such confounds might include mothers' prenatal status or type of psychopathology, children's health status, or patterns of attrition. With respect to type of pathology, we generally have not found much impact of specific diagnosis in this study (Sameroff et al., 1982). With respect to selective attrition, we noted above that there were no significant differences in the dropout families on major demographic factors . However, without the ability to study those families that dropped out, one can only speculate as to their impact on the results presented here. Confounds of risk group with demographic factors (Table 1) are not a concern because most of the analyses were within risk groups, and those conducted across risk groups (the interaction effects) explicitly covaried the multiple risk score. Development and Assessment of Competence

We were able to identify concurrently at 13 years of age many factors related to positive versus negative change in the risk population, but there were relatively few aspects of 4-year child behavior that were predictive . The personality and social characteristics of children that can be measured effectively at these two developmental points are quite different. Unlike adolescents, preschool children are notoriously poor at providing any information useful to the systematic assessment of theoretically important internal states such as locus of control, self-esteem, or social networks. To the extent that outside forces might positively impact on the future outcomes of preschool children at risk, it would be useful to work at developing techniques that more directly assess such qualities. Summary

This study examined the impact of many potential protective factors on changes in cognitive and social-emotional competence between 4 and 13 years of age. These relations were examined in low-risk and high-risk groups defined by a multiple risk index at 4 years of age. Social-emotional outcomes were obtained from both mothers and children. There were many relations between protective factors and change in cognitive and social-emotional status, especially in domains of perceived competence, locus of control , maternal teaching style, parenting values, and expressed emotion. Some of these relations were stronger in the high-risk group, while others were common to the high- and low-risk families. In sum, these results support the idea that individual and family factors can ameliorate the impact of multiple risk factors in children between 4 and 13 years of age. Several methodological issues were discussed including the impact of development, the source of information, and the difficulties inherent in identifying resilient or protected individuals. The task of researchers in this area is to translate

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