Child and Adolescent Social Work Journal, Vol. 21, No. 3, June 2004 ( 2004)
Risk and Resilience Ecological
Framework for Assessment
and Goal Formulation
Jacqueline Corcoran, Ph.D. and
Ann Nichols-Casebolt, Ph.D.
ABSTRACT: This paper describes the use of the risk and resilience ecological
framework as an assessment and goal setting tool for social workers. A rationale for the framework is provided, along with identification of risk and protective factors across the micro, meso, and macro level systems. Goal formulation from identification of factors follow, with implications for social work
interventions.
KEY WORDS: Risk Factors; Protective Factors; Risk and Resilience.
Social workers are faced with multiple challenges in their efforts to
assess and intervene in increasingly complex situations. First, social
work is unique to the helping professions in expecting practitioners to
understand, assess, and ultimately intervene at a variety of system
levels. While multi-system intervention is the expectation, given the
complexity of human behavior and that factors at different system
levels interact dynamically with each other, identifying appropriate
interventions can often be confusing and overwhelming. In addition,
most social workers specialize in a particular level of practice (i.e., the
micro, mezzo, or macro system level), often without a true awareness
and understanding of how to assess and intervene at another, perhaps
potentially more significant, level of change. A second challenge is our
professional commitment to focus on strengths rather than pathology.
Social workers are expected to recognize and build on client strengths
Jacqueline Corcoran and Ann Nichols-Casebolt are affiliated with Virginia Commonwealth University.
Grateful acknowledgment to Gordon Casebolt for assistance with the preparation of
this manuscript.
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 2004 Human Sciences Press, Inc.
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as a source of intervention. However, an examination of models of intervention suggests that practice may more typically be driven by a
pathology and problem focus. This is evident in some of the theories
often employed in social work intervention, including the problemsolving model, the psychosocial model, and cognitive-behavioral theory.
A third current challenge facing social work, as well as other mental
health and social service providers, is the emphasis on evidence-based
practice. The expectation is that assessment and intervention decisions should be tested and have some empirical support before being
used with children and families in need. Gaps in our empirical knowledge base, as well as the range of potential interventions, makes this
a daunting task for many practitioners.
In order to assist social work practitioners in facing these challenges, this article will discuss and illustrate how a risk and resilience
framework can provide a theoretical basis for social workers to conceptualize at multi-levels, and assist them in identifying and bolstering
strengths, as well as reducing risk. The risk and resilience framework
was developed in other disciplines (e.g., psychology and education) for
the understanding of individual behavior. The framework considers
the balance of risk (forces contributing to a problem condition) and
protective (internal and external resources for the protection against
risk) factors that interact to determine an individual’s ability to function adaptively despite stressful life events (Kirby & Fraser, 1997).
Social work researchers, Fraser (1997) and colleagues, in particular,
have expanded the framework, organizing risk and protective factors
into micro, mezzo, and macro-level system levels and referring to it as
the “risk and resilience ecological framework.” This framework fits
well with social work’s emphasis on empowerment and the strengthsbased perspective. The strengths perspective underlies the concepts of
“protective factors” and “resilience” in which people are not only able
to survive and endure, but also triumph over difficult life circumstances. And, the ecological emphasis of the framework expands the
focus beyond the individual to a recognition of systemic factors that
can create problems as well as ameliorate them.
The risk and resilience framework has also been empirically validated. That is, risk and protective factors have been identified through
empirical study, initially in several groundbreaking longitudinal studies in which at-risk youth were followed over time to determine the
factors that seemed to produce adaptation despite the adversity they
faced (e.g., Rutter, Maugham, Mortimore, & Ouston, 1979; Rutter,
1987; Wallerstein & Lewis, 1998; Werner & Smith, 1982). (See Gar-
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menzy, 1993, for a review). Other longitudinal and cross-sectional research (e.g., Bowen, Richman, Brewster, & Bowen, 1998; Carbonell,
Reinherz, & Giaconia, 1998; Dubow, Edwards, & Ippolito, 1997; Grant,
O’Koon, Davis et al., 2000; Nash & Bowen, 1999; Richters & Martinez,
1993; Resnick, Bearman, Blum et al., 1997; Runyan, Hunter, Scololar
et al., 1998; Weist, Freedman, Paskewitz et al., 1995; Wyman, Cowen,
Work et al., 1999) has followed, resulting in the accumulation of a
substantial literature.
To summarize, the risk and resilience ecological framework holds
a number of advantages for social work education and practice. The
framework offers a balanced view of systems in that it looks at both
risk and strength, and recognizes the complexity of individuals and
the systems in which they are nested. Risk and protective factors have
been delineated at their various system levels, through empirical evidence over repeated studies. However, in order to be of utility for social work assessment and intervention, several gaps must be addressed. First, despite the amount of writing and research amassed
on the risk and resilience framework, attention has focused primarily
on the understanding of individual behavior rather than being used
for goal formulation and intervention at the micro, mezzo, and macro
levels. The risk and resilience framework has tended to remain conceptualized at a theoretical level rather than becoming a tool for practitioners to assess and intervene most effectively with children and
their families (e.g., Hawley, 2000). In this paper we begin to fill these
gaps by presenting empirically-identified risk and protective factors,
organized at the micro, mezzo and macro levels. The objective of this
paper is to illustrate the potential utility of the framework as a means
for assisting clients to identify the multiple risks they face, and the
strengths they bring to the issues facing them. Although it is beyond
the scope of this paper to present intervention strategies at each of
the levels, we begin the discussion of how assessment and goal formulation can proceed from this risk and resilience ecological framework
across the three system levels.
Risk and Resilience Theory/Framework
Definitions
Although resilience has been identified in different ways, resilience
generally refers to the “absence of significant developmental delays or
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serious learning and behavior problems and the mastery of developmental tasks that are appropriate for a given age and culture” in spite
of the exposure to adversity (e.g., Werner, 2000, p. 116). Risk and protective factors resulting in resilience have been found in longitudinal
studies following children facing such adversities as poverty (e.g.,
Werner & Smith, 1982) or the mental illness of a parent (e.g., Rutter
et al., 1979). Some studies have examined the risk and protective factors that are correlated with the occurrence (or lack of occurrence) of
specific problems, such as teenage pregnancy (Kalil & Kuntz, 1999),
psychiatric disorders (Rutter et al., 1979), substance abuse (Johnson,
Bryant, Collins, Noe, Strader, & Berbaum, 1998; Wallace, 1999), and
adolescent depression (Carbonell, Reinherz, & Giaconia, 1998). Other
studies examined disorders that present risk, such as learning disorders (Svetaz, Ireland, & Blum, 2000) or health problems (Patterson
& Blum, 1996; Zimmerman, Smith, Gruber-Baldini et al., 1999) and
reported on the risk and protective factors that improved outcomes for
these conditions. Although different variables have been evaluated,
depending on the study, consensus has been reached about a number
of risk and protective factors operating for different problems, and
these are described below.
Identified Risk and Protective Factors
The following section discusses the risk and protective factors that
have been identified from empirical studies with thousands of at-risk
children and families. We have conducted an extensive research review and relied on the reviews of others, but recognize that we have
not captured all studies in this literature. However, every attempt has
been made to report main findings that have emerged.
While risk and resilience factors do interact with each other (discussed further in the following section on systemic effects), these have
been grouped by micro, mezzo and macro levels. The reader will also
note that at times, risk and protective factors are the converse of each
other. For instance, difficult temperament is a risk factor and easy
temperament is a protective factor at the individual micro level. Indeed, researchers have found risk and protective factors to be negatively correlated with each other (−.42) [Jessor, Van Den Bos, Vanderryn, Costa, & Turbin, 1997], suggesting the relationship between risk
and resiliency.
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Micro Level
The micro level comprises both individual factors of the child and environmental characteristics of the family, although we recognize the
intertwining of influences in that families transmit both genetic material and an environmental context to children (Wachs, 2000).
Individual Factors. Temperament is defined as “an early and persistent pattern of personality characteristics, including activity level, intensity or degree of energy in a response, persistence or attention span,
demandingness of others, quality of mood (irritability or quickness to
anger or display emotion), adaptability or capacity to adjust to change,
and rhythmicity or the regularity of sleep-waking periods, eating, and
elimination” (Barkley, 2000, p. 84). Easy temperament and an engaging, sociable, and affectionate personality have been identified as a
protective factor for infants and toddlers (Epps & Jackson, 2000),
whereas a child with an irritable temperament and who has difficulty
being soothed, is at risk for poor caregiving (Moffitt, 1993).
Good health is a protective factor; conversely, children with chronic
physical disorders are at moderate risk for adjustment problems (Lavigne & Faier-Routman, 1992), which may persist into adulthood, particularly for males (Pless, Power, & Peckham, 1993). In addition, the
parents of children with disabilities have double the risk of depression
as parents with non-disabled children (Singer & Yovanoff, 1996, as
cited in Patterson & Blum, 1996).
Intelligence (IQ) is a protective factor, producing higher school performance despite life stress and more effective problem-solving in peer
social situations (Wachs, 2000). Conversely, low IQ is a central risk
factor for anti-social behavior, over and above socioeconomic status
and race. Wachs (2000) cites evidence that the average juvenile offender has an IQ an average of one-half standard deviation lower than
youth without a criminal history. Moreover, youth with IQ one standard deviation lower than normal are at triple the risk for the development of conduct disorders.
Children with positive self-concepts and a self-perception characterized by an internal sense of control, and a belief that they can influence their environment and show effective coping strategies, are better equipped to face life stressors (Wachs, 2000).
Family Factors. Many studies have shown the central importance
of family factors in promoting resilience. Family factors identified
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have been safety in the home (Richters & Martinez, 1993), stability in
the home (Richters & Martinez, 1993), monitoring and structure (Li,
Stanton, & Feigelman, 2000; Steinberg, 2000), attachment (Erickson,
Egeland, & Pianta, 1989), and parental involvement in schooling (visiting the school, providing enrichment experiences, and supervising
homework) [Shumow et al., 1999], and the presence of these factors
exceeds the effects of neighborhood risk (Shumow et al., 1999) and low
socioeconomic status (Wyman et al., 1999). For school-age and adolescent children, authoritative parenting, defined as warmth and
involvement, but also firmness and consistency in developing rules
and limits that are developmentally appropriate, has been associated
with positive outcomes (Steinberg, 2000). More specifically, a father’s
involvement, support, and connection with the child further encourage
positive child outcomes (Biller & Trotter, 1994; Coltrane & Parke,
1998; McLanahan & Teitler, 1998). Conversely, factors compromising
parents’ abilities, such as parental substance abuse (Hawkins, Catalono, & Miller, 1992; Phares, 1997), are associated with substantial
risk.
Chronic marital discord and family violence are associated with maternal mental health in terms of increased risk of depression and posttraumatic stress disorder (Golding, 1999), aversive parenting practices (Krishnakumar & Buehler, 2000), and poor outcomes for children
in terms of traumatic symptoms and internalizing and externalizing
problems (e.g., Herrenkohl, Herrenkohl, Rupert, Egolf, & Lutz, 1995;
McCloskey, Southwick, Fernandez-Esquer, & Locke, 1995; Wolfe,
Jaffe, Wilson, & Zak, 1985).
Household composition refers to both the size of the family and the
number of parents in the home. Larger family size is a risk factor
as precious family resources are then spread among many children
(Werner, 2000). Living in a single-parent family has also been identified as a risk factor. While in dual-parent families, two adults can
provide financial security, guidance, and emotional support (Young,
Jensen, Olsen, & Cundick, 1991), single parents are more likely to
work full-time and therefore, are not as available for supervision,
monitoring, or time spent with the child (Newcomer & Udry, 1985).
Mezzo Level
The mezzo level includes those factors in the immediate social environment including neighborhood context, church, school and other
community resources available to families. The influence of each of
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these factors is discussed below; however, it is important to point out
(and evident in the discussion) that these aspects of the community
context intersect and interact with one another (e.g., schools are part
of the neighborhood), and other levels (e.g., individuals and families
make up neighborhoods).
Neighborhood. Although individual and family characteristics are
major contributors to child and young adult outcomes, numerous studies conclude the importance of neighborhood (Ellen, 2000; Levanthal
& Brooks-Gunn, 2000). Studies that have examined the effect of
neighborhood characteristics on individual and family outcomes found
that neighborhoods with high levels of economic disadvantage and social disorganization had poorer educational outcomes, and higher
rates of child abuse, crime and delinquency.
An extensive review of the literature on neighborhood effects (Levanthal & Brooks-Gunn, 2000) found evidence that living in a disadvantaged neighborhood had negative effects on various measures of
educational functioning, with effects becoming stronger as children
age. Further, neighborhood context has been identified as a factor in
whether individuals are at risk of engaging in such potentially harmful behaviors as the use of alcohol and drugs. Individuals in primarily
minority neighborhoods have greater exposure to alcohol, drugs and
tobacco. For example, reports on studies of billboard content have
found that alcohol and tobacco advertisements are more prevalent in
African-American and Hispanic-populated areas than in other communities (Wallace, 1999). In addition, African-American and Hispanic
children are more likely to report having been exposed to drug selling,
and perceive that drugs are easy to obtain in their community (Wallace, 1999). Moreover, neighborhood poverty is significantly associated
with alcohol-related problems among African-American men (JonesWebb, Snowden, Herd, Short & Hannan, 1997), and in antisocial behavior and drug use for youth (Dubow et al., 1997).
Criminal violence in neighborhoods is also associated with high
rates of unemployment and underemployment (Crutchfield & Pitchford, 1997), and exposure to violence can exact a price on children’s
mental health. A study of adolescents in Los Angeles County found
that the more threatening the neighborhood, the more likely adolescents were to report symptoms of depression, anxiety, oppositional defiant disorder, and conduct disorder (Aneshensel & Sucoff, 1996). Another study using data from a national survey of youth found that
neighborhoods with more social and physical problems were a predic-
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tor of depressive symptoms of youth (Eamon, 2002). And, a nationwide
study of 2-year-old twins concluded “that children in deprived neighborhoods were at increased risk for emotional and behavioral problems over and above any genetic liability” (Caspi, Taylor, Moffitt &
Plomin, 2000, p. 338).
Neighborhoods can however, represent a source of protective factors, especially for children. While neighborhood peers may have negative influences on such behaviors as drug and alcohol use, and criminal activity, some studies have found that adult neighbors who offer
structure and monitoring can be an important source of support for
children experiencing risks in their families (Werner & Smith, 1982).
Studies have also shown that middle-class and affluent neighborhoods
have generally positive effects on educational attainment and persistence in school for adolescents, and high SES neighbors contribute to
better cognitive outcomes for young children. Some recent studies
have also found that the more a neighborhood exhibited informal social controls, the lower its levels of violence and adolescent problem
behavior (for a review of these studies, see Levanthal & Brooks-Gunn,
2000).
Social Support Networks. Social supports can buffer the effects of
negative life events including teen parenthood (Brooks-Gunn & Furstenberg, 1986), divorce (Wolchik, Ruehlman, Braver & Sandler, 1989),
health problems (Hurdle, 2001), and violence (Berman, Kurtines, Silverman & Serafini, 1996). Perceived availability of social support has
also been shown to contribute to positive outcomes in programs targeted at reducing welfare dependency (Sansone, 1998). For younger
children in poverty, the presence of alternative caregivers and supportive persons, such as grandparents, older siblings, child-care providers, or nursery school teachers, is an important resiliency mechanism (e.g., Werner & Smith, 1982). Adolescents, too, seem to benefit
from available support. Among adolescents, those who feel close to parents, teachers, or classmates had better emotional health and were
less likely to engage in risky behaviors such as substance use, violence, and early sexual activity (Resnick et al., 1997). Negative social
relationships, on the other hand, can pose risks to mental health (for
a review of these studies see Lincoln, 2000).
More formal support systems enacted by community members may
also enhance protection for children. Research has shown that engaging in out-of-school activities and availability of community supports
has positive outcomes for children in terms of educational attainment
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and health status. Empirically-validated programs, such as Big Brothers/Big Sisters (e.g., Thompson & Kelly-Vance, 2001), and Head Start
(e.g., Currie & Thomas, 1995), and other youth organizations present
substantial protective factors (Werner, 2000). Conversely, the lack of
needed formal supports such as health care services can be a risk factor for families. For example, one study found an association between
late entry into prenatal care and residence in a distressed neighborhood with a shortage of office-based primary care physicians (Perloff
& Jaffee, 1999). Low income neighborhoods also have fewer community programs in which children can participate, limiting the range of
positive role models and supports available to them (Furstenberg,
Cook, Eccles, Elder & Sameroff, 1999).
Church/Religious Involvement. A particular type of social network
identified with positive health and mental health, as well as buffering
the effects of neighborhood risks, involves church or religious participation (Taylor, Ellison, Chatters, Levin & Lincoln, 2000). A study of
Hispanic, White, and African-American high school students determined that church attendance was significantly related to healthenhancing behaviors (e.g., healthy diet, exercise, etc.) [Jessor, Turbin
& Costa, 1998]. Religious attendance and religiosity have also been
significantly associated with a decreased likelihood of drug use among
adolescents (Albrecht, Amey & Miller, 1996; Miller, Davies, & Greenwald, 2000), reduced criminal involvement (Johnson, Jang, Larson &
Li, 2001), and lower levels of depressive symptomatology (Wright,
Frost & Wisecarver, 1993). In addition for African-American youth,
religious involvement may buffer the impact of neighborhood risk on
criminal offending (Johnson, Jang, Li & Larson, 2000). Research further indicates the positive relationship between religious involvement
and adult health outcomes and coping with stress (McCullough, Larson, Hoyt & Koenig, 2000).
School Environment. The importance of children’s perception of being safe at school and having supportive teachers, those who convey
caring and regard for their students with high expectations for children’s scholastic ability, is confirmed in most studies of at-risk children (Baker, 1999; Bowen et al., 1998; Garmezy, 1993). The protective
effect of school relationships may persist well beyond elementary
school, with early child-teacher relationships predicting long-term
school outcomes (Hamre & Pianta, 2001). A national longitudinal
study also found that perceived school connectedness is important to
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adolescents, providing a protective factor against numerous health
risk behaviors (Resnick et al., 1997).
Schools can also be a risk factor for children. Durlak’s (1998) review
of 1200 outcome studies found that in poor quality schools, characterized by such attributes as a nondemanding curriculum, ineffective
leadership, and generally poor relationships among school personnel
and with parents, students are more likely to drop out, have higher
rates of teen pregnancy and higher rates of behavior problems. In addition, negative teacher reactions, expectations, and responses to atrisk students have been linked to poorer academic achievement (Montague & Rinaldi, 2001; Babad, 1993).
Macro Level
Although the literature has not generally applied the terminology of
“risk and protective factors” at the macro level, ample evidence exists
that within the broad societal level, factors contribute to both individual problem situations and those that provide protection against risk.
At the macro level poverty, discrimination, and segregation are risks
that impact individual level functioning, whereas protection against
these risks is provided through the availability of social and income
supports, tax policies, and legal sanctions. While there may be some
disagreement as to the definition of what constitutes a “naturally occurring” protective factor at this level, we have chosen to follow the
example of others who categorize social policies, and access to resources and opportunities as community or environmental protective
factors (e.g., Durlak, 1998; Smokowski, 1998).
Income and Employment. Numerous studies have substantiated the
relationship between poverty and individual behavior and outcomes.
For example, in several studies, poverty was significantly related to
poorer cognitive outcomes for children (Brooks-Gunn, Duncan & Aber,
1997; Duncan, Brooks-Gunn & Klebanov, 1994; Shumow, Vandell &
Posner, 1999), and in others it was evident that those who have spent
at least part of their adolescence in a family below poverty are less
like to graduate from school than those who never lived in a poor family (Teachman, Paasch, Day & Carver, 1997). Poverty is also correlated with increased risk for child abuse and neglect (Garbarino,
1992); family violence (Gelles & Strauss, 1988); substance abuse (Wallace, 1999); and substandard housing with its related risks of exposure
to lead and other hazards resulting in poor health outcomes (McLoyd,
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1998; Yinger, 2000). Chronic poverty is also correlated with stress and
increased risk for mental health problems, particularly among African-American children (Grant et al., 2000). A review of studies provides evidence that unemployment has a detrimental effect on psychological well-being (see Murphy & Athanasou, 1999). In addition, high
unemployment and the lack of employment opportunities contribute
to fighting and drug use among adolescents (Bellair & Roscigno, 2000).
On the protective side, social policies and a strong economy both
have positive effects on the income and employment of individuals.
For example, Social Security payments to the elderly have a significant effect on reducing the percentage of individuals who are poor,
and Medicare covers many of their major health care costs. For the
working poor, economic supports include such programs as the Earned
Income Tax Credit (EITC) and food stamps which help them meet
household expenses (for a review of income support policies see Scholz
and Levine, 2000). The prosperity of the recent years demonstrates
that economic growth can increase both employment prospects and
wages of low-income workers (Freeman, 2000), and increases in the
minimum wage benefit women (Bernstein, Hartmann & Schmitt,
2000) and other low-wage workers (Addison & Blackburn, 1999).
Strong child support policies have also been shown to improve the
income of single-mother families (Garfinkel, Heintz & Huang, 2001).
Discrimination. According to national survey data, perceived discrimination has a strong association with measures of stress and mental health (Kessler, Mickelson & Williams, 1999). Community-based
surveys echo these findings with data indicating that experiences of
unfair treatment are significantly associated with psychological distress and life satisfaction (Schultz et al., 2000), and experiencing discrimination is directly related to depression (Finch, Kolody & Vega,
2000). As protective factors, when institutions adhere to the anti-discrimination laws in place in this country, employment and occupational outcomes for individuals are improved (Holzer & Neumark,
2000).
Ample evidence indicates discrimination is experienced by women
in the labor market, health care, housing, and social services (for a
review see Ladrine & Klonoff, 1997). However, only recently has research examined health and mental health correlates of discrimination for women. Findings from one study found that “sexist discrimination contributes to physical and psychiatric symptoms among
women, whether those women subjectively appraise sexist acts as
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stressful or dismiss them as inconsequential” (Ladrine & Klonoff,
1997, p. 117).
Many of the studies of risk and resilience have centered on minority
samples, African-Americans in particular, because of the overrepresentation of minorities in low SES stratas and communities (e.g.,
Bowen et al., 1998; Bradley, Whiteside, Mundfrom, Casey, Kelleher,
& Pope, 1994; Dubow et al., 1997; Grant et al., 2000; Lie et al., 2000;
Richters et al., 1993; Weist et al., 1995; Wyman et al., 1999). Belonging to a minority group compounds the effects of poverty. Not only are
minorities more likely to be poor (Institute for Research on Poverty,
2001), but their ability to escape poverty is hampered by discrimination in the labor market (Stoll, et al., 1999; Tomaskovic-Devey and
Roscigno, 1996), and housing (Galster, 1991; Massey & Lundy, 2001;
Ondrich, Ross & Yinger, 2000). In addition, minority children, particularly African-Americans, are less likely to receive the same education
as their non-minority counterparts. They are more likely to be identified for placement in special education classrooms (Coutinho & Oswald, 2000), and to have lower teacher expectations for academic
achievement (Roscigno, 1998).
Segregation. Several studies find that it is not just poverty that increases the risks of negative outcomes for ethnic/racial minority
groups, but also the segregation of those families within communities.
Strong and consistent evidence indicates that outcomes for AfricanAmericans are “substantially worse (both in absolute terms and relative to whites) in racially segregated cities than they are in integrated
cities. As segregation increases, blacks have lower high school graduation rates, are more likely to be idle (neither in school or working),
earn less income, and are more likely to become single mothers. A one
standard deviation reduction in segregation eliminates approximately
one-third of the difference between blacks and whites in most outcomes” (Cutler & Gaeser, 1997, p. 828). In another study, it was estimated that for black teens “compared with living in a racially mixed
neighborhood, living in a highly segregated neighborhood is associated
with a 50 percent increase in the rate of premarital first birth, regardless of neighborhood socioeconomic status” (Sucoff & Upchurch, 1998,
p. 571). Educational achievement is also influenced by the school segregation. There is a significant reduction in math and reading scores
for students who attend black segregated schools, and a significant
increase in those same scores for children in white segregated schools.
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These results hold even after controlling for family differences and
per-pupil expenditures within the school (Roscigno, 1998).
Residential segregation of minority populations into central cities
contributes to poverty because of relocation of jobs from the minority
neighborhoods to primarily white suburbs. This “spatial mismatch”
has resulted in “the creation of an oversupply of low-skilled workers
relative to the number of jobs for which they are qualified in the central city” (Stoll, Holzer & Ihlanfeldt, 1999, p. 2). Studies have shown
that access to jobs explains a significant proportion of the gap between
the employment of white and minority youth (Yinger, 2000).
Macro-level factors, however, don’t occur in isolation from risk and
protective factors at the other levels. For example, employment may
open opportunities for interacting with others and expanding social
support networks, which in turn may help the family provide a safe
and secure home. As noted earlier, the nature of ecological systems is
that the factors within each system have interactional influences on
each other.
Mechanisms Underlying Risk and Resilience
In a risk and resilience conceptualization, these interactional effects
may play themselves out in a couple of different ways. Namely, the
presence of a certain risk or protective factor may increase the likelihood of other risk and protective factors. Wachs (2000) provides the
example of how an aversive parenting style with poor monitoring increases the risk of children socializing with deviant peers. If parents
are overwhelmed by many environmental stressors, such as unemployment, lack of transportation and medical care, living in an unsafe
neighborhood, their ability to provide consistent warmth and nurturance may be compromised. This phenomenon also operates for protective factors. For example, adolescents whose parents provide emotional support and structure the environment with consistent rules
and monitoring, tend to group with peers who share similar family
backgrounds (Steinberg, 2000). Supportive parenting will, in turn, impact the characteristics of the child in that, through receiving it, children learn to regulate their emotional process and develop cognitive
and social competence (Wachs, 2000).
The systemic influences also play themselves out with certain individual characteristics. If a child has resilient qualities, such as social
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skills, effective coping strategies, intelligence, and self-esteem, they
are more likely to attract quality caregiving. Another example involves attachment patterns formed with early caregivers in infancy.
The attachment pattern persists into other relationships, for example,
with pre-school teachers (Wachs, 2000).
While the exact nature of how risk and protective factors work together are unknown, different mechanisms are hypothesized. Two
main models proposed are the additive (also called the compensatory)
model and the interactive (also called the immunity) model. In an additive model, protective factors exert an opposite positive effect counterbalancing the negative influence of risk (Pollard, Hawkins, & Arthur, 1999; Werner, 2000). In an interactive model, protective factors
enact a buffering function against risk. Although the exact mechanisms are not specified, information has accumulated about the number of risk factors that will begin to overwhelm a system and result in
negative outcomes (e.g., Fraser, Richman, and Galinsky, 1999; Kalil
& Kunz, 1999). The cumulative results of different studies seem to
indicate that that four or more risk factors represent a threat to adaptation (Epps & Jackson, 2000; Garmezy, 1993; Kalil & Kunz, 1999;
Runyan et al., 1998; Rutter et al., 1979). The next section will discuss
how risk factors can be ameliorated and protective factors can be bolstered through goal-setting and intervention planning.
Implications of the Resiliency Framework
for Assessment and Goal Formulation
Taking into account risk and protective factors and their interplay
within and among systems, several guidelines are suggested for assisting clients to assess the issues they face by examining risks and
protective factors available to them, and setting goals across system
levels. Table 1 highlights some of the identified risk and protective
factors (columns 1 and 2), and provides some potential intervention
goals suggested by the factors (column 3) within each system level.
Although specific interventions need to be guided by empirical evidence about what works for whom and in what setting, intervention
goals can be set by examining the risks and protective factors available in a given situation at the different system levels. Therefore, the
micro, mezzo and macro levels each need to be considered with the
client as potential points of intervention. For example, goals to reduce
the risk of child abuse for a family (a micro level risk factor) might
Micro:
Phenotypic:
Individual • Difficult temperament (Epps et
& family
al., 2000)
level
• Disability of child (Patterson &
Blum, 1996)
• Low intelligence (Wachs, 2000)
Environmental:
• Unstable or Unsafe home (Richters & Martinez, 1993)
• Early parental disruption (Rutter et al., 1979; Wallerstein &
Lewis, 1998)
• Inconsistent parental discipline
(Wachs, 2000)
• Parental substance abuse
(Hawkins, Catalano, & Miller,
1992; Phares, 1997)
• Family violence (Herrenkohl et
al., 1995; McCloskey et al.,
1995)
Risk Factors
Protective Factors
Phenotypic:
• Easy temperament (Wyman et
al., 1999)
• Intelligence (Wachs, 2000)
• Self-efficacy (Wachs, 2000)
• Self-esteem (Wachs, 2000)
• Good health (Werner, 2000)
Environmental:
• Safety in home (Richters & Martinez, 1993)
• Stability in home (Richters &
Martinez, 1993)
• Monitoring and structure in
family (Steinberg, 2000)
• Secure attachment (Erickson,
Egeland, & Pianta, 1989)
• Authoritative parenting (Steinberg, 2000)
• Parental school involvement
(Shumow et al., 1999; Steinberg, 2000)
Assessment
Micro Level:
• Build parent capacities (attachment and bonding, supervision
and monitoring, authoritative
parenting)
• Increase parental involvement
in school
• Involvement of children in support groups, church, etc.
• Strengthen marital/partner relationship
• Increase child’s self-esteem &
efficacy
Mezzo Level:
• Assure access to physical &
mental health services
• Develop school programs for
special needs children
• Assure availability of pre-school
programs
• Develop programs for fathers
Goals
Goals for Intervention
Risk and Protective Factors Across Systems Levels
TABLE 1
JACQUELINE CORCORAN AND ANN NICHOLS-CASEBOLT
225
Neighborhood context:
• Economically disadvantaged
neighborhood (Dubow, 1997; Levanthal & Brooks-Gunn, 2000;
Shumow et al., 1999)
• High levels of substance availability (Wallace, 1999; JonesWebb et al., 1997)
Mezzo: Im• Substandard housing (Yinger,
mediate
2000)
Social En- • Violence (Aneshensel & Sucoff,
vironment
1996; Crutchfield & Pitchford,
(neighbor1997)
hood,
Social Support:
school, & • Limited health care resources
church)
(Perloff & Jaffee, 1999)
Misc:
• Multiple risk factors present
(Wachs, 2000)
Risk Factors
• Assure availability of safe
houses for women & children
• Develop family violence prevention & treatment programs
Macro Level:
Advocate for
• Adequate health care for families
• Appropriate child welfare policies
• Adequate educational funding
for special needs children
Micro Level:
• Move to more affluent neighborhood
• Build family support network
• Engage family in community
support organizations
Mezzo Level:
• Increase community policing in
poor neighborhoods
• Improve physical environment
of neighborhood by decreasing
lead levels, improving lighting,
etc.
• Increase availability of physical
& mental health services and
community support organizations
• Sound caregiving system (Wyman et al., 1999)
• HS graduation (Werner, 2000)
• Nurturing, supportive parent
(Steinberg, 2000)
• Father’s cnnection with child
(Biller & Trotter, 1994; Coltrane & Parke, 1998; McLanahan & Teitler, 1998)
Neighborhood context:
• Affluent neighbors (Levanthal
& Brooks-Gunn, 2000)
• Supportive neighbors (Shumow,
1999)
Social Support:
• Social support networks (Berman, 1996; Brooks-Gunn & Furstenberg, 1986; Hurdle, 2000;
Wolchik, 1989; Sansone, 1998)
• Alternative caregivers and supportive persons (Resnick et al.,
1997; Werner & Smith, 1982)
• Community organizations (Currie & Thomas, 1995; Thompson
& Kelly-Vance, 2001; Werner,
2000)
Goals
Goals for Intervention
Protective Factors
Assessment
TABLE 1 (Continued)
226
CHILD AND ADOLESCENT SOCIAL WORK JOURNAL
Macro:
Broad
Socioeconomic
Level
• Few community social support
organizations (Furstenberg et
al., 1999)
• Negative social relationships
(Lincoln, 2000)
School factors:
• Poor quality schools (Durlak,
1998)
• Tracking of minority students
(Coutinho & Oswald, 2000)
• Negative teacher attitudes (Babad, 1993; Montague & Rinaldi,
2001)
Income:
• Poverty (Duncan et al., 1994;
Garbarino, 1992; Gelles &
Strauss, 1988; Grant et al.,
2000; McLoyd, 1998; Teachman, et al., 1997; Wallace,
1999)
• Unemployment (Bellair & Roscigno, 2000; Murphy & Athanasou, 1999)
Church/religious factors:
• Churches & religious involvement (Albrecht et al., 1996; Jessor et al., 1998; Johnson et al.,
2000; Miller et al., 2000; Taylor
et al., 2000; Wright et al., 1993)
School factors:
• Safe school & supportive teachers (Baker, 1999; Bowen et al.,
1998; Garmezy, 1993; Wachs,
2000)
• Positive relationships w/teachers (Hamre & Pianta, 2001)
Income:
• Availability of economic supports including: minimum wage
laws (Bernstein et al., 2000; Addison & Blackburn, 1999); income support programs (Scholz
& Levine, 2000); tax policies
such as EITC (Scholz & Levine,
2000); child support policies
(Garfinkel et al., 2001)
• Organize community (including
schools and churches) to address crime, provide social activities, etc.
• Improve safety of school
• Provide teacher training
Macro Level:
Advocate for:
• Increased funding for social services
• Increased funding for schools
• Policies to mandate teacher
training
Micro Level:
• Encourage self-advocacy in obtaining benefits
• Encourage application for EITC
• Encourage pursuing child support
Mezzo Level:
• Community economic development
JACQUELINE CORCORAN AND ANN NICHOLS-CASEBOLT
227
Goals
• Community anti-discrimination
policies
• Community strategies for integration
Macro Level:
Advocate for:
• Stronger child support policies
• More progressive tax policies
• Stronger anti-discrimination
laws
Protective Factors
• Strong economy (Freeman,
2000)
Discimination:
• Anti-discrimination laws
(Holzer & Neumark, 2000)
Segregation:
• Racially integrated city (Cutler
& Glaeser, 1997)
Discrimination:
• Effects on mental health (Finch
et al., 2000; Kessler et al.,
1999; Schultz et al., 2000)
• Racial discrimination (Galster,
1991; Massey & Lundy, 2001;
Ondrich et al., 2000; Roscigno,
1998; Steinberg, 2000; Stoll, et
al., 1999; Tomaskovic-Devey &
Roscigno, 1996)
• Differential application of laws
(Wallace, 1999)
• Gender discrimination (Ladrine
& Klonoff, 1997)
Segregation:
• Residential segregation (Cutler
& Glaeser, 1997; Galster, 1991;
Stoll et al., 1999; Sucoff &
Upchurch, 1998; Yinger, 2000)
Goals for Intervention
Risk Factors
Assessment
TABLE 1 (Continued)
228
CHILD AND ADOLESCENT SOCIAL WORK JOURNAL
JACQUELINE CORCORAN AND ANN NICHOLS-CASEBOLT
229
include working with families to identify and address needed parenting skills (micro level intervention), community support resources
(mezzo level intervention), and policies that reduce poverty (macro
level intervention). As another example, goals to address housing discrimination faced by a client (a macro level risk factor) might include
assisting the client to assertively discuss the situation with a local
authority (micro level intervention), organize the community to protest the discrimination (mezzo level intervention), and file a class action law suit (macro level intervention).
As can be seen in Table 1, goal formulation for micro risk and protective factors include identifying interventions that reduce the risks
and build on the strengths of families and children through enhancing
their skills, their access to programs and services, and the availability
of adequate and appropriate resources and policies. Goal setting for
the mezzo risk and protective factors include micro-level interventions
that focus on changing the situation of the family (e.g., helping them
move out of a high-risk neighborhood), mezzo-level strategies that focus on changing the social environment in which the family interacts,
and macro-level strategies that address inequalities within the social
environment. The macro risk and protective factors suggest intervention goals that encourage individuals to advocate on their own behalf,
for communities to address economic and social inadequacies and inequities, and for macro systems to develop policies that improve income and reduce discrimination and segregation.
The resilience framework provides direction for strategies that can
be considered for both the prevention of risks as well as the reduction
or amelioration of the effects of risk factors once they have occurred.
Adequate prenatal care can prevent birth related risks associated
with low birth weight and premature birth, and improving the safety
of a neighborhood may help prevent mental health problems among
children. Once the risk has been experienced, supports can be put in
place to help reduce the negative impact. For example, programs that
focus on enhancing fathers’ involvement in single-mother families
may reduce the risks associated with this family structure, and the
provision of employment and income supports can alleviate the problems associated with poverty.
While social work practitioners may not be experts in implementing
interventions in all system levels, they must be knowledgeable about
the potential range of micro, mezzo and macro factors that affect the
functioning of individuals and families. And, more importantly, they
must be committed to assuring that their assessment and goal setting
230
CHILD AND ADOLESCENT SOCIAL WORK JOURNAL
with the client system consider each of these levels as a potential target for intervention.
Conclusion
This paper illustrates that the risk and resilience ecological model can
be used as a framework for assessment and intervention planning. It
organizes potential strengths to bolster the individual and the environment, and pinpoints the risks to ameliorate from the different system level influences that social workers can potentially enact.
Although this framework holds great promise, there are still considerable gaps in our knowledge regarding strategies for enhancing
protective factors and reducing risks. Research has identified the “naturally occurring” risk and protective factors that contribute to resiliency, but there is a continuing need for empirically validating interventions that build on the strengths of client systems, and result in
positive outcomes for families and children. Empirical evidence has
shown that the most effective interventions target risk and protective
factors across system levels (Durlak, 1998; Smokowski, 1998). Social
Work, with its strengths-based perspective that recognizes the person
in the environment, is in a unique position to contribute to the knowledge in this area. Our work across system levels and within the range
of organizations provides an opportunity for implementing and evaluating a range of strategies.
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