1 Family Relations, 55 (January 2006), Blackwell Publishing. Copyright 2006 by the National Council on Family Relations. Protective Family Factors in the Context of Neighborhood: Promoting Positive School Outcomes Michael E. Woolley Andrew Grogan-Kaylor* Abstract: Three developmental contexts school, neighborhood, and family influence school outcomes. The focus of the current investigation was on the promotive role of 4 family factors family satisfaction, family support, family integration, and home academic culture on 3 school outcomes. These outcomes included student self-reported sense of school coherence, avoidance of problem behavior, and academic performance. Utilizing a hierarchical linear modeling strategy and a national probability sample, the family protective factors of interest displayed a significant but differential pattern of impact on the 3 school outcomes studied. Findings related to neighborhood and school factors, as well as race/ethnicity, are also reported and discussed. The implications of these findings with respect to practice and policy are addressed. Key Words: child development, family functioning, neighborhood effects, risk and protective factors, school outcomes. School success is a central outcome of the complex processes that influence child development. Such processes occur within and among three key environments: school, neighborhood, and family (Richman, Bowen, & Woolley, 2004). For example, various characteristics of the school environment have been demonstrated to affect school behavior and academic outcomes such as the relationships between and among staff and students, school safety, and school size (Freiberg, 1999). Likewise, neighborhood factors such as crime and violence, peer culture, poverty, and neighborhood satisfaction have also been shown to have an impact on school outcomes (Bowen, Bowen, & Ware, 2002). Theoretical Framework and Study Aims Guided by a contextualist worldview (Goldhaber, 2000), the current study conceptualizes physical and social environments as playing key roles in developmental outcomes. This conceptualization was informed by the eco-interactional-developmental (EID) perspective (Richman et al., 2004). Informed by both the ecological systems theory and a developmental orientation, the EID perspective suggests that there are hierarchical environmental contexts that impact developmental outcomes (Bronfenbrenner, 1986). Microsystems are settings that directly influence a child including both the physical environment and his or her social relationships. Mesosystems are the connections among these microsystems; examples would include the family culture with respect to educational issues, or the relationships between the family and neighborhood residents and organizations. This nested map of the environments that youth inhabit is typically the central aspect of ecological theory that is discussed. However, Bronfenbrenner *Michael E. Woolley is an Assistant Professor in the Schools of Social Work and Education, University of Michigan, 1080 South University Avenue, Ann Arbor, MI Andrew Grogan-Kaylor is an Assistant Professor in the School of Social Work, University of Michigan.
2 94 Family Relations Volume 55, Number 1 January 2006 (2005) has also presented two mechanisms for how these environments impact development. Proximal processes consist of the interpersonal relationships between the developing child and the adults and peers in his or her microsystems. Environmental contexts are the other characteristics of these microsystems, from the local economy to neighborhood crime rates and the availability of recreational activities. Both the mechanisms inform us about how the environment influences school outcomes. In combining ecological theory with a risk, protection, and resilience perspective, Fraser (2004) also provides a conceptual framework that informs practice and policy. Risk factors are environmental characteristics that predict poor developmental outcomes, whereas protective factors promote positive developmental outcomes. Resilience is the dynamic interplay of environmental, social, and individual protective factors, in the context of risk exposure, leading to positive adaptation and desirable outcomes (Luthar, Cicchetti, & Becker, 2000). From an EID perspective, resilience-based practice requires both assessing strengths and building protection while assessing deficits and reducing risk exposure (Pollard, Hawkins, & Arthur, 1999). Informed by an EID perspective, school outcomes can be conceptualized on a developmental continuum of distal to proximal outcomes with respect to school achievement. Similar to the hierarchy of needs as described by Maslow (1970), students have a hierarchy of school achievement needs in which certain conditions must be satisfied in order for school achievement to be realized. Essentially, positive and supportive social environments are foundational to appropriate school behavior, which in turn leads to children s perceptions of school as enjoyable and meaningful, which ultimately leads to successful academic performance. Further, it can be anticipated that factors impacting school outcomes will have differential impact at various points on this continuum. For example, supportive parenting may be an important predictor of appropriate school behavior but may have little influence on grades. Such a hierarchical model can inform targeted intervention approaches. For example, if a student has behavioral problems, those must be addressed before significant changes in academic performance will be attainable. Therefore, to be informative of effective practices and policies, school-focused research should be informed by this school outcome continuum and include important variables from the three key microsystems. Below, we review recent literature addressing the influence of these three microsystems school, neighborhood, and family on school outcomes. School Factors The social climate of a school has been shown to influence the spectrum of student outcomes from social-emotional functioning and behavior to grades and academic performance (Cook, Murphy, & Hunt, 2000; Freiberg, 1999). For example, the relationships among school staff, and the level of trust in particular, have been shown to have an effect on student outcomes (Hoy & Sweetland, 2001). Also, peer social interactions, such as the level of teasing and bullying, have been shown to impact student performance (Smith & Brain, 2000). Similarly, student perception of school safety has been shown to have a significant association with school performance (Bowen, Richman, Brewster, & Bowen, 1998). School outcomes are impacted by how a student perceives and feels about school. This is often referred to as a student s sense of school coherence, which is measured as the extent to which a student looks forward to school, feels competent, and sees school as meaningful. A student s relationship with teachers has a significant impact on his or her sense of school coherence (Croninger & Lee, 2001). Research has shown that students who see teachers as supportivehavebetterattendance,spendmoretimestudying, avoid problem behaviors, are more engaged in school, and make better grades (Rosenfeld, Richman, & Bowen, 2000). The critical nature of the relationships between students and teachers, and school climate in general, is even more important to the success of students from families who are lower income or ethnically diverse (Johns, 2001). Other school factors have been investigated such as school size (Bowen, Bowen, & Richman, 2000) and the emphasis on academic achievement within the climate of the school (Goddard, Sweetland, & Hoy, 2000). Neighborhood Factors Mounting evidence also supports the connection between neighborhood factors and school outcomes. For example, Bowen et al. (2002) reported that negative school behaviors were associated with increased neighborhood social disorganization. Likewise, Vartanian
3 Protective Family Factors and School Outcomes Woolley and Grogan-Kaylor 95 and Gleason (1999) reported that African American students who lived in neighborhoods with higher average household incomes, or increased percentages of twoparent households, demonstrated higher high school graduation rates. Similarly, Williams, Davis, Miller- Cribbs, Saunder, and Williams (2002) reported that neighborhoods with higher levels of deterioration uch as abandoned buildings, drug dealing, and violent crime predicted decreased intention to finish high school and lower grade point averages (GPAs). Neighborhood characteristics have also been associated with students feelings and attitudes toward school. Nash (2002) found that neighborhood informal social control, crime, and negative peer culture had direct negative effects on a student s sense of school coherence. South, Baumer, and Lutz (2003) likewise found that exposure to peer groups that devalue education leads to lower educational attainment. Neighborhood crime and violence have also been associated with school outcomes. In a study investigating crime rates and school violence, Bowen and Van Dorn (2002) found that increasing levels of neighborhood crime predicted increased violent school behaviors such as fighting and property destruction. Others have found similar connections between crime and youth actingout behaviors (Nash & Bowen, 1999). However, selection bias leads to concerns about the findings in such studies because unobserved variables may jointly determine neighborhood choice and school outcomes. Randomized studies of neighborhood effects are a possible answer to this confound, but randomized studies of neighborhoods are difficult to do for obvious reasons. Leventhal and Brooks-Gunn (2004) were able to complete such a randomized study because of a housing relocation program with a randomized component and found that male students who moved from a high-poverty neighborhood to a low-poverty neighborhood experienced increased achievement scores. This finding was explained by both more time spent on homework and increased feelings of school safety. Family Factors Most family practitioners and researchers would quickly agree that family factors influence child development and therefore school outcomes. Research from a variety of disciplines have investigated such family factors. For example, Bowen and Bowen (1998b) found that the culture within a family as it relates to education was linked to academic performance, although mediated by adolescents level of school coherence. Other demographic family characteristics, such as family structure and socioeconomic status, have also been linked to student behavior and sense of coherence about school. Nash (2002) found that higher economic resources, and having two parents in the household, had direct effects on educational behavior, which included grades, attendance, and negative behaviors such as fighting and skipping classes. Although research on the impact of school, neighborhood, and family factors on school outcomes is burgeoning, many researchers are also focusing on the mesosystem-level interactions. For example, several studies have focused on how the linkages between school and home influence school success (Booth & Dunn, 1996; Bowen & Bowen, 1998a; Chavkin & Garza-Lubeck, 1990; Comer & Haynes, 1991; Eccles, Lord, & Roeser, 1996; Lawson, 2003; Noblit, Malloy, & Malloy, 2001; Thompson, 2003). Other studies have investigated the interplay between school and neighborhood factors (Bowen & Van Dorn, 2002; Bowen et al., 2002; Ensminger, Lamkin, & Jacobson, 1996). Still other studies have focused on the connections between neighborhood and family factors (Coley & Hoffman, 1996; Garbarino & Kostelny, 1993; Kupersmidt, Griesler, DeRosier, Patterson, & Davis, 1995). The current study includes school and neighborhood factors in models to investigate the role family protective factors play with respect to school outcomes. Method Utilizing a nationally representative sample of middle and high school students, the current study investigated the influence of four family protective factors on school outcomes. These family protective factors were student reported and included (a) family satisfaction, (b) family support, (c) family integration, and (d) home academic culture. The school outcomes investigated were also measured by student self-report and included (a) sense of school coherence, (b) avoidance of problem behavior, and (c) academic performance. Included in the analyses were school climate characteristics and known neighborhood risk and protective factors. When individuals are nested such as within schools or neighborhoods there are environmental
4 96 Family Relations Volume 55, Number 1 January 2006 factors that are shared across those individuals. Such shared environments, for example, the students within the schools in the current research, violate assumptions required for ordinary least squares regression analyses about the independent and identical distribution of error terms. To appropriately model such multilevel data, an analytic strategy should incorporate the nested nature of that data. Therefore, a two-level hierarchical linear modeling (HLM) strategy was utilized in the current research. The first level contained individual responses from the School Success Profile (SSP), whereas the second level contained variables aggregated by either the county or the zip code in which the school was located. Because only a single school was sampled in each Level 2 unit zip code and county a two-level model was appropriate (Raudenbush & Bryk, 2002). Sample The sample was selected utilizing a two-stage stratified design similar to that used by the National Center for Education Statistics to collect data from a nationally representative sample of 2,099 middle and high public school students. This sampling strategy ensured adequate representation of students across gender, race, local population base, school size, and region of the country. The sampled students were members of a randomly selected English class in each of 93 schools with 93 different zip codes, representing 84 counties, in 31 states. Louis Harris and associates collected the data between October 1996 and February Measures The data utilized for this study came from three sources. First, the SSP (Bowen, Woolley, Richman, & Bowen, 2001) was administered to all students. The SSP is a self-report instrument for use with middle and high school students that measures risk and protective factors impacting school outcomes. The SSP has been used for both research and school practice for more than 10 years, and Bowen, Rose, and Bowen (in press) have recently reported extensive psychometric studies of its validity and reliability. The second and third data sources were the FBI Uniform Crime Report (UCR) and the 1990 U.S. Census. The various measures utilized from these three data sources are described below. Reported reliabilities Cronbach s alphas or Kuder- Richardson 20s (K-R 20) for the scales with dichotomous responses were estimated using the current data set. Level 1 School Measures Two Level 1 school variables were coded from the SSP survey. These variables reflect students perceptions about school safety and teacher support. School safety. This SSP scale includes 15 items that measure aggressive, acting-out, and violent behavior by students at school. The scale measures the behaviors of students other than the respondent and includes items that ask about other students stealing, destroying property, fighting, physically abusing teachers, and using drugs or alcohol (a ¼.91). Teacher support. This SSP scale includes nine items measuring students perceptions of the social support they receive from their teachers. Items ask about such teacher behaviors as really listening to what students have to say, willingness to help students after school, encouraging students to do well, respecting and appreciating students, and caring whether or not students come to school (K-R 20 ¼.82). Level 1 Neighborhood Measures Level 1 neighborhood variables included three SSP scales. These scales measured students perception of neighborhood satisfaction, safety, and peer behavior. Neighborhood satisfaction. This SSP scale consists of seven items that measure a student s satisfaction with his or her neighborhood by targeting such aspects as interpersonal relationships, feelings of safety, and availability of enjoyable activities (K-R 20 ¼.65). Neighborhood safety. This SSP scale includes 12 items measuring a student s perception of his or her neighborhood as having a low incidence of crime and violence. Items ask about neighborhood occurrences including neighbors being robbed or mugged, hearing gunshots, the sale of drugs, gang fights, and youth being threatened with a weapon (K-R 20 ¼.72). Neighborhood peer culture. This SSP scale includes seven items measuring the likelihood of various positive and negative behaviors by youth in the student s neighborhood. The behaviors measured include getting good grades, graduating from high school, going to college, getting in trouble with the police, using drugs, or joining a gang (K-R 20 ¼.84).
5 Protective Family Factors and School Outcomes Woolley and Grogan-Kaylor 97 Level 1 Family Measures Four family variables predicted to promote positive school outcomes were the focus of the current analyses. These four measures were SSP scales that measured students perception of family integration, satisfaction, support, and home academic culture. Family satisfaction. This SSP scale includes five items that measure a student s satisfaction with the way his or her family respond to the youth in situations such as needing help when something is bothering him or her, responding to his or her feelings, and talking things over when he or she needs to (KR-20 ¼.84). Family integration. This 7-item SSP scale measures positive interactions among all family members, such as support during difficult times, loving and caring, spending time together, and working together to solve problems (a ¼.90). Family support. This SSP scale includes 20 items that measure social and instrumental support provided to the student by adults in the home, such as took the student places when needed, told the student that he or she did a good job, gave encouragement, stood up for the student when he or she was in trouble, gave the student privacy when he or she needed it, and cared for the student when he or she was sick or upset (a ¼.96). Home academic culture. This SSP scale includes six items that measure student reports of behaviors exhibited by the adults at home that contribute to a positive home culture with respect to school. Items in this scale ask about those adults showing interest in what a student is studying at school, in other school activities, selecting courses, and homework (K-R 20 ¼.70). Level 1 Student Demographics and Control Measures Five variables were entered at Level 1 in the models to control for student demographic characteristics. These variables include age, gender, race/ethnicity, and a proxy variable for family income. Finally, an SSP item asking students about having repeated one or more grades was included. This variable was included because previous analyses using SSP data have consistently revealed that this variable is a significant predictor of school outcomes beyond variables from all three key microsystems. Age. This variable was measured using an SSP item, with response options ranging from 9 years old or younger to 20 years old or older in 1-year increments. Gender. This variable was measured using an SSP item self-reporting gender. Race/ethnicity. This variable was measured using an SSP item, with response options including Black/ African American, Hispanic/Latino, White, and other race/ethnicity ( Multiracial, Asian or Pacific Islander, Native American or Alaska Native, and Other were combined into the other race/ ethnicity category because of small sample sizes). Free or reduced price lunch. An SSP item asking students if they receive free or reduced price lunch at school was utilized to measure this proxy for socioeconomic status. Repeated one or more grades. This variable was measured with an SSP item asking each student how many grades he or she had repeated in school; students reported repeating none, one, two, or three or more grades. For the current analyses, this variable was dichotomized to indicate if each student had repeated no grades, or repeated one or more grades. Level 2 Neighborhood Measures Level 2 neighborhood variables include data from the FBI s 1993 UCR and the 1990 Census. It is important to point out that in most neighborhood effects research, neighborhood is defined as where the family resides. However, in this study, neighborhood is defined by the location of the child s school (county or zip code). This is because the outcomes investigated are school outcomes; therefore, these outcomes are nested within the neighborhood of the school. Violent crime index. This county-level 1993 UCR measure represents rates per population of violent crimes including murder, manslaughter, rape, assault, and robberies. Child poverty rate. This county-level census variable is the percentage of children below the age of 17 years who are living below the poverty level. Neighborhood affluence. This zip code level census measure is the proportion of households with an income of $50,000 or higher. Residential stability. This zip code level census variable is the proportion of neighborhood residents who moved into the neighborhood within the past 10 years.
6 98 Family Relations Volume 55, Number 1 January 2006 School Outcome Measures Three SSP scales were used to represent a continuum of school outcomes starting with school behavior, then school coherence, and finally school performance. Avoidance of problem behavior. This SSP scale includes seven items that measure self-reported indicators of student avoidance or engagement in problem behaviors at school. Problem behaviors asked about include the student getting sent out of class for his or her behavior, calling other students bad names, fighting, and getting suspended or expelled (a ¼.72). Student sense of school coherence. This 9-item SSP scale measures a student s sense of school as coherent that school makes sense and the student feels comfortable about his or her ability to succeed at school. Individual items ask about a student s feelings of looking forward to going to school, being able to figure out what to do in most situations at school, feeling unsure at school, and feeling mixed up or confused at school (a ¼.72). Academic performance. This measure is a single SSP item where students self-reported grades on his or her most recent report card on a 5-point scale ranging from Mostly a s and b s to Mostly d s and f s. Previous research with the SSP found that the students were quite accurate when self-reporting their grades (Richman, Rosenfeld, & Bowen, 1998). Results We have included both standardized and unstandardized coefficients in the results for the current study. Unstandardized coefficients are appropriate when assessing the magnitude of a significant variable in relation to its measurement scale. However, standardized coefficients are more appropriate when looking across variables within a model to compare the relative influence of variables originally measured on different scales. Standardized coefficients were computed according to the standardization procedure as detailed in Agresti and Finlay (1997), which Hox (2002) has noted is appropriate in the HLM context. Descriptive Statistics Please refer to Table 1 for detailed descriptive statistics for the sample. Briefly, the sample was evenly divided by gender and ethnically representative of the U.S. population. On average, the students were just older than 14 years. Utilized as a proxy for economic need, 29% of the students qualified for free or reduced price lunch. Hierarchical Linear Models The intraclass correlation coefficients for the three school outcomes reveal that 5.7% of school behavior, 3.3% of school coherence, and 17.5% of academic performance variance was found between the schools. These percentages reinforce the nested nature of school outcomes and indicate differential impact of the key microsystems across the school outcome continuum. Family factors. Several family factors were associated with school outcomes. Interestingly, of the family factors, only home academic culture was associated with students grades (see Table 2, Model 3). Students who reported a stronger home academic culture also reported higher grades. As can be seen in Table 2, Model 2, family factors were most consistently associated with school coherence. Increases in family integration, family support, and home academic culture were all associated with increases in school coherence. Family satisfaction and family integration were associated with avoiding problem behavior. Neighborhood factors. Neighborhood-level factors, as measured by respondents perceptions of their neighborhoods, were also related to school outcomes. In Table 2, Model 3, it can be seen that increases in perceptions of neighborhood safety were associated with improved academic grades. Neighborhood satisfaction was associated with school coherence. Increases in neighborhood safety and improvements in neighborhood peer culture were associated with a greater ability to avoid problem behaviors (see Table 2, Model 1). The data set used in the current study also contained several variables measuring community characteristics from the 1990 Census or from the 1993 UCR. These variables were associated with several school outcomes. Increases in the neighborhood violent crime index were associated with decreases in grades as well as a decreased ability to avoid problem behavior. Interestingly, changes in the neighborhood level of child poverty were not associated with any of the school outcomes that we examined. However, in Table 2, it can be seen that increases in affluent
7 Protective Family Factors and School Outcomes Woolley and Grogan-Kaylor 99 Table 1. Descriptive Statistics of Key Study Variables Variables Level 1 Variables Level 2 Variables M SD % M SD Grades School cohesion Avoiding problem behavior Child s age in years Family satisfaction Family integration Family support Home academic culture Educational monitoring Neighborhood satisfaction Neighborhood peer culture Neighborhood safety School climate Teacher help Gender Female 52 Male 48 Repeated a grade Yes 21 No 79 Race White 63 Black 15 Latino 10 Other 12 Eligible for free lunch Yes 29 No 71 Violent crime index Child poverty Affluent Stability Vacant Note. Means and standard deviations are reported for continuous variables, whereas percentages are reported for dichotomous variables. neighbors were associated with an increased ability of avoiding problem behavior. Similarly, in Table 2, Model 3, increased neighborhood stability was associated with better grades. School factors. The data set used in the current study also contained two measures of school climate: school safety and teacher support. School safety was associated with improvements in school coherence, as well as increased success at avoiding problem behaviors. Teacher support was associated with improvements in all three school outcomes studied. Repeating a grade showed associations with all three school outcomes. Students who had repeated a grade reported lower grades than students who had not repeated a grade. Students who had repeated a grade also reported lower levels of school coherence than students who had not repeated a grade. Additionally, students who had not repeated a grade reported a higher level of avoiding problem behaviors than students who had repeated a grade.
8 100 Family Relations Volume 55, Number 1 January 2006 Table 2. Hierarchical Models of Three School Outcomes: Problem Behavior, Sense of School Coherence, and Academic Performance Model 1: Avoidance of Problem Behavior Model 2: Sense of School Coherence Model 3: Academic Performance Variable Coefficient SE Standard Coefficient t Coefficient SE Standard Coefficient t Coefficient SE Standard Coefficient t Level 1 variables Gender, c ** ** Child s age, c ** * Black, c ** Latino, c Other race, c * Eligible for free lunch, c ** Repeated a grade, c ** ** ** Family measures Family satisfaction, c * Family integration, c * * Family support, c * Home academic culture, c ** ** Neighborhood measures Neighborhood satisfaction, c ** Neighborhood peer culture, c * Neighborhood safety, c ** ** School measures School safety, c ** * Teacher support, c ** ** ** Level 2 variables Intercept, c ** ** ** Violent Crime Index, c * * Child poverty, c Affluent, c * Stability, c * Note. The title of each of the three models is the outcome variable for that model. *p,.05. **p,. 01.
9 Protective Family Factors and School Outcomes Woolley and Grogan-Kaylor 101 Other variables. Net of all factors, child ethnicity did not have an effect on academic performance or avoidance of problematic school behaviors. Compared with White students, Black students and students of other races demonstrated higher levels of school coherence (see Table 2 all models). Controlling for other variables, eligibility for free lunch only had an effect on one school outcome, lower grades. Gender had an effect on some school outcomes. Female students reported higher grades than male students, and female students were more able to avoid problem behavior than male students. However, gender did not have an effect on school coherence. Students ages also had an effect on some school outcomes. Older students reported slightly lower grades but higher levels of school coherence than younger students. Discussion Results in the current study contribute to the accumulating evidence that the contextual aspects of school outcomes are complex to model and analyze. This complexity comes from both the multivariate nature of the school context and because different school outcomes are influenced by different factors within the family, school, and neighborhood microsystems. All three of these contexts presented significant factors, and we will start our discussion with the family factors. It was predicted that the four family protective factors would reveal a pattern of differential influence on the three school outcomes. The results of the current analyses support such a pattern. Starting with Table 2, Model 1, which depicts the model for school behavior, only two of the family protective factors showed promotive effects on the avoidance of school problem behaviors. These two factors were family integration and family satisfaction. These results indicate that the family factors most linked to school behaviors are family emotional interactions. Such family interactions would include those that lead youth to feel satisfied about being helped out in times of distress, feel loved and cared for, and feel that they were given plenty of parental time and attention. Table 2, Model 1 details the school coherence model, in which three of the family protective factors were significant family integration, family support, and home academic culture. These results indicate that school coherence is strongest in youth whose family displays a pattern of cooperative and supportive interactions such as work together to solve problems, provide each other with loving support, talk about things youth study in school, and encourage youth to do well in school. Additionally, a pattern of differential roles of these four family factors with respect to the continuum of school outcomes is emerging with the family integration factor significant for both school behavior and coherence; however, the three other family factors were only associated with either the school behavior or school coherence outcomes. Looking at Table 2, Model 3, the model for school performance, the only statistically significant family factor was home academic culture. This indicates that although family integration, support, and satisfaction are significantly associated with school behavior and coherence, these family factors were not associated with academic performance. This result suggests that the most influential family processes on academic performance are parental behaviors such as attending school events or meetings, checking on homework, talking with youth about their studies, or encouraging youth to do well in school. This finding further supports the assertion that the four family protective factors differentially impact school outcomes along the proposed continuum from school behavior to academic performance. Such a finding illustrates the benefit of conceptualizing a model that presents outcomes along a continuum, then formulating research strategies that identify the association between that continuum and predicted risk and protective factors. If this study had simply investigated school, family, and neighborhood factors with respect to school achievement, the role of family satisfaction, family integration, and family support would have been missed. Examining the standardized coefficients across the three models reveals the role of school and neighborhood factors, with respect to the three school outcomes. For school behavior, the factors with the largest impact were neighborhood safety and peer culture. This finding fits with previous research using this same data set (Bowen et al., 2002). The next two factors were teacher support and school safety, a finding also in-line with previous research with the SSP (Rosenfeld et al., 2000). Therefore, caring and interested adults at school and at home, and safety at school and in the neighborhood, set the stage for positive school behaviors.
10 102 Family Relations Volume 55, Number 1 January 2006 In terms of school coherence, it is not surprising that teacher support emerged as the most predictive factor. As discussed above, the social climate within a school is critical to school outcomes, and a central part of that social climate is determined by teachers. However, home academic culture came next, followed by family support and integration. In fact, that constellation of family factors accounted for more variance than teacher support, reiterating the powerful impact of family on school outcomes. In terms of school academic performance, teacher support revealed the largest coefficient, which is consistent with previous research (e.g., Croninger & Lee, 2001; Johns, 2001). Neighborhood safety came next, which further supports previous research findings about the importance of safe environments to students (Bowen & Van Dorn, 2002; Kupersmidt et al., 1995). Home academic culture had the third largest coefficient. The top three predictors of school performance came from each of the three microsystems neighborhood, school, and family reiterating the multisystemic influences and morphogenetic nature of school outcomes, supporting the application of the EID perspective. Other findings from the current study are noteworthy. With two exceptions African American and other race/ethnicity students in the school coherence model race/ethnicity was not a significant factor in these three models when important family, neighborhood, and school variables were included. This suggests that previously reported race/ethnicity differences may have been confounded by contextual variables and that insight into the achievement gap may be found in these contextual domains. Additionally, when students reported repeating one or more grades, significantly poorer results were found across the school outcomes continuum. Although it is likely that repeating a grade may function as a proxy measure for a cluster of school risk factors, this finding should lead school professionals to be cautious about holding students back. Some methodological limitations of the current study should be noted. First, because of the crosssectional nature of the data used in this study, causal direction cannot be established. Alternative causal directions and relationships are possible. Indeed, it is likely that poor school outcomes have reciprocal causal relationships with teacher, parent, and family interactions. However, the current study is guided by the underlying assumption that it is the adults in a youth s life who should take responsibility for making positive change and creating promotive influences. Selection bias may have been a factor in some of the observed neighborhood effects. Such effects found may be confounded by unobserved variables associated with the decision about where to live, which is interconnected with the choice of school. However, it must be noted that the four measures of family functioning and the demographic characteristics that were included in this study provided a measure of control for selection bias. Future research should investigate the differential impact of family, neighborhood, and school factors on school outcomes, including examining cross-level mediation and moderation effects. Such research would profit from longitudinal data and analytic techniques designed to address causal direction. Research efforts are also needed to develop and test interventions focusing on specific protective variables and their associated outcomes. This presents an ambitious but potentially fruitful research agenda for improving school outcomes for youth. Implications for Family Practice and Policy The current findings can inform both practice and policy. Two factors that were most associated with avoiding problem behavior at school were family integration and family satisfaction, suggesting that interventions aimed at increasing family integration and youth satisfaction with his or her family may decrease school behavior problems. With regard to school coherence, three of the family protective factors were significant family integration, family support, and home academic culture. This finding also can inform family intervention programing with respect to efforts to increase student school coherence. The current findings suggest that school coherence is a vital precondition to academic achievement. Therefore, family interventions that advance supportive family interactions and parental school involvement will likely increase school coherence and therefore academic performance. The current findings suggest that if a student does not exhibit behavior problems and has a positive sense of school as coherent, the most effective family intervention to advance school academic achievement is to increase parental attention to school issues. Examples might include (a) school-based
11 Protective Family Factors and School Outcomes Woolley and Grogan-Kaylor 103 programs to reach out to parents to involve them in the school process, (b) school practitioners such as counselors and social workers providing psychoeducational programing to assist parents to be more involved in their child s education and to communicate the importance of school to their child s future, or (c) Parent Teacher Organizations that provide workshops for all parents about how to be positively involved in their child s schooling. The findings from all three models indicate that to efficiently affect school outcomes, the first step is to assess where a student currently is on the continuum from school behavior to school achievement. Interventions should then focus on the family factors that are most strongly associated with where that student is on the continuum. These findings should also stress to schools that team members who have family intervention skills are vital school social workers and family therapists and that reaching out to families to create connections to promote family functioning that advance school outcomes is essential. From a policy perspective, the current findings suggest that school outcomes are the result of multiple factors from multiple contexts. Thus, schools should not be held solely responsible to effect change. Schools alone are simply not in the position to change many of the significant factors. Current findings likewise suggest that interventions targeting and implemented within multiple microsystems would be the most beneficial, even necessary, to improve school outcomes. Indeed, our findings revealed that all three school outcomes were affected by at least one proximal process within each of the three key microsystems. Narrowly focused policies that affect only a segment of children s lives for example, only the school context will have less impact than more broadly conceived policies and programing that focus on families and neighborhoods as well. This means assessing both risk and protective factors from all microsystems, and related efforts to build resilience across all three. Essentially, we need no neighborhood left behind and no family left behind to accompany the schoolfocused No Child Left Behind Act of 2001 legislation. On a related note, the large impact of having repeated one or more grades on school outcomes also informs policy. The No Child Left Behind Act of 2001 calls for holding students back based on high stakes achievement test scores; such a policy may put students on a trajectory to failure and drop out. Finally, in two of the HLM models investigating school behavior and academic performance, race/ ethnicity was not a significant factor. Only in the school coherence model, and only for African American students, was a significant effect found for race/ ethnicity. We believe that this finding is the result of including other important environmental factors and proximal processes impacting school outcomes from the key environments of neighborhood, family, and school social climate. The implication is that policy and practice efforts with respect to reducing the achievement gap experienced by African American and Latino students should focus on both the hierarchy of school needs as described in this article and the multiple microsystems in which these needs must be met and not simply focus on academic issues such as curriculum planning and high stakes testing. The current research suggests that effective strategies to reduce the achievement gap should address factors in all three key microsystems and (a) promote more supportive social climates in schools, (b) target family protective factors such as those investigated in the current study, and (c) intervene with neighborhood factors such as violent crime and negative peer cultures. References Agresti, A., & Finlay, B. (1997). Statistical methods for the social sciences. Upper Saddle River, NJ: Prentice Hall. Booth, A., & Dunn, J. F. (Eds.). (1996). Family-school links: How do they affect educational outcomes? Mahwah, NJ: Lawrence Erlbaum. Bowen, G. L., Bowen, N. K., & Richman, J. M. (2000). School size and middle school students perceptions of the school environment. Social Work in Education, 22, Bowen, G. L., Richman, J. M., Brewster, A., & Bowen, N. K. (1998). Sense of school coherence, perceptions of danger at school, and teacher support among youth at risk of school failure. 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