Exploring educational pathways over the life course in children with out-of-home care experience: A multi-group path analysis

Journal Pre-proofs Exploring educational pathways over the life course in children with out-ofhome care experience: A multi-group path analysis Hilma Forsman PII: DOI: Reference:

S0190-7409(19)31245-9 https://doi.org/10.1016/j.childyouth.2020.104852 CYSR 104852

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Children and Youth Services Review

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Please cite this article as: H. Forsman, Exploring educational pathways over the life course in children with outof-home care experience: A multi-group path analysis, Children and Youth Services Review (2020), doi: https:// doi.org/10.1016/j.childyouth.2020.104852

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Exploring educational pathways over the life course in children with out-of-home care experience: A multi-group path analysis Hilma Forsmana a Department of Social Work, Stockholm University Corresponding author: Hilma Forsman Department of Social Work Stockholm University SE-106 91 Stockholm, Sweden [email protected] Funding: This work was supported by the Swedish Research Council (grant no. 2017-01476). Exploring educational pathways over the life course in children with out-of-home care experience: A multi-group path analysis Abstract It is well-established that children with out-of-home care (OHC) experience perform poorly in the educational system. However, we know less about their educational pathways over the life course. Utilizing longitudinal prospective survey and register data with a follow-up to more than 60 years of age, this study compared educational outcomes over the life course between children with OHC experience and their same-aged peers. Moreover, by means of multi-group path analysis, the study explored differences in educational pathways. The results showed that the OHC group had lower school grades in sixth grade, in ninth grade as well as lower educational attainment in middle age. Cognitive ability and previous school performance had the largest associations with the outcomes in both groups. Yet, these predictors had significantly weaker influence in the OHC-group. Conversely, the birth family’s attitude towards higher education was more important among children with OHC experience. Implications for policy and practice are discussed. Keywords: out-of-home care; educational outcomes; pathways; longitudinal; path analysis

1. Introduction Previous research has consistently reported that children with experience of out-of-home care (OHC) tend to perform poorly in school, and have lower educational attainment in adulthood, compared to their same-aged peers (Stone, 2007; Trout, Hagaman, Casey, Reid, & Epstein, 2008;

Vinnerljung & Hjern, 2011). However, the literature offers much less insight into their pathways through the educational system and over the life course. Findings on educational outcomes of children with OHC experience are mostly based on cross-sectional studies, and there is an overall dearth of long-term longitudinal studies (O'Higgins, Sebba, & Gardner, 2017; Stone, 2007). Most report on relatively short term educational outcomes and focus on links to singular variables, thereby not addressing the complexity of the life course and the relationships between multiple factors that may shape educational careers. Meanwhile, a better understanding of these processes is crucial in conceptualizing and designing appropriate interventions targeting OHC children’s school performance. In light of the above, scholars have called for a development of a comprehensive model of the pathways to varied educational outcomes for children with OHC experience (O'Higgins et al., 2017; Pears, Kim, & Brown, 2018). However, this requires longitudinal research based on large samples, advanced statistical models and access to a wide array of detailed data on the children, their families, their schooling and OHC placement. Another viable approach might be to assess the importance and transferability of what we know from wider educational research based on the general population (O'Higgins et al., 2017), which requires a better understanding of how the educational pathways of children with OHC experience might or might not differ to those of their same-aged peers in the general population. The current study adds to the knowledge by combining elements from both of these strategies. Using longitudinal prospective survey and register data on more than 12,000 Swedes born in 1953, the purpose of this study is to compare educational outcomes over the life course between children with OHC experience and their same-aged peers, and to explore differences in educational pathways. By studying educational trajectories from a life course perspective (Pallas, 2003), some shortcomings in previous research can be addressed. First, the cohort includes a wide range of variables apart from those reflecting OHC placement and educational outcomes. This encompasses socioeconomic conditions of the birth family, as well as measures of the individual’s cognitive ability and other school-related factors, all of which are known to influence educational outcomes. Second, the study is not dependent on cross-sectional data or retrospective reports. Third, the longitudinal setting allows for tracking of educational outcomes at different stages in the educational career. Moreover, the long follow-up time makes it possible to explore whether this educationally vulnerable group experiences educational recovery over the life

course. This question might be of particular interest since the Swedish educational system is typically referred to as inclusive through e.g. second learning chances for adults (OECD, 2016). Finally, multi-group path analysis allows for contrasting the paths to educational outcomes in children with OHC experience with those of their general population peers, and to explore whether and how there are differences in how the relationships between different predictors affect their educational pathways. As such, this study provides insights into how practice and policymakers can be more responsive to the educational needs of children enrolled in the OHC system of today.

2. Methods 2.1.

Data and sample

The present study used data from the prospective Stockholm Birth Cohort Multigenerational Study (SBC Multigen), defined as all individuals born in 1953 who were resident in the greater Stockholm metropolitan area ten years later. The SBC Multigen encompasses survey and register data from birth up until retirement age for 14,608 individuals (Almquist, Grotta, Vågerö, Stenberg, & Modin, 2019). The study population consists of children who participated in one of the surveys included in the larger project; the School Study in 1966 (age 13; n=13,641), and who were alive in 2015 (age 62; n=12,296). Cohort members with only six years of schooling at age 62 (n=84) were excluded, since the path analysis estimation technique would result in illogical imputation of school grades in the ninth grade. Information about OHC experience was retrieved from manual collection of data from the social registers kept by the municipalities of Stockholm. The data are sorted into age-periods (ages 0-6, 7-12 and 13-19 years), and include information about OHC placement, causes for placement (family-related and/or own behavior), placement type (foster family and/or residential care), and total placement duration for each age-period. The data do not include information about the number of placements. Children in the OHC group were identified through a record of any placement between 1953 and 1965 (ages 0–12). The majority had short-term placements (<2 years=62%, ≥2 years=7%, unspecified=31%), and were placed due to familyrelated problems (ca. 91%). Children who had their first placement in OHC during their teens (n=156) were excluded, since this would occur after the first measurement of school grades. Thus, the analytical sample consists of 12,296 individuals, out of which around 6% (n=771) had OHC experience. The study was approved by the Stockholm Regional Ethics Committee (no 2016/481-31/5, 2017/34-31/5, 2017/684-32).

2.1.1. Context Growing up in the 1950s and 1960s – a time of improved living conditions – the cohort can be viewed as part of Sweden’s first welfare state generation. However, the rather homogenous cultural and ethnic composition of the 1953 cohort is in striking contrast to the heterogeneous Swedish society of today. The educational system was repeatedly reformed during the cohort members’ principal schooling years, moving from an elitist to a more egalitarian system (Bask, Ferrer-Wreder, Salmela-Aro, & Bergman, 2014). Still, compared to today’s system, children’s educational careers were shaped at an earlier age. The ninth and final year of compulsory school was divided into different streams, i.e. academic or vocational. Moreover, this division was partly based on choices children had made in the sixth grade. Also, whilst a majority of children today proceed directly to upper secondary education following compulsory school completion, almost half of the 1953 cohort did not. The process of educational expansion has furthermore resulted in a larger proportion of the Swedish population reaching higher levels of education. Still, compared to today, only having a basic education was generally not an obstacle for entering the labor market. Although reliable comparative data are scarce, it is evident that both the OHC system and the OHC population during the 1950s and 1960s to some extent differed from today. Back then, Sweden did not have a national placement policy. This resulted in an extremely heterogeneous child welfare system. Authorities believed strongly in the preventive abilities of OHC, which is reflected in a higher OHC prevalence in the 1953 cohort, especially among younger children, compared to more recent cohorts (e.g. the national OHC prevalence before age 13 in cohorts born between 1980-1994 is ca 1.6 %: Berlin et al., 2018). Just like today, younger children were placed due to neglect, alcohol misuse and mental health problems in the birth family. However, many were taken into care due to presumed maternal immaturity (teenage mothers), unsatisfactory housing, poverty, and by request from single mothers who were ill or lacked social/economic support (Vinnerljung, 1996). Today, more children are placed due to child abuse, family violence, maternal substance misuse or serious parental criminality (Khoo, Skoog, & Dalin, 2012). Thus, it is reasonable to assume that today’s OHC population has more adverse childhood experiences (e.g. traumas) before entering care than the local cohort in this study. Still, national inquiries have identified that a considerable share of the children placed in OHC between 1950 and 1980

experienced inferior and hostile care (SOU 2011:61). Furthermore, residential care was more common, even among younger children. Today OHC is dominated by foster family care. 2.2.

Measures

2.2.1. Educational outcomes Educational outcomes are indicated by three variables at various stages of the educational career: school grades in the sixth grade (1966, age 13), in the ninth and final year of compulsory school (1969, age 16), and educational attainment in middle age (2015, age 62). Grades ranged from 100-500, and were based on the average performance in all subjects except physical education. The grading system was relative, i.e. the grades were given in proportion to the performance of all students taking the course during a given year. The distribution was thus intended to follow a Gaussian distribution at the national level, with the average value fixed at 300. Grades were retrieved from local school records, administered by Stockholm City and Stockholm County. Educational attainment was derived from the Longitudinal Integration Database for Health Insurance and Labor Market Studies and reflects pseudo-years of education. It corresponds to the number of years typically related to the cohort member’s highest level of education (ranging from compulsory education to post-graduate education), e.g. if the highest level was upper secondary education, maximum 2 years, this would be equivalent to 11 pseudo-years of education (9 years compulsory school + 2 years). As already mentioned, only about half of the cohort members continued to vocational or upper secondary school after compulsory school completion. Grades from upper secondary school (1971-1972, age 18-19) were therefore not included since this would either result in dropping about half of the observations or illogical imputing of missing values. (Table 1 in about here)

2.2.2. Covariates The choice of covariates was guided by previous research on conceptual predictors of educational outcomes among children with OHC experience (for reviews, see Ferguson & Wolkow, 2012; O'Higgins et al., 2017) and/or children in the general population, and for which operational measures in the SBC Multigen dataset existed. The cohort member’s biological sex is indicated by the variable female (female=1/male=0). A recent systematic review of risk and protective factors of educational success among children with OHC experience found that male gender consistently predicted lower attainment (O'Higgins et al., 2017). Since socioeconomic status is widely recognized to impact children’s educational achievement (Bradley & Corwyn, 2002), three variables reflecting the socioeconomic conditions in the birth family were included. Family education (age 7), based on information in the 1960 Census, refers to the total number of household members in the birth family who had graduated from upper secondary school or equivalent. Educational background has a strong influence on children’s achievements (Coleman, 1968). Furthermore, the educational attainment of children with OHC experience (including long-term placements) is clearly associated with their birth mothers’ level of education (Vinnerljung, Öman, & Gunnarson, 2005). ‘Mother teen mum’, reflects whether the mother was a teenager 1953 (age 0), which in general was associated with social and economic disadvantage. In addition, children to teen mothers tend to have poorer educational outcomes (Jutte et al., 2010). Household poverty has been shown to have a detrimental impact on educational attainment into adulthood (Duncan & Magnuson, 2014), and is here indicated by the number of years the cohort member’s birth family received means-tested social assistance in 1953–1965 (ages 0–12) according to the social registers. The following measures are based on the School Study survey taken by the cohort members, and refer to circumstances in 1966 when they attended sixth grade (age 13). Cognitive ability was recorded through the total number of points on three subtests comprising verbal analogies, number series, and geometric figures (Härnqvist, 1968). Each subtest had 40 tasks, making the highest possible overall score 120. Links between cognitive ability and academic achievements are strong among children in general (Deary, Strand, Smith, & Fernandes, 2007). However, studies

have shown that children with OHC experience have substantially lower school grades, and lower educational attainment level in young adulthood compared to peers with similar cognitive capacity (Berlin, Vinnerljung, & Hjern, 2011; Vinnerljung, Berlin, & Hjern, 2010), which suggests that this association is weaker in this group. Family’s attitude to education was measured by the sum of 10 two-response items (yes=1, no=0) addressing the child’s perception of the parents’ attitude to higher education (e.g. “Do your father and mother think you should go on to another school when you have finished compulsory school?”). Parents’ educational expectations seem to affect children’s educational attainment net of other essential factors, such as socioeconomic status, and the child’s cognitive ability and academic achievement (Bask et al., 2014). Insecurity at school was indicated by the total points of 10 two-response items (yes=1, no=0) aimed at capturing the child’s feelings of insecurity at school (e.g. “Do you often sit worrying about things at school?”). A secure environment is a prerequisite for learning. Moreover, it has been shown that students who report feeling unsafe in school have higher absence and experience a consistent negative effect on test scores (Lacoe, 2016). Classroom misconduct was indicated through the child’s report about being told to leave the classroom because of something he/she had done with the following responses: 0=”No”, 1=”Yes, once or twice”, and 2=”Yes, several times”. This could act as an indicator of behavior problems, a factor strongly linked to poor educational outcomes (Johnson, McGue, & Iacono, 2009). Moreover, the high prevalence of behavioral problems among children in OHC has been brought forward as an explanatory factor for school failure. However, the evidence is mixed (O'Higgins et al., 2017). Academic interest, school engagement, and similar concepts are commonly linked to school success, including achievement and persistence in school (Fredricks, Blumenfeld, & Paris, 2004). Here, it is indicated by the sum of 10 two-response items (yes=1, no=0) capturing the child’s interest in schoolwork (e.g. “Do you think you learn new things in an interesting way at school?”). Future prospects were measured using the question: “If you compare your future prospects with those of your age, do you think your future will be worse, similar or better?” with responses ranging from 1=“Much worse” to 5=“Much better”. It has been shown that the cohort members’

expectations are related to health and work-related outcomes in middle age. Their prospects may thus reflect known facts i.e. their own abilities and achievements as well as conditions in the birth family (Halleröd, 2011). Finally, peer status is based on a sociometric question where cohort members were asked to nominate three classmates whom they would prefer to work with at school. Previous research has shown that peer status is associated with the likelihood of proceeding to higher levels of education (Almquist, Modin, & Östberg, 2010). Apart from reflecting how the child performs in school it is assumed to capture dimensions of friendship, likeability, and social inclusion among peers (Stütz, 1985). The variable was divided into five categories: 0=0 votes, 1=1 vote, 2=2-3 votes, 3=4-6 votes, 4=7 or more votes. 2.3.

Path model of educational pathways

The conceptualization of the path model of educational pathways was guided by previous research, and the included variables’ temporal ordering. Yet, some operational measures and paths were modified in order to better fit the data. The application could be described as model generation (Kline, 2015). The final model is as follows (see Figure 1 for a simplified conceptual model of the pathways): Family education and mother is a teen mum precedes household poverty. These background factors and the children’s sex are presumed to influence cognitive ability, which in turn influence each of the school-related factors (i.e. family’s attitude to education, insecurity at school, classroom misconduct, academic interest, future prospects, and peer status). All of the above are treated as determinants on school grades in the sixth grade, followed by grades in the ninth grade, and finally educational attainment in middle age. The effect of each covariate on the educational outcomes is thus assumed to be direct, and mediated via variables that appear later in the temporal sequence. However, there is no direct path between school grades in sixth grade and educational attainment since cohort members with only six years of schooling were excluded from the sample. Still, the error terms were allowed to correlate. Paths allowing correlation between each pair of the error terms of the school-related factors were also added. These correlated errors mean that both variables in each pair could be influenced by variables not included in the model (Acock, 2013). (Figure 1 in about here)

2.4.

Statistical analysis

Descriptive statistics, including bivariate comparisons of the OHC and non-OHC group with results from two-sample tests of proportions/means, are presented in Table 2. Additionally, a correlation matrix between study variables for the sample as a whole, and for the non-OHC and OHC group separately is provided in Appendix A. Multi-group path analysis within a structural equation modeling (SEM) framework was used to explore educational pathways, and to examine differences in path coefficients between children with OHC experience and their same-aged peers without such experience. The analysis was carried out in four steps: First, an unconstrained model in which all parameters were allowed to differ across groups was performed. Second, a series of Wald’s tests were performed to determine if any of the parameters were significantly different between the non-OHC and the OHC group, i.e. if any predictor is more or less important for one group than it is for the other. Third, a constrained model was performed, in which parameters that were not statistically different (p >0.1) across groups were constrained to be equal across groups. Last, the direct, indirect, and total effects for each predictor in the constrained model were estimated (Acock, 2013). Estimation for all models was performed using full information maximum likelihood (FIML) to account for missing data. FIML identifies the parameter values with the highest probability of producing the sample data based on all available data (complete and incomplete) and is considered superior to traditional listwise approaches (Enders, 2010). Complete data were available for sex and household poverty. The other variables had missing values for 1.3-16.4% of the observations (for information about missing values for each variable for the whole sample and across groups, see Table 2). Using complete cases only, would have reduced the effective sample by around 40%. Model fit to the data was assessed using multiple fit indices including the chi-square test of model fit, the Comparative Fit Index (CFI), the Tucker-Lewis Index (TLI), and the Root Mean Square-Error of Approximation (RMSEA). Adequate model fit is generally indicated by a nonsignificant chi-square, CFI/TFI >0.95, and RMSEA <0.06 (Hu & Bentler, 1999). The path models were estimated with the SEM-function in Stata/MP 15.0 (StataCorp, 2017). All variables, except for mother teen mum and sex, were treated as continuous. Both standardized and unstandardized estimates were obtained.

(Table 2 in about here)

3. Results 3.1.

Descriptive statistics

Table 2 provides descriptive statistics including bivariate comparisons of the OHC and non-OHC group with results from two-sample tests of proportions/ means. Compared to their same-aged peers, children with OHC experience have significantly lower educational outcomes over the life course. Though, it should be noted that the differences across groups are more modest compared to findings from more recent Swedish cohorts (e.g. Vinnerljung et al., 2010). There are also significant differences in the socioeconomic background with lower family education background, higher rates of household poverty and a higher proportion of teenage birth mothers in the OHC group compared to the non-OHC group. Furthermore, cognitive ability, peer status, and the family’s attitude to higher education are significantly lower. Moreover, the OHC group has significantly higher levels of feelings of insecurity at school and classroom misconduct. However, men and women are equally represented across groups and there are no significant differences in the children’s academic interest and future prospects.

3.2.

Multi-group path analysis

In Table 3, unstandardized and standardized parameters are presented by groups for each direct path to the educational outcomes (results from the specific regression equations on household poverty, cognitive ability, and the school-related factors have been omitted to save space). The left part of the table shows the results of the unconstrained path model in which all parameters were allowed to differ across groups. In the non-OHC group, the model accounts for 58% of the variance in school grades in sixth grade, 52% in ninth grade, and 39% in educational attainment.

Equivalent numbers in the OHC-group are 48%, 34%, and 30% respectively. The evidence from the fit indices suggest good overall model fit: x2(2)=4.60, p=0.10; RMSEA=0.015; CFI=1.000; TLI=0.993. As can be seen, some of the unstandardized coefficients appear to be different between the non-OHC and OHC group. A series of Wald’s tests were performed to determine if any of the parameters were significantly different (p <0.1). Results indicate significant differences in how parental household poverty, cognitive ability, feelings of insecurity at school, and academic interest influence school grades in sixth grade. Paths to school grades in ninth grade from grades in sixth grade, cognitive ability, and family’s attitude towards education, also differ significantly across groups. Furthermore, significant differences are found on paths from school grades in ninth grade and cognitive ability to educational attainment. The right part of Table 3 presents the results from a re-estimation of the model, in which all parameters that are not statistically different are constrained to be equal across groups (see Appendix B for the standardized direct, indirect, and total effects on the educational outcomes for each predictor). Compared to the unconstrained solution, the explained share of the variance in the educational outcomes remains at the same level for both groups. However, constraining parameters improved the overall model fit to the data: x2(53)=35.73, p=0.97; RMSEA=0.000; CFI=1.000; TLI=1.002. (Table 3 in about here) A comparison of the unstandardized coefficients across groups reveals that cognitive ability and academic interest have weaker direct positive influence on school grades in sixth grade in the OHC group. In fact, higher academic interest among OHC children is actually significantly associated with lower grades. Furthermore, the negative direct influence of household poverty is weaker, whilst the negative relationship between grades and feelings of insecurity at school is stronger among children with OHC experience. There are no group differences in the direct effects of the other variables, which all influence the outcome in the expected directions. From the standardized coefficients, family education has more predictive power in the non-OHC group. The indirect effect is also notably stronger (Appendix B). Similar results are found for cognitive ability.

Still, it is the strongest predictor in both groups, followed by peer status. Furthermore, the relative importance of the family’s attitude towards education, insecurity at school, and future prospects seem to be greater among children with OHC experience, compared to their peers. Turning to school grades in the ninth and final year of compulsory school, the positive direct influence of previous educational outcomes and cognitive ability are weaker in the OHC than in the non-OHC group. A stronger direct positive influence of the family’s attitude to education among children with OHC experience can be noted. However, the path is not statistically significant in any of the groups. In contrast to previous measure of educational outcomes, the association with being female is significantly negative in both groups. All other determinants have the expected direction. Looking at the magnitude of the parameters, school grades in sixth grade, cognitive ability, and family education have smaller predictive power in the OHC compared to the non-OHC group. The relative importance of household poverty and having a teenage mother at birth is somewhat larger in the OHC group. Furthermore, the total effect (i.e. the direct and indirect influence) of family education, and academic interest is quite substantially smaller in the OHC group, whilst it is bigger for the family’s attitude towards education (Appendix B). Differences in paths to educational attainment are a weaker positive association with school grades in ninth grade and a stronger positive influence of cognitive ability among children with OHC experience. Being female is now again positively associated with higher educational outcomes in both groups. Surprisingly, classroom misconduct has a positively significant direct influence across groups. The relationships with the other measures are as expected. Similar to previous equations, the relative importance of previous educational outcomes and family education is smaller in the OHC than in the non-OHC group. Family education and school grades in sixth grade also have smaller indirect influence among children with OHC experience (Appendix B). The direct negative influence of having a teenage mother and household poverty is somewhat stronger. Yet in contrast to previous outcomes, the direct influence of cognitive ability is larger in the OHC-group. However, there are no notable group differences in cognitive ability’s total effect on educational attainment in midlife (Appendix B).

4. Discussion Adding to the body of knowledge on the educational outcomes of children with OHC experience, this study aimed to compare educational outcomes over the life course between these children and their same-aged peers, and to explore whether and how there are differences in their educational pathways by means of multi-group path analysis. The results show that children with OHC experience have significantly lower school grades than their same-aged peers in sixth grade (age 13), and in the ninth and final year of compulsory school (age 16). Furthermore, the OHC group had significantly lower educational attainment (age 62). This suggests that the educational gap between children with OHC experience and their peers persists over the life course, and that OHC placement before the age of 13 is a strong marker for lower educational outcomes way past the childhood years. However, the differences across groups are quite modest in comparison to findings from more recent Swedish cohorts (Vinnerljung et al., 2010; Vinnerljung et al., 2005). This might be due to contextual differences. During the 1950s and 1960s, OHC had higher interventionist ambitions (Vinnerljung, 1996), which resulted in a more heterogeneous OHC population compared to later cohorts. Later cohorts probably had more adverse backgrounds. Moreover, although the 1953 cohort grew up in a time of educational expansion, the educational requirements for entering the labor market were low and the demand for low-skilled workers was high. Hence, incitements for further education were lower. Nevertheless, the results could also reflect selection bias, i.e. a larger proportion of the OHC group did not participate in the School Study and was thus excluded from the study sample. Additionally, by excluding those who died during the long follow-up time, the outcomes of the OHC group in the current study are probably biased upwards. Results from the multi-group path analysis on educational outcomes over the life course showed that the educational pathways of children with OHC experience were similar to those of their same-aged peers without such experience. However, the model had more explanatory power in the non-OHC group, suggesting that unobserved factors accounted for a comparatively larger share of the variance in the educational outcomes in the OHC-group. Notable is the increased explanatory gap between sixth and ninth grade, which could suggest increased influence of unobservable predictors that are particularly important or even specific for children with OHC experience during this time window. Moreover, there were some meaningful differences in the relationships between some variables and the outcomes at different stages of the life course.

A consistent finding was that previous school performance had a substantially weaker direct and indirect positive influence on subsequent educational outcomes in the OHC than in the non-OHC group. In other words, controlling for the other factors, children with OHC experience had lower educational outcomes compared to peers with the same level of previous school performance. These results reflect a common finding in educational social stratification research (e.g. Erikson, Goldthorpe, Jackson, Yaish, & Cox, 2005). Namely, children from less advantaged backgrounds perform worse at school compared to their more advantaged peers, and are less likely to continue to further education given the same performance. Similar findings have been reported in studies comparing child welfare children’s educational outcomes to those of their general population peers’ (Vinnerljung et al., 2010). These processes might also explain why family educational background had notably smaller direct and indirect influence on educational outcomes in the OHC group. A similar pattern was found in the positive association between cognitive ability and school grades in sixth and in ninth grade, which was significantly weaker in the OHC group. Based on their cognitive ability, it thus seems as if they were underperforming in school. This phenomenon has previously been noted in Swedish national population studies of cohorts born 1973-82 (Berlin et al., 2011). However, the direct influence of cognitive ability on educational attainment in middle age was actually stronger in the OHC group. Yet, the total effect was rather similar across groups. Given previous underperformance in the OHC group, this could be interpreted as if their educational attainment reflects their cognitive capacities more accurately than what their school grades in compulsory school do. Furthermore, it could indicate that some children with OHC experience are catching up with their same-aged peers over the life course in terms of the cognitive ability ‘reward’ on educational outcomes. This might be accounted for by second learning chances for adults within the Swedish educational system. Another interesting finding was that the relative importance of the family’s attitude to higher education was stronger in the OHC group (direct and/or total effects). Thus, although the influence got weaker over time, a positive attitude seems to matter more for children with OHC experience than it does for their peers. Still, sample characteristics showed that the family’s attitude to education was significantly lower in the OHC group. Furthermore, qualitative studies have shown a pervasive disregard for school issues, and pessimistic expectations among significant others in the systems in charge of children in OHC (Ferguson & Wolkow, 2012). In light of this, it seems as if there is potential in working with the adults in how they directly and indirectly influence the children’s educational pathways.

Additional significant group differences in the paths to school grades in sixth grade, were that academic interest had a negative influence and that feelings of insecurity at school had a worse detrimental effect among children with OHC experience compared to their same-aged peers. The former relationship is not fully understood. In light of significantly higher levels of insecurities in the OHC group, the latter finding suggests that safety at school is another area that could be informative in providing children in OHC with better opportunities to school success. 4.1.

Strengths and limitations

Strengths of this study include its prospective design with a long follow-up time, the large sample size (comprising of a sizeable number of individuals with OHC experience), and a wide range of data including socioeconomic indicators in the birth family, the children’s cognitive ability, and other school-related factors at age 13. However, there are also several limitations worth noting. First, this study provides a simplified description of complex life-course processes. Regrettably, data that could be important for our understanding of the educational outcomes of children with OHC experience were not available. Examples of such data include e.g. information about the care environment, placement stability, educational support, school changes, and indications of early mental health problems. Furthermore, whilst the SBC Multigen contains rather detailed information about placements, it was not possible to utilize these data in the multigroup path analysis. These limitations might account for some of the unexplained variance in the OHC group’s educational outcomes. Second, there is a possibility that some children in the OHC group currently in care might have referred to their foster parents when answering the survey questions about the family’s attitude towards education. Third, although path models is sometimes referred to as causal models, analysis based on observational data do not allow for causal interpretations in a strict sense (Acock, 2013). Accordingly, although the proposed model demonstrated adequate fit to the data, alternative models cannot be ruled out. Fourth, the findings of this study are exploratory. The tests for group differences were not driven by an outlined theoretical model, which could increase the likelihood of detecting differences that in fact do not exist (Schreiber, Nora, Stage, Barlow, & King, 2006). However, the findings do not contradict those reported in other studies on educational outcomes among children with OHC experience.

Last, an additional shortcoming, related to the above, is the comparability between the 1953 Stockholm cohort and today’s children. The educational and child welfare system have undergone changes. As a result, the composition of the OHC sample and their life circumstances will differ. However, the educational gap between children with OHC experience and their peers seems to be a constant over time and place (Trout et al., 2008; Vinnerljung et al., 2005). Moreover, single longitudinal cohort studies can yield insights into generic processes that shape life courses, and such mechanisms tend to be more general than specific with regards to historical period and geographical site (cf. Bäckman & Nilsson, 2010). 4.2.

Implications

The findings of this study suggest that, in principle, the understanding of educational pathways over the life course among children with OHC experience largely could be informed by general theories of educational inequality. Such application also offers some insights into how the educational gap between children with OHC experience and their peers could be addressed. Like other disadvantaged groups in the majority population, youth aging out of care and OHC alumni may benefit from e.g. adult education initiatives and reduced costs for higher education (Erikson & Jonsson, 1996; OECD, 2016). However, educational research and previous studies on child welfare clients’ educational transitions (e.g. Dæhlen, 2017) also point to the importance of educational choices. Hence, motivating children in OHC to proceed with their educational careers over different stages may also result in increased attainment levels. For youth aging out of care, after-care services and programs with a particular focus on education may also hold promise. Successful prevention programs are typically based on the identification and targeting of predictive factors that can be influenced (FerrerWreder, Stattin, Lorente, Tubman, & Adamson, 2004). Overall, cognitive ability and previous school performance had the largest influence on subsequent educational outcomes. This emphasizes the importance of promoting cognitive and intellectual development among children in OHC, and continuously providing them with opportunities to reach the highest educational levels that they can. Adoption studies have shown that disadvantaged children’s cognitive functioning can be improved (e.g. Duyme, Dumaret, & Tomkiewicz, 1999). Intervention studies furthermore suggest that foster children’s academic skills and cognitive ability can be improved while in OHC (Forsman & Vinnerljung, 2012). Offering such support, preferably at an early age, could thus be seen as a viable path for improving their educational outcomes over the life course. The positive

influence of the family’s attitude to higher education suggests that focusing on attitudes and expectations among adults in the surrounding systems also could be beneficial. Given the strong links between poor school performance and future adverse outcomes among children with OHC experience (Berlin et al., 2011; Forsman, Brännström, Vinnerljung, & Hjern, 2016), such efforts may also contribute to improved overall life chances.

5. References Acock, A. C. (2013). Discovering structural equation modeling using Stata: Revised edition. Texas: Stata Press. Almquist, Y. B., Grotta, A., Vågerö, D., Stenberg, S.-Å., & Modin, B. (2019). Cohort profile update: The Stockholm birth cohort study. International Journal of Epidemiology. doi:10.1093/ije/dyz185 Almquist, Y., Modin, B., & Östberg, V. (2010). Childhood social status in society and school: Implications for the transition to higher levels of education. British Journal of Sociology of Education, 31, 31-45. Bask, M., Ferrer-Wreder, L., Salmela-Aro, K., & Bergman, L. R. (2014). Pathways to educational attainment in middle adulthood: The role of gender and parental educational expectations in adolescence. In J. Eccles & I. Schoon (Eds.), Gender differences in aspirations and attainment: A life course perspective, (pp. 389-411). Cambridge: Cambridge University Press. Berlin, M., Mensah, T., Lundgren, F., Klingberg, G., Hjern, A., Vinnerljung, B., & Cederlund, A. (2018). Dental healthcare utilisation among young adults who were in societal out-of-home care as children: A Swedish national cohort study. International Journal of Social Welfare, 27, 325336. Berlin, M., Vinnerljung, B., & Hjern, A. (2011). School performance in primary school and psychosocial problems in young adulthood among care leavers from long term foster care. Children and Youth Services Review, 33, 2489-2497. Bradley, R. H., & Corwyn, R. F. (2002). Socioeconomic status and child development. Annual Review of Psychology, 53, 371-399. Bäckman, O., & Nilsson, A. (2010). Pathways to social exclusion: A life-course study. European Sociological Review, 27, 107-123.

Coleman, J. S. (1968). Equality of educational opportunity. Integrated Education, 6, 19-28. Dæhlen, M. (2017). Child welfare clients and educational transitions. Child & Family Social Work, 22, 317-329. Deary, I. J., Strand, S., Smith, P., & Fernandes, C. (2007). Intelligence and educational achievement. Intelligence, 35, 13-21. Duncan, G. J., & Magnuson, K. (2014). The long reach of early childhood poverty. In D. B. Grusky (Ed.), Social stratification: Class, race and gender in sociological perspective (pp. 417-423). Boulder, Colorado: Westview Press. Duyme, M., Dumaret, A.-C., & Tomkiewicz, S. (1999). How can we boost IQs of “dull children”? A late adoption study. Proceedings of the National Academy of Sciences, 96, 8790-8794. Enders, C. K. (2010). Applied missing data analysis. New York: Guilford Press. Erikson, R., Goldthorpe, J. H., Jackson, M., Yaish, M., & Cox, D. R. (2005). On class differentials in educational attainment. Proceedings of the National Academy of Sciences, 102, 9730-9733. Erikson, R., & Jonsson, J. O. (1996). The Swedish context: Educational reform and long-term change in educational inequality. In R. Erikson & J.O. Jonsson (Eds.), Can education be equalized? The Swedish case in comparative research (pp. 65-93). Boulder, Colorado: Westview Press. Ferguson, H. B., & Wolkow, K. (2012). Educating children and youth in care: A review of barriers to school progress and strategies for change. Children and Youth Services Review, 34, 1143-1149. Ferrer-Wreder, L., Stattin, H., Lorente, C. C., Tubman, J. G., & Adamson, L. (2004). Successful prevention and youth development programs: Across borders. New York: Kluwer/Plenum. Forsman, H., Brännström, L., Vinnerljung, B., & Hjern, A. (2016). Does poor school performance cause later psychosocial problems among children in foster care? Evidence from national longitudinal registry data. Child Abuse & Neglect, 57, 61-71. Forsman, H., & Vinnerljung, B. (2012). Interventions aiming to improve school achievements of children in out-of-home care: A scoping review. Children and Youth Services Review, 34, 1084-1091. Fredricks, J. A., Blumenfeld, P. C., & Paris, A. H. (2004). School engagement: Potential of the concept, state of the evidence. Review of Educational Research, 74, 59-109.

Halleröd, B. (2011). What do children know about their futures: Do children's expectations predict outcomes in middle age? Social Forces, 90, 65-83. Hu, L. t., & Bentler, P. M. (1999). Cutoff criteria for fit indexes in covariance structure analysis: Conventional criteria versus new alternatives. Structural Equation Modeling, 6, 1-55. Härnqvist, K. (1968). Relative changes in intelligence from 13 to 18: I. Background and methodology. Scandinavian Journal of Psychology, 9, 50-64. Johnson, W., McGue, M., & Iacono, W. G. (2009). School performance and genetic and environmental variance in antisocial behavior at the transition from adolescence to adulthood. Developmental Psychology, 45, 973-987. Jutte, D. P., Roos, N. P., Brownell, M. D., Briggs, G., MacWilliam, L., & Roos, L. L. (2010). The ripples of adolescent motherhood: Social, educational, and medical outcomes for children of teen and prior teen mothers. Academic Pediatrics, 10, 293-301. Khoo, E., Skoog, V., & Dalin, R. (2012). In and out of care: A profile and analysis of children in the out-of-home care system in Sweden. Children and Youth Services Review, 34, 900-907. Kline, R. B. (2015). Principles and practice of structural equation modeling. New York: Guilford Publications. Lacoe, J. (2016). Too scared to learn? The academic consequences of feeling unsafe in the classroom. Urban Education. doi:10.1177/0042085916674059 O'Higgins, A., Sebba, J., & Gardner, F. (2017). What are the factors associated with educational achievement for children in kinship or foster care: A systematic review. Children and Youth Services Review, 79, 198-220. OECD. (2016). Education at a glance 2016: OECD indicators. Paris: OECD Publishing. Pallas, A. M. (2003). Educational transitions, trajectories, and pathways. In J. T. Mortimer & M. J. Shanahan (Eds.), Handbook of the life course (pp. 165-184). Boston, MA: Springer. Pears, K. C., Kim, H. K., & Brown, K. L. (2018). Factors affecting the educational trajectories and outcomes of youth in foster care. In E. TrejosCastillo & N. Trevino-Schafer (Eds.), Handbook of foster youth (pp. 208-222). New York: Routledge.

Schreiber, J. B., Nora, A., Stage, F. K., Barlow, E. A., & King, J. (2006). Reporting structural equation modeling and confirmatory factor analysis results: A review. The Journal of Educational Research, 99, 323-338. SOU 2011:61. Vanvård i social barnavård [Abuse and neglect in child welfare]. Stockholm: Socialdepartementet. StataCorp. (2017). Stata 15 base reference manual. College Station, TX: StataCorp LP. Stone, S. (2007). Child maltreatment, out-of-home placement and academic vulnerability: A fifteen-year review of evidence and future directions. Children and Youth Services Review, 29, 139-161. Stütz, G. (1985). Kamratstatus [Peer status]. Stockholm: Stockholm University. Trout, A. L., Hagaman, J., Casey, K., Reid, R., & Epstein, M. H. (2008). The academic status of children and youth in out-of-home care: A review of the literature. Children and Youth Services Review, 30, 979-994. Vinnerljung, B. (1996). Fosterbarn som vuxna [Foster children as adults]. Lund: Lund University. Vinnerljung, B., Berlin, M., & Hjern, A. (2010). Skolbetyg, utbildning och risker för ogynnsam utveckling hos barn [School performance, educational attainments, and risks for unfavorable development among children]. In Socialstyrelsen (Ed.), Social rapport 2010 [Social report 2010] (pp. 227-266). Stockholm: Socialstyrelsen. Vinnerljung, B., & Hjern, A. (2011). Cognitive, educational and self-support outcomes of long-term foster care versus adoption: A Swedish national cohort study. Children and Youth Services Review, 33, 1902-1910. Vinnerljung, B., Öman, M., & Gunnarson, T. (2005). Educational attainments of former child welfare clients: A Swedish national cohort study. International Journal of Social Welfare, 14, 265-276.

Exploring educational pathways over the life course in children with out-of-home care experience: A multi-group path analysis Author Statement Hilma Forsman: Conceptualization, methodology, formal analysis, writing

Controlled for: Mother teen mum Sex

Cognitive ability

Family's attitude to education

Family education

Insecurity at school

Household Childhood poverty

Classroom misconduct

Figure 1. Simplified correlations between error

Academic interest Future prospects Peer status

School grades 6th grade

School grades 9th grade

Educational attainment

13 years 16 years

62 years

conceptual path model of educational pathways, direct effects (single-headed arrows) and terms (double-headed arrows).

Table 1. Overview of variables, definition, categories or values, age and year information refers to, and data source. Variables

Definition

Sex Biological sex at birth Mother teen mum The mother was a teenager at the cohort member’s birth OHC (out-ofAny placement in out-of-home care (foster home care) family and/or residential care) before age 13 Household The number of years the birth family received poverty means-tested social assistance Family education The number of household members in the birth family who had graduated from upper secondary school or equivalent Cognitive ability Total number of points on three tests: verbal, numerical and geometrical Family’s attitude An index based on ten questions about the to education child’s perception of the parents’ attitude to higher education (higher values=more positive attitude) Insecurity at An index based on ten questions about the school child’s feelings of insecurity at school (higher values=more insecurity) Classroom The child’s report about being told to leave the misconduct classroom because of something he/she had done Academic An index based on ten questions about the interest child’s interest in schoolwork (higher values=more interest) Future prospects The child’s perception of his/hers future prospects compared to same-aged peers’

Categories/Values

Age (year) 0 (1953) 0 (1953)

Source

0-4 individuals

0-12 (1953-65) 0-12 (1953-65) 7 (1960)

Dependency and Child Welfare Committee data Dependency and Child Welfare Committee data The 1960 Census

0-120 points

13 (1966)

The School Study survey

0-10

13 (1966)

The School Study survey

0-10

13 (1966)

The School Study survey

No/Yes, once or twice /Yes, several times 0-10

13 (1966)

The School Study survey

13 (1966)

The School Study survey

Much worse/ A little worse/Just as good/A little better/Much better

13 (1966)

The School Study survey

Female/Male Yes/No Yes/No 0-13 years

Delivery records Delivery records

Peer status

School grades 6th grade School grades 9th grade Educational attainment

The number of votes the child received when cohort members were asked to nominate three classmates whom they would prefer to work with at school Average performance in all subjects except physical education Average performance in all subjects except physical education The number of years of education typically related to the highest level of education (pseudoyears of education)

0 votes/1 vote/2-3 votes/4-6 votes/7 or more votes

13 (1966)

The School Study survey

100-500 points

13 (1966)

Local school records

100-500 points

16 (1969)

Local school records

9-19 years

62 (2015)

The Longitudinal Integration Database for Health Insurance and Labor Market Studies

Table 2. Sample characteristics. Alla Variables

OHCb % missing

Mean (SD)

Non-OHCc % missing

Mean (SD)

Diff.

Min-max

Mean (SD)

% missing

School grades 6th grade

100-500

326.90 (69.03)

1.3

298.23 (64.50)

1.2

328.82 (68.90)

1.3

-30.59*

School grades 9th grade

100-500

320.84 (76.29)

6.1

291.58 (73.41)

12.6

322.66 (76.10)

5.7

-31.18*

Educational attainment

9-19

12.46 (2.28)

4.3

11.69 (2.07)

3.6

12.52 (2.28)

4.3

-0.83*

Family education

0-4

0.35 (0.61)

5.5

0.11 (0.33)

3.8

0.36 (0.62)

5.6

-0.26*

Mother teen mum

0-1

0.03

16.4

0.09

8.4

0.03

17.0

0.06*

Female

0-1

0.51

0.0

0.49

0.0

0.51

0.0

Household poverty

0-13

0.61 (1.91)

0.0

2.98 (3.72)

0.0

0.45 (1.60)

0.0

2.53*

Cognitive ability

0-120

69.06 (17.84)

4.5

60.70 (19.10)

5.8

69.61 (17.61)

4.4

-8.91*

Family’s attitude to education Insecurity at school

0-10

6.07 (2.30)

11.7

5.38 (2.41)

15.0

6.11 (2.29)

11.4

-0.73*

0-10

3.60 (2.34)

4.9

4.19 (2.38)

6.5

3.57 (2.34)

4.8

0.62*

Classroom misconduct

0-2

0.68 (0.68)

4.9

0.80 (0.70)

7.1

0.67 (0.68)

4.8

0.13*

Academic interest

0-10

5.02 (2.48)

4.9

5.00 (2.48)

6.2

5.02 (2.48)

4.8

-0.02

Future prospects

1-5

3.11 (0.64)

6.2

3.08 (0.73)

7.7

3.11 (0.63)

6.1

-0.03

Peer status

0-4

1.96 (1.07)

9.2

1.68 (1.03)

14.9

1.98 (1.07)

8.8

-0.30*

Educational outcomes

Covariates

Total: 40.4

Total: 43.8

Total: 40.2

Note: a N=12,296. bOHC=Out-of-home care, N=771. c Non-OHC=Non-out-of-home care, N=11,525. *Difference, p <0.001.

-0.02

Table 3. Summary table for the multiple-groups results. Relationship

Unconstrained solution Non-OHCa OHCb B β B

β

Constrained solution Non-OHCa OHCb B β B

β

6th

School grades grade Family education Mother teen mum Female Household poverty Cognitive ability Family’s attitude to education Insecurity at school Classroom misconduct Academic interest Future prospects Peer status School grades 9th grade School grades 6th grade Family education Mother teen mum Female Household poverty Cognitive ability Family’s attitude to education Insecurity at school Classroom misconduct Academic interest Future prospects Peer status Educational attainment School grades 9th grade Family education Mother teen mum

12.004*** -2.270 21.988*** -1.464*** 1.699*** 4.734*** -2.856*** -8.950*** 1.461*** 9.287*** 14.785***

0.107*** -0.006 0.159*** -0.034*** 0.435*** 0.157*** -0.097*** -0.089*** 0.053*** 0.085*** 0.229***

11.253* 3.911 25.326*** -0.299 1.238*** 6.307*** -5.033*** -8.239** -1.986* 5.117* 13.459***

0.058* 0.017 0.196*** -0.017 0.366*** 0.235*** -0.186*** -0.090** -0.075* 0.058* 0.215***

12.004*** -1.344 22.167*** -1.451*** 1.697*** 4.833*** -2.880*** -8.896*** 1.445*** 8.975*** 14.694***

0.107*** -0.003 0.161*** -0.034*** 0.435*** 0.161*** -0.098*** -0.088*** 0.052*** 0.082*** 0.228***

12.004*** -1.344 22.167*** -0.408 1.283*** 4.833*** -4.794*** -8.896*** -1.550* 8.975*** 14.694***

0.062*** -0.006 0.171*** -0.023 0.379*** 0.182*** -0.177*** -0.096*** -0.058* 0.101*** 0.234***

0.618*** 10.894*** -8.332* -7.100*** -0.376 0.606*** -0.458 -0.707** -7.070*** 1.255*** 2.595** 1.251*

0.556*** 0.088*** -0.019* -0.046*** -0.008 0.140*** -0.014 -0.022** -0.063*** 0.041*** 0.021** 0.017*

0.545*** 6.449 -0.986 -10.500* -1.169 0.297 1.818 0.838 -6.496 2.265* 0.962 0.412

0.477*** 0.029 -0.004 -0.071* -0.059 0.077 0.059 0.027 -0.062 0.074* 0.001 0.006

0.619*** 10.818*** -7.348* -7.249*** -0.526 0.606*** -0.460 -0.634* -7.052*** 1.301*** 2.422** 1.215*

0.557*** 0.087*** -0.017* -0.047*** -0.011 0.140*** -0.014 -0.019* -0.063*** 0.042*** 0.020** 0.017*

0.515*** 10.818*** -7.348* -7.249*** -0.526 0.312* 1.940 -0.634* -7.052*** 1.301*** 2.422** 1.215*

0.451*** 0.049*** -0.028* -0.049*** -0.026 0.080* 0.064 -0.020* -0.067*** 0.042*** 0.024** 0.017*

0.010*** 0.604*** -0.281*

0.327*** 0.163*** -0.021*

0.006*** 0.573** -0.221

0.199*** 0.092** -0.030

0.010*** 0.604*** -0.269**

0.327*** 0.163*** -0.020**

0.006*** 0.604*** -0.269**

0.197*** 0.097*** -0.037**

Female 0.304*** 0.067*** 0.534*** 0.129*** 0.320*** 0.070*** 0.320*** 0.077*** Household poverty -0.030** -0.021** -0.014 -0.025 -0.026** -0.018** -0.026** -0.047** Cognitive ability 0.017*** 0.134*** 0.025*** 0.228*** 0.017*** 0.134*** 0.025*** 0.229*** Family’s attitude to education 0.159*** 0.160*** 0.170*** 0.198*** 0.160*** 0.160*** 0.160*** 0.188*** Insecurity at school -0.008 -0.009 -0.049 -0.056 -0.011 -0.012 -0.011 -0.013 Classroom misconduct 0.102** 0.030** 0.242* 0.082* 0.111*** 0.033*** 0.111*** 0.038*** Academic interest 0.008 0.009 -0.001 -0.002 0.008 0.008 0.008 0.009 Future prospects 0.124*** 0.034*** 0.100 0.035 0.122*** 0.034*** 0.122*** 0.043*** Peer status 0.033 0.015 -0.011 -0.006 0.030 0.014 0.030 0.015 R2 educational attainment 0.39 0.30 0.39 0.30 R2 school grades 9th grade 0.52 0.34 0.52 0.34 R2 school grades 6th grade 0.58 0.48 0.58 0.48 c c x2 by group df=1, 0.70, p=0.40 df=1, 3.90, p=0.05 2 x overall df=2, 4.60, p=0.10 df=53, 35.73, p=0.97 RMSEA 0.015 0.000 CFI 1.000 1.000 TLI 0.993 1.002 a b Note: B=unstandardized coefficients. β=standardized coefficients. Non-out-of-home-care, N=11,525. Out-of-home-care, N=771. c Not reported because of constraints between groups. *p <0.05. **p <0.01. ***p <0.001.

27

Appendix A. Bivariate correlations for full sample and by groups. Variable s 1. Educatio nal attainme nt 2. School grades 9th gr. 3. School grades 6th gr. 4. Family educati on 5. Mother teen mum 6. Female 7. Househo ld poverty 8. Cognitiv e ability 9. Family’s attitude to edu. 10. Insecurit y at school 11. Classroo m miscond uct 12.

1.

2.

3.

4.

5.

6.

7.

-

.55*** .55***/.4 0***

-

.53*** .53***/.4 4***

.69*** .69***/.5 5***

-

.35*** .35***/.2 2***

.31*** .31***/.1 5***

.32*** .32***/.2 0***

-

-.07*** -.07***/.03

-.06*** .06***/.0 1 .03*** 0.03***/. 00 -.16*** -.14***/.16***

-.06*** .06***/.0 1 .14*** .14***/.1 4*** -.19*** -.17***/.15***

-.08*** -.08***/.04

-

-.01 -.01/.01

-.02 -.01/-.03

-

-.17*** -.15***/.18***

.06*** .04***/.0 4

.00 -.01/.07

.05*** 0.04***/. 06 -.15*** -.14***/.15***

-

.43*** .52*** .62*** .28*** -.06*** -.07*** -.17*** .43***/.3 .52***/.3 .62***/.5 .28***/.1 -.05***/- -.07***/- -.15***/9*** 7*** 2*** 5*** .00 .10** .18*** .38*** .34*** .45*** .25*** -.06*** -.06*** -.14*** .38***/.3 .34***/.3 .45***/.4 .24***/.2 -.06***/- -.05***/- -.12***/8*** 3*** 2*** 4*** .01 .08 .17*** -.20*** -.20***/.19***

-.28*** -.28***/.19***

-.33*** -.32***/.33***

-.14*** -.13***/.16***

.02* .03**/.06

.15*** .10*** .15***/.1 .08***/.1 3*** 4***

-.06*** -.06***/.01

-.16*** -.16***/.10*

-.18*** -.18***/.15***

.02 .02/.08*

.02* .02/-.00

-.38*** -.38***/.38***

.04*** .03***/.0 2

.11***

.18***

.19***

.03***

.01

.04***

-.03**

Academi .12***/.0 .18***/.1 .19***/.0 .03***/.0 c interest 8* 3** 9* 4

.01/.09*

13. Future prospect s 14. Peer status

.16*** .19*** .23*** .12*** .17***/.0 .20***/.0 .23***/.1 .12***/.1 9* 9* 6*** 1**

.01 .01/.02

.19*** .29*** .41*** .09*** .19***/.0 .29***/.1 .41***/.3 .08***/.0 7 5*** 0*** 2

-.03** -.02*/.01

.03**/.13 *** .03***/.0 2 -.06*** -.04*** -.06***/- -.04***/.02 .03 -.01 -.01/-.00

-.08*** -.07***/.01

Variable 8. 9. 10. 11. 12. 13. 14. s 8. Cognitiv e ability 9. .41*** Family’s .41***/.3 attitude 9*** to edu. 10. -.26*** -.25*** Insecurit -.26***/- -.25***/y at .21*** .26*** school -.01 -.04*** -.06*** 11. Classroo -.01/-.00 m .04***/.0 .06***/.0 miscond 2 4 uct 12. .04*** .22*** -.36*** -.24*** Academi .05***/.0 .22***/.2 -.36***/- -.25***/c interest 0 5*** .28*** .23*** .16*** .17*** -.18*** .01 .09*** 13. Future .17***/.0 .18***/.1 -.18***/- .01/-.00 .09***/.0 prospect 6 4*** 13*** 5 s 14. Peer .25*** .17*** -.19*** -.03** .06*** .09*** status .25***/.1 .18***/.0 -.19***/- -.03**/- .06***/.0 .09***/.0 3** 2 .13** .01 2 6 Note: Boldface correlations are for full sample (n=12,296). Correlations by groups are listed beneath full sample correlations [non-out-of-home care (n=11,525)/out-of-home care (n=771)]. *p <0.05. **p <0.01. ***p <0.001.

29

Appendix B. Standardized direct, indirect, and total effects for each predictor on the educational outcomes. Direct effect Non-OHCa OHCb School grades 6th grade Family education Mother teen mum Female Household poverty Cognitive ability Family’s attitude to education Insecurity at school

Indirect effect Non-OHCa OHCb

Total effect Non-OHCa OHCb

0.107*** 0.062*** 0.206*** 0.130*** 0.314*** 0.003 0.006 -0.023*** 0.035*** 0.026** 0.161*** 0.171*** -0.023** 0.032*** 0.138*** 0.034*** 0.023 -0.089*** 0.117*** 0.123*** 0.435*** 0.379*** 0.155*** 0.138*** 0.590***

0.161*** 0.182*** 0.098*** 0.177*** Classroom misconduct 0.088*** 0.096*** Academic interest 0.052*** 0.058* Future prospects 0.082*** 0.101*** Peer status 0.228*** 0.234*** School grades 9th grade School grades 6th grade 0.557*** 0.451*** Family education 0.087*** 0.049*** Mother teen mum 0.017* 0.028* Female 0.047*** 0.049*** Household poverty 0.011 0.026 Cognitive ability 0.140*** 0.080* Family’s attitude to education 0.014 0.064 Insecurity at school 0.019* 0.020* Classroom misconduct 0.063*** 0.067*** Academic interest 0.042*** 0.042*** Future prospects 0.020** 0.024** Peer status 0.017* 0.017* Educational attainment School grades 9th grade 0.327 *** 0.197*** School grades 6th grade Family education 0.163 *** 0.097*** Mother teen mum 0.020 ** 0.037**

30

-

-

-

-

-

-

-

-

0.192*** 0.041** 0.138*** 0.140*** 0.517***

0.161*** 0.182*** 0.098*** 0.177*** 0.088*** 0.096*** 0.052*** 0.058* 0.082*** 0.101*** 0.228*** 0.234***

0.557*** 0.451*** 0.219*** 0.117*** 0.306*** 0.166*** -0.019*** 0.026*** 0.035*** 0.054*** 0.089*** 0.080*** 0.042*** 0.031** -0.089*** 0.093*** 0.100*** 0.119*** 0.339*** 0.269*** 0.479*** 0.349*** 0.090*** 0.082*** -0.054*** 0.080*** -0.049*** 0.043*** 0.029*** 0.026* 0.046*** 0.046*** 0.127*** 0.105***

0.076*** 0.146*** 0.074*** 0.100*** 0.112*** 0.110*** 0.071*** 0.016 0.065*** 0.070*** 0.144*** 0.122***

0.327*** 0.197*** 0.182*** 0.089*** 0.182*** 0.089*** 0.186*** 0.126*** 0.349*** 0.223*** 0.025*** 0.030*** 0.049*** 0.042***

Female Household poverty Cognitive ability Family’s attitude to education Insecurity at school

0.070 *** 0.077*** 0.021*** 0.030*** 0.048*** 0.062*** 0.018 ** 0.047** 0.063*** 0.087*** 0.041*** 0.067*** 0.134 *** 0.229*** 0.225*** 0.144*** 0.359*** 0.373***

0.160 *** 0.188*** 0.025*** 0.029** 0.185*** 0.217*** 0.012 0.013 0.024*** 0.020*** 0.036*** 0.033** Classroom misconduct 0.033 *** 0.038*** 0.037*** 0.022*** 0.003 0.016 Academic interest 0.008 0.009 0.023*** 0.003 0.032*** 0.012 Future prospects 0.034 *** 0.043*** 0.021*** 0.014*** 0.055*** 0.057*** Peer status 0.014 0.015 0.047*** 0.024*** 0.061*** 0.039*** a b Note: Non-out-of-home-care, N=11,525. Out-of-home-care, N=771. c The significance levels shown here are for the unstandardized solution. *p <0.05. **p <0.01. ***p <0.001.

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Exploring educational pathways over the life course in children with out-of-home care experience: A multi-group path analysis

Highlights    

Children in out-of-home care had lower educational outcomes over the life course compared to peers Overall, the educational pathways were rather similar across groups Cognitive ability and previous school performance had the largest associations with the outcomes, but these predictors had a weaker influence in the care group The positive influence of the birth family’s attitude towards higher education was stronger in the care group

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