I will most likely use the data collected from summit county juvenile court and perhaps

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1 Bethany Phillips April 30 I will most likely use the data collected from summit county juvenile court and perhaps some data that will be collected with Dr. Zhao over the summer. I am not sure exactly what my thesis will encompass. I do however want to look at:child maltreatment family environment, child behaviors & attitudes, assessment of these according to family systems theory & child development theories as well. I will also be looking at attachments these children do/do not have with friends and family. To do this I will investigate the presence/absence of a parent, what the family unit is comprised of, how the child describes the relationship, what kind(s) of behavior the parent exhibits, and which of these behaviors may the child be mirroring. But most importantly I will be looking at the family's stability, whether or not the child was maltreated, the child's attitude/behavior, etc. I think it would be important to assess any clinical levels (i.e. depression, anger) the child is either physically expressing or is keeping on the inside. There is so much information that can be gathered from this dataset. Right now the dataset includes over 300 juveniles that were assessed according to the SPPI which was administered by a clinical forensic psychologist. All of the juveniles have exhibited antisocial behavior/attitudes and were referred b/c of suspicion of psychiatric problems. So again, there is much that I can do with this database. Literature Review Previous research on juvenile crime has found a variety of environmental factors

2 to be related to the occurrences of juvenile crime, such as key family variables (Hay et. al, 2006), direct file waiver laws (Steiner & Wright, 2006), institution of parenting programs (Ralph & Sanders, 2006), and the presence of maltreatment during childhood (Kelley, Thornberry, & Smith, 1997). Research has also investigated the role of a parent s socioeconomic status, measured according to parental reported education and occupational status (Tuvblad, Grann, & Lichtenstein, 2006). Although there has been extensive research, reports often are not cohesive as they measure isolated variables that cannot be compared to reports from other studies. Research on juvenile crime is extensive; previous research has found a variety of variables to be related to the occurrences of juvenile crime. These variables mainly focus on environmental factors surrounding a child. The following articles focus on the relative impact of community disadvantage in relation to family and juvenile crime (Hay et. al., 206), the deterrence effects of direct file waiver laws (Steiner & Wright, 2006), and the impact of the Teen Triple P Positive Parenting Program (Ralph & Sanders, 2006). It is first necessary to assess the role one s environment plays. In this case, community disadvantage will be assessed. Hay et al. (2006) sought to identify whether key family variables depend on the level of disadvantage in the community. And also, whether community disadvantage significantly moderate the effects of these family variables, and if so, does it amplify those effects. This study used a national sample of adolescents (NSC); they were first interviewed when they were age 7 11 and a follow up was conducted when they were age The NSC data was supplemented with data from the 1980 census, in a format of two waves. Waves 1 and 2 data assessed five family variables; parent child attachment, parental monitoring, parental reinforcement of

3 prosocial behavior, parents use of physical punishment, and parental coercion. These five measures were coded in such a way that high scorers were exposed to family environments that should increase crime. In the second wave, two measures of community disadvantage were also assessed. One measure was objective (level of community poverty) and the other measure was perceptual (parents were asked to rate their own communities. Seven items in the NSC that measured involvement in more serious violations were instituted as the crime variables; these variables were used to construct three category specific scales (for acts against persons or property, drug use, and police contacts) and one general scale that included all items (Hay et al.). This study was founded in three theories; Agnew s (1992) General Strain Theory, and Hirschi s (1969) Social bonding Theory. Agnew s theory proposes that the effects of strain are greatest when strain is combined with factors that promote use of criminal adaptations while Hirschi s theory proposes that the differences in crime between those with strong and weak bonds are greatest in environments [filled] with criminal influences (Hay et al.). All family variables were significantly related to overall crime: in essence, a weak family environment was associated with greater crime. This study solidifies the propositions of Agnew and Hirschi s theories. Steiner and Wright (2006) assessed the relative effects of state direct file waiver laws on violent juvenile crime. It sought to identify what kind(s) of deterrent effects, if any, do juvenile transfer laws have on juvenile crime. A legislative history of the statutes for each state that has direct file waiver laws (14 in total) and an internet survey of each state s attorney general s office were conducted. A quasi experimental multiple interrupted time series was instituted that consisted of each state s monthly juvenile

4 arrest rate (per 100,000 persons under 18) for homicide/manslaughter, and all violent index crime (homicide/manslaughter, rape, robbery, aggravated assault) for each month during the five year period prior to the effective law date and for each month of the five year period after the effective law date. Steiner & Wright (2006) found the direct file laws to have little effect on violent juvenile crime; most states violent crime rates were not lower in the period after the effective law date. In total, nine states were complete unaffected, and several states saw an increase most likely due to a history effect, only Michigan evidence deterrent effect. Ralph and Sanders (2006) evaluated the Teen Triple P Positive Parenting Program to see if this program has the power to significantly reduce a variety of risk factors for adolescents. This study assessed 771 parents with year old children from four schools in Australia. Initially telephone interviews with the parents were conducted. Parents were assessed using the Strengths and Difficulties Questionnaire (SDQ) and the Family Background Questionnaire (FBQ). They were reassessed on these same measures twelve months later. The students were assessed using the Adolescent Health and Well being Survey. After both parents and children were assessed, a group Teen Triple P Program was instituted. Out of the 334 families who had completed both parents and students questionnaires, only 56 families completed the group program. In the group Triple P Program families were assessed on parent child conflict, parenting style, conflicts over parenting, parenting beliefs, and parental adjustment. Compared with pre treatment scores, parents who participated in the group programs did report significant improvements on almost all of the assessment measures (Ralph & Sanders). This study reported insufficient funding as it s reasoning behind the final population

5 number being so small. As has been shown in these articles, vast research has been conducted with juvenile crime as the variable of interest and there continues to be a great interest in a variety of factors that influence juvenile crime. Further, there is more to be done with the research, with great implications of how to decrease juvenile crime. Present Study The present study seeks to incorporate varied environmental factors established in previous research to be related to occurrences of juvenile crime. Summit County Juvenile Court de identified secondary data is used to investigate possible interactions between an individual family s socioeconomic information (i.e. the first and second economic providers economic and educational levels), maltreatment as a child (presence or absence), and family stability (i.e. family functioning). Correlational analysis will be used to determine how, and if, these variables interact. In accordance with research in this field, this study will be modeled after the Family Systems Theory. This theory presupposes that one s quality of life is a function of individual characteristics, family characteristics, and community characteristics. Families are considered systems because they are made up of interrelated elements or objectives, they exhibit coherent behaviors, they have regular interactions, and they are interdependent on one another. In accordance with this theory, the present study aims to identify the relationship of individual and familial characteristics on juvenile delinquency. Methods

6 Setting This current study utilized de identified secondary data from the Summit County Court of Common Pleas Juvenile Division. The juvenile court has five divisions, but only three (truancy, delinquency, and crossroads) were assessed for purposes of this study. Participants Participants were 69 juveniles, aged 11 23, the mean is 15.5, the mode is 16, and referred to the Summit County Court of Common Pleas Juvenile Division because of suspected psychiatric problems. Data on both males and females were included. The participants were either from the community area or detention centers. Measures The Standard Pediatric Psychosocial Interview (SPPI) was administered to each respondent by a clinical forensic psychologist or trained graduate student. Since data from the Juvenile Court did not have enough community variables to include in the overall model of the family systems theory, only individual and familial characteristics were investigated. The first model measured individual characteristics through the incorporation of objective and subjective variables, e.g., age, gender, likelihood of maltreatment, age at which maltreatment began, psychiatric symptoms, demise of parent/caregiver relationship, and antisocial impulses/stealing. Age or respondent was grouped into three categories: younger adolescence (11 13), middle adolescence (14 16), and older adolescence (17 23). The respondents were grouped as such to allow for identification of

7 fundamental differences in these age categories. Psychiatric symptoms were measured via a calculation of the respondent s current Estimated Global Adaptive Functioning for severity. Because responses ranged from 0 80 and to allow for better understanding of the data, the responses were recoded into three categories: very severe (0 40), moderately severe (41 60), and mildly severe (61 80). The recoded variables were given the respective values of 1, 2, and 3 in the order in which they were previously introduced. The demise of parental/caregiver relationship was subjectively measured as respondents were asked if this relationship had worsened in the past three months. Finally, antisocial impulses/stealing were assessed according to an index of repeated behaviors. The second model measured familial characteristics through the inception of both objective and subjective variables, e.g., diffusion of authority, total number of children in household, catastrophic events affecting family of origin, maternal and/or paternal substance abuse during respondent s early childhood, racial/ethnic background, maternal and paternal educational levels, and maternal and paternal economic statuses. None of the familial characteristics were recoded. It was also assessed as to whether either model correlates with the respondent s scaled score for angry tension. This variable had ten response options so was recoded into three categories to allow for easier analysis. Scores ranging from 0 3 were relabeled with a 1 for low angry tension, scores 4 6 were relabeled with a 2 for normal angry tension, and scores with 7 10 were relabeled with a 3 for high angry tension. It was determined important to assess angry tension in these particular individuals, as angry tension is the anger not verbally expressed, and therefore difficult to catch. Results

8 Of the 69 juveniles 75.4% were male (N= 52), 24.6% were female (N=17). The mean age was 15.5 years of age. In accordance with the established age categories, middle adolescence comprised 66.7% (N=46), followed in succession by older adolescence (24.6%, N=17) and younger adolescence (8.7%, N=6). In regards to maternal education, the majority possessed a high school education (29%, N=20). Thirteen percent received a technical education or partially completed college (N=9); 11.6% completed college (N=8). In regards to paternal education, the majority were high school graduates (20.3%, N=14). Sixteen percent received a technical education or partially completed college (N=11). Twenty two respondents (31.9%) did not report on maternal education while twenty nine respondents (42%) did not report on paternal education. When assessing maternal economic status, thirty two percent were employed in a technical position (N=22). Ten worked in manual service (14.5%) and seven as skilled professionals (N=7). Twenty two percent reported a paternal figure to be employed as a technical professional (N=15) and ten percent employed in a manual service/labor position (N=7). Nineteen (27.5%) did not report on maternal economic status while twenty seven (39%) did not report on paternal economic status. Bivariate correlational analysis revealed numerous significant correlations in both Model 1 and Model 2. In Model 1, five significant correlations were found. At the 0.05 level, age of respondent exhibited a significant relationship with the age at which maltreatment began (r =. 249) and the index for demise in relations with parent/caregiver in past three months (r =. 274). The likelihood a respondent experienced maltreatment was significantly related to the respondent s estimated global adaptive functioning for

9 severity of psychiatric symptoms (r =.299). At the 0.01 level, the age at which maltreatment began was significantly related to two variables, likelihood of maltreatment (r=.467) and the respondent s estimated GAF (r =.350). In Model 2, a total of eleven significant correlations were found. At the 0.05 level, the respondent s scaled score for angry tension was significant in its relationship with the index for catastrophic events affecting the family of origin (r =.259). The index of racial/ethnic background of respondent exhibited a significant relationship with four variables, maternal education level (r =.803), maternal economic status (r =.848), paternal education level (r =.697), and paternal economic status (r =.687). Paternal education level was also significantly correlated with two other variables: maternal education level (r =.742), and maternal economic status (r =.722). Paternal economic status was also significantly correlated with three other variables outside racial/ethnic background; maternal education level (r =.663), maternal economic status (r =.767), and paternal education level (r =.941). Finally, the possibility of maternal substance abuse during the respondent s early childhood was significantly correlated with the possibility of paternal substance abuse during the same time period (r =.842). Conclusions This study sought to examine the interconnectedness of individual and familial characteristics as related to the lives of juveniles. Previous research has generally assumed that delinquents come from socioecomically disadvantaged backgrounds (Rutter et al., 1998) and the findings from this study support this research. This study also further supports the impact of race and ethnicity on the educational and economic levels of both maternal and paternal figures. The significant findings within the individual and

10 familial characteristics support the already well established research base that key family variables do affect juvenile delinquency. The current study did not find any new information for the field of juvenile delinquency, but was able to support previous research. There were many limitations to this study, but the greatest limitation was the time constraint. More time is indeed necessary to delve deeper into this database. Currently the SPPI has been administered to over 200 juveniles, though only 69 were completed at the time of this study. This in and of itself displays innumerable possibilities for future findings with more time. Also with the study relying on secondary data, it was difficult to interpret and understand a database that was collected by other individuals and to arrange meetings to interpret the data s variables and values on such a limited time frame. Initial References Barton, W.H., Watkins, M., & Jarjoura, R. (1997). Youths and communities: Toward comprehensive strategies for youth development. Social Work, Vol 42 (5), Brank, E.M., & Weisz, V. (2004). Paying for the crimes of their children: Public support of parental responsibility. Journal of Criminal Justice, Vol 32, Hay, C., Fortson, E.N., Hollist, D.R., Altheimer, I., & Schaible, L.M. (2006). The impact of community disadvantage on the relationship between the family and juvenile crime. Journal of Research in Crime and Delinquency, Vol 43 (4),

11 Hinton, W.J., Sheperis, C., & Sims, P. (2003). Family based approaches to juvenile delinquency: A review of the literature. The Family Journal: Counseling and Therapy for Couples and Families, Vol 11 (2), Ralph, A. & Sanders, M. (2006). The Teen Triple P Positive Parenting Program: a preliminary evaluation. Youth Studies Australia, Vol 25 (2), Simons, L.G., & Conger, R.D. (2007). Linking mother father differences in parenting to a typology of family parenting styles and adolescent outcomes. Journal of Family Issues, Vol 28 (2), Steiner, B., & Wright, E. (2006). Assessing the relative effects of state direct file waiver laws on violent juvenile crime: deterrence or irrelevance? The Journal of Criminal Law & Criminology, Vol 96 (4), Tuvblad, C., Grann, M., & Lichtenstein, P. (2005). Heritability for adolescent antisocial behavior differs with socioeconomic status: gene environment interaction. Journal of Child Psychology and Psychiatry, Vol 47 (7), Table Below

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