The differential relationship among peer group indicators and internalizing symptoms in a problematic absenteeism population.
Problematic school absenteeism may result from school refusal behavior, or child-motivated refusal to attend school (Kearney, 1996). This term encompasses many subtypes of absenteeism, including truancy, school phobia, and anxiety-based nonattendance, as well as the length of nonattendance (Kearney, 2003). Previous research has estimated that school refusal behavior may affect as many as 5 to 28% of youths in their lifetime (Kearney, 2001). Indeed, school absenteeism can manifest both short-term (i.e., immediate) difficulties for children, their families, and school communities, as well as yield broad societal impact and long-term consequences for youths if nonattendance leads to school dropout. Long-term consequences include such as lower socioeconomic attainment, lower overall life-earnings, downward social mobility, higher incidences of criminal activity, and larger families (Hathaway, Reynolds, & Monachesi 1969; Hibbett & Fogelman, 1990; Hibbett, Fogelman, & Manor, 1990; US Census Bureau, 2005).
To better understand factors that facilitate or contribute to school refusal behavior, and increase comparability across disciplines, researchers have hypothesized an Interdisciplinary Model that addresses both proximal and distal factors that contribute to a youth's absenteeism (Kearney, 2008). This model details five levels, each with furthering degrees of proximity to the youth. The Primary level focuses on youths' variables associated with nonattendance, such as psychopathology.
The Secondary level is parental characteristics associated with youths' nonattendance, such as parental disengagement, confusion, parent-based school withdrawal, or parent-based psychopathology. This level could and frequently does intersect with the Primary level. For example, nonattendance could be exacerbated by both the psychopathology of the youths as well as parental disengagement, confusion, parent-based school withdrawal, and/or parent-based psychopathology.
The Tertiary level is where previous factors (e.g., youth's psychopathology, family dysfunction) could intersect with more distal factors, such as youths' peers. A common example is youths who associate with deviant peers who, in turn, create further opportunities for nonattendance. On-going absences and continued engagement in deviant peer groups may then be propelled by parent disengagement.
The Quaternary level is where youths, parent/family, and peer influences could intersect with school-oriented factors. Variables at this level can include school climate, inadequate responsiveness to student academic needs, teacher absenteeism, and inflexible disciplinary practices (Brookmeyer, Fanti, & Henrich, 2006; Jimerson, Anderson, & Whipple, 2002; Lee & Burkam, 2003). If the youths do not have support socially or within their family, school characteristics such as these can increase the likelihood of school dropout (Kearney, 2008).
The Quinary level represents how community factors could intersect with youths, parent/family, peer, and school factors. These community factors can include but are not limited to disorganized/unsafe neighborhoods, geographical, cultural, and subcultural values, gang-related activity, and school-based racism and discrimination (Kearney, 2008). For example, an unsafe neighborhood may contribute to an increase in school violence, engender more engagement with deviant peers, create dysfunction in family parenting practices, and increase youths' access to substance use. These interactions can coalesce to promote school nonattendance. Intersections with each of the other levels are frequent but are not necessary for a variable to be considered part of a more distal level. For example, community factors (i.e., Quinary level) may interact with youths and peer factors, but may not intersect with parental factors, such as disengagement or family dysfunction.
Most extant research has focused on the Primary level, which includes intra-individual variables (e.g., psychopathology) that may contribute to nonattendance. Internalizing disorders, such as anxiety and depression, are often associated with decreased attendance (Kearney, 2001). Indeed, in a sample of 143 chronically absent youth, Kearney and Albano (2004) found that 41.3% of children met criteria for a primary anxiety diagnosis. An inspection of this sample revealed subtypes that included separation anxiety (22.4%), generalized anxiety (10.5%), specific phobia (4.2%), social anxiety (3.5%), panic (1.4%), and posttraumatic stress (0.7%) disorders.
Similarly, past studies have found an association between depression and chronic absenteeism (Agras, 1959; Egger, Costello, & Angold, 2003; Kearney, 1993). A recent review examined this association across several studies and found that approximately one third (i.e., 31.4%) of chronically absent youths met the criteria for a diagnosis of depression (Kearney, 1993). Furthermore, this study estimated that nearly half (i.e., 47.6%) of school refusing youths reported sub-threshold symptoms of depression. Taken together, past research suggests high rates of mood disorder and anxiety among school refusing youths.
However, primary factors are only one component of the broader constellation of factors that facilitate nonattendance. Few studies have investigated the intersection of primary factors (e.g., youths' mental health) and broader factors (e.g., family functioning, peer groups, school environment). Therefore, the purpose of the present paper is to investigate the associations between peer relationships and youths' psychological health in a problematic absenteeism sample.
There is a dearth in the literature assessing peer group quality and youths' mental health in a non-attending population. As such, literature in other domains of academic functioning was assessed and has highlighted the salience of peer groups relative to academic and social success. Specifically, previous studies have demonstrated the importance of assessing both peer support and acceptance, as independent predictors of youths' academic achievement (Wentzel, 1991). However, these variables are rarely assessed simultaneously, with most research focusing on one or the other.
Peer acceptance has been defined as how much children are liked by their peers (Eisenberg, Fabes, & Spinrad, 2006). In regard to peer support, previous studies have operationalized this construct as a multifaceted variable that includes material assistance (i.e., taking action to help further one's goal), cognitive aspects (i.e., helping one think through problems), and emotional support (i.e., recognizing and demonstrating empathy for one's emotions) (Rigby, 2000). Peer support has been demonstrated to predict school attendance. Specifically, youths who perceive support from their friends have higher rates of attendance (De Wit, Karioja, & Rye, 2010).
In contrast, rejection by one's peer group (i.e., an absence of peer acceptance) has been found to predict detrimental academic outcomes, including poor attendance and disenrollment from school (Bellmore, 2011; Buhs, Ladd, & Herald, 2006; French & Conrad, 2001; Kearney, 2001). However, youths who report peer support while experiencing overall peer rejection (e.g., bullying) generally demonstrate better mental health outcomes. These youths were rejected from the majority peer group, but experienced emotional support through few close acquaintances (Rigby, 2000). In view of these findings from past research, both adaptive and maladaptive patterns of peer support and peer acceptance should be studied in tandem to better understand the association between overall peer group quality and absenteeism.
In addition to understanding school absenteeism, peer acceptance and support are associated with symptoms of psychopathology in non-attending youths (Parker & Asher, 1987). In particular, both low peer acceptance and peer support has often been associated with meeting diagnostic criteria for depression and sub-threshold symptoms of depression among youths in cross-sectional study designs (Lara, Leader, Klein, 1997; Segrin, 2000). Longitudinal studies also highlight how peer variables, such as peer rejection, will precede later depressive symptoms (Boivin, Hymel, & Bukowski, 1995; Cole, 2001; Peirce, Frone, Russell, Cooper, & Mudar, 2000). For example, Boivin and colleagues (1995), as cited above, found in their sample of 567 children that peer withdrawal and rejection predicted higher scores of depression as measured two years later as compared to those who did not experience such peer dysfunction. Peer rejection has also been found to predict symptoms of anxiety, both experimentally-induced peer rejection (Nesdale & Pelyhe, 2009) as well as in longitudinal studies (Keiley, Bates, Dodge, & Pettit, 2000).
Despite the observed associations between peer acceptance, peer support, and internalizing symptoms in children, few studies have assessed these predictors simultaneously. This paper sought to address this gap in the literature by investigating the differential associations among peer support, peer acceptance, and youths' mental health in a non-attending sample of truant court-referred youth. We hypothesized that both peer acceptance and peer support would emerge as significant independent predictors of symptoms of anxiety and depression. Peer acceptance was defined as youth social standing in the peer group (i.e., accepted versus rejected) and peer support defined as the youth perception of social support within the peer group.
Participants were 31 rural parent-youth dyads recruited from a regional Juvenile Court Truancy Court Program in a Northwestern State. The age of youth participants ranged from 8 to 17 years (M=13.70, SD=2.63). Most of the youths included in the sample were male (n=16, 51.6%). Seventy percent of parent participants were mothers, followed by 18% fathers, and 5% other (e.g., legal guardians). Participants identified as predominantly European-American (n=19, 61%), American Indian (n=5, 16%), Latino/a (n=5, 16%), Asian American (n=1, 3.2%) and unknown (n=1, 3.2%). Youths reported missing between 1 and 60 unexcused days of school (M=16.32, SD=15.61) and on average were in 8th grade, with a range from 1st grade to 12th grade.
All youth were referred to the Regional Juvenile Court under the charge of habitual truancy. Habitual truancy was defined as three or more days of unexcused absences in a given semester. The Truancy Court program is a diversionary program that serves as an alternative to formal probation or other adjudication.
School Success Profile. The School Success Profile (SSP; Bowen & Richman, 2005) is a self-report measure for children and adolescents. It assesses the social environment through systematic factors related to family, youths, and parents. Eighteen different dimensions measure these factors such as Neighborhood Support, Neighborhood Youth Behavior, Neighborhood Safety, Learning Climate, School Satisfaction, Teacher Support, School Safety, Peer Support, Peer Group Acceptance, Friend Behavior, Family Togetherness, Parental Support, Home Academic Environment, Parent Education Support, and School Behavior Expectations.
For the purpose of this study, only the friend dimension of the SSP was used, consisting of subcomponents of Peer Support and Peer Group Acceptance. Peer Support assesses students' perception of emotional support and satisfaction with peer relationships. High scores on Peer Support reflect satisfaction with peer group. Peer Acceptance assesses students' perceptions of their relative standing in their peer group, their ability to be themselves, and their ability to resist peer pressure. High scores on Peer Acceptance reflect the perception of a loss of standing in peer group. In the interest of clarity, we hereafter refer to this subscale as "Peer Rejection" (i.e., an absence of peer acceptance). For this sample, the Cronbach's coefficient alphas of Peer Rejection and Peer support were .85 and .86, respectively, suggesting good internal consistency. Moreover, the internal consistency reliability analysis demonstrates SSP correlating significantly with other youth assessment surveys (Bowen, Rose, & Bowen, 2005). Further, all dimensions of the SSP demonstrate good construct validity (Bowen, Rose, & Bowen, 2005). The SSP has a 4th grade reading level.
Behavior Assessment System for Children-Second Edition. The Behavior Assessment System for Children-Second Edition (BASC-2; Reynolds & Kamphaus, 2004) is a norm-referenced rating scale designed to examine the emotional and behavioral functioning of a child. It consists of 139-item or 176-item statements, depending on the age of the respondent, that generate composite scores of School Problems, Internalizing Problems, Inattention/Hyperactivity, Personal Adjustment, and an overall composite score--Emotional Symptom Index (ESI). Additionally, 14 primary scales are generated. These assess a wide range of developmental and emotional functioning. For the purpose of the current study, subscales used in analyses were Depression, Anxiety, and Sense of Inadequacy. T-scores in the "At-Risk" range are T-scores of 60 through 69, whereas T-scores of 70 and above are considered clinically significant. Within this sample, the Cronbach's coefficient alpha for Depression, Anxiety, and Sense of Inadequacy was .84, .82, and .78, respectively, overall suggesting moderate to good internal consistency. Research has demonstrated this measure is a valid and reliable assessment of emotional functioning in children and adolescents (Reynolds & Kamphaus, 2004). The BASC-2 requires a 2nd grade reading level. For the purpose of the present study, only the youth report of the BASC-2 was used.
Each of the subscales that we used captures different aspects of psychopathology. The Anxiety subscale assesses generalized fears, nervousness, and worries that typically are irrational and poorly defined, whereas the Depression subscale assesses traditional symptoms associated with depression, such as loneliness, sadness, and inability to feel joy. The Sense of Inadequacy subscale assesses perceptions of low achievement expectations, a tendency not to persevere, and a perception of being unsuccessful (primarily in academic endeavors).
Youths refusing school between the ages of 8.0-17.9 years of age accompanied by legal guardians/parents (18 years of age or older) who had a basic reading ability (1st grade or above), spoke English, and had been referred to truancy court participated in the study. After initial intake at truancy court, parents/legal guardians and youths were asked to participate in the study. If all agreed to participate, they were taken into a separate area from truancy court where the informed consent and assent were explained and any questions answered. The youths and parents/legal guardians completed the self-report measures after signing the consent and assent. Participation in the entire study took approximately 2 hours. Data collection began in the spring of 2014 and concluded in the spring of 2015.
Based on previous longitudinal research of peer relationships and youth mental health (e.g., Boivin, Hymel, & Bukowski, 1995), this study hypothesized that Peer Rejection and Peer Support would be related to internalizing disorders and their symptoms. Correlations were used to assess relations among variables and ordinary least square multiple regressions were planned to examine the unique contributions of each peer variable to outcome variables of depression, anxiety, and sense of inadequacy. Predictors were entered into the model simultaneously. To identify whether Peer Support and Peer Rejection had differential relationships with internalizing disorders and their symptoms, three simultaneous multiple regression analyses were performed. The unique contributions of each predictor in the models were assessed.
Descriptive statistics and correlations of all variables are presented in Tables 1 and 2. The means of the scales of youth psychopathology revealed that 16.2% and 3.2% of the sample were in the at-risk (i.e., T scores of 60 through 69) and clinically significant range (i.e., T-scores 70 and above), respectively. Correlations among variables of interest revealed significant correlations among variables of internalizing symptoms as well as their relationships with Peer Rejection. Peer Support was not significantly correlated with any of the variables of interest or Peer Rejection. Peer Support was included in the regression models since previous research has outlined the importance of assessing both peer support and rejection simultaneously (Rigby, 2000; Wentzel, 1991) as a way to offer a more thorough understanding of peer relationships.
Three multiple regression models tested the relationship between adolescent peer relationships and internalizing symptoms. The models used peer variables of the SSP, Peer Rejection and Peer Support, to predict the various aspects of internalizing disorders (i.e., BASC-2 Depression, BASC-2 Anxiety, and Inadequacy). Each of these models was significant at p < .05. More specifically, Peer Support and Peer Rejection significantly predicted Sense of Inadequacy (F(2, 28) = 3.91, p < .05), Anxiety (F(2, 28) = 5.72, p < .05) and Depression (F(2, 28) = 3.68, p < .05).
A closer inspection of the beta coefficients and semi-partial correlations demonstrated differential relationships between Peer Rejection and Peer Support. Specifically, the semi-partial correlations revealed that Peer Rejection predicted the dependent variables of choice above and beyond Peer Support for models with BASC-2 Anxiety (Peer Rejection: [beta] = 0.43, [sr.sup.2] = 0.46, p < .05; Peer Support: [beta] = -0.314, [sr.sup.2] = 0.35, p = .06), BASC-2 Depression (Peer Rejection: [beta] = 0.36, [sr.sup.2] = 0.37, p < .05; Peer Support: [beta] = -0.28, [sr.sup.2] = -0.30, p = .11), and Sense of Inadequacy (Peer Rejection: [beta] = 0.44, [sr.sup.2] = 0.45, p < .05; Peer Support: [beta] = -.14, [sr.sup.2] = -0.16, p = .40) (See Table 3).
Previous research on school refusal behavior has focused primarily on proximal levels of influence, such as the individual and individual school variables. Research on broader systemic levels of influence, such as peer relationships, school climate, and the community, has been limited. Previous research in other domains (e.g., education, school psychology, family systems) of academic success shows that quality of peer relationships may influence youth's ability to succeed in school, through such avenues as academic achievement and academic completion (Alika, 2012; Kiuru et al., 2015; Polanksy, Villanueva, & Bonfield, 2008) as well as youths' mental health (Parker & Asher, 1987; Rigby, 2000). Research directly assessing the relationship between peers' influence and mental health within a non-attending population has been limited (Kearney, 2008).
The goal of this paper was to assess how peer acceptance and support were associated with symptoms of anxiety and depression in a non-attending population. Our study found that peer rejection (i.e., an absence of peer acceptance) was associated with anxiety and depression and their symptoms. Interestingly, peer support demonstrated no relation to internalizing symptoms. To our knowledge, there has not been a study of this kind that attests to this relationship in a problematic absenteeism population. Moreover, this study highlights the critical need to assess more far reaching systemic factors in the intersection of youths' non-attendance behaviors.
This study also assessed the differential relationships peer rejection and peer support had with internalizing disorders and their symptoms. Our results consistently demonstrated that peer rejection predicted these variables, whereas peer support did not. A role of future research could be to parse apart whether the perception of being accepted by one's peers is more protective against the development of later psychopathology than the perception of being supported. If these results hold, one possibility for this may be because as youth progress through development, their peer group becomes more central to the formation of their self-concept than their nuclear family (Harris, 1995). Therefore, the acceptance of their peers becomes more integral to their self-worth. Peer support may not have the same potency in building youths' self-concepts and identity than acceptance offers. Specifically, peer acceptance may determine whether youths even have a peer group that can offer them support.
These findings have important practical implications. First, corroborating with previous research, this study highlights the importance of students' social groups and their association with internalizing disorders. As such, programs and initiatives designed to help young people develop and/or maintain strong social connections may be related to internalizing symptoms. However, as our results have shown, these programs should emphasize promoting group acceptance rather than merely social support.
This study also suggests an important potential prevention strategy for educators. A decline in attendance is one of many risk factors associated with reduced academic achievement, mental health, and overall wellbeing. Unlike many risk factors that may be covert in a public setting (e.g., family dysfunction or delinquent peer involvement), poor attendance is an overt measure. It can be easily and economically monitored by school officials to target services at the appropriate students. That is, a decline in attendance may indicate that students are at risk for dysfunctional peer groups and/or the onset of psychopathology. Thus, at-risk students can be quickly identified and selected for the further assessment.
There were limiting factors to the present study. First, the data are limited by the retrospective and self-report nature of the instruments employed. Second, the cross-sectional research design employed does not allow for causal inference concerning the variables of interest. Third, a normal comparison group was not used in the present study. Therefore, comments regarding the relationship between peer variables and internalizing symptoms being specific to a non-attending population cannot be made. The specific nature of the sample employed may also limit the generalizability of the present findings. Specifically, this sample of rural court-referred youths may not generalize to school-refusing youths who are not involved in the justice system, or to court-referred youths in other regions of the country. Finally, this study had a relatively modest sample size, which could influence its power. That being said, the present study was conducted with a rural population and with data collection specified for a short time period (i.e., a calendar year). The accruement of the present sample size is therefore understandable. Despite these limitations, this study furthers the understanding of the role peers play in emotional wellbeing in this vulnerable population. A direction for future research could address the efficacy of strengthening peer acceptance in improving emotional wellbeing of non-attending youths. Additionally, investigation should assess the generalizability of the differential importance of peer acceptance and peer support with other populations.
In summary, this study demonstrated a significant association between peer relationship variables and internalizing disorders in a school refusal population. Interestingly, our results deviate from previous studies that found strong inverse associations with peer support and acceptance and internalizing disorders in populations without attendance issues (Rigby, 2000). Specifically, our study demonstrated that peer acceptance predicts internalizing disorders, whereas peer support had no relationship with variables of mental health. School officials and other professionals should be sensitive to these differences when assessing and treating those exhibiting internalizing disorders in this population. Overall, these results, in combination with findings by others, support the necessity of assessing broader systemic factors when conceptualizing and treating problematic school absenteeism.
Agras, S. (1959). The relationship of school phobia to childhood depression. American Journal of Psychiatry, 116, 533-536.
Alika, H. I. (2012). Bullying as a correlate of dropout from school among adolescents in delta state: Implication for counselling. Education, 132, 523-531.
Bellmore, A. (2011). Peer rejection and unpopularity: Associations with GPAs across the transition to middle school. Journal of Educational Psychology, 103, 282-295.
Boivin, M., Hymel, S., & Bukowski, W. M. (1995). The roles of social withdrawal, peer rejection, and victimization by peers in predicting loneliness and depressed mood in childhood. Development and Psychopathology,7, 765-785.
Bowen, G. L., & Richman, J. M. (2005). School success profile. Philadelphia, PA: Xlibris Corporation.
Bowen, G. L., Rose, R. A., & Bowen, N. K. (2005). The reliability and validity of the school success profile. Philadelphia, PA: Xlibris Corporation.
Brookmeyer, K. A., Fanti, K. A., & Henrich, C. C. (2006). Schools, parents, and youth violence: A multilevel, ecological analysis. Journal of Clinical Child and Adolescent Psychology, 35, 504-514.
Buhs, E. S., Ladd, G. W., & Herald, S. L. (2006). Peer exclusion and victimization: Processes that mediate the relation between peer group rejection and children's classroom engagement and achievement? Journal of Educational Psychology, 98, 1-13.
Chou, L., Ho, C., Chen, C., & Chen, W. J. (2006). Truancy and illicit drug use among adolescents surveyed via street outreach. Addictive Behaviors, 31, 149-154.
Cole, D. A., Jacquez, F. M., & Maschman, T. L. (2001). Social origins of depressive cognitions: A longitudinal study of self-perceived competence in children. Cognitive Therapy and Research, 25, 377-395.
De Wit, D. J., Karioja, K., & Rye, B. J. (2010). Student perceptions of diminished teacher and classmate support following the transition to high school: Are they related to declining attendance? School Effectiveness and School Improvement, 21, 451-472.
Egger, H. L., Costello, E. J., & Angold, A. (2003). School refusal and psychiatric disorders: A community study. Journal of the American Academy of Child & Adolescent Psychiatry, 42, 797-807.
Eisenberg, N., Fabes, R. A., & Spinrad, T. L. (2006). Handbook of child psychology. Hoboken, NJ: John Wiley & Sons.
French, D. C., & Conrad, J. (2001). School dropout as predicted by peer rejection and antisocial behavior. Journal of Research on Adolescence, 11, 225-244.
Garry, E. M. (1996). Truancy: First step to a lifetime of problems. Juvenile Justice Bulletin, 1-7.
Guttmacher, S., Weitzman, B. C., Kapadia, F., & Weinberg, S. L. (2002). Classroom-based surveys of adolescent risk-taking behaviors: Reducing the bias of absenteeism. American Journal of Public Health, 92, 235-237.
Hallfors, D., Vevea, J. L., Iritani, B., Cho, H., Khatapoush, S., & Saxe, L. (2002). Truancy, grade point average, and sexual activity: A meta-analysis of risk indicators for youth substance use. Journal
of School Health, 72, 205-211.
Harris, J. R. (1995). Where is the child's environment? A group socialization theory of development. Psychological Review, 102, 458-489.
Hathaway, S. R., Reynolds, P. C., & Monachesi, E. D. (1969). Follow-up of the later careers and lives of 1,000 boys who dropped out of high school. Journal of Consulting and Clinical Psychology, 33, 370-380.
Hibbett, A., & Fogelman, K. (1990). Future lives of truants: Family formation and health-related behaviour. British Journal of Educational Psychology, 60, 171-179.
Hibbett, A., Fogelman, K., & Manor, O. (1990). Occupational outcomes of truancy. The British Journal of Educational Psychology, 60, 23-36.
Jimerson, S. R., Anderson, G. E., & Whipple, A. D. (2002). Winning the battle and losing the war: Examining the relation between grade retention and dropping out of high school. Psychology in the Schools, 39, 441-457.
Kearney, C. A. (1993). Depression and school refusal behavior: A review with comments on classification and treatment. Journal of School Psychology, 31, 267-279.
Kearney, C. A. (1996). The evolution and reconciliation of taxonomic strategies for school refusal behavior. Clinical Psychology: Science and Practice, 3, 339-354.
Kearney, C. A. (2001). School refusal behavior in youth: A functional approach to assessment and treatment. American Psychological Association: Washington, DC.
Kearney, C.A. (2003). Bridging the gap among professionals who address youth with school absenteeism: Overview and suggestions for consen sus. Professional Psychology: Research and Practice, 34, 57-65.
Kearney, C.A. (2008). An interdisciplinary model of school absenteeism in youth to inform professional practice and public policy. Educational Psychology Review, 20, 257-282.
Kearney, C.A., & Albano, A.M. (2004). The functional profiles of school refusal behavior: Diagnostic aspects. Behavior Modification, 28, 147-161.
Keiley, M. K., Bates, J. E., Dodge, K. A., & Pettit, G. S. (2000). A cross-domain growth analysis: Externalizing and internalizing behaviors during 8 years of childhood. Journal of Abnormal Child Psychology, 28, 161-179.
Kiuru, N., Aunola, K., Lerkkanen, M., Pakarinen, E., Poskiparta, E., Ahonen, T., Poikkeus, A. M., Nurmi, J. (2015). Positive teacher and peer relations combine to predict primary school students' academic skill development. Developmental Psychology, 51, 434-446.
Lara, M. E., Leader, J., & Klein, D. N. (1997). The association between social support and course of depression: is it confounded with personality? Journal of Abnormal Psychology, 106, 478-482.
Lee, V. E., & Burkam, D. T. (2003). Dropping out of high school: The role of school organization and structure. American Educational Research Journal, 40, 353-393.
Nesdale, D., & Pelyhe, H. (2009). Effects of experimentally induced peer-group rejection and out-group ethnicity on children's anxiety, self-esteem, and ingroup and out-group attitudes. European Journal of Developmental Psychology, 6(3), 294-317.
Office for Civil Rights. (2016). 2013-2014 Civil Rights Data Collection. Washington DC: Department of Education: http://www2.ed.gov/ about/ offices/list/ocr/docs/2013-14-first-look.pdf.
Parker, J. G., & Asher, S. R. (1987). Peer relations and later personal adjustment: Are low-accepted children at risk? Psychological Bulletin, 102, 357-389.
Peirce, R. S., Frone, M. R., Russell, M., Cooper, M. L., & Mudar, P. (2000). A longitudinal model of social contact, social support, depression, and alcohol use. Health Psychology, 19, 28-38.
Polanksy, M., Villanueva, A. M., & Bonfield, J. (2008). Responses to violence related questionnaires by delinquent, truant and state-dependent boys receiving treatment in an extended day program. Journal of Offender Rehabilitation, 47, 407-432.
Reynolds, C. R., & Kamphaus, R. W. (2004). BASC-2: Behavior assessment system for children. Bloomington, MN: Pearson, Inc.
Rigby, K. (2000). Effects of peer victimization in schools and perceived social support on adolescent well-being. Journal of Adolescence, 23, 57-68.
Segrin, C. (2000). Social skills deficits associated with depression. Clinical Psychology Review, 20, 379-403.
US Census Bureau (2005). Educational attainment in the United States: 2004. Washington DC: US Census Bureau.
Wentzel, K. R. (1991). Relations between social competence and academic achievement in early adolescence. Child Development, 62, 1066-1078.
Elizabeth A. Craun, Courtney Haight, Christopher R. DeCou, Stephanie C. Babbitt, & Maria M. Wong
Idaho State University
Author info: Correspondence should be sent to: Elizabeth Craun, 921 S. 8th Ave., Pocatello, Idaho. 83209. Craueliz@isu.edu
TABLE 1 Descriptive Statistics of Variables of Interest Variables Mean (SD) Minimum Maximum Anxiety 51.30 (11.87) 37 73 Depression 49.61 (11.43) 40 83 Inadequacy 54.82 (10.42) 36 77 Peer Rejection 9.45 (2.32) 2 15 Peer Support 13.03 (2.31) 3 15 TABLE 2 Pearson Correlations of Variables of Interest Anxiety Depression Inadequacy Peer Peer Reject. Support Anxiety -- Depression .59 * -- Inadequacy .52 ** .67 ** -- Peer .44 * .36 * .45 * -- Rejection Peer Support -.32 -.28 -.15 0 -- * p <.05 ** p <.001 TABLE 3 Relationship with Peer Predictors & Internalizing Problems b (SE) [beta] T-value 95% CI [R.sup.2] Anxiety 0.29 Rejection 2.20 (0.80) 0.44 2.74 ** 0.55-3.86 Support -1.52 (0.77) -0.31 -1.97 -3.12-0.06 Depression 0.21 Rejection 1.30 (0.61) 0.36 2.14 * 0.05-2.55 Support -0.97 (0.59) -0.28 -1.67 -2.17-0.22 Inadeauacy 0.22 Rejection 2.10 (0.77) 0.45 2.66 ** 0.48-3.65 Support -0.63 (0.74) -0.14 -0.86 -2.17-0.88 * p <.05 ** p <.01
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|Author:||Craun, Elizabeth A.; Haight, Courtney; DeCou, Christopher R.; Babbitt, Stephanie C.; Wong, Maria M.|
|Publication:||North American Journal of Psychology|
|Date:||Jun 1, 2017|
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