Social relationships among adolescents with disabilities: unique and cumulative associations with adjustment.
Although supportive relationships are important for students of all ages, further understanding about the importance of relationships among adolescents is vital because evidence indicates that students receive diminishing levels of social support as they progress through adolescence (Barber & Olsen, 2004; De Wit et al., 2010; De Wit et al., 2011; Wang & Eccles, 2012). Deteriorations in relationship quality from early to late adolescence are associated with increasing social isolation and depressive symptoms, decreasing self-esteem, and declining scholastic competence (Cantin & Boivin, 2004).
Youth With Disabilities
Despite evidence that strong social relationships positively influence adolescent adjustment, few studies have examined how these relationships affect youth with disabilities, and even fewer have investigated multiple relationships concurrently. Youth with disabilities are particularly vulnerable to social isolation during adolescence (Al-Yagon, 2007, 2012a, 2013). The National Longitudinal Transition Study-2 revealed that social skills are a highly problematic area for students with disabilities, with over 80% reporting low to moderate social skills and just one in six reporting high social skills (Wagner, Newman, Cameto, Garza, & Levine, 2005). Moreover, between 1987 and 2003, approximately 28% of students with disabilities and 44% with emotional disturbance dropped out or were expelled from high school, and two reasons cited for dropout were dislike of school (36%) and poor relationships with teachers and peers (17%; Wagner, Newman, Cameto, Levine, & Garza, 2006). Although youth with disabilities often experience greater difficulties in school than do normative peers, these findings highlight the importance of social relationships and the potential negative consequences associated with negative social relationships in school settings.
Social relationships of adolescents with disabilities may be distinctive in their complexities. Panacek and Dunlap (2003) found that social networks of students with and without disabilities have similar size (number of people) and composition (type of member) at homes and in neighborhoods but not in schools. This distinctive pattern in school could be due to placement in special education, social skill deficits, and the stigma associated with labeling. Students with disabilities also experienced comorbid academic and socioemotional difficulties that have been associated with higher levels of negative affect, externalizing and internalizing problem behaviors, and poorer perception of adult support (Al-Yagon, 2012b, 2013; Pijl, Frostad, & Flem, 2008).
Adolescents must form multiple relationships to meet the multiplicity of their needs across time and context, and these relationships may differ in importance and stability. An exclusive focus on any one dyad potentially "minimizes the complexity of teen's ongoing negotiation of multiple relationships" (Kobak, Rosenthal, Zajac, & Madsen, 2007, p. 64). Prior examination of multiple relationships among students without disabilities contributes to understanding this complexity. For example, Wang and Eccles (2012) found that the influence of parents, peers, and teachers on school engagement are relatively independent and that support from one source could compensate for the lack of support from another source. They found that teachers had a greater influence on school-related outcomes than did parents and peers. Researchers such as Malecki and Demaray (2003) corroborated that supportive relationships with teachers may be a particularly salient resource in the context of school. These findings indicate that adolescents can develop relationships with teachers and peers that differ in terms of pattern and value compared to longer-term relationships formed with caregivers (Sabol & Pianta, 2012). Accordingly, relationships with nonfamily adults and peers may be less stable but may serve unique functions and should be studied concurrently rather than in isolation. At present, little is known about the concurrent influence of multiple social relationships on adjustment outcomes among adolescents with disabilities.
Relationship With Parents
Despite the apparent benefit of teacher--student relationships, prior research suggests that parents continue to be a primary source of security as adolescents explore new relationships with peers and nonfamily adults (Scharf & Mayseless, 2007). Even when interactions with peers grow in complexity, relationships with caregivers remain crucial in late childhood and early adolescence (Gifford-Smith & Brownell, 2003). Relationships that students with disabilities form with parents are sometimes of poorer quality than are those between typically developing youth and their caregivers (Al-Yagon 2007, 2012a). Moreover, relationship difficulties between parents and children are a risk factor for maladjustment across social, emotional, and behavioral domains (Al-Yagon & Mikulincer, 2004; Murray & Greenberg, 2006). A comparison study of parent-child communication found that parents of children with disabilities reported more problematic relationship patterns than did parents of children without disabilities (Heiman, Zinck, & Health, 2008).
Relationship With Peers
Although certainly less stable than parent--child relationships, peer acceptance is also associated with positive emotional and behavioral adjustment. Trust among friends sustains positive peer relationships (Bukowski, Newcomb, & Hartup, 1998), and positive peer relationships are linked to a high quality of life for students with disabilities (Carter, 2011). Research among youth without disabilities has revealed that negative peer relationships can intensify academic difficulties and compromise social development (Gifford-Smith & Brownell, 2003; Wang & Eccles, 2012). Other researchers have found that students with disabilities experience social isolation and peer aggression in school more often than do students without disabilities (Panacek & Dunlap, 2003). Students with disabilities also experience higher incidences of socioemotional difficulties, such as peer-dyadic loneliness, than do students without disabilities (Al-Yagon, 2012a, 2012b). Youth with disabilities who experienced peer alienation face a higher risk for school failure and are more likely to engage in deviant behaviors, such as violence and gang-related activities (Brown, Higgins, Pierce, Hong, & Thoma, 2003).
Although less is currently known about teacher-student relationships among adolescents with disabilities, teacher support is associated with socioemotional wellness (Suldo et al., 2009), life satisfaction (Suldo, Shaffer, & Riley, 2008), and school engagement (Wang & Eccles, 2012) among normative samples. Students' emotional well-being in the classroom, in turn, appears to shape students' academic engagement and achievement (Pekrun & Linnenbrink-Garcia, 2012). Positive relationships with teachers also seem to buffer deleterious effects of behavioral problems among students who smuggle in school (Baker, Grant, & Morlock, 2008; Wang & Eccles, 2012). Recent findings have indicated that among high school students, teacher-student relationships are more important for academic achievement than are peer relationships (Roorda, Koomen, Spilt, & Oort, 2011; Wang & Eccles, 2012).
Relationship With Mentors
A mentor is an adult outside of immediate family or school settings "willing to help ease the transition to adulthood by providing support and challenging students to make good decisions" (Drewry, Burge, & Driscoll, 2010, p. 513). The influence of adults outside the family has not been adequately studied, particularly among students with disabilities. Mentors play an important role in the lives of at-risk youth because they can provide guidance, serve as models of achievement, and facilitate an adolescent's adoption of desirable behaviors and attitudes--all of which can improve school performance and completion (Klaw, Rhodes, & Fitzgerald, 2003). Klaw et al. (2003) found that pregnant teens who had mentors for 2 years postpartum were 3.5 times more likely to stay in school or graduate than pregnant teens who did not have a mentor. Drewry et al. (2010) reported that school retention among young males was associated with mentor relationships with religious leaders (e.g., pastor) and extended family members (e.g., uncle). Even when mentors are not models of academic and career success, they can still advocate on behalf of the youth, set higher expectations for desirable behaviors, reinforce appropriate norms and values, and keep youth focused on positive paths (Hurd, Zimmerman, & Reischl, 2011).
Summary of the Literature and Current Study
Converging evidence suggests that social relationships are a critical dimension of adolescent development, but research in this area has focused extensively on typically developing students. In addition research in this area has not adequately examined the impact of multiple relationships concurrently. Finally, most prior investigations have treated social relationships as a unidimensional construct and failed to identify which dimensions of one's relationship are beneficial or problematic. Assessing multiple dimensions (e.g., trust, communication, alienation) allows for meaningful understanding of the mechanisms that contribute to the influences of each relationship and therefore facilitate the development of relationship-focused interventions.
Converging evidence suggests that social relationships are a critical dimension of adolescent development, but research in this area has focused extensively on typically developing students.
The current study was designed to address these research gaps by examining cumulative and unique associations between social relationships with adults and peers and the emotional, behavioral, and school-related adjustment of adolescents with disabilities. Based on prior research among adolescents without disabilities, we anticipated finding significant positive associations between social relationships and adjustment among adolescents with disabilities. Informed by Wang and Eccles (2012), we hypothesized that relationships with adults would have stronger associations with indicators of adjustment than would peer relationships. However, we did not form directional hypotheses about which adult relationship (i.e., parent, teacher, or mentor) would contribute most to explaining adjustment over and above the influence of other relationships, nor did we hypothesize that a specific dimension of relationships (e.g., trust, communication, alienation) would be more meaningfully associated with adjustment due to limited research of this nature among youth with disabilities. Thus, the following exploratory research questions guided this study:
Research Question 1: Collectively, are relationships with parents, peers, teachers, and mentors significantly associated with the emotional, behavioral, and school-related adjustment of adolescents with disabilities?
Research Question 2: After controlling for other relationships, which social agent has the most significant influence on the adjustment of adolescents with disabilities?
Research Question 3: Which specific dimensions of social relationships contribute to explaining the variance in adjustment indicators among adolescents with disabilities?
The sample for this investigation consisted of 228 students (65% male, 35% female) with disabilities: 73%, learning disabilities; 8%, autism spectrum disorder; 7%, emotional or behavioral disorders; 5%, other health impairments; 4%, intellectual disability; 4%, others, including multiple disabilities. In terms of race/ ethnicity, student participants were as follows: approximately 50%, White; 8%, Black; 22%, Hispanic; 4%, Native American; 2%, Asian/ Pacific Islander; and 8%, multiracial (the remaining 6% of participants did not specify). Participants attended one of 10 public high schools in seven districts across four states, and their ages ranged from 13 to 19 years (M = 16.24). School districts located in fringe rural areas and towns to small, midsize, and large cities in the Midwest, Northwest, Southwest, and Northeast regions of the United States were represented. Approximately 56% of students (n = 128) reported living with both parents; 33% lived with one parent (n = 74); 3% lived on their own (n = 6); and 8% reported other, unspecified living conditions (" = 18). Nearly 14% (n = 32) of students spoke a language other than English at home (27 students spoke Spanish, five students spoke other languages), and the remaining 86% (n = 196) reported English as their primary language. Roughly 23% (n = 52) had relocated at least once within the last 12 months; 13% (n = 30) were working part-time; 49% (n = 112) were planning to attend college. According to teacher reports, 58% (n = 133) of students spent 80% or more of the school day in general education, and 27% (n = 61) spent <40% of the school day in such settings. Also, according to teachers, 44% (n = 101) of participants came from low socioeconomic status backgrounds, 34% (n = 77) from middle backgrounds, 3% (n = 6) from high backgrounds, and 19% (n = 44) of the sample reported unknown socioeconomic status.
Two male and 15 female special education teachers participated in this study; their teaching experiences ranged from 4 to 32 years (M= 14, SD = 9). Fourteen teachers self-identified as White, one as Black, one as Hispanic, and one as Asian. Seven teachers taught English language arts as a core academic subject, four taught mathematics, four taught social studies, one taught science, and one did not specify.
As part of a larger study on social capital, (Pham, 2013) the first author sought permission from 13 school districts to conduct this research after receiving approval from the Institutional Review Board at our home institution. Selection of districts was based on geographical location and district locales because we were interested in sampling students from diverse geographical backgrounds. We contacted small, midsize, and large school districts across the United States, but many were unresponsive. Four were not accepting any research proposals and did not provide any explanations for this decision. Of the 13 districts that accepted applications, two never responded despite more than three attempts to contact them via phone and e-mail. Three districts denied our request: The first gave no reason for the denial; the second said that schools and students were already overwhelmed with testing, so they did not want to support a survey study; and the third district said that our study had no direct benefit to teachers and students. Last, one district confirmed receipt of our application but never responded with a decision. Table 1 summarizes key characteristics of the seven districts that permitted us to conduct our study in their schools. We calculated the response rate based on all 13 districts that were accepting research applications, including the two that never responded to our inquiries, which yielded a 54% response rate.
After acquiring district approval, the first author contacted all high school principals in each district to obtain permission to conduct research in their schools. The principal response rate varied from 17% in one district to 100% in another (M = 53.33%). Next, we contacted special education teachers from schools where principal approval was granted. Selection criteria for teachers were as follows: (a) licensed special education teachers who were (b) working in public high schools.
Teachers who agreed to participate were then asked to help recruit students who (a) could read at or above the fourth-grade level, (b) were receiving special education services, and (c) were attending a public high school. All teachers were asked to record the number of students that they attempted to recruit for this study and the number who actually agreed to participate. The student response rate, calculated by dividing the number of students who participated by the total number recruited, ranged from 35% to 100% (M = 79%).
Because teachers were asked to help with recruitment and collection of student consent forms and surveys, we took the following steps to protect students' confidentiality and to minimize coercion. First, we asked teachers to follow a 16-item checklist that we created for this study. Items on the checklist were divided into three phases: before students completed the survey (e.g., "Explain to students that their participation is completely voluntary"), while students were completing the survey (e.g., "Address any questions that students may have"), and after students had completed the survey (e.g., "Please do not look at students' responses"). Teachers were also asked not to look at students' survey responses on multiple occasions, including the teacher consent form. Second, teachers were given individual envelopes to seal students' completed surveys to protect students' confidentiality. Finally, students had the option to complete and submit the survey online, which 56 students opted to do. All students received a $5 gift card for their participation, and teachers received $10 per student for each package of surveys submitted (with a prestated cap of 20 students per teacher). Per district requirements, students and teachers completed their surveys outside of regular school hours. Data collection began and was completed during the spring semester of the 2012-2013 school year, and teachers mailed completed student surveys to the first author.
The six instruments used in this study (described subsequently) were administered as parts of a larger study on social capital that included 18 instruments total in two surveys: 11 instruments in the student survey and seven in the teacher survey. For the current study, we used five of the 11 student-rated instruments and one of the seven teacher-rated instruments (i.e., Problem Behavior).
All 18 instruments were piloted with four students with disabilities and one without disabilities in Grades 9 through 12 prior to the study to check for clarity, wording, and format. Information gleaned from pilot testing was used to revise the survey prior to implementation; however, only one of original items was changed. The one item originally stated, "I feel alone or apart when I am with my friends." The pilot group said that the word apart was confusing and suggested changing it to lonely. Students were asked to think of their primary caregivers when completing the parent measure (i.e., not necessarily biological), their close friends when completing the peer measure, their teachers in general (instead of a specific teacher) when completing the teacher measure, and adults outside their immediate family for the mentor measure.
Parents and peers. Student self-reports of relationships with parents and peers were assessed using the 24-item brief version of the Inventory of Parent and Peer Attachment (Armsden & Greenberg, 1987; Nada Raja, McGee, & Stanton, 1992). The inventory was designed to assess adolescents' perceptions of cognitive--affective dimensions of relationships with parents and peers. It was adapted and shortened by Nada Raja et al. (1992) using items with highest item-total correlation coefficients within each parent and peer scale. The adapted instrument contains two higher-order factors (parent and peer attachment) and three lower-order factors within each domain: four items that measure parent trust (e.g., "My parents accept me as I am"), four items that measure parent communication (e.g., "I tell my parents about my problems"), and four items that measure parent alienation (e.g., "I feel angry with my parents"). Parallel scales (four items each) measure peer trust, communication, and alienation. Responses are provided on a 4-point Likert-type scale ranging from 1 (almost never true) to 4 (almost always true). Negatively worded items were reverse coded prior to computing total scores. Nada Raja et al. (1992) reported internal consistency alphas of .82 (parent items) and .80 (friend items) and significant correlation coefficients with measures of psychological well-being among a sample of 935 adolescents. Montague et al. (2010) reported Cronbach's alphas of .83 (parent) and .82 (friend) from a sample of 212 adolescents (91% African American and/or Hispanic) who were at risk for developing emotional and behavioral disorders in an urban school district. In the current sample, Cronbach's alphas were .86 for the overall Parent Scale (trust, [alpha] = .75; communication, a = .70; and alienation, [alpha] = .79) and .80 for the Peer Scale (trust, [alpha] = .69; communication, a = .87; and alienation, [alpha] = .78).
Teachers. Relationships with teachers were assessed with the Inventory of Teacher-Student Relationships (Murray & Zvoch, 2011). The inventory is adapted from the Inventory of Parent and Peer Attachment (Armsden & Greenberg, 1987) and includes 19 items that assess students' perceptions of trust (e.g., "I tell my teachers about my problems and troubles"), communication (e.g., "If my teachers know something is bothering me, they ask me about it"), and alienation (e.g., "My teachers don't understand what I'm going through these days"). Responses are provided on a 4-point scale ranging from 1 (almost never or never true) to 4 (almost always or always true). Murray and Zvoch (2011) reported Cronbach's alphas of .85 (trust), .88 (communication), and .73 (alienation) on a sample of early adolescents in urban schools. In the current study, Cronbach's alphas were .85 (total scale), .79 (trust), .89 (communication), and .82 (alienation).
Mentors. The Influence of Others on Academic and Career Decisions Scale (Nauta & Kokaly, 2001) was used to measure the degree of support that students receive from mentors. The scale includes 15 items and two factors: Guidance and Inspiration. The instrument uses a 5-point Likert-type scale ranging from 1 (strongly disagree) to 5 (strongly agree). Sample items include "There is someone I can count on to help me make academic and career choices" (Guidance) and "In the academic or career path I am pursuing, there is no one who inspires me" (Inspiration). Negatively worded items were reverse coded prior to computing total scores. Nauta and Kokaly (2001) found that the internal consistency coefficients for the Guidance subscale ranged from .89 to .94, and the coefficients for the Inspiration subscale ranged from .89 to .91. Other studies that used the Inspiration subscale reported internal consistency alphas of .87 (Nauta, Saucier, & Woodard, 2001) and .91 (Quimbly & DeSantis, 2006). Evidence of construct validity was supported with measures of general social support, career indecision, career certainty, and social desirability (Nauta & Kokaly, 2001). In the current sample, Cronbach's alphas were .80 for the entire scale, .77 for the Guidance factor, and .66 for the Inspiration factor.
Life satisfaction. We used the brief version of the Multidimensional Students' Life Satisfaction Scale (Gilman, Huebner, & Laughlin, 2000) to assess students' life satisfaction across six items pertaining to self, family, friend, school, living environment, and overall life (e.g., "I would describe my satisfaction with my family life as ..."). Students responded to a 7-point Likert-type scale ranging from 1 (terrible) to 7 (delighted). The brief version has strong evidence of convergent and discriminant validity, as demonstrated by significant associations with factors from the Behavior Assessment System for Children (Reynolds & Kamphaus, 1992) and strong internal consistency with a sample of adolescents (Cronbach's alpha = .85; Zullig, Valois, Huebner, Oeltmann, & Drane, 2001). In the current study, Cronbach's alpha was .81.
Problem behavior. Teachers completed a 30-item rating of problem behaviors from the Social Skills Improvement System-Teacher Rating Scale (SS1S; Gresham & Elliott, 2008). The SSIS assesses externalizing (e.g., "Talks back to adults"), internalizing (e.g., "Acts sad or depressed"), bullying (e.g., "Bullies others"), hyperactivity/inattention (e.g., "Gets distracted easily"), and autistic behavior (e.g., "Becomes upset when routines change"). The SSIS is the second generation of the Social Skills Rating System (Gresham & Elliott, 1990), a widely used measure of social skills, problem behaviors, and academic competence. The SSIS has strong evidence of reliability with an internal consistency coefficient of .96, a test-retest reliability coefficient of .92, and an interrater reliability coefficient of .58 (Gresham & Elliot, 2008). Analyses of patterns of correlations with other measures provide support for the criterion-related validity of the SSIS, including the Behavior Assessment System for Children-2, the Walker-McConnell Scale of Social Competence and School Adjustment, and the Vineland Adaptive Behavior Scales-2 (Gresham & Elliott, 2008). Teacher ratings are provided on a 4-point Likert-type scale ranging from 1 (never) to 4 (always). Internal consistency alpha for this subscale was .95 (Gresham & Elliot, 2008). The Cronbach's alpha from the current sample was .93.
School bonding. We used a seven-item measure from Murray and Greenberg's (2001) study to measure school bonding (e.g., "I look forward to going to school" and "I like to take part in class discussion and activities"). Responses are provided on a 4-point Likert-type scale ranging from 1 (almost never or never true) to 4 (almost always or always true). A negatively worded item was reverse-coded prior to computing total scores. Murray and Greenberg reported a coefficient alpha of .82 and found significant correlations between this measure and measures of school competence (r = .33-50) on a sample of early adolescents with and without disabilities. The Cronbach's alpha from this study's sample was .85.
Power analysis (Faul, Erdfelder, Buchner, & Lang, 2009) revealed that the sample size was adequate. We analyzed data using SPSS 21. After checking for outliers, missing data, and the assumptions of linearity, normality, and homogeneity of all continuous variables, we examined the means, standard deviations, and intercorrelations of all variables. Next, we conducted a multivariate analysis of variance to test the relationship between key demographics and all relationship and adjustment variables to determine if we needed to control for demographics in subsequent analyses. We then investigated our research questions using hierarchical multiple regression with parents, peers, teachers, and mentors entered as predictors, in that order. The choice to enter the predictors in this order was guided by Bronfenbrenner's (2005) ecological system framework and research on adolescents' attachment hierarchies (Rosenthal & Kobak, 2010). We hypothesized that parents and peers occupy higher positions on an adolescent's social hierarchy than do teachers and mentors.
Histograms and frequency distributions showed that life satisfaction was negatively skewed and problem behavior positively skewed. All other variables approximated normal distributions, and none had severe outliers. Normal probability plots showed that assumptions of linearity and homoscedasticity were tenable (Pedhazur, 1997). Intercorrelations among the predictors were low to moderate (see Table 2), except for the Trust and Communication subscales within the parent, peer, and teacher relationship measures. However, collinearity statistics (i.e., tolerance) were within acceptable limits, suggesting that the assumption of multicollinearity was tenable.
We ran multivariate analyses of variance to examine group differences in sample means on the linear combination of the relationship and adjustment variables. Grouping variables were as follow: placement (i.e., percentage of time spent in general education settings), race/ ethnicity, sex, grade level, and disability status. Significant differences were found among disability types (learning disabilities, emotional and behavioral disorders, intellectual disability, other health impairments, autism spectrum disorder, and other) on dependent measures, [LAMBDA] = .47, F(35, 460) = 2.57, p < .001, [[eta].sup.2] = .14. There were no other significant group differences on the dependent measures. Follow-up analysis of variance using a Bonferroni correction ([alpha] = .005) revealed that disability types were significantly different in life satisfaction, F(5, 115) = 3.69, p = .004, [[eta].sup.2] = .14, and problem behavior only, F(5, 115)= 13.41, p < .001, [[eta].sup.2] = .37. Post hoc pairwise comparisons with Bonferroni corrections revealed that students with learning disabilities and intellectual disability reported significantly more positive life satisfaction than did students with other health impairments. Other disability groups were not significantly different from one another on life satisfaction. For problem behaviors, students with learning disabilities had significantly fewer problem behaviors than did students with emotional or behavioral disorders intellectual disability, other health impairments, and autism spectrum disorder. Students with emotional disturbance and intellectual disabilities had significantly fewer problem behaviors than did students with other disabilities. In subsequent regression analyses, we controlled for disability status (dummy coded) when examining associations between relationships and adjustment.
Research Question I: Cumulative Associations With Adjustment
Relationships with all four social agents were regressed on students' life satisfaction, problem behaviors, and school bonding, with disabilities as the covariate. Results of these analyses are summarized in Table 3. After controlling for disabilities, the four relationship scores accounted for approximately one third of the variance in student life satisfaction, [DELTA][R.sup.2] = .29, F(4, 218) = 24.80, p < .001, <10% of the variance in problem behaviors, [DELTA][R.sup.2] = .05, F(4, 218) = 3.41,p = .01, and more than one third of the variance in school bonding, [DELTA][R.sup.2] = .37, F(4, 218) = 33.24, p < .001.
Research Question 2: Unique Associations With Adjustment
Next, changes in the squared multiple correlations ([DELTA][R.sup.2]) between each step were used to evaluate the contribution that each relationship source made to the three adjustment variables. As shown in Table 3, students' relationships with parents (Step 2) accounted for one fifth of the variance in students' life satisfaction, [DELTA][R.sup.2] = .20, [DELTA]F(3, 219) = 20.35, p < .001. Relationships with peers (Step 3) did not add significantly to the equation. After controlling for relationships with parents and peers, relationships with teachers, [DELTA][R.sup.2] = .07, [DELTA]F(3, 213) = 7.45, p < .001, and mentors, [DELTA][R.sup.2] = .02, [DELTA]F(2, 211) = 4.02, p = .019, both made significant unique contributions to students' life satisfaction. For problem behaviors, only teacher-student relationships made a unique contribution to the model, [DELTA][R.sup.2] = .05, [DELTA]F(3, 213) = 4.99,p = .002. On school bonding, relationships with parents, [DELTA][R.sup.2] = .11, [DELTA]F(3,219) = 8.70,p< .001, peers, [DELTA][R.sup.2] = .09, AF(3, 216) = 7.64, p < .001, and teachers, [DELTA][R.sup.2] = .20, [DELTA]F(3, 213) = 24.22, p < .001, all made unique contributions to the equation. Relationships with mentors did not add significant unique variance to this model.
Research Question 3: Unique Contributions of Each Relationship Dimension
The third research question focused on the importance of specific dimensions of each relationship. We examined standardized beta weights and semipartial (part) correlations to identify which dimensions made the strongest unique contribution to adjustment. The squared semipartial correlation provides the unique variance associated with each predictor after accounting for all other predictors in the final model. After controlling for all other predictors in the model on life satisfaction, only two dimensions made significant unique contributions to the model: alienation in teacher-student relationships (t = -3.02, p = .003) and mentor inspiration (t = 2.47, p = .014). Teacher alienation accounted for 2.66% unique variance in the model and indicated that students with greater levels of alienation in relationships with teachers had lower life satisfaction scores. Mentor inspiration accounted for 1.77% unique variance and indicated that students with greater mentor inspiration scores had greater life satisfaction. With regard to problem behavior, only trust in teacher-student relationships made unique contributions to the equation (t = -2.25, p = .026), accounting for 1.64% of the variance. This result indicated that students with greater trust in teachers had lower problem behavior.
Last, we investigated how dimensions of relationships contributed to school bonding. Again, after controlling for all other predictors, teacher relationship variables were the only ones uniquely associated with school bonding. In this model, all three dimensions of teacher-student relationships were significant: trust (t = 231, p = .019), communication (t = 3.98, p < .001), and alienation (t = -4.27, p < .001). Teacher-student trust contributed 1.59%; teacher-student communication contributed 4.41%; and teacher-student alienation contributed 5.11% unique variance. Students with greater trust and greater communication had greater school bonding scores, whereas students with greater alienation in relationships with teachers had lower school bonding scores.
Adolescents' interpersonal relationships are nested within a complex ecological system that is influenced by factors both proximal (e.g., families and peers) and distal (e.g., school and community). Despite substantial evidence showing the impact of social relationships on a variety of developmental outcomes for students without disabilities, few studies have investigated these relationships among students with disabilities, and we know of no investigations that have examined the combined and unique effects of all four relationships among adolescents with disabilities. Overall, our findings indicated that positive relationships with parents, peers, teachers, and mentors were associated with some but not all of the adjustment indicators studied here. This finding is consistent with the "independent effects" hypothesis, which states that relationships with parents, peers, and teachers have unique influences on adolescents' emotional, behavioral, and school adjustment (Verschueren, Doumen, & Buyse, 2012). In the current study, the two consistently important sources of relational support for adolescents with disabilities were parents and teachers: Parent-child relationships were meaningfully related to students' life satisfaction and perceptions of school bonding; teacher-student relationships contributed to all three adjustment indicators. From a developmental perspective, these findings are important because they highlight the continued importance of adult relationships in the lives of adolescents with disabilities.
Adolescents' interpersonal relationships are nested within a complex ecological system that is influenced by factors both proximal (e.g., families and peers) and distal (e.g., school and community).
It is important to note that students' relationships with teachers appeared to be particularly meaningful: The influence of teacher-student relationships was demonstrated after controlling for parent and peer relationships. Moreover, results of our evaluation of semipartial correlations indicated that, with the exception of mentor inspiration, dimensions of teacher-student relationships were the only variables that were independently associated with the three adjustment indicators. After controlling for all other predictors, alienation in teacher-student relationships was significantly associated with students' life satisfaction and school bonding; trust in teacher-student relationships was associated with problem behavior and school bonding; and communication in teacher-student relationships was uniquely associated with school bonding. These findings are consistent with other research highlighting the importance of teacher-student relationships (e.g., Murray & Greenberg, 2006; Pianta, Hamre, & Stuhlman, 2003) but add to prior research by showing that (a) relationships with teachers remain important after controlling for other relationships within students' microsystem, (b) the importance of teacher-student relationships extends beyond childhood, and (c) these relationships are meaningfully related to the adjustment of youth with disabilities. It is also noteworthy that results of our group comparisons contrasting students with different disability designations to one another on relationship variables were not significant, which suggests that teacher-student relationships are important for all students studied here, regardless of disability status.
Relationships with parents and peers were not significantly associated with any adjustment outcomes after accounting for relationships with teachers and mentors--most likely because criterion variables in this study were gathered in the context of schools and were therefore most relevant to the educational setting. In addition, research on peer relationships has found that adolescents with disabilities interpret typical features of friendship (e.g., support, trust, communication, loyalty) differently due to their problems with communication, cognition, and memory (Matheson, Olsen, Weisner, & Dykens, 2007). Matheson et al. (2007) found that 81% of students with disabilities in their sample described friendship in terms of companionship (e.g., friends are those who do things together) and failed to articulate deeper qualities of friendship, such as emotional bonds. School-based interventions for adolescents with disabilities should not only capitalize on potential positive influences of teachers and mentors but also take into account these students' different priorities relating to friendships.
School-based interventions for adolescents with disabilities should not only capitalize on potential positive influences of teachers and mentors but also take into account these students ' different priorities relating to friendships
Finally, positive intercorrelations between these relationships are consistent with an attachment theory perspective in that a child's early attachment with parents provides the foundation for similar patterns of relationships with others (Ainsworth, Blehar, Waters, & Wall, 1978). However, the low to moderate magnitudes of these intercorrelations suggest that adolescents' relationships with others do not necessarily follow the same attachment patterns formed in child-caregiver relationships. These results reinforce the need to examine multiple social relationships simultaneously due to their differentiated ordering in an adolescent's social hierarchy (Rosenthal & Kobak, 2010).
This study has several limitations; two warrant discussion. First, causal relation cannot be inferred due to the correlational nature of survey data collected at one point in time from the same source of informants. We cannot establish if secure relationships with teachers and mentors led to positive adjustment outcomes or if students who are already well adjusted were more likely to build positive relationships with these adults. Consequently, we cannot claim definitively if changes should start from students, peers, teachers, or non-family adults. Experimental or longitudinal data are needed to make causal inferences and to validate findings in this study. Second, self-report measures are prone to response bias. Substantively, we cannot determine if students' self-ratings of the quality of their social relationships truly captured the dynamics of these relationships or if their responses were shaped by their perceptions of what this study was about. One way to address this limitation in future research is to evaluate if results found in this study would hold across different raters of relationship and outcome variables. In light of these limitations, we provide some additional suggestions for practice and research below.
Together, our findings regarding the importance of teacher-student relationships further support the need for interventions designed to improve these relationships. Currently, there is a shortage of research focused on intervening in teacher-student relationships. Although the correlational findings presented here prohibit making any broad recommendations regarding practice, they do highlight important dimensions of relationships that should be considered by interventionists (i.e., trust, communication, and alienation). Interventions seem warranted that focus on improving student relationship skills, such as social skills instruction, while also providing students with opportunities to use these skills with teachers who are cognizant of the importance of building trust, communication, and reducing alienation in their relationships with students. A focus on multiple levels of the relationship dyad (i.e., student skills and teacher behavior) is also consistent with an ecological perspective in that it highlights the transactional nature of relationship processes.
Given the current limited attention on the role of teacher-student relationship as an impetus for student learning and adjustment in the classroom and the positive associations indicated by our findings, we believe that the teacher-student relationship warrants a legitimate place in discussions on effective classroom practices for students with disabilities. Building positive teacher-student relationships requires sustained, rather than time-limited or random, efforts. Specifically, our findings suggest the need for teachers to think about the importance of communicating with students in a manner that enhances trust and diminishes feelings of alienation because these specific dimensions of a relationship can make a difference in the adjustment of students with disabilities.
In addition, the association between mentor inspiration and life satisfaction of youth with disabilities over and above relationships with parents, peers, and teachers provides tentative support for the proliferation of mentoring as an intervention strategy to address the needs of adolescents for adult guidance (DuBois, Portillo, Rhodes, Silverthom, & Valentine, 2011). Prior research found that natural mentors could compensate for a youth's exposure to negative adult behaviors (Hurd, Zimmerman, & Xue, 2009). This study showed that mentor inspiration, not guidance, made a significant contribution to the adjustment of students with disabilities. Perhaps students with disabilities are already receiving guidance from adults and need more exposures to role models who can inspire them to achieve more in school and career, instead of more adults who tell them what to do. Extant research has identified that the presence of self-determined role models is one of five key elements in the environment that facilitate successful transition outcomes for youth with disabilities (Field, Sarver, & Shaw, 2003). Parents, extended family adults, teachers, related service providers, and other school staff should be cognizant of their roles as potential role models for students with disabilities and not undermine this potential impact. Although our study did not examine this issue, our findings lend support to this phenomenon and show that adults, rather than peers, play more significant roles in the lives of adolescents with disabilities (Roorda et al., 2011).
Implications for Future Research
Our findings show that teachers and mentors have important roles in influencing the adjustment of students with disabilities. Although further research is needed to understand how to better conceptualize and measure relationships with teachers and natural mentors, our preliminary findings suggest the importance of noncognitive teacher-level variables (i.e., trust, communication, alienation) and mentor-level variable (i.e., inspiration) for students with disabilities and the need to consider the bidirectional nature of these interactions. Additional research is still needed to examine which of the following variables facilitate optimal interpersonal relationships for adolescents with disabilities: student-, parent-, peer-, teacher-, or mentor-variables. Understanding the level of influence from each of these agents can inform researchers and practitioners on where to target intervention efforts when time and resources are limited.
This study adds to the body of research on the social relationships of youth with disabilities by looking beyond the dyadic paradigm and examining multiple influences of family (via parents), school (via peers and teachers), and community (via mentors). Although each social agent contributes asymmetrically to adjustment outcomes of youth with disabilities, overall, results show that parents, teachers, and mentors contribute the most to improving the emotional, behavioral, and school-related outcomes for these youth. This finding suggests that efforts to develop or improve adolescents' relationships with adults, rather than peers, may be more effective at improving outcomes for youth with disabilities. Future research using experimental or longitudinal data is necessary to make causal inferences on the long-term impact of these relationships.
Ainsworth, M. D. S., Blehar, M. C., Waters, E., & Wall, S. (1978). Patterns of attachment: A psychological study of the strange situation. Hillsdale, NJ: Erlbaum.
Al-Yagon, M. (2007). Socioemotional and behavioral adjustment among school-age children with learning disabilities: The moderating role of maternal personal resources. The Journal of Special Education, 40, 205-217. doi: 10.1177/ 00224669070400040201
Al-Yagon, M. (2012a). Adolescents with learning disabilities: Socioemotional and behavioral functioning and attachment relationships with fathers, mothers, and teachers. Journal of Youth and Adolescence, 41, 1294-1311. doi: 10.1007/s 10964-012-9767-6
Al-Yagon, M. (2012b). Subtypes of attachment security in school-age children with learning disabilities. Learning Disability Quarterly, 35, 170-183. doi: 10.1177/0731948712436398
Al-Yagon, M. (2013). Child-mother and child-father attachment security: Links to internalizing adjustment among children with learning disabilities. Child Psychiatry & Human Development, 45, 119-131. doi: 10.1007/ s10578-013-0383-9
Al-Yagon, M., & Mikulincer, M. (2004). Patterns of close relationships and socioemotional and academic adjustment among school-age children with learning disabilities. Learning Disabilities Research & Practice, 19, 12-19. doi: 10.1111/j. 1540-5826.2004.00085.x
Armsden, G. C., & Greenberg, M. T. (1987). The inventory of parent and peer attachment: Relationships to well-being in adolescence. Journal of Youth and Adolescence, 16, 427454. doi: 10.1007/BF02202939
Baker, J. A., Grant, S., & Morlock, L. (2008). The teacher-student relationship as a developmental context for children with internalizing or externalizing behavior problems. School Psychology Quarterly, 23, 3-15. doi: 10.103 7/1045-38188.8.131.52
Barber, B. K... & Olsen. J. A. (2004). Assessing the transitions to middle and high school. Journal of Adolescent Research, 19, 3-30. doi: 10.1177/0743558403258113
Bronfenbrenner, U. (2005). Making human beings human: Bioecological perspectives on human development. Thousand Oaks, CA: SAGE.
Brown, M. R., Higgins, K., Pierce, T., Hong, E., & Thoma, C. (2003). Secondary students' perceptions of school life with regard to alienation: The effects of disability, gender, and race. Learning Disability Quarterly, 26, 227-238. doi: 10.2307/1593636
Bukowski, M. W., Newcomb, F. A., & Hartup, W. W. (1998). The company they keep: Friendship in childhood and adolescence. Cambridge, England: Cambridge University Press.
Cantin, S., & Boivin, M. (2004). Change and stability in children's social network and selfperceptions during transition from elementary to junior high school. International Journal of Behavioral Development, 28, 561-570. doi: 10.1080/01650250444000289
Carter, E. (2011). Supporting peer relationships. In M. E. Snell & F. Brown (Eds.), Instruction of students with severe disabilities (7th ed., pp. 431-460). Upper Saddle River, NJ: Merrill.
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, 451^172. doi: 10.1080/0924 3453.2010.532010
De Wit, D. J., Karioja, K., Rye, B. J., & Shain, M. (2011). Perceptions of declining classmate and teacher support following the transition to high school: Potential correlates of increasing student mental health difficulties. Psychology in the Schools, 48, 556-572. doi: 10.1002/ pits.20576
Drewry, J. A., Burge, P. L., & Driscoll, L. G. (2010). A tripartite perspective of social capital and its access by high school dropouts. Education and Urban Society, 42, 499-521. doi: 10.1177/0013124510366799
DuBois, D. L., Portillo, N., Rhodes, J. E., Silverthom, N., & Valentine, J. C. (2011). How effective are mentoring programs for youth? A systematic assessment of the evidence. Psychological Science in the Public Interest, 12, 57-91. doi: 10.1177/1529100611414806
Faul, F., Erdfelder, E., Buchner, A., & Lang, A. G. (2009). Statistical power analyses using G*Power 3.1: Tests for correlation and regression analyses. Behavior Research Methods, 41, 1149-1160. doi: 10.3758/BRM.41.4.1149
Field, S., Sarver, M. D., & Shaw, S. F. (2003). Self-determination: A key to success in post-secondary education for students with learning disabilities. Remedial and Special Education, 24, 339-349. doi: 10.1177/074193250302400 60501
Gifford-Smith, M. E., & Brownell, C. A. (2003). Childhood peer relationships: Social acceptance, friendships, and peer networks. Journal of School Psychology, 41, 235-284. doi: 10.1016/s0022-4405(03)00048-7
Gilman, R., Huebner, E., & Laughlin, J. (2000). A first study of the multidimensional students' life satisfaction scale with adolescents. Social Indicators Research, 52, 135-160. doi: 10.1023/A: 1007059227507
Gresham, F. M., & Elliott, S. N. (1990). The Social Skills Rating System. Circle Pines, MN: American Guidance Service.
Gresham, F. M., & Elliott, S. N. (2008). SSiS: Teacher Rating Scales. Bloomington, MN: Pearson.
Heiman, T., Zinck, L. C., & Heath, N. L. (2008). Parents and youth with learning disabilities: Perceptions of relationships and communication. Journal of Learning Disabilities, 41, 524-534. doi:10.1177/0022219408317860
Hurd, N. M., Zimmerman, M. A., & Reischl, T. M. (2011). Role model behavior and youth violence: A study of positive and negative effects. Journal of Early Adolescence, 31, 323-354. doi: 10.1177/0272431610363160
Hurd, N. M., Zimmerman. M. A., & Xue, Y. (2009). Negative adult influences and the protective effects of role models: A study with urban adolescents. Journal of Youth and Adolescence, 38, 777-789. doi: 10.1007/s 10964-008-9296-5
Klaw, E. L., Rhodes, J. E., & Fitzgerald, L. L. (2003). Natural mentors in the lives of African-American adolescent mothers: Tracking relationships over time. Journal of Youth and Adolescence, 32, 223-232. doi: 10.1023/ A: 1022551721565
Kobak, R., Rosenthal, N. L., Zajac, K., & Madsen, S. D. (2007). Adolescent attachment hierarchies and the search for an adult pair-bond. New Directions for Child and Adolescent Development, 117, 57-72. doi: 10.1002/cd. 194
Lerner, J. V., Phelps, E., Forman, Y., & Bowers, E. P. (2009). Positive youth development. In R. M. Lemer & L. Steinberg (Eds.), Handbook of adolescent psychology: Vol 1. Individual bases of adolescent development (3rd ed., pp. 404-434). Hoboken, NJ: Wiley.
Malecki, C. K., & Demaray, M. K. (2003). What type of support do they need? Investigating student adjustment as related to emotional, informational, appraisal, and instrumental support. School Psychology Quarterly, 18, 231-252. doi: 10.1521/scpq. 184.108.40.20676
Matheson, C., Olsen, J. R., Weisner, T., & Dykens, E. (2007). A good friend is hard to find: Friendship among adolescents with disabilities. American Journal on Mental Retardation, 112, 319-329. doi: 10.1352/0895-8017(2007) 112%5B0319: A GFIHT%5D2.0.CO;2
Montague, M., Cavendish, W., Enders, C., & Dietz, S. (2010). Interpersonal relationships and the development of behavior problems in adolescents in urban schools: A longitudinal study. Journal of Youth and Adolescence, 39, 646-657. doi: 10.1007/s10964-009-9440-x
Murray, C., & Greenberg, M. T. (2001). Relationships with teachers and bonds with school: Social emotional adjustment correlates for children with and without disabilities. Psychology in the Schools, 38, 25-41. doi:10.1002/15206807(200101)38:1 <25:: AID-PITS4>3.0.CO; 2-C
Murray, C., & Greenberg, M. T. (2006). Examining the importance of social relationships and social contexts in the lives of children with high-incidence disabilities. Journal of Special Education, 39, 220-233. doi: 10.1177/002246 69060390040301
Murray, C., & Zvoch, K.. (2011). The Inventory of Teacher-Student Relationships: Factor structure, reliability, and validity among African American youth in low-income urban schools. Journal of Early Adolescence, 31, 493-525. doi: 10.1177/0272431610366250
Nada Raja, S., McGee, R., & Stanton, W. R. (1992). Perceived attachments to parents and peers and psychological well-being in adolescence. Journal of Youth and Adolescence, 21, 471-485. doi: 10.1007/BF01537898
Nauta, M. M., & Kokaly, M. L. (2001). Assessing role model influences on students' academic and vocational decisions. Journal of Career Assessment, 9, 81-99. doi: 10.11 HI 106907270100900106
Nauta, M. M., Saucier, A. M., & Woodard, L. E. (2001). Interpersonal influences on students' academic and career decisions: The impact of sexual orientation. The Career Development Quarterly, 49, 352-362. doi: 10.1002/j.2161 -0045.2001 ,tb00962.x Panacek, L. J., & Dunlap, G. (2003). The social lives of children with emotional and behavioral disorders in self-contained classrooms: A descriptive analysis. Exceptional Children, 69, 333-348.
Pedhazur, E. J. (1997). Multiple regression in behavioral research: Explanation and prediction (3rd ed.). Orlando, FL: Harcourt Brace.
Pekrun, R., & Linnenbrink-Garcia, L. (2012). Academic emotions and student engagement. In S. L. Christenson, A. L. Reschly, & C. Wylie (Eds.), The handbook of research on student engagement (pp. 259-282). New York, NY: Springer, doi: 10.1007/978-1 -4614-2018-7 12
Pham, Y. K. (2013). The relationship between social capital and school-related outcomes for youth with disabilities (Unpublished doctoral dissertation). University of Oregon, Eugene, OR. Pianta, R. C., Hamre, B., & Stuhlman, M. (2003). Relationships between teachers and children. In W. M. Reynolds & G. E. Miller (Eds.), Handbook of child psycholog}': Vol. 7. Educational psychology (pp. 199-234). Hoboken, NJ: Wiley.
Pijl, S. J., Frostad, P., & Flem, A. (2008). The social position of pupils with special needs in regular schools. Scandinavian Journal of Educational Research, 52, 387-405. doi:0.1080/00313830802184558
Quimby, J., & DeSantis, A. (2006). The influence of role models on women's career choices. Career Development Quarterly, 54, 297-306. doi: 10.1002/j.2161 -0045.2006. tbOO 195.x
Reynolds, C. R., & Kamphaus, R. W. (1992). Manual for the Behavioral Assessment System for Children. Circle Pines, MN: American Guidance Service.
Roorda, D. L.. Koomen, H. M. Y., Spilt, J. L., & Oort, F. J. (2011). The influence of affective teacher-student relationships on students' school engagement and achievement: A meta-analytic approach. Review of Educational Research, 81, 493-529. doi: 10.3102/0034654311421793
Rosenthal, N. L., & Kobak, R. (2010). Assessing adolescents' attachment hierarchies: Differences across developmental periods and associations with individual adaptation. Journal of Research on Adolescence, 20, 678-706. doi: 10.1111/ j. 1532-7795.2010.00655.x
Sabol, T. J.. & Pianta, R. C. (2012). Recent trends in research on teacher-child relationships. Attachment & Human Development, 14, 213231. doi: 10.1080/14616734.2012.672262
Scharf, M., & Mayseless, O. (2007). Putting eggs in more than one basket: A new look at developmental processes of attachment in adolescence. New Directions for Child and Adolescent Development, 117, 1-22. doi: 10.1002/cd. 191
Suldo, S. M.. Friedrich, A. A., White, T., Farmer, J., Minch, D., & Michalowski, J. (2009). Teacher support and adolescents' subjective well-being: A mixed-methods investigation. School Psychology Review, 38, 67-85.
Suldo, S. M., Shaffer, E. J., & Riley, K. N. (2008). A social-cognitive-behavioral model of academic predictors of adolescents' life satisfaction. School Psychology' Quarterly, 23, 56-69. doi: 10.1037/1045-38220.127.116.11
Verschueren, K., Doumen, S., & Buyse, E. (2012). Relationships with mother, teacher, and peers: Unique and joint effects on young children's self-concept. Attachment and Human Development, 14, 233-248. doi: 10.1080/1461 6734.2012.672263
Wagner, M., Newman, L., Cameto, R., Garza, N., & Levine, P. (2005). After high school: A first look at the postschool experiences of youth with disabilities. A report from the National Longitudinal Transition Study-2 (NLTS2). Menlo Park, CA: SRI International.
Wagner, M., Newman, L., Cameto, R., Levine, P., & Garza, N. (2006). An overview of findings from wave 2 of the National Longitudinal Transition Studv-2 (NLTS2) (NCSER Report No. 20063004). Menlo Park, CA: SRI International.
Wang, M. T.. & Eccles, J. S. (2012). Social support matters: Longitudinal effects of social support on three dimensions of school engagement from middle to high school. Child Development, 83, 877-895. doi: 10.1111/ j. 1467-8624.2012.01745.x
Whitlock, J. L. (2006). Youth perceptions of life at school: Contextual correlates of school connectedness in adolescence. Applied Developmental Science, 1, 13-29. doi: 10.1207/s 1532480 xads1001_2
Zullig, K., Valois, R., Huebner, E., Oeltmann, J., & Drane, W. (2001). Relationship between perceived life satisfaction and adolescents' substance abuse. Journal of Adolescent Health, 29, 279-288. doi: 10.1016/S1054-139X(01)00
This study was supported in part by the Sammie Barker McCormack Scholarship and the Doctoral Research Award from the Graduate School at the University of Oregon. Opinions expressed herein are the authors' and do not reflect the position of funders, and such endorsements should not be inferred. The authors declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article. All underlying research materials related to this study can be obtained by contacting the first author.
Manuscript received June 2014; accepted February 2015.
Yen K. Pham (1) and Christopher Murray (2)
(1) University of New Mexico
(2) University of Oregon
Yen K. Pham, Department of Educational Specialties, University of New Mexico, MSC05 3040, I University of New Mexico, Albuquerque, NM, 87131, USA. E-mail: email@example.com
Table 1. Number of Participants by Districts. District Region Locale Schools Teachers Students 1 Midwest Fringe rural 1 1 15 2 Northwest Fringe town 1 1 14 3 Northwest Small city 1 3 59 4 Northwest Midsize city 2 7 83 5 Northwest Large city 2 2 15 6 Southwest Large city 2 2 22 7 Northeast Large city 1 1 20 Total 10 17 228 Table 2. Correlation, Means, and Standard Deviations of All Variables. 1 2 3 4 5 1. Parent T 2. Parent C .72 ** 3. Parent A -.47 * -.42 ** 4. Peer T .23 ** .14 * -.16 * 5. Peer C .18 ** .14 * .05 .62 ** 6. Peer A -.05 -.06 .54 ** -.23 ** .08 7. Teacher T .41 ** .32 ** -.17 ** .26 ** .22 ** 8. Teacher C .32 ** .36 ** -.12 .22 ** .31 ** 9. Teacher A -.18 ** -.18 ** .45 ** -.09 .09 10. Guidance .39 ** .40 ** -.29 ** .27 ** -.28 ** 11. Inspiration .26 ** .29 ** -.26 ** .16 * .11 12. Emotional .37 ** .40 ** -.35 ** .14 * .16 * 13. Behavior -.09 -.05 .08 -.16 * -.14 * 14. School .25 ** .32 ** -.19 ** .31 ** .30 ** M 3.15 2.70 1.94 3.14 2.69 SD 0.68 0.75 0.78 0.63 0.80 6 7 8 9 10 1. Parent T 2. Parent C 3. Parent A 4. Peer T 5. Peer C 6. Peer A 7. Teacher T -.03 8. Teacher C .10 .60 ** 9. Teacher A .53 ** -.10 .04 10. Guidance -.25 ** .51 ** .39 ** -.26 ** 11. Inspiration -.22 ** .29 ** .31 ** -.15 * .53 ** 12. Emotional -.19 ** .34 ** .33 ** -.30 ** .40 ** 13. Behavior .10 -.22 ** -.08 .19 ** -.22 ** 14. School -.12 .46 ** .48 ** -.27 ** .41 ** M 1.86 3.01 2.46 2.07 3.61 SD 0.76 0.60 0.75 0.72 0.70 11 12 13 14 1. Parent T 2. Parent C 3. Parent A 4. Peer T 5. Peer C 6. Peer A 7. Teacher T 8. Teacher C 9. Teacher A 10. Guidance 11. Inspiration 12. Emotional .36 ** 13. Behavior -.10 -.14 14. School .26 ** .52 ** -.11 M 3.31 5.34 1.46 2.72 SD 0.70 1.03 0.40 0.68 Note. Students, n = 228. T = trust; C = communication; A = alienation; emotional = life satisfaction; behavior = problem behavior; school = school bonding. * p < .05. ** p < .01. Table 3. Regression Analyses Predicting Adjustment From Students' Perceptions of Relationships With Parents, Peers, Teachers, and Mentors. Adjustment variables Life Satisfaction Problem Behavior [DELTA] [DELTA] Predictor [R.sup.2] [beta] [R.sup.2] [beta] Step 1 .08 ** .24 ** LD -.01 -.05 ED -.12 .34 ** ID .08 .23 ** OHI -.21 .15 ASD -.16 .23 * Step 2 .20 *** .004 Parent T .12 -.04 Parent C .23 ** -.01 Parent A -.20 ** .03 Step 3 .02 .01 Peer T -.12 -.20 Peer C .15 .03 Peer A -.14 -.02 Step 4 .07 ** .05 ** Teacher T .09 -.23 ** Teacher C .18 * .04 Teacher A -.20 ** .13 Step 5 .02 * .01 Mentor G .02 -.15 Mentor I .16 * .04 Total [R.sup.2] .39 .32 Adjusted [R.sup.2] .34 .27 Adjustment variables School Bonding [DELTA] Predictor [R.sup.2] [beta] Step 1 .01 LD -.01 ED -.05 ID .07 OHI -.04 ASD -.07 Step 2 .11 ** Parent T .02 Parent C .27 ** Parent A -.08 Step 3 .09 ** Peer T .13 Peer C .19 * Peer A -.09 Step 4 .20 *** Teacher T .20 ** Teacher C .30 ** Teacher A -.29 *** Step 5 .004 Mentor G .06 Mentor I .03 Total [R.sup.2] .41 Adjusted [R.sup.2] .37 Note. Students, n = 228. [DELTA][R.sup.2] = change in the squared multiple correlation; p = standardized weight; LD = learning disabilities; ED = emotional/behavioral disorders; ID = intellectual disability; OHI = other health impairments; ASD = autism spectrum disorder; T = trust; C = communication; A = alienation; G = guidance; I = inspiration. * p < .05. ** p < .01. *** p < .001.
|Printer friendly Cite/link Email Feedback|
|Author:||Pham, Yen K.; Murray, Christopher|
|Date:||Jan 1, 2016|
|Previous Article:||Randomized evaluation of peer support arrangements to support the inclusion of high school students with severe disabilities.|
|Next Article:||Parent concern and enrollment in intervention services for young children with developmental delays: 2007 National Survey of Children's Health.|