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Cumulative interpersonal relationship risk and resilience models for bullying victimization and depression in adolescents
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Cumulative interpersonal relationship risk and resilience models for bullying victimization and depression in adolescents ⁎
Zhao Yongpinga, , Zhao Yufanga, Lee Yueh-Tingb, Chen Lic a
Faculty of Psychology, Southwest University, Chongqing, China Department of Psychology, Southern Illinois University Carbondale, IL, USA c Student Development Center, Fuling Bashu Secondary School, Fuling, China b
A R T I C LE I N FO
A B S T R A C T
Keywords: Cumulative interpersonal relationship risks (CIRR) Resilience School bullying victimization (SBV) Depression Serial mediation
Studies have documented that school bullying victimization (SBV) triggered by interpersonal relationship risks (IRRs) can increase depression. However, the predictive patterns of cumulative IRRs (CIRR; classmate, parentchild, teacher-student, and friend relationships risks) on SBV and depression and its psychological mechanism remain unclear from a positive psychological perspective. This study explored CIRR models for SBV and depression and tested two mediation models of resilience in relationships among CIRR, SBV and depression. Selfreport questionnaires were answered by 742 valid participants between 11 and 19 years of age. Findings showed that CIRR significantly predicted SBV and depression, with a proportionate increase in SBV and depression as the CIRR increased. Furthermore, the results confirmed the two mediation hypotheses. CIRR could directly decrease one's resilience and, therefore, increase one's SBV and level of depression. CIRR could also indirectly decrease one's resilience by SBV and further increase one's level of depression. The results construct CIRR linear model for SBV and depression and mediation models of resilience among CIRR, SBV and depression. Our results indicate that, to decrease SBV and depression based on multiple IRRs exposures, comprehensive intervening in four IRRs from a psychopathological perspective or cultivating resilience in adolescents from a positive psychological perspective is required.
1. Introduction1 School bullying victimization (SBV) is a topic of concern for youths, parents, school staff, and mental health practitioners (Arseneault, Bowes & Shakoor, 2010). A survey from 79 high and low income countries showed that approximately 30% of adolescents have reported bullying victimization experience (Elgar et al., 2015), which were enacted intentionally and repeatedly by an individual or group based on an imbalance of power between victims and perpetrators (Olweus, 2013). SBV has been found to be associated with a number of negative outcomes (Chester et al., 2015; Gámez-Guadix, Orue, Smith & Calvete, 2013), of which depression is one of the major undesirable outcomes. For example, adolescents who experience SBV are 2 to 7 times more likely to report depressive symptoms than those who are not bullied (Klomek, Marrocco, Kleinman, Schonfeld & Gould, 2007). Specifically, victims of frequent bullying in childhood had higher rates of depression at age 45 than their non-victimized peers (Takizawa, Maughan & &Arseneault, 2014).
Several reviews have been devoted to integrate risk factors that may lead to SBV (Cook, Williams, Guerra, Kim & Sadek, 2010; Hong & Espelage, 2012; Huang, Hong & Espelage, 2013; Maunder & Crafter, 2018) from different perspectives, all of which highlight the importance of considering SBV in the socio-ecological context. According to socio-ecological theory (Bronfenbrenner & Morris, 1998), human development is impacted by multiple ecological subsystems of family, school, and peers. Therefore, as a negative interpersonal interaction phenomenon in youth, SBV can be predicted by adolescents’ negative interpersonal relationships with parents, teachers, and peers (Cook et al., 2010; Hong & Espelage, 2012; Huang et al., 2013; Maunder & Crafter, 2018). However, many studies focused on one or two-way combinations of interpersonal risk factors (IRRs) such as parents and teacher (Bjereld, Daneback & Petzold, 2017), parents and peer (Burke, 2017; Healy & Sanders, 2018), teacher-student and peer (Sulkowski & Simmons, 2017), peer and friendship (Strohmeier, Kärnä & Salmivalli, 2011). Although these studies largely help us understand SBV in youth
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Corresponding author. E-mail address: [email protected] (Y. Zhao). 1 CIRR= Cumulative interpersonal relationship risks; SBV= School bullying victimization https://doi.org/10.1016/j.paid.2019.109706 Received 29 August 2019; Received in revised form 5 November 2019; Accepted 10 November 2019 0191-8869/ © 2019 Elsevier Ltd. All rights reserved.
Please cite this article as: Zhao Yongping, et al., Personality and Individual Differences, https://doi.org/10.1016/j.paid.2019.109706
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the capacity to spring back, rebound, successfully adapt in the face of adversity, and develop social and academic competence despite exposure to severe stress (Hinduja & Patchin, 2017). Relationships are one of important factors that influence resilience (Geitsidou & Giovazolias, 2016). For example, a secure attachment relationship can reduce negative feelings aroused by stressful events and reinforce resilience (Rutter, 1987, 2006). Furthermore, students with a strong resilience profile were less likely to be bullied than those who reported fewer developmental strengths such as “parental involvement,” “positive peer influence” (Donnon, 2010; Hinduja & Patchin, 2017). Thus, negative interpersonal relationship could indirectly affect SBV through a decrease in resilience. In addition, students reporting greater resilience experienced less depression regarding bullying victimization (Moore & Woodcock, 2017). Resilience partially mediated the relationship between SBV and depressive symptoms (Zhou, Liu, Niu, Sun & Fan, 2017). That is, SBV can decease resilience and in turn increase level of depression. Last, several studies have explored the cumulative risk model of depression (Epkins & Heckler, 2011; Gerard & Buehler, 2004; Margolin, Vickerman, Oliver & Gordis, 2010; Schumm, Briggs-Phillips & Hobfoll, 2006) and found a linear model between cumulative risks and depression (Gerard & Buehler, 2004) and a positive acceleration model between cumulative risks and negative outcomes, including depression (Margolin et al., 2010). Therefore, resilience can be a mediator among CIRR, SBV, and depression. CIRR could directly or indirectly decrease an individual's resilience, and therefore, increase an individual's SBV and level of depression. To our knowledge, a few related studies confirm the role of resilience in the relationships among CIRR (classmate, parent-child, teacher-student, and friend relationships risks), SBV, and depression. The Resilience model can help us understand the underlying psychological mechanisms of the relations among CIRR, SBV, and depression, which can then inform intervention program design for SBV and depression triggered by CIRR. Especially, when the functional form between CIRR, SBV, and depression followed a linear or positive acceleration model, it was difficult for practitioners to intervene in multiple IRRs. Thus, we can cultivate youths’ resilience to decrease the negative chain reaction triggered by CIRR. The present research would extend anti-bullying approaches from a positive psychological perspective, and shift the focus of anti-bullying intervention from individual deficits to individual strengths. Thus, the second aim of the present study was to explore resilience models of CIRR, SBV, and depression. Based on the abovementioned review, we can hypothesize that CIRR can predict SBV and depression. However, the possible functional form among them cannot be deduced because similar researches on CIRR model of SBV and CIRR model of depression were not found. Furthermore, the cumulative risk model of depression has different functional forms (Gerard & Buehler, 2004; Margolin et al., 2010). With regard to resilience models of CIRR, SBV, and depression, we proposed two concept models (Figs. 1 and 2) and planned to explore whether model 1 or 2, or both, were valid. We put forth three specific hypotheses as follows: Hypotheses 1. CIRR would significantly predict SBV and depression. Hypotheses 2. CIRR could directly decrease levels of resilience and subsequently increase SBV and depression (Fig. 1). Hypotheses 3. CIRR could indirectly decrease levels of resilience by increasing SBV and subsequently result in more depressive symptoms (Fig. 2).
from different levels of IRR, it is vital to consider multiple IRRs simultaneously. First, risk factors in different fields are often synergistic, and individuals are often faced with risk factors in one field as well as in another (Evans, Li & Whipple, 2013). For example, a student who has poor social skills can have a poor teacher-student relationship and, simultaneously, a poor relationship with classmates. Therefore, paying attention to the influence of multi-field risk factors on adolescents’ development as opposed to a single or two minor risk factors’ influence is more relevant to the individual's reality. Second, if a risk factor is related to other risk factors, considering a single or two minor risk factors can lead to an overestimation of its/their effects, because children experiencing multiple risk factors are much more likely to experience psychological disorders (Evans et al., 2013). To our knowledge, existing literature does not yet clarify how exposure to multiple IRRs (classmate, parent-child, teacher-student and friend relationships risks) affect SBV and in turn influence depression, using a cumulative risk approach (Gerard & Buehler, 2004; Rauer, Karney, Garvan & Hou, 2008). Existing literature has shown that the cumulative risk model is the most widely used method for modeling multiple risks (Evans et al., 2013). Specifically, in cumulative risk model, each risk factor was dichotomized. Scores below the 25th percentile were deemed as risk factors and given a score of 1, with the remaining 75% scored as 0. CIRR index is obtained by summing the scores of all risk factors, and this is used as an independent variable to construct the cumulative risk model. Previous studies have found that cumulative risk models could show different functional forms such as linear, positive acceleration, and negative acceleration models (Appleyard, Egeland, van Dulmen & Sroufe, 2005; Gerard & Buehler, 2004; Rauer et al., 2008). The linear model assumes that problematic outcomes show a reasonably steady increase with an increasing number of risk factors. Positive acceleration model assumes that the correlation between each risk factor and problematic outcome is stronger when other risk factors occur simultaneously than when no other risk factors are concurrent. Negative acceleration models assume that the effect of new risk factors on individual problems becomes smaller and smaller with the increase of cumulative risk. Exploring different functional forms between CIRR and SBV and depression were important because different functional forms can mean different intervention practices for SBV and depression. If the functional form shows a linear model, comprehensive prevention effort is needed. Because the effectiveness of intervention while targeting a particular IRR factor is not affected by other IRR factors, reduction of individual IRR factors is crucial (Appleyard et al., 2005). If the functional form shows a positive acceleration model, it means SBV and depression accelerates after a certain critical point in the number of IRRs (Appleyard et al., 2005). It was particularly difficult to deal with SBV and depression triggered by CIRR. If the functional form shows a negative acceleration model, interventions for individuals with a medium number of IRRs is more effective because the benefits of reducing each risk factor are more obvious than the benefits of reducing a single risk when individuals encounter a large number of risk factors (Rauer et al., 2008). Thus, the first aim of the present study was to explore the CIRR model (classmate, parent-child, teacher-student, and friend relationships risks) of SBV and depression. Although multiple IRRs have been considered as risk factors associated with SBV and depression, the relationships between IRRs and SBV and depression could be indirect to a certain extent. This is because many students exposed to the same level of risks do not inevitably develop the same negative outcomes, and these students are believed to possess resilience against risks (Richardson, 2002). Resilience refers to
Fig. 1. Concept figure of Model 1.
2
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Fig. 2. Concept figure of Model 2. Note. CIRR = cumulative interpersonal relationship risks, SBV = school bullying victimization.
2. Method
risk factors (Evans et al., 2013).
2.1. Participants
2.3.2. California bully/Victimization scale (CBVS) CBVS (Felix, Sharkey, Green, Furlong & Tanigawa, 2011) was employed to assess SBV in the past month. The scale includes items asking about eight forms of victimization that respondents may have experienced at school (e.g., How often have you been teased or called names in a mean or hurtful way?). Students rated the frequency of each of these experiences on a five-point scale (1 = Never in the past month, 2 = once in the past month, 3 = 2 or 3 times in the past month, 4 = about once a week, and 5 = several times a week). Power imbalance was ascertained using a series of items asking students to compare themselves to the primary individual who bullied them. Students responded to how popular, smart in schoolwork, and physically strong that individual is compared to them, as rated on a three-point scale (less than me, same as me, more than me). The Cronbach's α value for the present sample was 0.86.
The study included 840 middle school students from five schools located in Chongqing. The effective sample included 742 middle school students, of whom 48.38% were males. The sample size was sufficient for model analysis (Wu, 2010). These students were in grades 7 to 11 and ranged in age from 11 to 19 (M = 14.32, SD =1.54) years. There were 131 to 190 students in every grade. Ninety-eight questionnaires were discarded because students reported “no” in two validity items, which indicated that these students had not filled out the questionnaire seriously and carefully. 2.2. Procedures The first author (YZ) explained the project to psychology graduate students (all of them are middle school teachers) in the university classroom and invited them to recommend schools that would be interested in participating in the study. Five interested middle schools participated in the project. The fourth author and psychology teachers in these schools administered paper-pencil surveys to the participants in an ordinary classroom setting. The participants were assured of the confidentiality and anonymity of their responses. Verbal informed consent was obtained from all students prior to the survey. The five schools and the Ethics Committee at the Faculty of Psychology of Southwest University, China, approved this study.
2.3.3. Connor–Davidson resilience scale (CD-RISC) The concise 10-item version of the 25-item self-report CD-RISC (Hinduja & Patchin, 2017) was employed (e.g., “I can deal with whatever comes my way”) to assess resilience. Participants had to respond on a five-point scale (0 = Not True at All, 1 = Rarely True, 2 = Sometimes True, 3 = Often True, and 4 = True Nearly All the Time). The Cronbach's α value for the present sample was 0.83. 2.3.4. Center for epidemiological studies depression scale (CES-D) The 20-item CES-D (Radloff, 1977) was employed to assess symptoms of depression. Participants rated the frequency of depressive symptoms in the previous week on a scale of 0 (less than 1 day) to 3 (5–7 days) (e.g., ‘‘I felt depressed.’’). The Cronbach's α value for the present sample was 0.90.
2.3. Measurements 2.3.1. Interpersonal relationship scales Existing literature shows that social support significantly predicts interpersonal relationships (for detailed information, see Sun, 2017) and can be subsumed under a broader concept of interpersonal relationships (Stoetzer et al., 2009). Thus, we employed three subscales of the Child and Adolescent Social Support Scale (CASSS; Malecki & Demaray 2002) to assess parent-child relations, teacher-student relations, and classmate relations. These subscales have good reliability and validity (Malecki & Demaray, 2002). Parent subscale of CASSS. This subscale was employed to assess parent-child relations. It includes 10 items (e.g., “My parent(s) listen to me when I'm mad”) using a response scale from 1 (Never) to 6 (Always). The Cronbach's α value for the present sample was 0.88. Teacher subscale of CASSS. This subscale was employed to assess teacher-student relations. It includes 10 items (e.g., “My teacher(s) cares about me”) using a response scale from 1 (Never) to 6 (Always). The Cronbach's α value for the present sample was 0.93. Classmate subscale of CASSS. This subscale was employed to assess classmate relations. It includes 10 items (e.g., “My classmates ask me to join activities”) using a response scale from 1 (Never) to 6 (Always). The Cronbach's α value for the present sample was 0.92. Friend relations questionnaire. Friendlessness was assessed using two items, “I have good friends in my classroom” and “I have friends in my own class,” to which the students responded on a 4-point scale (1totally disagree, 4-totally agree) (Strohmeier et al., 2011). The Cronbach's α value for the present sample was 0.60. Scores of parent-child, teacher-student, classmate, and friend relationships below the 25th percentile were deemed as risk factors and given a score of 1, with the remaining 75% scored as 0. The number of IRRs (i.e., CIRR index) was obtained by summing the scores of all four
2.3.5. Validity items In order to improve the validity of the questionnaire, two items were used. One was “I am taking this survey seriously”; the other was “I am answering the questionnaire carefully.” Participants were asked to choose “no” or “yes.” If students chose “no,” the questionnaire was to be discarded. 2.4. Data analysis Statistical analysis was performed using SPSS Version 22 and Mplus 7.0. We did not substitute missing values because the missing data was below 3%. First, we conducted a serial descriptive analysis of mean, standard deviation, and correlation to assess the overall patterns of the main variables. Then, we analyzed the direct effects of CIRR on SBV and depression to explore the CIRR model of SBV and depression. Scores of classmate, parent-child, teacher-student, and friend relationships below the 25th percentile were deemed as risk factors and given a score of 1, with the remaining 75% scored as 0. The CIRR index (i.e., the number of IRRs) was obtained by summing the scores of all four risk factors. Last, we conducted bootstrap tests in Mplus 7.0 software to explore two serial mediating effects of resilience among CIRR, SBV, and depression. The bootstrap method is currently the best method of testing mediation effect (Preacher & Hayes 2008). 3. Results The present findings for this sample showed a 41.91% prevalence of 3
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Table 1 Zero-order correlations, means, and standard deviations of main variables. Variables
Gender
Age
CIRR index
SBV
Depression
Resilience
Gender Age CIRR index SBV Depression Resilience M SD
–
−0.066 –
−0.015 −0.018 –
−0.17*** −0.17*** 0.34*** –
−0.045 −0.035 0.43*** 0.39*** –
1.52 0.50
14.32 1.54
1.12 1.18
1.51 0.68
0.99 0.57
0.097** −0.058 −0.36*** −0.22*** −0.57*** – 2.52 0.66
Note. Gender is coded: Male = 1; Female = 2. Age is coded in years. CIRR index = Cumulative interpersonal relationship risk index; SBV = school bullying victimization. ⁎⁎ p < 0.01,. ⁎⁎⁎ p < 0.001.
SBV using the traditional cutoff point “2 to 3 times a month” (Solberg & Olweus, 2010). The prevalence found in the present study was within the prevalence range of existing studies (Chan & Wong, 2015).
p < 0.001) after controlling for gender, age, and grade. As suggested by statisticians (Cohen, Cohen, West & Aiken, 2003), the corresponding quadratic term was included in the regression model to test the functional form of the relationships between variables. A quadratic term is created by centralizing the mean of CIRR scores and then squaring it (Oldfield, Humphrey & Hebron, 2015). If the squared cumulative risk score (i.e., a quadratic term) accounts for additional variance beyond the CIRR score (i.e., a linear term) and results in a better overall model fit, it can be concluded that a disproportional relationship between CIRR and SBV and depression is present. The results showed that all of the predictive roles of the quadratic term on SBV (β = −0.002, p > 0.05) and depression (β = 0.026, p > 0.05) were not significant. These results suggest that a linear relationship is a better fit between CIRR and SBV and depression. Therefore, the present study demonstrates there is a proportionate increase in SBV and depression when CIRR increases (linear model). CIRR has a significantly adverse impact on SBV and depression. Thus, the CIRR hypothesis was supported (Hypothesis 1), and the functional form was found to be linear.
3.1. Descriptive statistics of main variables Descriptive statistics of the sample are presented in Table 1. Table 1 showed that SBV is significantly negatively correlated with gender and age. Further analysis found that boys have significantly higher SBV score than girls (M = 1.63, SD = 0.75; M = 1.40, SD = 0.58, respectively). With an increase in age, SBV significantly decreased. Resilience is significantly positively correlated with gender. Further analysis found that female students have significantly higher resilience than their male counterparts do (M = 2.58, SD = 0.64; M = 2.46, SD = 0.66, respectively). The CIRR index had a significant positive correlation with SBV and depression, and negative correlation with resilience. SBV was significantly positively correlated with depression and negatively correlated with resilience. Depression was significantly negatively correlated with resilience.
3.3. Test of mediating effect of resilience on the relationship among CIRR, SBV, and depression
3.2. Test of the direct effect of CIRR on SBV and depression Tests were conducted in two phases: first, to examine whether increased risk exposure was associated with increased SBV and depression; and second, to assess the functional forms of the relationship between CIRR, SBV, and depression. The outcomes related to risk exposure, SBV, and depression are presented in Table 2. As Table 2 shows, 33.96% of middle school students experienced two or more interpersonal risks. As CIRR index increased, both SBV and depression scores increased. Subsequently, regression analysis was conducted to explore whether cumulative effects existed between CIRR and the two variables. The predictive variable was the CIRR index and the demographic risk factors (gender, age, and grade) were added as covariates. SBV and depression were added as the outcome variables, respectively. The results showed that CIRR significantly and positively predicted SBV (β = 0.35, p < 0.001) and depression (β = 0.43,
We conducted bootstrap analyses on Model 1 and Model 2 using Mplus 7.0. Both models were supported (Hypothesis 2 and 3). The results of STDYX standardization have been presented in Figs. 3 and 4; these figures show that CIRR could positively predict SBV and depression and negatively predict resilience. Resilience negatively predicted depression. Resilience and SBV were mutual predictors. Resilience could affect SBV and, in turn, impact depression. In addition, resilience could directly affect depression triggered by SBV. All indirect effect values (STDYX Standardization) have been presented in Tables 3 and 4, which show that all mediation paths were significant. In the present study, SBV was not only an important
Table 2 Number (percentage) of participants within each risk category and mean and standard deviation of SBV and depression. CIRR index
Number (percentage) of participants in each risk number
SBV (M ± SD)
Depression (M ± SD)
0 1 2 3 4
300 (40.43%) 190 (25.61%) 145 (19.54%) 73 (9.84%) 34 (4.58%)
1.29 1.47 1.67 1.88 2.08
0.75 0.94 1.22 1.31 1.62
± ± ± ± ±
0.43 0.55 0.81 0.91 0.85
± ± ± ± ±
0.46 0.52 0.58 0.59 0.67
Fig. 3. Testing of Hypothesis 2. Note. CIRR = Cumulative interpersonal relationship risk; SBV = school bullying victimization.
Note. SBV = school bullying victimization. 4
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(Epkins & Heckler, 2011; Gerard & Buehler, 2004; Margolin et al., 2010; Schumm et al., 2006) and furthermore, supported linear models between cumulative ecological risk and other psychopathological problems (Appleyard et al., 2005; Gerard & Buehler, 2004). These results suggest that the adverse effects of cumulative ecological risk on adolescents are interdisciplinary in nature. That is, cumulative ecological risk can result in multiple negative outcomes, such as internet addiction (Li, Zhou, Zhao, Wang & Sun, 2016), anxiety (Epkins & Heckler, 2011), internalizing and externalizing of problems (Appleyard et al., 2005), and SBV and depression, as the present research shows. Furthermore, the direct effects of CIRR on SBV and depression show that SBV and depression scores increase linearly as CIRR index increases. This suggests that it is essential to reduce every interpersonal relationship risk factor. The effectiveness of interventions for specific IRR factors are not significantly affected by that of other risk factors, so comprehensive prevention efforts for IRRs (classmate, parent-child, teacher-student, and friend relationships risks) must be carried out to decrease the possibility of SBV and depression. In recent years, the concept of cumulative risk models has received significant attention in developmental psychopathology (e.g., MacKenzie, Kotch & &Lee, 2011). The cumulative interpersonal risk model of the current research is an important extension of previous studies in investigating bullying and depressive problems in middle school students, and, also, enriching connotations of the socio-ecological theory (Bronfenbrenner & Morris, 1998). The results show that resilience can mediate the relationship between CIRR and SBV. The results are in line with existing literature (Geitsidou & Giovazolias, 2016; Hinduja & Patchin, 2017). That is, CIRR can weaken individual resilience levels. Low resilience level can increase the possibility of individuals being bullied. Resilient adolescents show few victim characteristics, such as cowardice and weakness (Zhao, Lee, Tang, & York, 2019), and do not easily attract bullies. Therefore, resilience can decrease SBV. Further, SBV can increase with a decrease in resilience. In addition, resilience can mediate the relationship between SBV and depression. The result is in accord with the of previous study (Zhou et al., 2017). Experience with bullying victimization can reduce one's resilience and in turn increase one's level of depression. Resilient adolescents can handle pressure and deal with unpleasant or painful feelings such as sadness, fear, and anger. In addition, resilient adolescents try to see the humorous side of things when faced with bullying problems and may be less inclined to view it as hurtful behavior (e.g., teasing or name-calling), as purposeful, and they are less likely to seriously affected by it. Therefore, resilience can decrease depression. Additionally, depression can increase with a decrease in resilience. In the end, resilience and SBV can mediate the relationship between CIRR and depression. CIRR destroy adolescents’ internal protective resources and increase their external maladaptive behaviors, and in turn, increase adolescents’ level of depression. Traditionally, approaches to prevent SBV have been pathogenic and focus on mitigating risk factors, and identifying and ameliorating deficiencies in the lives of an individual (Garbarino, 2001). However, it can be especially difficult for practitioners to intervene in all IRRs, based on the linear model of CIRR in the present research. Our results reveal that cultivating resilience among adolescents may be an effective approach towards decreasing SBV and depression that follows from multiple interpersonal relationship risk exposures.
Fig. 4. Testing of Hypothesis 3. Note. CIRR = cumulative interpersonal relationship risks, SBV = school bullying victimization. Table 3 Indirect effect of CIRR on depression in Model 1. The path of effect
Point estimate
S.E.
Bootstrap 95% CI Lower Upper
p
Ratio
ind1 ind2 ind3 Total indirect effect
0.16 0.009 0.066 0.24
0.019 0.004 0.013 0.024
0.13 0.003 0.046 0.20
<0.001 <0.05 <0.001 <0.001
36.78% 2.11% 15.17% 54.06%
0.19 0.018 0.088 0.28
Note. CIRR = Cumulative interpersonal relationship risk; ind1: CIRRResilience-Depression; ind2: CIRR-Resilience-SBV-Depression; ind3: CIRR-SBVDepression; Ratio equals to indirect to total effect of CIRR on depression. Table 4 Indirect effect of CIRR on depression in Model 2. The path of effect
Point estimate
S.E.
Bootstrap 95% CI Lower Upper
p
Ratio
ind1 ind2 ind3 Total indirect effect
0.14 0.018 0.075 0.24
0.020 0.008 0.014 0.022
0.11 0.006 0.053 0.20
<0.001 <0.05 <0.001 <0.001
32.33% 4.16% 17.32% 53.81%
0.18 0.031 0.099 0.28
Note. CIRR = Cumulative interpersonal relationship risk; ind1: CIRRResilience-Depression; ind2: CIRR-SBV-Resilience-Depression; ind3: CIRR-SBVDepression; Ratio equals to indirect to total effect of CIRR on depression.
outcome variable of CIRR but also an important mediation variable between CIRR and depression. As a mediation variable, the role of SBV was weaker than that of resilience. The total mediation effect ratio of resilience to total effect of CIRR was 38.89% in Model 1 and 36.49% in Model 2. However, the total mediation effect ratio of SBV to total effect of CIRR was 17.28% in Model 1 and 21.48% in Model 2. 4. Discussion The main purpose of this study was to explore how cumulative interpersonal relationship risks (CIRR; classmate, parent-child, teacherstudent, and friend relationships risks) impact school bullying victimization (SBV) and depression, and why CIRR could affect SBV and depression from a positive psychological perspective. The results supported all three hypotheses. CIRR linearly and significantly predicts SBV and depression. CIRR could directly or indirectly decrease an individual's resilience, and therefore, increase an individual's SBV and level of depression. Our results help us construct CIRR linear models of SBV and depression and mediation models of resilience among CIRR, SBV, and depression. The results confirmed the cumulative risks model of depression
5. Conclusion The present research established cumulative interpersonal relationship risk (CIRR) linear models for school bullying victimization (SBV) and depression, and two mediation models of resilience in the relationships among CIRR, SBV, and depression. The current research extends knowledge from previous studies of SBV and depressive problems triggered by SBV by using a positive psychology perspective as opposed to a pathological perspective. 5
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However, this study has some limitations. First, causality cannot be inferred between variables, as this research is a cross-sectional study. In our study, a key point is the relationship between resilience and SBV, but we cannot confirm whether the relationship is one-way or two-way. If the relationship is two-way, there is another possible pathway: CIRR -> resilience -> SBV -> resilience -> depression. That is, CIRR decreases an individual's resilience and in turn, increases SBV. SBV further decreases resilience and leads to depression in the end. In the future, we can employ a longitudinal design to track the relationship between variables to better test the serial mediation model established in this study. Second, all data in this study were obtained from student selfreports. Future researches should nonetheless use multiple information sources to collect data to better investigate the model established in this study. Despite these limitations, the findings of this study have important implications for intervention programs for adolescents experiencing bullying victimization and depressive symptoms. On one hand, we must help adolescents develop warm, supported, friendly relationships with their parents, teachers and peers, which can directly decrease SBV and depression. For example, we can conduct trainings for improving social skills and self-confidence and start peer support programs. On the other hand, we can cultivate resilience in adolescents. For example, early prevention is pivotal and essential, such as establishing warm and safe attachment relationships between child and parents. In addition, education programs on how to deal with frustration effectively should be carried out for holistic personality development in adolescents. The results suggest two possible strategies to decrease SBV and depression that follows from multiple IRRs exposures. The strategies involve comprehensively intervening in four IRRs from a psychopathological perspective or cultivating resilience in adolescents from a positive psychological perspective.
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Declaration of Competing Interest The authors declare that they have no conflict of interest. Acknowledgements This work was supported by Key Project of National Education and Scientific Planning of the Ministry of Education: Using Stereotype EPA Model to Identify and Intervene School Bullying Behavior in Primary and Middle School [grant numbers DBA170299]. References Appleyard, K., Egeland, B., van Dulmen, M. H. M., & Sroufe, L. A. (2005). When more is not better: The role of cumulative risk in child behavior outcomes. Journal of Child Psychology and Psychiatry, 46(3), 235–245. https://doi.org/10.1111/j.1469-7610. 2004.00351.x. Arseneault, L., Bowes, L., & Shakoor, S. (2010). Bullying victimization in youths and mental health problems: ‘Much ado about nothing’? Psychological Medicine, 40(05), 717–729. https://doi.org/10.1017/S0033291709991383. Bjereld, Y., Daneback, K., & Petzold, M. (2017). Do bullied children have poor relationships with their parents and teachers? a cross-sectional study of Swedish children. Children and Youth Services Review, 73, 347–351. https://doi.org/10.1016/j. childyouth.2017.01.012. Bronfenbrenner, U., & Morris, P. A. (1998). The ecology of developmental processes. In W. Damon, & R. M. Lerner (Vol. Eds.), (5th ed.). Handbook of child psychology: 1, (pp. 993–1028). New York, NY: Wiley. Burke, T. (2017). Everything's gonna be alright! The longitudinal interplay among social support, peer victimization, and depressive symptoms. Journal of Youth and Adolescence, 46(9), 1999–2014. https://doi.org/10.1007/s10964-017-0653-0. Chan, H. C., & Wong, D. S. W. (2015). Traditional school bullying and cyberbullying in Chinese societies: Prevalence and a review of the whole-school intervention approach. Aggression & Violent Behavior, 23, 98–108. https://doi.org/10.1016/j.avb. 2015.05.010. Chester, K. L., Callaghan, M., Cosma, A., Donnelly, P., Craig, W., Walsh, S., et al. (2015). Cross-national time trends in bullying victimisation among children aged 11, 13 and 15 from 2002 to 2010. European Journal of Public Health, 25(2), 61–64. https://doi. org/10.1039/c4cp00175c. Cohen, J., Cohen, P., West, S. G., & Aiken, L. S. (2003). Applied multiple regression/correlation analysis for the behavioral sciences (3rd ed.). Mahwah, NJ: Lawrence.
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Cumulative interpersonal relationship risk and resilience models for bullying victimization and depression in adolescents ⁎
Zhao Yongpinga, , Zhao Yufanga, Lee Yueh-Tingb, Chen Lic a
Faculty of Psychology, Southwest University, Chongqing, China Department of Psychology, Southern Illinois University Carbondale, IL, USA c Student Development Center, Fuling Bashu Secondary School, Fuling, China b
A R T I C LE I N FO
A B S T R A C T
Keywords: Cumulative interpersonal relationship risks (CIRR) Resilience School bullying victimization (SBV) Depression Serial mediation
Studies have documented that school bullying victimization (SBV) triggered by interpersonal relationship risks (IRRs) can increase depression. However, the predictive patterns of cumulative IRRs (CIRR; classmate, parentchild, teacher-student, and friend relationships risks) on SBV and depression and its psychological mechanism remain unclear from a positive psychological perspective. This study explored CIRR models for SBV and depression and tested two mediation models of resilience in relationships among CIRR, SBV and depression. Selfreport questionnaires were answered by 742 valid participants between 11 and 19 years of age. Findings showed that CIRR significantly predicted SBV and depression, with a proportionate increase in SBV and depression as the CIRR increased. Furthermore, the results confirmed the two mediation hypotheses. CIRR could directly decrease one's resilience and, therefore, increase one's SBV and level of depression. CIRR could also indirectly decrease one's resilience by SBV and further increase one's level of depression. The results construct CIRR linear model for SBV and depression and mediation models of resilience among CIRR, SBV and depression. Our results indicate that, to decrease SBV and depression based on multiple IRRs exposures, comprehensive intervening in four IRRs from a psychopathological perspective or cultivating resilience in adolescents from a positive psychological perspective is required.
1. Introduction1 School bullying victimization (SBV) is a topic of concern for youths, parents, school staff, and mental health practitioners (Arseneault, Bowes & Shakoor, 2010). A survey from 79 high and low income countries showed that approximately 30% of adolescents have reported bullying victimization experience (Elgar et al., 2015), which were enacted intentionally and repeatedly by an individual or group based on an imbalance of power between victims and perpetrators (Olweus, 2013). SBV has been found to be associated with a number of negative outcomes (Chester et al., 2015; Gámez-Guadix, Orue, Smith & Calvete, 2013), of which depression is one of the major undesirable outcomes. For example, adolescents who experience SBV are 2 to 7 times more likely to report depressive symptoms than those who are not bullied (Klomek, Marrocco, Kleinman, Schonfeld & Gould, 2007). Specifically, victims of frequent bullying in childhood had higher rates of depression at age 45 than their non-victimized peers (Takizawa, Maughan & &Arseneault, 2014).
Several reviews have been devoted to integrate risk factors that may lead to SBV (Cook, Williams, Guerra, Kim & Sadek, 2010; Hong & Espelage, 2012; Huang, Hong & Espelage, 2013; Maunder & Crafter, 2018) from different perspectives, all of which highlight the importance of considering SBV in the socio-ecological context. According to socio-ecological theory (Bronfenbrenner & Morris, 1998), human development is impacted by multiple ecological subsystems of family, school, and peers. Therefore, as a negative interpersonal interaction phenomenon in youth, SBV can be predicted by adolescents’ negative interpersonal relationships with parents, teachers, and peers (Cook et al., 2010; Hong & Espelage, 2012; Huang et al., 2013; Maunder & Crafter, 2018). However, many studies focused on one or two-way combinations of interpersonal risk factors (IRRs) such as parents and teacher (Bjereld, Daneback & Petzold, 2017), parents and peer (Burke, 2017; Healy & Sanders, 2018), teacher-student and peer (Sulkowski & Simmons, 2017), peer and friendship (Strohmeier, Kärnä & Salmivalli, 2011). Although these studies largely help us understand SBV in youth
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Corresponding author. E-mail address: [email protected] (Y. Zhao). 1 CIRR= Cumulative interpersonal relationship risks; SBV= School bullying victimization https://doi.org/10.1016/j.paid.2019.109706 Received 29 August 2019; Received in revised form 5 November 2019; Accepted 10 November 2019 0191-8869/ © 2019 Elsevier Ltd. All rights reserved.
Please cite this article as: Zhao Yongping, et al., Personality and Individual Differences, https://doi.org/10.1016/j.paid.2019.109706
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the capacity to spring back, rebound, successfully adapt in the face of adversity, and develop social and academic competence despite exposure to severe stress (Hinduja & Patchin, 2017). Relationships are one of important factors that influence resilience (Geitsidou & Giovazolias, 2016). For example, a secure attachment relationship can reduce negative feelings aroused by stressful events and reinforce resilience (Rutter, 1987, 2006). Furthermore, students with a strong resilience profile were less likely to be bullied than those who reported fewer developmental strengths such as “parental involvement,” “positive peer influence” (Donnon, 2010; Hinduja & Patchin, 2017). Thus, negative interpersonal relationship could indirectly affect SBV through a decrease in resilience. In addition, students reporting greater resilience experienced less depression regarding bullying victimization (Moore & Woodcock, 2017). Resilience partially mediated the relationship between SBV and depressive symptoms (Zhou, Liu, Niu, Sun & Fan, 2017). That is, SBV can decease resilience and in turn increase level of depression. Last, several studies have explored the cumulative risk model of depression (Epkins & Heckler, 2011; Gerard & Buehler, 2004; Margolin, Vickerman, Oliver & Gordis, 2010; Schumm, Briggs-Phillips & Hobfoll, 2006) and found a linear model between cumulative risks and depression (Gerard & Buehler, 2004) and a positive acceleration model between cumulative risks and negative outcomes, including depression (Margolin et al., 2010). Therefore, resilience can be a mediator among CIRR, SBV, and depression. CIRR could directly or indirectly decrease an individual's resilience, and therefore, increase an individual's SBV and level of depression. To our knowledge, a few related studies confirm the role of resilience in the relationships among CIRR (classmate, parent-child, teacher-student, and friend relationships risks), SBV, and depression. The Resilience model can help us understand the underlying psychological mechanisms of the relations among CIRR, SBV, and depression, which can then inform intervention program design for SBV and depression triggered by CIRR. Especially, when the functional form between CIRR, SBV, and depression followed a linear or positive acceleration model, it was difficult for practitioners to intervene in multiple IRRs. Thus, we can cultivate youths’ resilience to decrease the negative chain reaction triggered by CIRR. The present research would extend anti-bullying approaches from a positive psychological perspective, and shift the focus of anti-bullying intervention from individual deficits to individual strengths. Thus, the second aim of the present study was to explore resilience models of CIRR, SBV, and depression. Based on the abovementioned review, we can hypothesize that CIRR can predict SBV and depression. However, the possible functional form among them cannot be deduced because similar researches on CIRR model of SBV and CIRR model of depression were not found. Furthermore, the cumulative risk model of depression has different functional forms (Gerard & Buehler, 2004; Margolin et al., 2010). With regard to resilience models of CIRR, SBV, and depression, we proposed two concept models (Figs. 1 and 2) and planned to explore whether model 1 or 2, or both, were valid. We put forth three specific hypotheses as follows: Hypotheses 1. CIRR would significantly predict SBV and depression. Hypotheses 2. CIRR could directly decrease levels of resilience and subsequently increase SBV and depression (Fig. 1). Hypotheses 3. CIRR could indirectly decrease levels of resilience by increasing SBV and subsequently result in more depressive symptoms (Fig. 2).
from different levels of IRR, it is vital to consider multiple IRRs simultaneously. First, risk factors in different fields are often synergistic, and individuals are often faced with risk factors in one field as well as in another (Evans, Li & Whipple, 2013). For example, a student who has poor social skills can have a poor teacher-student relationship and, simultaneously, a poor relationship with classmates. Therefore, paying attention to the influence of multi-field risk factors on adolescents’ development as opposed to a single or two minor risk factors’ influence is more relevant to the individual's reality. Second, if a risk factor is related to other risk factors, considering a single or two minor risk factors can lead to an overestimation of its/their effects, because children experiencing multiple risk factors are much more likely to experience psychological disorders (Evans et al., 2013). To our knowledge, existing literature does not yet clarify how exposure to multiple IRRs (classmate, parent-child, teacher-student and friend relationships risks) affect SBV and in turn influence depression, using a cumulative risk approach (Gerard & Buehler, 2004; Rauer, Karney, Garvan & Hou, 2008). Existing literature has shown that the cumulative risk model is the most widely used method for modeling multiple risks (Evans et al., 2013). Specifically, in cumulative risk model, each risk factor was dichotomized. Scores below the 25th percentile were deemed as risk factors and given a score of 1, with the remaining 75% scored as 0. CIRR index is obtained by summing the scores of all risk factors, and this is used as an independent variable to construct the cumulative risk model. Previous studies have found that cumulative risk models could show different functional forms such as linear, positive acceleration, and negative acceleration models (Appleyard, Egeland, van Dulmen & Sroufe, 2005; Gerard & Buehler, 2004; Rauer et al., 2008). The linear model assumes that problematic outcomes show a reasonably steady increase with an increasing number of risk factors. Positive acceleration model assumes that the correlation between each risk factor and problematic outcome is stronger when other risk factors occur simultaneously than when no other risk factors are concurrent. Negative acceleration models assume that the effect of new risk factors on individual problems becomes smaller and smaller with the increase of cumulative risk. Exploring different functional forms between CIRR and SBV and depression were important because different functional forms can mean different intervention practices for SBV and depression. If the functional form shows a linear model, comprehensive prevention effort is needed. Because the effectiveness of intervention while targeting a particular IRR factor is not affected by other IRR factors, reduction of individual IRR factors is crucial (Appleyard et al., 2005). If the functional form shows a positive acceleration model, it means SBV and depression accelerates after a certain critical point in the number of IRRs (Appleyard et al., 2005). It was particularly difficult to deal with SBV and depression triggered by CIRR. If the functional form shows a negative acceleration model, interventions for individuals with a medium number of IRRs is more effective because the benefits of reducing each risk factor are more obvious than the benefits of reducing a single risk when individuals encounter a large number of risk factors (Rauer et al., 2008). Thus, the first aim of the present study was to explore the CIRR model (classmate, parent-child, teacher-student, and friend relationships risks) of SBV and depression. Although multiple IRRs have been considered as risk factors associated with SBV and depression, the relationships between IRRs and SBV and depression could be indirect to a certain extent. This is because many students exposed to the same level of risks do not inevitably develop the same negative outcomes, and these students are believed to possess resilience against risks (Richardson, 2002). Resilience refers to
Fig. 1. Concept figure of Model 1.
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Fig. 2. Concept figure of Model 2. Note. CIRR = cumulative interpersonal relationship risks, SBV = school bullying victimization.
2. Method
risk factors (Evans et al., 2013).
2.1. Participants
2.3.2. California bully/Victimization scale (CBVS) CBVS (Felix, Sharkey, Green, Furlong & Tanigawa, 2011) was employed to assess SBV in the past month. The scale includes items asking about eight forms of victimization that respondents may have experienced at school (e.g., How often have you been teased or called names in a mean or hurtful way?). Students rated the frequency of each of these experiences on a five-point scale (1 = Never in the past month, 2 = once in the past month, 3 = 2 or 3 times in the past month, 4 = about once a week, and 5 = several times a week). Power imbalance was ascertained using a series of items asking students to compare themselves to the primary individual who bullied them. Students responded to how popular, smart in schoolwork, and physically strong that individual is compared to them, as rated on a three-point scale (less than me, same as me, more than me). The Cronbach's α value for the present sample was 0.86.
The study included 840 middle school students from five schools located in Chongqing. The effective sample included 742 middle school students, of whom 48.38% were males. The sample size was sufficient for model analysis (Wu, 2010). These students were in grades 7 to 11 and ranged in age from 11 to 19 (M = 14.32, SD =1.54) years. There were 131 to 190 students in every grade. Ninety-eight questionnaires were discarded because students reported “no” in two validity items, which indicated that these students had not filled out the questionnaire seriously and carefully. 2.2. Procedures The first author (YZ) explained the project to psychology graduate students (all of them are middle school teachers) in the university classroom and invited them to recommend schools that would be interested in participating in the study. Five interested middle schools participated in the project. The fourth author and psychology teachers in these schools administered paper-pencil surveys to the participants in an ordinary classroom setting. The participants were assured of the confidentiality and anonymity of their responses. Verbal informed consent was obtained from all students prior to the survey. The five schools and the Ethics Committee at the Faculty of Psychology of Southwest University, China, approved this study.
2.3.3. Connor–Davidson resilience scale (CD-RISC) The concise 10-item version of the 25-item self-report CD-RISC (Hinduja & Patchin, 2017) was employed (e.g., “I can deal with whatever comes my way”) to assess resilience. Participants had to respond on a five-point scale (0 = Not True at All, 1 = Rarely True, 2 = Sometimes True, 3 = Often True, and 4 = True Nearly All the Time). The Cronbach's α value for the present sample was 0.83. 2.3.4. Center for epidemiological studies depression scale (CES-D) The 20-item CES-D (Radloff, 1977) was employed to assess symptoms of depression. Participants rated the frequency of depressive symptoms in the previous week on a scale of 0 (less than 1 day) to 3 (5–7 days) (e.g., ‘‘I felt depressed.’’). The Cronbach's α value for the present sample was 0.90.
2.3. Measurements 2.3.1. Interpersonal relationship scales Existing literature shows that social support significantly predicts interpersonal relationships (for detailed information, see Sun, 2017) and can be subsumed under a broader concept of interpersonal relationships (Stoetzer et al., 2009). Thus, we employed three subscales of the Child and Adolescent Social Support Scale (CASSS; Malecki & Demaray 2002) to assess parent-child relations, teacher-student relations, and classmate relations. These subscales have good reliability and validity (Malecki & Demaray, 2002). Parent subscale of CASSS. This subscale was employed to assess parent-child relations. It includes 10 items (e.g., “My parent(s) listen to me when I'm mad”) using a response scale from 1 (Never) to 6 (Always). The Cronbach's α value for the present sample was 0.88. Teacher subscale of CASSS. This subscale was employed to assess teacher-student relations. It includes 10 items (e.g., “My teacher(s) cares about me”) using a response scale from 1 (Never) to 6 (Always). The Cronbach's α value for the present sample was 0.93. Classmate subscale of CASSS. This subscale was employed to assess classmate relations. It includes 10 items (e.g., “My classmates ask me to join activities”) using a response scale from 1 (Never) to 6 (Always). The Cronbach's α value for the present sample was 0.92. Friend relations questionnaire. Friendlessness was assessed using two items, “I have good friends in my classroom” and “I have friends in my own class,” to which the students responded on a 4-point scale (1totally disagree, 4-totally agree) (Strohmeier et al., 2011). The Cronbach's α value for the present sample was 0.60. Scores of parent-child, teacher-student, classmate, and friend relationships below the 25th percentile were deemed as risk factors and given a score of 1, with the remaining 75% scored as 0. The number of IRRs (i.e., CIRR index) was obtained by summing the scores of all four
2.3.5. Validity items In order to improve the validity of the questionnaire, two items were used. One was “I am taking this survey seriously”; the other was “I am answering the questionnaire carefully.” Participants were asked to choose “no” or “yes.” If students chose “no,” the questionnaire was to be discarded. 2.4. Data analysis Statistical analysis was performed using SPSS Version 22 and Mplus 7.0. We did not substitute missing values because the missing data was below 3%. First, we conducted a serial descriptive analysis of mean, standard deviation, and correlation to assess the overall patterns of the main variables. Then, we analyzed the direct effects of CIRR on SBV and depression to explore the CIRR model of SBV and depression. Scores of classmate, parent-child, teacher-student, and friend relationships below the 25th percentile were deemed as risk factors and given a score of 1, with the remaining 75% scored as 0. The CIRR index (i.e., the number of IRRs) was obtained by summing the scores of all four risk factors. Last, we conducted bootstrap tests in Mplus 7.0 software to explore two serial mediating effects of resilience among CIRR, SBV, and depression. The bootstrap method is currently the best method of testing mediation effect (Preacher & Hayes 2008). 3. Results The present findings for this sample showed a 41.91% prevalence of 3
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Table 1 Zero-order correlations, means, and standard deviations of main variables. Variables
Gender
Age
CIRR index
SBV
Depression
Resilience
Gender Age CIRR index SBV Depression Resilience M SD
–
−0.066 –
−0.015 −0.018 –
−0.17*** −0.17*** 0.34*** –
−0.045 −0.035 0.43*** 0.39*** –
1.52 0.50
14.32 1.54
1.12 1.18
1.51 0.68
0.99 0.57
0.097** −0.058 −0.36*** −0.22*** −0.57*** – 2.52 0.66
Note. Gender is coded: Male = 1; Female = 2. Age is coded in years. CIRR index = Cumulative interpersonal relationship risk index; SBV = school bullying victimization. ⁎⁎ p < 0.01,. ⁎⁎⁎ p < 0.001.
SBV using the traditional cutoff point “2 to 3 times a month” (Solberg & Olweus, 2010). The prevalence found in the present study was within the prevalence range of existing studies (Chan & Wong, 2015).
p < 0.001) after controlling for gender, age, and grade. As suggested by statisticians (Cohen, Cohen, West & Aiken, 2003), the corresponding quadratic term was included in the regression model to test the functional form of the relationships between variables. A quadratic term is created by centralizing the mean of CIRR scores and then squaring it (Oldfield, Humphrey & Hebron, 2015). If the squared cumulative risk score (i.e., a quadratic term) accounts for additional variance beyond the CIRR score (i.e., a linear term) and results in a better overall model fit, it can be concluded that a disproportional relationship between CIRR and SBV and depression is present. The results showed that all of the predictive roles of the quadratic term on SBV (β = −0.002, p > 0.05) and depression (β = 0.026, p > 0.05) were not significant. These results suggest that a linear relationship is a better fit between CIRR and SBV and depression. Therefore, the present study demonstrates there is a proportionate increase in SBV and depression when CIRR increases (linear model). CIRR has a significantly adverse impact on SBV and depression. Thus, the CIRR hypothesis was supported (Hypothesis 1), and the functional form was found to be linear.
3.1. Descriptive statistics of main variables Descriptive statistics of the sample are presented in Table 1. Table 1 showed that SBV is significantly negatively correlated with gender and age. Further analysis found that boys have significantly higher SBV score than girls (M = 1.63, SD = 0.75; M = 1.40, SD = 0.58, respectively). With an increase in age, SBV significantly decreased. Resilience is significantly positively correlated with gender. Further analysis found that female students have significantly higher resilience than their male counterparts do (M = 2.58, SD = 0.64; M = 2.46, SD = 0.66, respectively). The CIRR index had a significant positive correlation with SBV and depression, and negative correlation with resilience. SBV was significantly positively correlated with depression and negatively correlated with resilience. Depression was significantly negatively correlated with resilience.
3.3. Test of mediating effect of resilience on the relationship among CIRR, SBV, and depression
3.2. Test of the direct effect of CIRR on SBV and depression Tests were conducted in two phases: first, to examine whether increased risk exposure was associated with increased SBV and depression; and second, to assess the functional forms of the relationship between CIRR, SBV, and depression. The outcomes related to risk exposure, SBV, and depression are presented in Table 2. As Table 2 shows, 33.96% of middle school students experienced two or more interpersonal risks. As CIRR index increased, both SBV and depression scores increased. Subsequently, regression analysis was conducted to explore whether cumulative effects existed between CIRR and the two variables. The predictive variable was the CIRR index and the demographic risk factors (gender, age, and grade) were added as covariates. SBV and depression were added as the outcome variables, respectively. The results showed that CIRR significantly and positively predicted SBV (β = 0.35, p < 0.001) and depression (β = 0.43,
We conducted bootstrap analyses on Model 1 and Model 2 using Mplus 7.0. Both models were supported (Hypothesis 2 and 3). The results of STDYX standardization have been presented in Figs. 3 and 4; these figures show that CIRR could positively predict SBV and depression and negatively predict resilience. Resilience negatively predicted depression. Resilience and SBV were mutual predictors. Resilience could affect SBV and, in turn, impact depression. In addition, resilience could directly affect depression triggered by SBV. All indirect effect values (STDYX Standardization) have been presented in Tables 3 and 4, which show that all mediation paths were significant. In the present study, SBV was not only an important
Table 2 Number (percentage) of participants within each risk category and mean and standard deviation of SBV and depression. CIRR index
Number (percentage) of participants in each risk number
SBV (M ± SD)
Depression (M ± SD)
0 1 2 3 4
300 (40.43%) 190 (25.61%) 145 (19.54%) 73 (9.84%) 34 (4.58%)
1.29 1.47 1.67 1.88 2.08
0.75 0.94 1.22 1.31 1.62
± ± ± ± ±
0.43 0.55 0.81 0.91 0.85
± ± ± ± ±
0.46 0.52 0.58 0.59 0.67
Fig. 3. Testing of Hypothesis 2. Note. CIRR = Cumulative interpersonal relationship risk; SBV = school bullying victimization.
Note. SBV = school bullying victimization. 4
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(Epkins & Heckler, 2011; Gerard & Buehler, 2004; Margolin et al., 2010; Schumm et al., 2006) and furthermore, supported linear models between cumulative ecological risk and other psychopathological problems (Appleyard et al., 2005; Gerard & Buehler, 2004). These results suggest that the adverse effects of cumulative ecological risk on adolescents are interdisciplinary in nature. That is, cumulative ecological risk can result in multiple negative outcomes, such as internet addiction (Li, Zhou, Zhao, Wang & Sun, 2016), anxiety (Epkins & Heckler, 2011), internalizing and externalizing of problems (Appleyard et al., 2005), and SBV and depression, as the present research shows. Furthermore, the direct effects of CIRR on SBV and depression show that SBV and depression scores increase linearly as CIRR index increases. This suggests that it is essential to reduce every interpersonal relationship risk factor. The effectiveness of interventions for specific IRR factors are not significantly affected by that of other risk factors, so comprehensive prevention efforts for IRRs (classmate, parent-child, teacher-student, and friend relationships risks) must be carried out to decrease the possibility of SBV and depression. In recent years, the concept of cumulative risk models has received significant attention in developmental psychopathology (e.g., MacKenzie, Kotch & &Lee, 2011). The cumulative interpersonal risk model of the current research is an important extension of previous studies in investigating bullying and depressive problems in middle school students, and, also, enriching connotations of the socio-ecological theory (Bronfenbrenner & Morris, 1998). The results show that resilience can mediate the relationship between CIRR and SBV. The results are in line with existing literature (Geitsidou & Giovazolias, 2016; Hinduja & Patchin, 2017). That is, CIRR can weaken individual resilience levels. Low resilience level can increase the possibility of individuals being bullied. Resilient adolescents show few victim characteristics, such as cowardice and weakness (Zhao, Lee, Tang, & York, 2019), and do not easily attract bullies. Therefore, resilience can decrease SBV. Further, SBV can increase with a decrease in resilience. In addition, resilience can mediate the relationship between SBV and depression. The result is in accord with the of previous study (Zhou et al., 2017). Experience with bullying victimization can reduce one's resilience and in turn increase one's level of depression. Resilient adolescents can handle pressure and deal with unpleasant or painful feelings such as sadness, fear, and anger. In addition, resilient adolescents try to see the humorous side of things when faced with bullying problems and may be less inclined to view it as hurtful behavior (e.g., teasing or name-calling), as purposeful, and they are less likely to seriously affected by it. Therefore, resilience can decrease depression. Additionally, depression can increase with a decrease in resilience. In the end, resilience and SBV can mediate the relationship between CIRR and depression. CIRR destroy adolescents’ internal protective resources and increase their external maladaptive behaviors, and in turn, increase adolescents’ level of depression. Traditionally, approaches to prevent SBV have been pathogenic and focus on mitigating risk factors, and identifying and ameliorating deficiencies in the lives of an individual (Garbarino, 2001). However, it can be especially difficult for practitioners to intervene in all IRRs, based on the linear model of CIRR in the present research. Our results reveal that cultivating resilience among adolescents may be an effective approach towards decreasing SBV and depression that follows from multiple interpersonal relationship risk exposures.
Fig. 4. Testing of Hypothesis 3. Note. CIRR = cumulative interpersonal relationship risks, SBV = school bullying victimization. Table 3 Indirect effect of CIRR on depression in Model 1. The path of effect
Point estimate
S.E.
Bootstrap 95% CI Lower Upper
p
Ratio
ind1 ind2 ind3 Total indirect effect
0.16 0.009 0.066 0.24
0.019 0.004 0.013 0.024
0.13 0.003 0.046 0.20
<0.001 <0.05 <0.001 <0.001
36.78% 2.11% 15.17% 54.06%
0.19 0.018 0.088 0.28
Note. CIRR = Cumulative interpersonal relationship risk; ind1: CIRRResilience-Depression; ind2: CIRR-Resilience-SBV-Depression; ind3: CIRR-SBVDepression; Ratio equals to indirect to total effect of CIRR on depression. Table 4 Indirect effect of CIRR on depression in Model 2. The path of effect
Point estimate
S.E.
Bootstrap 95% CI Lower Upper
p
Ratio
ind1 ind2 ind3 Total indirect effect
0.14 0.018 0.075 0.24
0.020 0.008 0.014 0.022
0.11 0.006 0.053 0.20
<0.001 <0.05 <0.001 <0.001
32.33% 4.16% 17.32% 53.81%
0.18 0.031 0.099 0.28
Note. CIRR = Cumulative interpersonal relationship risk; ind1: CIRRResilience-Depression; ind2: CIRR-SBV-Resilience-Depression; ind3: CIRR-SBVDepression; Ratio equals to indirect to total effect of CIRR on depression.
outcome variable of CIRR but also an important mediation variable between CIRR and depression. As a mediation variable, the role of SBV was weaker than that of resilience. The total mediation effect ratio of resilience to total effect of CIRR was 38.89% in Model 1 and 36.49% in Model 2. However, the total mediation effect ratio of SBV to total effect of CIRR was 17.28% in Model 1 and 21.48% in Model 2. 4. Discussion The main purpose of this study was to explore how cumulative interpersonal relationship risks (CIRR; classmate, parent-child, teacherstudent, and friend relationships risks) impact school bullying victimization (SBV) and depression, and why CIRR could affect SBV and depression from a positive psychological perspective. The results supported all three hypotheses. CIRR linearly and significantly predicts SBV and depression. CIRR could directly or indirectly decrease an individual's resilience, and therefore, increase an individual's SBV and level of depression. Our results help us construct CIRR linear models of SBV and depression and mediation models of resilience among CIRR, SBV, and depression. The results confirmed the cumulative risks model of depression
5. Conclusion The present research established cumulative interpersonal relationship risk (CIRR) linear models for school bullying victimization (SBV) and depression, and two mediation models of resilience in the relationships among CIRR, SBV, and depression. The current research extends knowledge from previous studies of SBV and depressive problems triggered by SBV by using a positive psychology perspective as opposed to a pathological perspective. 5
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However, this study has some limitations. First, causality cannot be inferred between variables, as this research is a cross-sectional study. In our study, a key point is the relationship between resilience and SBV, but we cannot confirm whether the relationship is one-way or two-way. If the relationship is two-way, there is another possible pathway: CIRR -> resilience -> SBV -> resilience -> depression. That is, CIRR decreases an individual's resilience and in turn, increases SBV. SBV further decreases resilience and leads to depression in the end. In the future, we can employ a longitudinal design to track the relationship between variables to better test the serial mediation model established in this study. Second, all data in this study were obtained from student selfreports. Future researches should nonetheless use multiple information sources to collect data to better investigate the model established in this study. Despite these limitations, the findings of this study have important implications for intervention programs for adolescents experiencing bullying victimization and depressive symptoms. On one hand, we must help adolescents develop warm, supported, friendly relationships with their parents, teachers and peers, which can directly decrease SBV and depression. For example, we can conduct trainings for improving social skills and self-confidence and start peer support programs. On the other hand, we can cultivate resilience in adolescents. For example, early prevention is pivotal and essential, such as establishing warm and safe attachment relationships between child and parents. In addition, education programs on how to deal with frustration effectively should be carried out for holistic personality development in adolescents. The results suggest two possible strategies to decrease SBV and depression that follows from multiple IRRs exposures. The strategies involve comprehensively intervening in four IRRs from a psychopathological perspective or cultivating resilience in adolescents from a positive psychological perspective.
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