







































 

 

 

 

 

 

Patterns of Bullying Victimization among 

Adolescents in China: Based on a Latent 

Profile Analysis

Yumin Wei
1

, Jiashu Xie
1
, Zhuorong Zhu

2
 

 
1.  Hunan Normal University, Changsha, China 

2. Case Western Reserve University, Cleveland, OH, USA 

 

Abstract. This study was to explore potential patterns of bullying victim-

ization among adolescents in China. By cluster sampling, Delaware Bul-

lying Victimization Scale-Student (DBVS-S), Patient Health Question-

naire-9 (PHQ-9) and Generalized Anxiety Disorder Scale-7 (CAD-7) 

were administered to 3,761 school adolescents in Hunan Province. La-
tent profile analysis (LPA) was conducted on victimization by verbal, 

physical, social and cyberbullying. We found that (i) There is a high de-
gree of co-occurrence among four subtypes of bullying victimization. 

Four latent classes were identified, including an all-type (traditional and 

cyber) bullying victimization class (1.5%), a traditional victimization 
class (3.9%), a mild traditional victimization class (14.9%), and a non-

victimization class (79.6%). (ii) Males, middle school students, rural 
students and poor students were more likely to be all types of victims. 

(iii) There was a graded relationship between the four latent classes and 

the level of depression as well as anxiety. 
Best Evid Chin Edu 2019; 3(2):361-375. 

Doi: 10.15354/bece.19.ar1270. 

Keywords: Bullying Victimization; Co-Occurrence; Latent Profile Analysis; Ado-

lescent; Psychological Health

 
 

Correspondence to: Jiashu Xie, Cognition and Human Behavior Key Laboratory of Hunan Province, Hunan Nor-
mal University, Changsha 410081, China. Email: xjiashu@hunnu.edu.cn. 

About the Author: Yumin Wei, Cognition and Human Behavior Key Laboratory of Hunan Province, Hunan Nor-

mal University, Changsha 410081, China. Email: 504068520@qq.com. 

Zhuorong Zhu, Case Western Reserve University, Cleveland, OH 44106, USA; Email: 741853660@qq.com. 

Funding: Hunan Province Natural Science Foundation Project "Tracking the Relationship between Adolescent 

Bullying Victims and Depression: A Study Based on a Mixed Growth Model of Latent Variables" (2017JJ2184). 
Conflict of Interests: None. 



Wei, et al., Bullying Victimization among Adolescents in China. 

Vol.3, No. 2, 2019 362 

Introduction 

ULLYING victimization refers to the phenomenon that an individual is bullied 

or injured by one or several peers for a long time or repeated times (Olweus, 

1993), with the characteristics of power imbalance, deliberateness, repetitive-

ness, and harmfulness (Smith & Wilson, 1998), and is an essential risk factor affecting 

the physical and mental health of Children and adolescents (Gini & Pozzoli, 2009, 

Hawker & Boulton, 2000). Studies have shown that victims of bullying have higher 

risks in social and emotional problems, and are more prone to psychological introver-

sion problems such as depression and anxiety (Li et al., 2012; Menesini et al., 2009). 

Among the various types of people who are involved in the bullying, the proportions of 

victims of bullying are the highest. A survey of tens of thousands of elementary and 

middle school students in Norway found that about 15% of students were involved in 

bullying, of which about 9% were victims of bullying (Olweus, 1993). Zhang (2002) 

found that nearly one-fifth of elementary and middle school students in China were in-

volved in school bullying, and 14.9% of students were victims of bullying. A compara-

tive study of bullying in China and the US show that 22.05% of American students and 

21.77% of Chinese students have been bullied (Xie et al., 2016). 

For the victims, bullying is a serious life event. Compared with ordinary life 

events, repeated and persistent bullying produces a negative impact on individual’s 

body and mind more profoundly. Besides, there are many forms of bullying including 

verbal, relational, physical, and cyber-bullying (Crick & Grotpeter, 1995; Olweus, 1993; 

Björkqvist, 1994; Smith et al, 2008). Accumulating data have shown that there is a high 

degree of symbiosis between various forms of bullying (Raskauskas & Stoltz, 2007; Li, 

2007; Smith, Mahdavi et al, 2008; Nylund et al., 2007; Wang et al., 2010; Zhang et al., 

2014). Most victims often suffer from more than one form of bullying. Within the vic-

tims, the forms of bullying and their combinations are different, the severity of bullying 

is different, and the victims are heterogeneous. 

Previous studies on campus bullying include the demographic characteristics of 

victims, the impact of bullying on individual mental health, introversion and extrover-

sion, etc (Zhang et al., 2000; Schwartz et al., 2001; Zhang, 2002; Chen & Le, 2002; 

Chen et al., 2013; Wu et al., 2016). Regardless of the results, there was a problem that 

ignores the heterogeneity within the victims. Positive Psychology, especially Psycho-

logical Elasticity Research, showed that the difference in mental health among disad-

vantaged individuals was more noteworthy than the difference among different groups 

(Rutter, 2000; Wan & Tang, 2016; Zhang et al., 2016). Understanding the heterogeneity 

within the victims can help people differentiate the different nature of the victim sub-

groups. On this basis, the study of different models of sub-groups was carried out to 

provide more targeted programs for different sub-groups in the formulation of bullying 

prevention and intervention programs. We explored the model of bullying in school, 

which was based on the characteristics of the heterogeneity of bullying, and the demo-

graphic characteristics and mental health of various types of bullying. 

B 



Wei, et al., Bullying Victimization among Adolescents in China. 

Vol.3, No. 2, 2019 363 

Latent Class Analysis (LCA) has been being used widely in heterogeneous 

group classification in many fields such as sociology, biomedicine, and psychology. 

LCA is a technique based on the response of individual manifest variable to the tenden-

cy to divide individuals into a few mutually exclusive Latent Class variables (Qiu, 

2008). LCA classification can ensure the greatest difference among latent classes and 

the smallest difference within the class. At the same time, the latent characteristics of 

each class can be judged according to the response modes of each item in the scale, and 

the proportion of the population of each class in the whole group can be understood, 

and explore the heterogeneous classification mode within the group. 

Of the studies of latent class of bullying, a LCA of the incidence of physical 

bullying, verbal bullying, social exclusion, rumors, and cyberbullying in American 

teenagers divided the subjects into three classes: full-type victim groups (9.7% for men 

and 6.2% for women), Verbal/Social victim group (28.1% male, 35.1% female), and 

uninjured group (62.2% male, 58.7% female) (Wang et al., 2010). Zhang (2014) con-

ducted potential class analysis on the occurrence of physical bullying, verbal bullying 

and relational bullying among students of grades 4, 6 and 8, and divided the subjects 

into four classes: verbal-body bullying (10.8%), verbal-body-social bullying (10.6%), 

verbal-social bullying (5.8%) and victimless bullying (72.9%). Li (2015) analyzed the 

subjects in grades 7, 8, 10 and 11 of two schools and found three types of bullies: all 

types of bullying (10.3%), cyber/verbal/social bullying (47.5%) and non-bullying 

(42.2%). These study tools, involving the crowd, and concluded that the results were 

inconsistent; for the victims, the bullying measurement used in the study were scored 

higher, if use the LCA, the original score points to 0/1 class for subsequent analysis. 

Due to the lack of accuracy of discrete data (Zhang et al., 2010), data information will 

be lost when continuous data is converted into discrete data resulting in deviation of 

classification results. Therefore, this study will use the Latent Profile Analysis (LPA) to 

extend the method of latent variables, so as to explore the pattern of Chinese bullying 

victimization more accurately. 

Therefore, our study intends to study the co-occurrence characteristics of the 

detection of four common forms of bullying victimization, including cyberbullying, and 

then build an LPA model based on the data of the four forms of bullying victimization, 

to explore the different bullying victimization patterns and their main demographic 

characteristics of Chinese adolescents. Based on the consideration of the heterogeneity 

within the bullying-victimized group, the psychological introversion of different bully-

ing victimization patterns (depression, anxiety) and their differences were further dis-

cussed. 

Objects and Methods 

Objects 

The method of cluster sampling in eight areas of Hunan Province was used. A total of 

3,788 middle to high school students (age range of 11 to 20 years old, M = 15.03, SD = 

1.685) from 20 schools (including 13 city schools, 7 township and rural schools) were 



Wei, et al., Bullying Victimization among Adolescents in China. 

Vol.3, No. 2, 2019 364 

included. To remove the demographic variable information (such as gender), recycling 

effective questionnaire was 3,761, and the effective rate was 99.29%. Detailed sampling 

information is shown in Table 1. 

Research Tools 

Delaware Bullying Victimization Scale-Student (DBVS-S) 

DBVS-S (2016 Chinese Edition) was adopted. The scale has a total of 17 items, which 

are divided into four dimensions: verbal bullying (4 items), physical bullying (4 items), 

social/relational bullying (4 items) and cyber bullying (4 items). Item 13 “I was bullied 

in this school” is a screening item, which is not included in the data analysis (Bear et al., 

2016). The scale was introduced by Xie (2015). The Chinese edition of the latest revi-

sion was adopted in this study (Xie et al., 2018). The Cronbach’s α coefficient of 

DBVS-S was 0.906, and the fitting factor of the four-factor model confirmative factor 

analysis was good (CFI = 0.922, RMSEA = 0.043 [0.040-0.046]). The scale uses the 

Likert six-point score, “1” = “never”, “2” = “occasionally”, “3” = “one or two times a 

month”, “4” = “once a week”, “5” = “multiple times a week” and “6” = “every day.” 

The higher was the score, the more serious was the bullying. 

Patient Health Questionnaire Depression Scale -9 (PHQ-9) 

PHQ-9 was used to assess the frequency of depressive symptoms in the past two weeks. 

The scale has a total of 9 items, of which the 9th item “whether there is suicidal or self-

mutilation thought” is not a clinical intervention for this study, and suicide or self-

mutilation was detected. The investigator could not provide further evidence for sub-

jects who have a positive answer. Based on ethical considerations and referring to the 

practices of similar studies, we did not include it, and only the first 8 items were used in 

the test. The scale uses the Likert four-point score, “0” = “nothing at all”, “1” = “with a 

few days”, “2” = “more than half of the number of days”, “3” = “almost every day”. 

The higher the rate was, the more severe the depressive symptoms were. Cronbach’s α 

coefficient was 0.850 when PHQ-9 was revised (Hu et al., 2014). The Cronbach’s α 

coefficient of PHQ-9 in our sample data was 0.834, and the fitting factor of the one-

factor model confirmative factor analysis was good (CFI = 0.933, RMSEA = 0.074 

[0.068-0.080]). 

Generalized Anxiety Disorder Scale-7 (CAD-7) 

GAD-7 was used to understand the frequency of anxiety symptoms such as stress and 

anxiety in the past two weeks. The scale consists of 7 items in total, and the scale adopts 

Likert four-point score, “0” = “none”, “1” = “several days”, “2” = “more than half of 

the days”, and “3” = “almost every day”. The higher the score was, the more serious the 

anxiety symptoms were. Cronbach’s α coefficient was 0.93 when GAD-7 was revised 

(Qu & Sheng, 2015). The Cronbach’s α coefficient of GAD-7 in our sample data was 

0.884, and the fitting factor of the one-factor model confirmative factor analysis was 

good (CFI = .973, RMSEA = 0.063 [0.056-0.071]). 



Wei, et al., Bullying Victimization among Adolescents in China. 

Vol.3, No. 2, 2019 365 

Table 1. Participants Distribution Information. 

 
7th 
Grade 

8th 
Grade 

9th 
Grade 

10th 
Grade 

11th 
Grade 

12th 
Grade 

Total 

Male 197 244 234 462 310 376 1,823 

Female 224 233 254 459 414 354 1,938 

Total 421 477 488 921 724 730 3,761 

 

 

Procedure 

All data were collected by the paper questionnaire, and the class was taken as the unit 

for a group test. Before the test, we communicated fully with the sample school, ob-

tained support from the school and informed consent from the parents (or guardians) of 

all the sampled students. The experimenters were specially trained graduate students in 

psychology, and each class was equipped with 1-2 experimenters. The test time was 

during the school break or self-study class, and the time for the participants to complete 

the questionnaire was about 15 minutes. The head teacher is required to be present dur-

ing the test (only present without patrolling). The experimenter explained the instruc-

tions and sample questions to the participants in detail. Of the instructions, experiment-

er explained the meaning of the survey and emphasized that the test content was only 

used for scientific research. The questionnaire was collected and taken away by the ex-

perimenters on the spot and would not be reviewed by the school or teachers. The sam-

pling began in early December 2016 and lasted about one month. 

Statistical Analysis 

Mplus 7.4 was used for Latent Profile Analysis, and SPSS 22.0 was used for multiple 

logistic regression analysis and variance analysis of Latent Profile Analysis results. 

Results 

Incidence and Co-Occurrence Percentage of Different Types 

of Bullying 

During data processing, as long as the score of each item in DBVS-S was ≥ 3, that is, 

the participants selected “once or twice a month” or more were considered to have been 

bullied by the dimension represented by this item. Individuals subjected to verbal, phys-

ical, and social bullying of any kind or more were classed as traditional bullying victims. 

The incidences of four types of bullying victims were: verbal bullying, 31.53% 

(male 37.74%, female 25.70%); physical bullying: 20.55% (27.65% for males and 

13.88% for females); social bullying 19.60% (22.65% for males and 16.72% for fe-



Wei, et al., Bullying Victimization among Adolescents in China. 

Vol.3, No. 2, 2019 366 

males); cyberbullying, 4.3% (5.76% for males, 2.94% for females). Verbal bullying is 

the most common type of bullying among males, followed by physical bullying; verbal 

bullying is the most common type of bullying among females, and social bullying is the 

second most common type. The percentage of victims of each type by other types is 

shown in Table 2: when cyberbullying occurred, the probability of traditional bullying 

occurring at the same time was 87% (89.5% for males and 82.5% for females); when 

traditional bullying occurred, the probability of simultaneous cyberbullying was 9.8% 

(11.4% for males and 7.7% for females). 

From the perspective of the co-occurrence characteristics of the four types of 

bullying victims, the co-occurrence rate of verbal bullying was the highest. Victims of 

physical, relational and cyber bullying were usually victims of verbal bullying. The 

three types of traditional bullying victimization have high co-occurrence. The occur-

rence of cyberbullying among Chinese teenagers was often accompanied by traditional 

bullying. 

The Results of Latent Profile Analysis of Adolescent Bullying 

Victims 

To further explore patterns of bullying victimization among adolescents, we then con-

ducted LPA based on the occurrence degree (i.e. frequency) of each type of bullying. 

The fitting indexes of 2-5 classes were extracted and summarized in Table 3, and con-

ducted a model test. The Model adaptation test indexes mainly include: Information 

Evaluation Index AIC, BIC, sample size-adjusted BIC, aBIC, Entropy index, Likeli-

hood Ratio Test Index LMR-LRT and Likelihood Ratio Test Index Based on Bootstrap 

(BLRT). The smaller the three information evaluation indicators are, the better the 

model fits. Entropy ranges from 0 to 1, and Entropy closer to 1 indicates the more accu-

rate the classification. Entropy < 0.60 is equivalent to over 20% of individuals with a 

classification error, and Entropy = 0.8 indicates an accuracy of over 90%. The p-values 

of the two indexes of LMR-LRT and BLRT reach a significant level, indicating that the 

k classes’ models are significantly better than the k-1 classes of models (Qiu, 2008).  

The data showed that the conclusion of the various information indicators was 

not consistent. The Entropy values of the five models exceed 0.8, and the BIC is the 

smallest when the five classes are retained. However, the LMR-LRT values are not sig-

nificant when the 5th class are retained, indicating that the 5th class are not excellent. In 

the 4th class, the LMR-LRT and BLRT indicators of the 4th class are significant, and 

the average probability (column) of the 4th class of the adolescents (rows) comprehen-

sive consideration, the 4th class is selected as best model (Nylund et al., 2007). The 

estimated conditional mean and individual value distribution on the 4 latent class model 

on the 16 items of bullying (reordering by dimension after removing the 13th question 

of the original scale) is shown in Figure 1. 

From Figure 1, the mean conditions of the four latent classes on the 16 items 

of the four factors of bullying victimization are significantly different, showing differ-

ent characteristics. Among them, Class 1 (C1) has a high mean value in the four bully-

ing dimensions, accounting for 1.5% of the total subjects. According to its score charac- 



Wei, et al., Bullying Victimization among Adolescents in China. 

Vol.3, No. 2, 2019 367 

Figure 1. Estimated Conditional Means of Four Latent Class of Bully-
ing Victims. 

 

 

 

 

teristics, C1 is defined as “all-type (traditional and cyber) bullying victimization class”. 

In Class 2 (C2), the mean value of the conditions in the dimension of cyberbullying was 

significantly lower than C1. The score trend and mean value of the conditions in items 

1-12, namely the three dimensions of traditional bullying victimization, were similar to 

C1, which was defined as “a traditional victimization class”, accounting for 3.9% of all 

subjects. The score trend of class 3 (C3) in the three dimensions of traditional bullying 

victimization was similar to that of C2, but the mean value of the conditions was lower 

than C2. The mean value of the conditions in the dimension of cyber bullying was con-

sistent with C2. Therefore, C3 was named as “a mild traditional victimization class”, 

accounting for 14.9% of all subjects. Class 4 (C4) was named “non-victimization class”, 

accounting for 79.6% of all subjects. 

Multivariate Logistic Regression Results of Demographic 

Variables for Four Latent Classes 

This research further explored the demographic characteristics of bullying victimization 

patterns based on the results of LPA. LPA results as dependent variables, gender (fe-

male as a reference), grade (high school as a reference), school type (city as a reference), 

boarding situation (day reading as a reference), and self-evaluation academic record 



Wei, et al., Bullying Victimization among Adolescents in China. 

Vol.3, No. 2, 2019 368 

Table 2. The Prevalence of All Four Types of Bullying.a 

 

Traditional Types Of Bullying Victims 
Cyber-
bullying 
(%) 

Verbal 
bullying 
(%) 

Physical 
bullying 
(%) 

Social 
Bullying 
(%) 

Traditional 
Bullying (%)

b
 

Total (n=3,761) 

Traditional Bullying (n=1,436) 9.8 

Verbal bullying 
(n=1,186) 

- 53.7
c
 50.1

c
  10.6

c
 

Physical bullying 
(n=773) 

80.9 - 62.0  15.5 

Social bullying 
(n=737) 

80.6 65.0 -  16.8 

Cyberbullying 
(n=162) 

77.8 74.1 76.5 87.0 - 

Male (n=1,823) 

Traditional bully-
ing (n=825)  

    11.4 

Verbal bullying 
(n=688) 

- 59.0 50.6  12.1 

Physical bullying 
(n=504) 

80.6 - 61.9  16.5 

Social bullying 
(n=413) 

84.3 75.5 -  20.1 

Cyberbullying 
(n=105) 

79.0 79.0 79.0 89.5 - 

Female (n=1,938) 

Traditional bully-
ing (n=611) 

    7.7 

Verbal bullying 
(n=498) 

- 44.08 49.4  8.6 

Physical bullying 
(n=269) 

81.4 - 62.1  13.8 

Social bullying 
(n=324) 

75.9 51.5 -  12.7 

Cyberbullying 
(n=57) 

75.4 64.9 71.9 82.5 - 

a. The percentage of each type of victim who was bullied by the other type. 

b. If an individual is bullied by one or more types of verbal bullying, physical bullying or social exclusion, 
it is considered as the traditional bullying victimization type. 

c. For example, among the 1,186 victims of verbal bullying, 53.7%, 50.1%, and 10.6% are also victims of 
physical bullying, social exclusion, and cyberbullying. 

 

 

 

(successful results as a reference) as self variables were subjected to multiple logistic 

regression analysis. Among them, the non-victimization class (C4) was used as the ref-

erence category for comparison, and the Odd Ratio coefficient was obtained through 

analysis. The OR coefficient reflected the ratios of different genders, grades, urban and 

rural locations, boarding situations, and self-assessment academic performance in the 



Wei, et al., Bullying Victimization among Adolescents in China. 

Vol.3, No. 2, 2019 369 

Table 3. Summary of Latent Profile Analysis Fit Information. 

Index Model Number 

Total (n=3761) 2 3 4 5 

AIC 134,874.143 127,284.693 123,542.594 118,438.308 

BIC 135,179.532 127,696.034 124,059.887 119,061.552 

aBIC 135,023.834 127,486.318 123,796.153 118,743.799 

Entropy 0.991 0.988 0.962 0.994 

LMR-LRT (p) < 0.001 0.1096 0.0261 0.6154 

BLRT (p) < 0.001 < 0.001 < 0.001 < 0.001 

 

 

 

Table 4. Multivariate Logistic Regression Results of Demographic Var-
iables for Four Latent Classes. 

  
All-type(traditional 
and cyber) bullying 
victimization (C1) 

A traditional vic-
timization (C2) 

A mild traditional 
victimization (C3) 

  
OR 

CI 
(95%) OR 

CI 
(95%) OR 

CI 
(95%) 

Gender Female 1.000  1.000  1.000  

Male 4.241
**
 

2.303-
7.809 

1.794
**
 

1.275-
2.523 

2.338
**
 

1.925-
2.838 

Grade 12th 
Grade 

1.000  1.000  1.000  

7th 
Grade 

9.471
**
 

3.741-
23.977 

15.029
**
 

6.636-
34.038 

3.803
**
 

2.703-
5.349 

8th 
Grade 

3.609
*
 

1.296-
10.050 

11.070
**
 

4.876-
25.131 

3.372
**
 

2.425-
4.689 

9th 
Grade 

1.991 
0.636-
6.237 

8.402
**
 

3.658-
19.295 

2.635
**
 

1.883-
3.688 

10th 
Grade 

1.237 
0.437-
3.500 

2.096 
0.870-
5.052 

1.084 
0.781-
1.504 

11th 
Grade 

1.338 
0.446-
4.015 

2.147 
0.860-
5.361 

1.067 
0.751-
1.517 

School 
Location 

Urban 1.000  1.000  1.000  

Rural 5.238
**
 

3.062-
8.961 

4.513
**
 

3.216-
6.331 

2.824
**
 

2.340-
3.409 

Boarding 
Situation 

Day- 
student 

1.000  1.000  1.000  

Boarder 1.342 
0.745-
2.149 

1.427 
0.982-
2.074 

1.037 
0.854-
1.258 

Academic 
Record 
(Self-
Assessed) 

Poor 1.000  1.000  1.000  

Medium 0.613 
0.337-
1.116 

0.563
*
 

0.381-
0.831 

0.775
*
 

0.617-
0.973 

Excellent 0.400
*
 

0.172-
0.935 

0.534
**
 

0.326-
0.876 

0.751
*
 

0.570-
0.990 

Note. *P<.05, **P<.01. 



Wei, et al., Bullying Victimization among Adolescents in China. 

Vol.3, No. 2, 2019 370 

potential categories of bullying victims. The results of multinomial logistic regression 

are shown in Table 4. 

Taking the C4 as the reference group, C1, C2, and C3 were compared with it. 

The OR results showed that the distribution of victims of bullying was affected by gen-

der, grade, school location, and student performance, the effect of boarding was not 

significant. 

Compared with females, males in the groups C1, C2 and C3 were suffered 

more bullying and victimization. Compared with the senior 3 students, in the C1, the 

bullying of the junior 1 and junior 2 students was more serious. The bullying injury 

among the junior 3, senior 1, and senior 2 students was not significant from that of the 

senior 3 students. In the C2 and C3, there are more bullying victims in the three grades 

of middle school, and the phenomenon of bullying in senior 1 and senior 2 students is 

not significant from that of senior 3 students. Compared with urban students, among the 

three classes of C1, C2 and C3, there are more bullying injuries among rural students. 

There was not significance in the victimization of boarding and day students. Compared 

with students with lower graders, there was not significance in bullying among students 

with poor grades and middle grades in the C1 class. Students with higher grades were 

less likely to suffer from bullying than those with lower grades. Among the C2 and C3, 

students with middle grades and excellent grades were less likely to suffer from bully-

ing than those with poorer grades. 

Comparison of Depression and Anxiety Symptoms among La-

tent Classes of Juvenile Bullying 

The results of the analysis of variance are shown in Table 5. The depression scores of 

adolescents in different categories of bullying victims (F(3,3757)=104.136, p < 0.01, η
2
 

= 0.077) and anxiety scores (F(3,3757)=121.953, p < 0.01, η
2
 = 0.089) was significant. 

The multiple comparison results show: The depression and anxiety scores in C1 were 

significantly higher than those in the other three groups. The depression and anxiety 

scores in C2 were lower than those in C1, which was significantly higher than that in 

C3 and C4. The depression and anxiety scores in C3 were significantly higher than 

those in group C4. 

Discussion 

The Co-Occurrence Characteristics and Heterogeneity of Ju-

venile School Bullying Model 

We explored the patterns of four common forms of bullying using latent profile analysis. 

There were four modes of bullying victimization in the tested adolescents: all-type (tra-

ditional and cyber) bullying victimization class, a traditional victimization class, a mild 

traditional victimization class, a non-victimization class. There were significant differ-

ences in the scores and trends of bullying victims in each group indicating the heteroge-

neity of bullying victims. There are three bullying victimization classes (C1, C2, and C3) 



Wei, et al., Bullying Victimization among Adolescents in China. 

Vol.3, No. 2, 2019 371 

Table 5. Comparison of Depression and Anxiety Symptoms among La-
tent Classes. 

 
C1 
(n=58) 

C2 
(n=147) 

C3 
(n=544) 

C4 
(n=3,012) 

F η
2
 

Depression 11.90±6.072 10.60±5.004 8.80±4.427 6.60±4.037 104.136
**
 0.077 

Anxiety 10.43±4.946 9.18±4.881 7.54±4.390 5.09±3.949 121.953
**
 0.089 

Note: Data are depicted as Mean ± SD. 

 

 

 

in the four modes, accounting for a total of 20.4%, among which the mild traditional 

victimization class has the largest number of people and the all-type bullying victimiza-

tion class has the smallest number. This indicates that bullying and victimization phe-

nomenon is prevalent in Chinese schools at present, and the distribution of all classes is 

pyramid-like, and the more severe the bullying, the less the number of people suffering 

from bullying. 

Among the three classes of bullying victims, the C1 and C2 were subjected to 

more serious traditional bullying, and the C3 group was subjected to mild traditional 

bullying. It can be seen that three forms of traditional bullying usually occur together. 

In terms of conditional means, verbal bullying is the most common form of bullying, 

which is consistent with the co-occurrence rate of the various forms of bullying in Ta-

ble 2. In addition, compared with the C2 and C3, only all types of bullying victims have 

more serious cyberbullying, which indicates that the cyberbullying of teenagers is more 

serious, and the victims may also suffer or encounter other traditional types of bullying. 

Victims of cyberbullying are often victims of traditional bullying, which is consistent 

with previous studies (Raskauskas & Stoltz, 2007; Li, 2007; Smith et al., 2008). The 

results also support the hypothesis that cyberbullying is an extension of campus bully-

ing (Zhang et al., 2015; Zhu et al., 2014). 

Demographic Characteristics and Analysis of Their Depres-

sion and Anxiety Indicators of Different Types Bullying Vic-

tims  

The analysis of demographic characteristics of victims of different types of bullying 

showed that there are differences in demographic variables such as gender, grade level, 

school location, and academic achievements. Compared with females, in all three types 

of bullying mode, males are more likely to be bullied, and the gender differences in bul-

lying patterns are consistent with previous studies (Rivers & Smith, 1994; Zhang et al., 

2000; Chen & Le, 2002; Chen et al., 2013). This suggests that more attention should be 

paid to the bullying of males. Of the grade level, the overall bullying is declining with 

the growth of grades. The bullying in middle school students is significantly more than 

that of high school students, but it has slightly different in different types. In the C1, 

bullying and victimization in the first and second grade were much higher than in other 



Wei, et al., Bullying Victimization among Adolescents in China. 

Vol.3, No. 2, 2019 372 

grades. In the C2 and C3, the three middle school grades are higher than the high school 

grades, and the severe bullying and victimization mainly occur in the middle and lower 

middle grades in middle school. A comparison of urban and rural schools showed that 

students whose schools are located in rural areas have a higher proportion of bullying 

than those whose schools are located in urban areas, which supported the previous find-

ings (Wu et al., 2016). In practice, national and local governments should strengthen the 

prevention and control of bullying in rural schools. Previous studies regarding the im-

pact of boarding on bullying suggested that the management system of rural boarding 

schools was not perfect and rural boarding students may lead to more bullying than ur-

ban boarding students (Wu & Hou, 2017; Wu et al., 2016). In this study, the compari-

son between day students and boarders showed that boarding students were more likely 

to suffer from bullying than day students, but there was no significant difference with 

the type of bullying. It may be due to the interaction between school location and board-

ing. The differences between rural and urban school boarding and the underlying mech-

anisms need further studies. Students with different self-assessment performance have 

different proportions in each bullying mode. In general, students with poor self -

assessment scores are more likely to be bullied, which is consistent with previous report 

(Schwartz et al., 2001). Compared with students with poor and middle-level self-

assessment scores, students with excellent self-assessment scores in C1 are less likely 

bullied, and students with middle and excellent self-assessment scores in C2 and C3 

group are less likely bullied than those with poor self-assessment scores. Taken together, 

the self-assessed high academic performance in Chinese adolescent students seems to 

be an advantageous factor in protecting themselves from being bullied. 

The results of the depression and anxiety scores of different types of victims 

showed that there were significant differences in the scores of depression and anxiety, 

and the higher the frequency of bullying suffered, the higher the level of depression and 

anxiety would be. It is worth emphasizing that the scores of a mild traditional victimiza-

tion class and the questionnaire on the two scales of depression and anxiety are signifi-

cantly higher than the non-victimization class, which means that as long as the students 

have the experience or feeling of being bullied, even if the frequency of bullying is not 

high, but it will produce a more serious negative impact on individual’s mental health. 

The results of the depression and anxiety scores of the victims of each model support 

the “zero tolerance” of bullying on campus (Zhao & Wang, 2018). 

Education and Intervention Enlightenment 

In 2017, China issued the Guidance on Preventing and Controlling Bullying and Vio-

lence among Primary and Middle School Students, which shows the importance of con-

trolling school bullying at the national level (Yao, 2017). Among the people who are 

involved in the bullying on campus, the proportion of bullying victims was the highest 

(Hu, 2017), and it has important practical significance. From our study, when students 

were noticed to have been suffering from a certain type of bullying, they should be paid 

more attention to the situation, i.e. whether they have suffered from multiple types of 

bullying at the same time, especially cyber bullying. Our findings indicated that the de-



Wei, et al., Bullying Victimization among Adolescents in China. 

Vol.3, No. 2, 2019 373 

gree of bullying was relatively more serious than the imagination. The exploration of 

bullying patterns of victims aimed to understand the qualitative differences within the 

bullied group. We found that even mild bullying can produce serious negative impact 

on students’ depression and anxiety. Therefore, in daily study life, teachers and parents 

should pay attention to the signs of bullying and victimization, and should not ignore 

the stigmatization, malicious mocking and other minor encroachment behaviors in the 

communication with students, so as to find and stop bullying and victimization in time, 

and to prevent further deterioration of the situation. In addition, the study also suggests 

that male, junior in high school, middle school, lower grade, rural schools, poor self-

rated academic performance are the demographic characteristics of the high incidence 

of bullying victimization. 

Conclusions 

In this study, the potential profile analysis was used to explore the bullying victimiza-

tion patterns of adolescents at school, and the demographic characteristics and psycho-

logical introversion problems (depression and anxiety) were analyzed, and we draw 

conclusions below: 

 Among the victims of school bullying, the four common types of bullying, 

namely verbal, physical, relational and cyber bullying, are co-occurring, and 

there are four typical patterns of school bullying victimization: all-type (tradi-

tional and cyber) bullying victimization class (1.5%), a traditional victimization 

class (3.9%), a mild traditional victimization class (14.9%), a non-victimization 

class (79.6%). 

 Verbal bullying is the most common form of bullying, and most victims of 

cyber bullying are also victims of traditional bullying. Different demographic 

characteristics (gender, grade, school location, self-assessed academic perfor-

mance) will affect the bullying mode of victimization. Male, middle school, ru-

ral school, and low self-evaluated students are more vulnerable to bullying. 

 Even mild bullying involvement can produce a serious negative impact on an 

individual’s mental health, and this is the solid evidence for a “zero tolerance” 

to bullying. 

 

 

 

 

 

 

 

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Received: 13 August 2019 

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The Chinese version of this article has been published in Psychol Develop Edu 2019; 35(1): 95-

102. The English version has been authorized for being publication in BECE by the author(s) and 

the Chinese journal. 

谢家树, 魏宇民, Zhuorong Zhu. 当代中国青少年校园欺凌受害模式探索: 基于潜在剖面分析. 

心理发展与教育, 2019; 35(1): 95-102. 

 


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