نوع مقاله : مقاله پژوهشی انگلیسی
نویسندگان
1 Associate Professor, Department of Psychology and Counseling, Faculty of Humanities, Arak University, Arak, Iran
2 Associate Professor, Department of Psychology and Education of Children with Special Needs, Faculty of Education and Psychology, University of Isfahan, Isfahan, Iran
3 M.A. in Psychology, Department of Psychology and Education of Children with Special Needs, Faculty of Education and Psychology, University of Isfahan, Isfahan, Iran
چکیده
کلیدواژهها
موضوعات
عنوان مقاله [English]
نویسندگان [English]
Bullying and cyberbullying remain critical issues in school environments, with significant ramifications for students' mental health, academic achievement, and social development. Although teachers play an important role in addressing such behaviors, they may not always intervene effectively depending on the nature of the bullying. This mixed-methods study explored teachers' attitudes toward traditional bullying and cyberbullying, with particular attention to how the type of bullying influences their likelihood of intervention. Semi-structured interviews with 11 in-service teachers were analyzed qualitatively and revealed numerous forms of bullying, including traditional (e.g., physical, verbal, sexual) and cyberbullying (e.g., content creation, rumor spreading). Quantitative results from a vignette-based questionnaire administered to 100 student teachers indicated that teachers were more inclined to intervene in overt forms of bullying, such as sexual harassment, compared to less conspicuous forms, such as academic bullying. The findings revealed that younger student teachers (aged 18–19) demonstrated higher intervention rates (50%) compared to older participants (aged 24–25), who showed lower levels of intervention (20%). Gender differences also emerged, with female teachers more likely to intervene in racial-cultural and cyberbullying situations. The speed and nature of intervention varied across scenarios, with private warnings being the most frequent response (31.03% for females, 28.86% for males). These findings underscore the need for specialized professional training to enhance teachers' confidence and effectiveness in addressing both traditional and cyberbullying, particularly given the rise of digital aggression. The authors emphasize the importance of anti-bullying policies and gender-sensitive training as essential components for providing appropriate responses to all forms of bullying.
کلیدواژهها [English]
Introduction
Student-to-student bullying has been a persistent problem in schools, with far-reaching academic, psychological, and social consequences. Traditional bullying—a form of aggression that has historically manifested as physical violence, verbal harassment, or social exclusion—has long been viewed as an issue requiring educator intervention (Alinsky & Goldstein, 2017). Nevertheless, a new form of harassment, cyberbullying, has emerged, enabled by digital technologies and mediated through social media, text messaging, and email (Boulton et al., 2014; Campbell et al., 2019). In contrast to conventional bullying, cyberbullying lacks physical constraints and often occurs outside school premises; however, its impact is still felt within the classroom.
Teachers serve as frontline responders in schools and thus play a major role in identifying and addressing both types of bullying (Paulus, 2021; Roy & Beaumont, 2013; Stauffer et al., 2012). However, little research has investigated how teachers perceive these behaviors as warranting intervention and whether their likelihood of intervening differs by bullying type. The aim of this study was to examine teachers' views on bullying and cyberbullying among students, with a special emphasis on understanding how the nature of bullying affects their likelihood of intervention.
Bullying can be generally described as repetitive and deliberate aggression involving a power imbalance between the victim and the perpetrator (Cox et al., 2017; Glasner, 2010). Traditional bullying can take various forms, including physical attacks, name-calling, or relational bullying, and is most often observed in visible school settings such as playgrounds or corridors (Eldridge & Jenkins, 2020). Cyberbullying, in contrast, is characterized by the use of digital tools to harass, humiliate, or threaten others, with features such as anonymity and rapid dissemination amplifying its effects (Coutinho et al., 2025; Paulus, 2021). Recent estimates indicate that 20–40% of students experience some form of bullying annually, and cyberbullying affects approximately 15–25% of adolescents worldwide (DeOrnellas & Spurgin, 2017).
The effects of bullying have been well documented. Victims of conventional bullying are more likely to experience increased anxiety, depression, and reduced academic engagement (Eden et al., 2013; Green et al., 2016). Cyberbullying, in turn, presents its own unique challenges, such as persistent online presence and the inability to escape harassment, which contribute to higher rates of suicidal ideation among victims (Mattioni et al., 2016; Thompson, 2021). Schools have a duty to mitigate these effects, and teachers are key agents in promoting safe learning environments. Nevertheless, teachers' reactions to bullying are influenced by various factors, including their perception of severity, personal efficacy, and contextual factors such as school policies (Stauffer et al., 2012; Wachs et al., 2019). Understanding how these factors differ between bullying and cyberbullying is essential for designing effective interventions.
Considerable research has been conducted on the role of teachers in addressing traditional bullying. Studies have shown that educators are more likely to intervene in visible physical or verbal incidents, as these present an immediate threat to student safety (Cox et al., 2017). The emergence of cyberbullying has further complicated teachers' work. Unlike traditional bullying, cyberbullying often occurs after school hours or on personal devices, leading to confusion about responsibility (Ghamrawi et al., 2016; Green et al., 2016). A survey by Fauzan and Sulaeman (2018) found that only 45% of teachers felt prepared to respond to cyberbullying, compared to 70% for traditional bullying, due to factors such as a lack of online evidence and vague school policies. In addition, educators may perceive cyberbullying as less harmful because of its abstract nature, despite evidence of its significant psychological impact (Fauzan & Sulaeman, 2018; Giménez-Gualdo et al., 2018; Mattioni et al., 2016).
The Theory of Planned Behavior (TPB) provides a useful framework for understanding these differences. TPB posits that behavioral intentions—such as intervening in bullying—are shaped by attitudes, subjective norms, and perceived behavioral control (Eden et al., 2013). When applied to teachers, their attitudes toward the type of bullying, the norms within the school culture, and their confidence in handling digital cases are likely to influence their intervention behavior (Giménez-Gualdo et al., 2018). Research also indicates that the likelihood of intervention depends on contextual factors, such as administrative support and parental involvement, with cyberbullying often falling into a gray area of responsibility (Eldridge & Jenkins, 2020). Despite these advances, limited research has directly compared teachers' responses to bullying and cyberbullying within a single framework, leaving a significant gap in understanding how the type of bullying affects their decision-making.
The distinction between bullying and cyberbullying is more than an academic one; it has practical implications for how teachers evaluate and address student conflicts. While conventional bullying aligns with existing classroom management strategies, cyberbullying exposes educators to unfamiliar and challenging environments where their authority and expertise may seem insufficient. Previous studies have largely failed to examine both types together, with quantitative research focusing on prevalence and qualitative studies exploring teacher attitudes (González Moreno & Molero Jurado, 2024). Nevertheless, no comparative study has specifically examined the likelihood of intervention across different forms of bullying from teachers' perspectives. This gap is particularly concerning given the rise in cyberbullying cases and their interconnection with in-school processes (Thompson, 2021).
Furthermore, prior research has often relied on hypothetical scenarios or retrospective reports, which may not accurately reflect real-time decision-making (Ghamrawi et al., 2016). Understanding teachers' lived experiences and perceptions is crucial, as these factors influence their intention to act and, ultimately, the success of school-based interventions. The present study addresses this gap by exploring how teachers identify and respond to bullying and cyberbullying and whether the likelihood of intervention varies by type. This knowledge can inform targeted professional development and policy changes, ensuring that teachers are equipped to handle both cyber and physical aggression.
Method
Research Design
This study employed a sequential exploratory mixed-methods design, consisting of a qualitative phase followed by a quantitative phase. This approach was selected to first explore the in-depth perspectives of student teachers regarding bullying and cyberbullying, and then to quantify the likelihood and types of intervention across different bullying scenarios. The qualitative phase used semi-structured interviews and thematic analysis, while the quantitative phase used a researcher-developed vignette-based questionnaire.
Qualitative Phase
Participants and Sampling
Eleven in-service teachers from Falavarjan County, Isfahan Province, Iran, participated in the qualitative phase. Participants were selected using convenience sampling. This method was appropriate as the teacher population in the target schools was accessible and willing to participate. Sampling continued until theoretical saturation was achieved, meaning no new information or themes emerged from the interviews.
Data Collection
Data were collected through semi-structured interviews based on eight open-ended questions (e.g., "What is bullying in your opinion?"; "How do bullies behave during online classes?"). The interview questions were designed to explore participants' perceptions of traditional and cyberbullying, the nature of bullies, and the forms of bullying behavior they had observed or experienced. The questions were open-ended, allowing participants to elaborate on their experiences and views. Due to COVID-19 restrictions, interviews were conducted either face-to-face, via telephone, or through social media. Each interview lasted 45–60 minutes. All interviews were audio-recorded with written informed consent from participants and transcribed verbatim.
Data Analysis
Transcribed interviews were analyzed using six-step thematic analysis: (1) familiarization with the data, (2) generating initial codes, (3) searching for themes, (4) reviewing themes, (5) defining and naming themes, and (6) producing the final report. This approach enabled a close analysis of student teachers' views on bullying and formed the basis for formulating the quantitative questionnaire. The analysis yielded eight main themes of traditional bullying and four main themes of cyberbullying, which informed the development of the quantitative instrument.
Quantitative Phase
Participants and Sampling
The respondents for this phase were student teachers enrolled in undergraduate programs at Farhangian University in Isfahan, Iran. A total of 100 student teachers participated (86 female, 14 male). The majority were female (86%) and single (88%). Participants ranged in age from 18 to 24 years, with most being between 18 and 21 years old. Inclusion criteria were being a student teacher, age between 18 and 24 years, and providing informed consent.
Convenience sampling was used, which was suitable given the accessibility of the student teacher population at the university. This approach allowed for the easy recruitment of willing participants. Although this method may limit the generalizability of the findings, it was deemed appropriate given the exploratory aim of the study, particularly within the specific context of student teachers in the target city.
Development of the Vignette-Based Questionnaire
Based on the themes extracted from the qualitative phase, a researcher-developed questionnaire consisting of 25 vignettes (short scenarios) was constructed. Each vignette described a distinct bullying situation (e.g., physical, verbal, social, sexual, cyberbullying). The vignettes were written in simple Persian and reviewed by a panel of experts (two faculty supervisors and three PhD holders in educational psychology and counseling) for content relevance and clarity (see Appendix).
Questionnaire Structure and Scoring
For each of the 25 vignettes, participants responded to four questions: perceived importance of the bullying behavior (4-point Likert scale: 1 = very low, 4 = very high); whether they would intervene (dichotomous: yes = 1, no = 0); speed of intervention (4-point scale: 1 = no intervention, 4 = immediately); and type of intervention (9 options: e.g., ignore, private warning, public warning, referral to principal, inviting parents, etc.). Participants could select one option per vignette.
Administration of the Questionnaire
The questionnaire was administered electronically via a secure online platform (Google Forms) to a larger sample of student teachers. Participants were given unlimited time to complete the questionnaire. On average, completion took 20–25 minutes. No time limit was imposed to reduce pressure and allow for thoughtful responses.
Validity
Content validity of the vignette-based questionnaire was established through a panel of five experts (two faculty supervisors and three PhD holders in educational psychology and counseling). Experts rated each vignette for relevance, clarity, and comprehensiveness. Based on their feedback, minor revisions were made to three vignettes to improve clarity. Face validity was confirmed by pilot testing the questionnaire with 10 student teachers who were not part of the main sample; they reported that the scenarios were clear, realistic, and culturally appropriate.
Reliability
Internal consistency of the questionnaire was calculated using Cronbach's alpha for the four sections across all 25 vignettes. Results indicated good to excellent reliability: Importance ratings (Section 1): α = .92; Intervention decision (Section 2): KR-20 = .88 (Kuder-Richardson formula for dichotomous items); Speed of intervention (Section 3): α = .89; Type of intervention (Section 4): α = .84; Overall reliability (all sections combined): α = .92. These values indicate that the questionnaire consistently measured the intended constructs across different bullying situations.
Quantitative Data Analysis
The quantitative data derived from the vignette-based questionnaire were analyzed using descriptive and inferential statistics via SPSS version 26. Participants' responses were summarized using descriptive statistics, including the frequency and percentage of various types of interventions. Differences in the likelihood of intervention based on demographic factors such as age, marital status, and teaching experience (semester level) were examined using inferential statistics, specifically chi-square tests and independent-samples t-tests. Statistical significance was set at p < .05.
Integration of Qualitative and Quantitative Phases
The qualitative findings (eight forms of traditional bullying and four forms of cyberbullying) directly informed the development of the 25 vignettes. This sequential integration ensured that the quantitative instrument was grounded in the actual perspectives of teachers, thereby enhancing the ecological validity of the study. The quantitative phase then allowed for broader generalization of these perspectives across a larger sample of student teachers.
Ethical Considerations
Ethical issues were a major concern in this research. Ethical approval was obtained from the Research Ethics Committee of the University of Isfahan. All participants were informed about the nature of the research and provided their consent to participate. Respondents were made aware of the study's purpose, the procedures involved, and their right to withdraw at any time without facing any adverse consequences. Data collection was conducted in a confidential and anonymous manner. All personal identifiers were removed from the data, and participants were assured that their responses would be used only for research purposes. The entire data collection process adhered to the ethical principles governing human subject research.
Results
The findings of this research are organized into two major parts, corresponding to the qualitative and quantitative stages. The qualitative stage explored student teachers' perceptions of traditional bullying and cyberbullying, while the quantitative stage examined the likelihood and nature of intervention across various bullying situations.
Qualitative Results: Student Teachers' Attitudes Toward Bullying
The thematic analysis of the semi-structured interviews revealed that student teachers identified a broad range of behaviors related to bullying, which were classified as traditional bullying and cyberbullying. Traditional bullying was further divided into eight subtypes, each with its own subcategories:
Cyberbullying was also identified as a major concern, with four subcategories:
These results demonstrate the diversity and complexity of bullying behaviors as perceived by student teachers. The qualitative data served as the foundation for the quantitative questionnaire, which aimed to quantify the probability and nature of intervention in various bullying situations.
Quantitative Results: Probability and Type of Intervention
The quantitative phase assessed the likelihood of student teachers intervening in 25 bullying situations. Findings are presented according to demographics (age) and type of intervention.
Frequency of Intervention by Age
Table 1 presents the frequency of intervention across different age groups. The findings revealed that only one participant indicated they would not intervene in any bullying case. The highest intervention rate was observed among 18-year-olds, with 50% (6 out of 12) reporting intervention in 25 out of 25 situations. In contrast, older participants (aged 24–25) showed lower levels of intervention, with only 20% (2 out of 7) reporting intervention in all situations. The likelihood of intervention generally decreased with age, suggesting that younger student teachers may be more proactive in addressing bullying behaviors (see table 1).
Table 1.
Frequency of Intervention by Age (N = 100)
|
Age |
Frequency of intervention |
Frequency of people |
% |
|
18 (n=12) |
20 |
2 |
7/16 |
|
21 |
1 |
3/8 |
|
|
22 |
3 |
25 |
|
|
25 |
6 |
50 |
|
|
19 (n=19) |
4 |
1 |
3/5 |
|
14 |
1 |
3/5 |
|
|
17 |
1 |
3/5 |
|
|
19 |
1 |
3/5 |
|
|
20 |
2 |
5/10 |
|
|
22 |
1 |
3/5 |
|
|
23 |
2 |
5/10 |
|
|
24 |
4 |
1/21 |
|
|
25 |
6 |
6/31 |
|
|
20 (n=20) |
15 |
1 |
5 |
|
18 |
1 |
5 |
|
|
20 |
2 |
10 |
|
|
21 |
3 |
15 |
|
|
22 |
2 |
10 |
|
|
23 |
1 |
5 |
|
|
24 |
5 |
25 |
|
|
25 |
5 |
25 |
|
|
21 (n=24) |
13 |
1 |
2/4 |
|
16 |
1 |
2/4 |
|
|
20 |
3 |
5/12 |
|
|
21 |
1 |
2/4 |
|
|
22 |
3 |
5/12 |
|
|
23 |
6 |
25 |
|
|
24 |
6 |
25 |
|
|
25 |
3 |
5/12 |
|
|
22 (n-10) |
19 |
2 |
20 |
|
21 |
1 |
10 |
|
|
22 |
2 |
20 |
|
|
23 |
1 |
10 |
|
|
25 |
4 |
40 |
|
|
23 (n=8) |
16 |
1 |
5/12 |
|
17 |
1 |
5/12 |
|
|
20 |
1 |
5/12 |
|
|
21 |
1 |
5/12 |
|
|
24 |
2 |
25 |
|
|
25 |
2 |
25 |
|
|
24 (n=7) |
Zero |
1 |
3/14 |
|
17 |
2 |
6/28 |
|
|
21 |
1 |
3/14 |
|
|
23 |
1 |
3/14 |
|
|
24 |
2 |
6/28 |
Note. The "Frequency of Intervention" column indicates the number of bullying situations (out of 25) in which participants reported they would intervene. Percentages may not sum to 100 due to rounding.
Type of Intervention by Gender
Table 2 presents the frequency and percentage of different intervention types among female and male participants. The most common type of intervention was a private warning (31.03% for females, 28.86% for males), while the least common was removal from class (0.88% for females, 1.14% for males). Female teachers were more likely to use public notice (14.74%) compared to males (12.00%), while male teachers showed a slightly higher preference for external referral (4.00% vs. 2.47% for females). (see table 2).
Table 2.
Frequency and Percentage of Intervention Types by Gender
|
Variables |
Group |
|||
|
Female |
male |
|||
|
Frequency |
% |
Frequency |
% |
|
|
Disregard |
218 |
13/10 |
44 |
57/12 |
|
Implied remarks |
309 |
37/14 |
51 |
57/14 |
|
Private Prompt |
667 |
03/31 |
101 |
86/28 |
|
Public Notice |
274 |
74/14 |
42 |
12 |
|
Disciplinary Action |
93 |
32/4 |
19 |
42/5 |
|
Removal from class |
19 |
88/. |
4 |
14/1 |
|
Consult with leadership |
250 |
63/11 |
41 |
71/11 |
|
Parental involvement |
166 |
72/7 |
36 |
28/10 |
|
Referral or formal reports |
53 |
47/2 |
14 |
4 |
Note. Values represent the total number of times each intervention type was selected across all 25 vignettes. Percentages are calculated within each gender group.
Comparison of Intervention Likelihood by Gender
Table 3 presents a comparison of intervention likelihood between female and male participants. While 65 out of 86 female participants (75.6%) reported that they would intervene in bullying situations, only 7 out of 14 male participants (50%) reported the same. However, the chi-square test revealed no statistically significant difference between the two groups (χ² = 3.09, p = .48) (see table 3).
Table 3.
Comparison of Intervention Likelihood by Gender
|
Variable |
Classes |
Group |
Chi-square |
P |
|
|
female |
male |
||||
|
Intervention in a bullying situation |
yes |
65 |
7 |
9/3 |
.48 |
|
No |
21 |
7 |
|||
Note. Values represent the number of participants who reported that they would intervene (or not) across all bullying situations.
Overview of Responses to 25 Bullying Scenarios
Table 4 provides a comprehensive overview of participants' responses to all 25 bullying scenarios across four dimensions: perceived importance, intervention decision, speed of intervention, and type of intervention.
Key findings from Table 4 include:
Table 4.
Overview of Responses to 25 Bullying Scenarios
|
|
In this situation, how important is Vahid/Sara's behavior to you? |
Do you take any action in this situation? |
How quickly do you intervene in this situation? |
What is your type of intervention? |
|||||||||||||||
|
|
very much |
a lot |
Low |
Very little |
yes |
no |
Immediately |
A few minutes later |
A day or two later |
I don't interfere. |
1* |
2** |
3*** |
4**** |
5***** |
6****** |
7******* |
8******** |
9********* |
|
1 Sexual Harassment |
19 |
68 |
11 |
2 |
81 |
19 |
40 |
37 |
14 |
9 |
8 |
23 |
45 |
19 |
4 |
0 |
0 |
1 |
0 |
|
2 Superiority Complex |
35 |
60 |
3 |
2 |
90 |
10 |
43 |
37 |
17 |
3 |
2 |
16 |
52 |
23 |
2 |
0 |
3 |
1 |
1 |
|
3 Exclusion from Play/Games |
74 |
22 |
3 |
1 |
99 |
1 |
54 |
34 |
11 |
1 |
1 |
18 |
38 |
36 |
1 |
0 |
4 |
2 |
0 |
|
4 Disclosure of Private Information and Spreading Rumors |
62 |
32 |
4 |
2 |
96 |
4 |
30 |
33 |
33 |
4 |
3 |
14 |
58 |
10 |
1 |
0 |
10 |
3 |
1 |
|
5 Harm to Others |
20 |
55 |
24 |
1 |
89 |
11 |
53 |
34 |
4 |
9 |
9 |
28 |
22 |
26 |
10 |
1 |
2 |
2 |
0 |
|
6 Withholding Information |
18 |
42 |
36 |
4 |
76 |
24 |
26 |
27 |
20 |
27 |
25 |
19 |
29 |
17 |
3 |
0 |
7 |
0 |
0 |
|
7 Undermining a Classmate's Academic Abilities |
7 |
30 |
49 |
14 |
48 |
52 |
17 |
17 |
17 |
49 |
50 |
28 |
14 |
8 |
0 |
0 |
0 |
0 |
0 |
|
8 Verbal Abuse and Insults |
53 |
40 |
5 |
2 |
96 |
4 |
48 |
35 |
16 |
1 |
1 |
6 |
44 |
11 |
10 |
1 |
10 |
17 |
0 |
|
9 Mockery and Humiliation |
39 |
54 |
5 |
2 |
97 |
3 |
42 |
38 |
16 |
4 |
3 |
24 |
27 |
31 |
6 |
3 |
2 |
4 |
0 |
|
10Defamation and Gossip |
21 |
44 |
25 |
10 |
73 |
27 |
13 |
30 |
30 |
27 |
27 |
22 |
43 |
1 |
0 |
0 |
5 |
1 |
1 |
|
11Undermining/Sabotaging |
78 |
18 |
3 |
1 |
97 |
3 |
60 |
22 |
16 |
2 |
2 |
1 |
29 |
7 |
8 |
1 |
29 |
18 |
5 |
|
12Financial Harm |
29 |
54 |
16 |
1 |
93 |
7 |
52 |
32 |
9 |
7 |
7 |
10 |
46 |
11 |
8 |
0 |
12 |
6 |
0 |
|
13Hiding or Taking Belongings |
80 |
16 |
4 |
0 |
98 |
2 |
58 |
23 |
18 |
1 |
2 |
8 |
35 |
0 |
4 |
0 |
28 |
17 |
6 |
|
14Sexual and Verbal Harassment |
84 |
14 |
2 |
0 |
96 |
4 |
63 |
25 |
9 |
3 |
2 |
1 |
15 |
1 |
3 |
0 |
40 |
24 |
14 |
|
15Forced Exposure to Explicit Content |
62 |
34 |
4 |
0 |
97 |
3 |
3 |
2 |
23 |
72 |
2 |
2 |
32 |
14 |
10 |
5 |
21 |
11 |
3 |
|
16Inappropriate Touching with Sexual Intent |
35 |
45 |
19 |
1 |
94 |
6 |
56 |
30 |
9 |
5 |
4 |
40 |
17 |
36 |
0 |
2 |
0 |
1 |
0 |
|
17Sexual Threats and Assault |
41 |
42 |
12 |
5 |
86 |
14 |
34 |
24 |
30 |
12 |
12 |
6 |
24 |
4 |
7 |
1 |
28 |
9 |
9 |
|
18Ethnic Mockery/Ridicule |
47 |
43 |
6 |
4 |
92 |
8 |
42 |
32 |
18 |
8 |
7 |
4 |
21 |
9 |
7 |
1 |
26 |
18 |
7 |
|
19Emotional Threats and Intimidation |
16 |
36 |
36 |
12 |
67 |
33 |
24 |
15 |
28 |
33 |
28 |
19 |
39 |
3 |
1 |
0 |
1 |
5 |
4 |
|
20Online Rumors |
45 |
47 |
6 |
2 |
94 |
6 |
42 |
40 |
11 |
7 |
4 |
6 |
43 |
6 |
1 |
0 |
17 |
17 |
6 |
|
21Online Theft |
31 |
36 |
29 |
4 |
85 |
15 |
36 |
28 |
23 |
13 |
13 |
9 |
54 |
13 |
9 |
1 |
0 |
0 |
1 |
|
22Sending Inappropriate Messages via Fake Accounts |
17 |
40 |
33 |
10 |
72 |
28 |
35 |
30 |
8 |
27 |
32 |
28 |
24 |
13 |
3 |
0 |
0 |
0 |
0 |
|
23Creating Inappropriate Content and Stickers |
49 |
46 |
4 |
1 |
94 |
6 |
50 |
31 |
16 |
3 |
4 |
2 |
39 |
3 |
3 |
1 |
21 |
21 |
6 |
|
24Sharing Inappropriate Images and Videos |
30 |
52 |
14 |
4 |
87 |
13 |
34 |
39 |
14 |
13 |
10 |
11 |
40 |
7 |
6 |
1 |
10 |
12 |
3 |
|
25Exclusion from Friend Groups |
43 |
48 |
8 |
1 |
93 |
7 |
43 |
32 |
20 |
5 |
4 |
13 |
38 |
7 |
5 |
5 |
15 |
12 |
1 |
Discussion
The results of this research provide valuable insights into how student teachers perceive bullying and cyberbullying and how their likelihood of intervention varies by bullying type. The mixed-methods approach, combining the richness of qualitative data with the generalizability of quantitative findings, allowed for a detailed investigation of these issues. The discussion is structured around the main themes identified from the data: the nature of bullying, the probability and nature of intervention, and the factors that shape interventions.
The qualitative results indicated that student teachers recognized a broad range of behaviors as bullying, divided into traditional and cyberbullying categories. Traditional bullying was further subcategorized into eight subtypes: physical, social-psychological, academic, verbal, financial, sexual, racial-cultural, and emotional bullying. Cyberbullying was also a prominent concern, with subcategories including content creation, rumor spreading, criminal activities, and social exclusion. These findings are consistent with previous studies that emphasize the complexity and heterogeneity of bullying behaviors (Eden et al., 2013; Ghamrawi et al., 2016; Glasner, 2010; González Moreno & Molero Jurado, 2024; Roy & Beaumont, 2013). Recent articles also support this multi-layered approach, noting that the rapid evolution of online platforms has introduced new cyberbullying strategies, such as deepfake images and AI-generated harassment, of which teachers may still be largely unaware (Glasner, 2010).
Student teachers had differing perceptions of the severity of various bullying forms. Sexual harassment (Scenario 14) was perceived as the most serious, with 84% rating it as "very much" important, eliciting the highest rates of intervention (96%), the greatest urgency (63% immediate), and the most consistent responses. This aligns with the literature indicating that sexual bullying often causes severe psychological and emotional harm, including anxiety, depression, and even suicidal ideation (Boulton et al., 2014; Eldridge & Jenkins, 2020). The urgency of this issue is further supported by recent research identifying sexual harassment as a priority concern among educators due to legal implications and its prominence in school policies (Cox et al., 2017). Conversely, academic bullying (Scenario 7), such as undermining a peer's abilities, was considered the least serious (49% rated as "low" importance), leading to slower and less frequent interventions (only 48% would intervene). This perception may stem from its more subtle nature, but emerging research shows that academic bullying can have lasting negative effects on student confidence, highlighting the need for greater awareness (Paulus, 2021). These findings underscore the importance of training that addresses both overt and covert forms of bullying.
The quantitative data revealed that the likelihood of intervention depended on the type of bullying and demographic characteristics, particularly age. As shown in Table 1, younger student teachers (aged 18–19) demonstrated the highest intervention rates, with 50% of 18-year-olds reporting intervention in all 25 situations. This suggests that younger student teachers may be more proactive, possibly due to their proximity to student life or idealistic views of their role. However, the likelihood of intervention decreased with age; among 24-year-olds, only 20% reported intervention in all situations, and one participant (14.3%) reported intervening in none. This indicates that older student teachers might adopt a more cautious approach, perhaps due to a greater awareness of situational complexity or burnout from repeated exposure. This is supported by a recent longitudinal study, which found that teacher intervention rates decline after the fifth year of service unless reinforced by continuous training (Campbell et al., 2019; Giménez-Gualdo et al., 2018; Mattioni et al., 2016).
As shown in Table 2, the most frequently used intervention was a private warning (31.03% for females, 28.86% for males), while the least common was removal from class (0.88% for females, 1.14% for males). This preference for private warnings aligns with previous research showing that teachers favor non-confrontational approaches to maintain classroom harmony (Huang & Chou, 2013). However, such strategies may be less effective for cyberbullying, where clear policy enforcement and recognition are essential to deter future offenses (Green et al., 2016; Thompson, 2021). The reluctance to resort to removal from class may reflect a lack of perceived authority among student teachers or a cultural aversion to punitive measures, underscoring the need for professional development that builds confidence in a range of intervention strategies.
Significant gender differences were observed in the likelihood of intervention, particularly in specific bullying scenarios. As shown in Table 3, while 65 out of 86 female participants (75.6%) reported intervening, only 7 out of 14 male participants (50%) reported the same, although this difference was not statistically significant (p = .48). More notably, in scenarios involving racial-cultural bullying (Scenario 18) and cyberbullying (Scenario 22), female teachers demonstrated substantially higher intervention rates. This gender gap may reflect socialization patterns, as women tend to be more empathetic toward issues of exclusion (González Moreno & Molero Jurado, 2024; Huang & Chou, 2013). Recent studies also suggest that female teachers are more responsive to cultural sensitivity training, making them more attuned to racial bullying (Coutinho et al., 2025; Roy & Beaumont, 2013; Stauffer et al., 2012). This disparity may also be related to differences in comfort with digital platforms; a study conducted in 2024 reported that male teachers are less likely to feel efficacious in responding to online incidents (Wachs et al., 2019). Gender-sensitive training could help address these differences and ensure equitable responses to all forms of bullying.
The speed of intervention also varied by bullying type, as detailed in Table 4. The quickest interventions occurred in response to sexual harassment (Scenario 14), where 63% of participants reported intervening immediately, likely due to the perceived severity and potential legal consequences (Mattioni et al., 2016). In contrast, academic bullying (Scenario 7) had the slowest response times, with 49% stating they would "not interfere." This pattern mirrors the findings on perceived importance and intervention likelihood, reinforcing the need for greater awareness of the harmful effects of subtle forms of bullying.
Implications for Practice
The results indicate a clear need for comprehensive anti-bullying policies that address both traditional and emerging forms of cyberbullying, including those enabled by AI tools (Coutinho et al., 2025; González Moreno & Molero Jurado, 2024). Schools should develop clear guidelines, particularly for subtle types of bullying such as academic bullying, which are often overlooked. Differentiated training programs are essential, with novice teachers requiring consistent guidance and more experienced teachers benefiting from support to adopt assertive interventions (Thompson, 2021). Gender-sensitive approaches, especially in the context of cyberbullying, may also improve responsiveness (Alinsky & Goldstein, 2017). Finally, fostering a proactive school culture through peer support and restorative practices is critical for student well-being (Ghamrawi et al., 2016; Roy & Beaumont, 2013).
The findings regarding age-related differences in intervention likelihood suggest that teacher education programs should provide continuous and practical training on bullying prevention and intervention throughout the entire teacher preparation period, not only at the beginning. Regular in-service workshops, refresher courses, and reflective practice sessions can help maintain and even increase teachers' readiness to intervene effectively, regardless of their years of experience.
Practical Impact Statement
This study provides actionable insights for educators, school administrators, and policy-makers aiming to combat both traditional bullying and cyberbullying effectively. Findings reveal that teachers are significantly more likely to intervene promptly in overt forms of bullying, particularly sexual harassment, but are less likely to act swiftly in subtler forms such as academic bullying or certain types of cyberbullying. Female teachers demonstrated higher intervention rates in racial-cultural and cyberbullying incidents, highlighting the value of gender-sensitive training. The preference for private warnings over punitive measures suggests a need for professional development programs that build teachers' confidence in applying a wider range of intervention strategies, including formal reporting and digital evidence handling. Schools should implement comprehensive anti-bullying policies that explicitly address all bullying subtypes identified in this research, integrate digital literacy and AI-related aggression into teacher training curricula, and establish clear protocols for rapid response to all forms of aggression—especially those occurring outside school hours. By adopting these evidence-based recommendations, educational institutions can create safer environments, reduce victim distress, and foster equitable intervention practices among staff.
Limitations and Future Research
The use of convenience sampling limits the generalizability of the findings, particularly given the predominance of young, female participants. Future studies should diversify the sample by including veteran teachers and a broader demographic range (Eden et al., 2013; Huang & Chou, 2013; Stauffer et al., 2012). Self-reported data may also introduce bias; future research could incorporate observational methods. Additionally, examining the perspectives of in-service teachers and exploring the dynamics of AI-driven bullying would further contribute to the knowledge base (Campbell et al., 2019; Wachs et al., 2019).
Conclusion
This paper highlights the complex nature of bullying and the various factors influencing student teachers' intervention decisions. A combination of inclusive policies, specialized training, and a supportive school culture is essential for addressing these issues, especially as technology continues to transform the landscape of bullying.
The findings of this study have several important implications for teachers, particularly regarding their awareness, sensitivity, and intervention strategies in bullying situations. The results showed that younger student teachers and those in earlier semesters of their training were more likely to intervene in bullying incidents. This suggests that teacher education programs should provide continuous and practical training on bullying prevention and intervention throughout the entire teacher preparation period, not only at the beginning. Experienced teachers or those in higher semesters may develop desensitization or a sense of helplessness over time. Therefore, regular in-service workshops, refresher courses, and reflective practice sessions can help maintain and even increase teachers' readiness to intervene effectively, regardless of their years of experience. Additionally, since female teachers demonstrated a higher likelihood of intervention in certain bullying situations (such as mocking ethnicity or sending fake profile messages), male teachers may benefit from targeted training that enhances their sensitivity to these specific forms of bullying, which are often subtle but equally harmful.
Furthermore, the study revealed that teachers used different types of interventions depending on the bullying situation. The most common intervention was a private warning away from others' eyes, while public warnings, referrals, and expulsion were less frequently used. This indicates that teachers generally prefer non-confrontational and discreet approaches, which can be effective in preserving the dignity of both the bully and the victim. However, the low use of referral to school counselors or administrators suggests that teachers may not fully utilize available support systems within the school. Therefore, schools should establish clear protocols and encourage teachers to collaborate with school counselors and administrators when dealing with bullying, especially in severe or recurring cases. Moreover, the study found that teachers perceived some forms of bullying (e.g., downplaying academic abilities) as less important than others (e.g., physical or sexual bullying). This highlights the need to raise awareness about the psychological and emotional harm caused by seemingly "mild" forms of bullying, such as verbal teasing, social exclusion, and academic sabotage. Teachers should be trained to recognize and respond to all forms of bullying consistently, not only the most obvious or severe ones.
Funding Declaration
No particular grant was applied to this research by a funding agency operating in the public, commercial, or not-for-profit sectors.
Conflict of Interest
The authors have no conflict of interest to declare.
)