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. 2025 Mar 14;25:1000. doi: 10.1186/s12889-025-22201-9

The relationship between early adolescent bullying victimization and suicidal ideation: the longitudinal mediating role of self-efficacy

Ziyi Chen 1, Jianhua Zhang 2,✉, Tiancheng Zhang 1, Fulan Zhang 1, Yang Liu 1,✉, Yuanyuan Ma 1, Yiyi Chen 1, Zeng Zhou 1,3
PMCID: PMC11907941  PMID: 40082915

Abstract

Objective

This study aims to investigate the longitudinal interplay between early adolescent bullying victimization and suicidal ideation, and to analyze the mediating role of self-efficacy in their dynamic relationship.

Methods

A cluster sampling method was employed to select 1,023 seventh-grade students from a middle school in an urban district of Hunan Province between March and December 2023. Three waves of data collection were conducted using questionnaires that included scales for adolescent bullying victimization, suicidal ideation (PANSI), and general self-efficacy (GSES). The cross-lagged panel model (CLPM) was utilized to explore the reciprocal relationships between early bullying victimization, suicidal ideation, and self-efficacy.

Results

Early adolescent bullying victimization was found to both directly and indirectly predict suicidal ideation through its impact on self-efficacy. Conversely, suicidal ideation did not directly predict the level of bullying victimization but was able to indirectly predict it through its effect on self-efficacy.

Conclusion

The bullying victimization in early adolescents can directly predict the level of suicidal ideation and can also indirectly influence suicidal ideation by affecting self-efficacy; Suicidal ideation does not directly predict the level of bullying victimization; rather, it can indirectly predict bullying victimization through its impact on self-efficacy.

Keywords: Adolescents, Bullying victimization, Suicidal ideation, Self-Efficacy, Cross-Lagged panel model

Introduction

Suicide continues to be a significant global public health challenge [1]. Among related behaviors, suicidal ideation is often regarded as a precursor to suicide, reflecting an individual’s clear desire to end their life without having acted on it [2, 3]. Recent reports indicate that the prevalence of suicidal thoughts among adolescents worldwide ranges from 8.3 to 31.3%, underscoring a concerning trend [4–6]. Research suggests that early adolescence is a critical period for the development of suicidal ideation, as individuals often encounter increased academic pressure and changes in their social environment [7, 8]. Adolescents experiencing suicidal thoughts may suffer from negative emotions such as depression, anxiety, and despair, which can lead to self-harm or suicide [9, 10]. This situation can have a profound psychological impact on their families and communities, resulting in adverse social consequences [11, 12]. Given the widespread and harmful nature of suicidal ideation among adolescents, research on early suicidal thoughts in this population is essential.

Beyond its impact on adolescents’ mental and physical health, increasing research attention has been given to the mechanisms underlying the development of suicidal ideation [13]. Frequent reports of youth bullying incidents in online and social media have drawn significant academic attention [14]. Bullying victimization, as a crucial factor influencing suicidal ideation, refers to the phenomenon where individuals experience prolonged or repeated harm from others, characterized by its repetitive, intentional nature and power imbalance [15, 16]. Studies indicate that bullying victimization is widespread during adolescence, severely harming the mental and physical development of youth [58–60]. Prolonged experiences of bullying can deepen levels of suicidal ideation, consequently affecting overall quality of life [17, 18]. Although previous scholars have conducted valuable explorations into the relationship between suicidal ideation and bullying victimization, research examining the early suicidal ideation of adolescents from a longitudinal perspective remains scarce. There is ongoing debate regarding whether the relationship between early bullying victimization and suicidal ideation is mutually predictive or unidirectional [19].

Self-efficacy refers to an individual’s belief in their capacity to navigate specific situations and achieve desired outcomes [20]. As a crucial positive psychological asset in early adolescence, it is widely recognized for its role in promoting healthy behaviors and intervening in problematic behaviors [21, 22]. Recent studies have extensively examined the detrimental effects of low self-efficacy on early health-compromising behaviors among adolescents. On the one hand, low self-efficacy may exacerbate emotional distress, intensifying negative emotions such as depression, hopelessness, and suicidal ideation [23, 24]. On the other hand, low self-efficacy is also viewed as a vulnerability factor for bullying victimization, affecting adolescents’ social adaptability. This may lead individuals to adopt avoidant attitudes towards interpersonal interactions, resulting in marginalization and increased susceptibility to bullying [25, 26]. Notably, there remains a lack of research on the mechanisms underlying the relationship between self-efficacy, bullying victimization, and suicidal ideation, particularly regarding their dynamic characteristics, which require further investigation.

In summary, this study proposes the following hypotheses:

Hypothesis

a: Bullying victimization in early adolescence predicts suicidal ideation.

Hypothesis

b: Suicidal ideation in early adolescence inversely predicts bullying victimization.

Hypothesis

a: Bullying victimization in early adolescence predicts suicidal ideation through self-efficacy.

Hypothesis

b: Suicidal ideation in early adolescence inversely predicts bullying victimization through self-efficacy.

Previous studies have predominantly employed cross-sectional designs, failing to adequately reveal the complex relationships among suicidal ideation, bullying victimization, and self-efficacy. Mediation analysis using longitudinal data can address the limitations of cross-sectional studies, providing more reliable evidence for clarifying the interactions and mediating mechanisms among these variables [27, 28]. Therefore, this study aims to construct a Cross-Lagged Panel Model (CLPM) and utilize a three-wave longitudinal survey to investigate the interplay between early suicidal ideation and bullying victimization, analyzing the mediating role of self-efficacy. This research seeks to provide evidence-based insights for the mental and physical health development of adolescents.

Materials and methods

Participants

This study focuses on seventh-grade students from five public middle schools in a district of Hunan Province, China, who have no cognitive impairments and can independently complete questionnaires. Using a random cluster sampling method, we selected five classes from each school, resulting in a total of 1,276 seventh-grade students as the tracking sample. Assessments were conducted in September 2023, March 2024, and September 2024. After excluding invalid questionnaires with missing values or inconsistent responses, 1,023 completed questionnaires with consistent coding across all three assessments were retained as the final valid research sample.

This study was approved by the Biomedical Ethics Committee of Jishou University (Approval No. JSDX-2023-0034), and data from the follow-up investigation will be used solely for academic analysis and research purposes. Prior to data collection, the research team contacted the administrative departments of the participating schools to introduce the study’s objectives, methods, and ethical considerations, obtaining written approval from the relevant authorities. In accordance with ethical guidelines for research involving minors, the research team informed all participating students and their parents about the study’s purpose, procedures, and confidentiality measures.Assent was obtained from all student participants, and informed consent was provided by their parents.

Procedures

The investigators in this study were graduate students from the School of Sports Science at Jishou University, demonstrating strong professional competence and a rigorous work ethic. Before data collection, all investigators received standardized training covering key terminology, questionnaire content, and relevant academic concepts. The assessments were conducted anonymously in classrooms, with questionnaires distributed and collected on-site. Informed consent was obtained from both class teachers and participants before data collection. At the beginning of the assessments, investigators explained the study’s purpose and provided standardized instructions to ensure participants fully understood the questionnaire requirements. Participants were informed that their data would be used exclusively for scientific research and that their personal information would remain confidential. They were encouraged to respond honestly and ask for clarification if needed. Investigators answered these inquiries following the original scale guidelines to ensure accurate completion.

Instruments

Basic information

In this study, participants’ basic demographic information was collected through a questionnaire, including gender, left-behind status and only-child status.

Left-behind status was categorized into left-behind adolescents and non-left-behind adolescents.Left-Behind adolescents were defined as those who, in the past six months, had been left in rural areas under the care of other relatives or guardians due to parental labor migration. In contrast, Non-Left-Behind adolescents were those who had lived with both parents during the past six months and had not been separated due to parental migration [29, 30]. Regarding only-child status, an Only-Child was defined as the sole child in a family, with parents having neither biological nor adopted siblings. Conversely, a Non-Only-Child referred to an individual who had at least one biological or adopted sibling within the family structure [31, 32].

Bullying victimization

The study utilized a bullying victimization scale from Ji Chengye’s “Comprehensive Survey Report on Health-Related/Risk Behaviors among Chinese Adolescents” [33]. This scale consists of seven items (e.g., “Have you been maliciously teased?“), employing a 4-point Likert scoring system, ranging from 1 = “Never” to 4 = “Always.” It encompasses four dimensions: physical bullying, verbal bullying, relational bullying, and sexual harassment. A higher total score indicates a greater severity of bullying experienced by the individual. In this study, the Cronbach’s alpha coefficients for this scale were 0.91, 0.89, and 0.92 across three assessments.

Self-Efficacy

The study employed the Chinese version of the General Self-Efficacy Scale (GSES), developed by Schwarzer et al. and translated and revised by Wang Caikang et al. [34, 35], to assess early self-efficacy in adolescents. The scale consists of 10 items (e.g., “If I try my best, I can always solve problems.“), employing a 4-point Likert scoring system, ranging from 1 = “Not at all true” to 4 = “Exactly true.” A higher total score indicates greater self-efficacy. In this research, the Cronbach’s alpha coefficients for the scale were 0.86, 0.87, and 0.85 across three assessments.

Suicidal ideation

The study utilized the Positive and Negative Suicide Ideation Scale (PANSI), developed by Osman et al. and translated by Wang Xuezhi et al. [36, 37], to assess early suicidal ideation in adolescents. This scale contains 14 items (e.g., “Feeling hopeless about the future and having thoughts of suicide.”), employing a 5-point Likert scoring system ranging from 1 = “Never” to 5 = “Often.” Participants rated each item based on their experiences over the past two weeks, which encompass two dimensions: positive suicidal ideation (6 items) and negative suicidal ideation (8 items). Positive suicidal ideation scores are reverse-coded, and the total score is calculated by summing the item scores, with higher scores indicating greater suicidal ideation. In this study, the Cronbach’s alpha coefficients for the scale across three assessments were 0.88, 0.90, and 0.89.

Data analysis

Statistical analyses were conducted using SPSS 27.0 and Mplus 8.3. Descriptive statistics were performed in SPSS 27.0, with categorical data expressed as frequencies and percentages, and continuous data presented as mean ± standard deviation (—x±s). Group comparisons were carried out using t-tests or one-way ANOVA. Pearson correlation analysis was employed to examine the relationships between variables.

After controlling for demographic factors such as gender, rural residency status, and only-child status, we constructed a cross-lagged model using Mplus 8.3. The cross-lagged model is a statistical approach designed for longitudinal data and is commonly used to test hypotheses and explore causal relationships among variables. By analyzing variable relationships at different time points, this method helps reveal causal directions and mutual influences. In this study, we used autoregressive and cross-lagged regression coefficients to analyze the longitudinal relationship between early suicidal ideation and bullying victimization in adolescents [38]. We employed the bootstrap method to examine the longitudinal mediating effect of self-efficacy between suicidal ideation and bullying victimization. We conducted model estimation using robust maximum likelihood estimation (MLR) and handled missing data with full information maximum likelihood estimation (FIML). We assessed model adequacy using multiple fit indices, including the comparative fit index (CFI), Tucker-Lewis index (TLI), root mean square error of approximation (RMSEA), and standardized root mean square residual (SRMR). According to standard cutoff criteria, CFI/TLI > 0.90 and SRMR/RMSEA < 0.10 indicate a good model fit [39, 40]. The significance level was set at α = 0.05.

Result

Participant characteristics

The sample comprised 528 boys and 495 girls; 124 left-behind adolescents and 899 non-left-behind adolescents; 235 Only-Child and 788 Non-Only Child, with a mean age of 12.28 ± 0.47 years at T1. Chi-square/t-test results indicated no statistically significant differences (all P > 0.05) in demographic variables, bullying victimization, self-efficacy, or suicidal ideation scores between participants who dropped out and those who completed all three surveys, suggesting no structural attrition among the participants.

Common method Bias

Given that the data for this study were obtained from subjective questionnaires, it is essential to examine whether the data are affected by systematic bias due to common method variance [41]. We employed Harman’s single-factor test to conduct unrotated exploratory factor analysis on all items from the three data collection rounds. The results indicated that the variance explained by the first factor was 14.25%, 17.83%, and 20.49% across the three measurements, all below the critical threshold of 40% [42]. This suggests that there is no significant common method bias present in this study.

Comparison of scores on various scales among adolescents with different demographic characteristics

A comparison of scores on early bullying victimization, self-efficacy, and suicidal ideation among adolescents with varying demographic characteristics (gender, left-behind status, and only-child status) revealed significant differences (see Table 1). Specifically, boy and girl adolescents exhibited statistically significant differences in bullying victimization at T1 and T3, as well as in self-efficacy and suicidal ideation scores across all stages (all p < 0.05). Additionally, differences in bullying victimization at T1 and T3, as well as in self-efficacy and suicidal ideation scores across all stages, were also statistically significant among adolescents based on their left-behind status (all p < 0.05). Furthermore, significant differences were found in bullying victimization at T3, as well as in self-efficacy scores at T2 and T3 among only children (all p < 0.05).

Table 1.

Scores on various scales among adolescents with different demographic characteristics

Variable Gender t Left-Behind Status t Only-Child Status t
Boy Girl Left-
Behind
Non-Left-
Behind
Only-Child Non-Only-Child
(n = 528) (n = 495) (n = 124) (n = 899) (n = 235) (n = 788)
T1 Bullying Victimization 9.72 ± 3.4 9.04 ± 2.6 3.54*** 10.19 ± 3.0 9.28 ± 3.1 -3.12*** 9.34 ± 2.9 9.40 ± 3.1 0.25
T2 Bullying Victimization 9.23 ± 4.1 8.68 ± 2.8 2.51* 9.44 ± 3.4 8.90 ± 3.5 -1.62 8.52 ± 2.6 9.07 ± 3.7 1.81
T3 Bullying Victimization 10.25 ± 5.3 9.65 ± 3.8 2.10* 10.72 ± 4.9 9.86 ± 4.6 -1.96* 9.27 ± 3.9 10.17 ± 4.8 2.66**
T1 Self-Efficacy 23.95 ± 7.0 25.82 ± 6.5 -4.44*** 23.11 ± 7.1 25.09 ± 6.7 3.06** 25.5 ± 7.1 24.66 ± 6.7 -1.69
T2 Self-Efficacy 24.37 ± 7.2 27.62 ± 7.0 -7.32*** 23.15 ± 6.9 26.33 ± 7.3 4.59*** 27.00 ± 7.5 25.63 ± 7.2 -2.54*
T3 Self-Efficacy 25.20 ± 7.1 27.74 ± 7.3 -5.63*** 23.04 ± 6.8 26.89 ± 7.2 5.59*** 28.00 ± 7.1 25.95 ± 7.3 -3.82***

T1 Suicidal

Ideation

30.84 ± 12.0 25.47 ± 9.2 8.02*** 31.7 ± 11.2 27.76 ± 10.9 -3.75*** 28.89 ± 12.2 28.04 ± 10.7 -1.04
T2 Suicidal Ideation 30.7 ± 11.9 24.88 ± 8.2 9.02*** 32.32 ± 11.2 27.27 ± 10.5 -4.98*** 27.47 ± 9.9 28.01 ± 10.9 0.69
T3 Suicidal Ideation 29.32 ± 11.3 24.13 ± 9.0 8.09*** 32.02 ± 11.1 26.09 ± 10.3 -5.94*** 25.53 ± 10.2 27.20 ± 10.7 2.13*

Note: n = 1023; *P < 0.05, **P < 0.01, ***P < 0.001。

Statistical analysis and correlation analysis

The means, standard errors, and correlation coefficient matrix for early bullying victimization, self-efficacy, and suicidal ideation in adolescents across three measurement points are presented in Table 2. Scores for bullying victimization fluctuated from T1 to T3, while self-efficacy scores showed an increasing trend, and suicidal ideation scores exhibited a decreasing trend. The self-efficacy scores from the three measurements were significantly negatively correlated with both bullying victimization and suicidal ideation scores (r = -0.237 to -0.580, P < 0.01). Additionally, bullying victimization scores were significantly positively correlated with suicidal ideation scores (r = 0.231 to 0.455, P < 0.01).

Table 2.

Statistical descriptions and correlation analysis at each measurement point

Variable M±s 1 2 3 4 5 6 7 8 9
1 T1 Bullying Victimization 9.39 ± 3.08 1
2 T2 Bullying Victimization 8.96 ± 3.53 0.566** 1
3 T3 Bullying Victimization 9.96 ± 4.61 0.429** 0.537** 1
4 T1 Self-Efficacy 24.85 ± 6.78 -0.323** -0.291** -0.237** 1
5 T2 Self-Efficacy 25.94 ± 7.29 -0.361** -0.356** -0.332** 0.597** 1
6 T3 Self-Efficacy 26.43 ± 7.30 -0.328** -0.344** -0.353** 0.522** 0.624** 1
7

T1 Suicidal

Ideation

28.24 ± 11.03 0.466** 0.362** 0.231* -0.580** -0.473** -0.427** 1
8 T2 Suicidal Ideation 27.89 ± 10.70 0.392** 0.431** 0.301** -0.455** -0.526** -0.462** 0.688** 1
9 T3 Suicidal Ideation 26.81 ± 10.58 0.399** 0.472** 0.356** -0.443** -0.514** -0.557** 0.583** 0.669** 1

Note: n = 1023; *P < 0.05, **P < 0.01; T1 = First Measurement; T2 = Second Measurement; T3 = Third Measurement

Constructing a Cross-Lagged model of early bullying victimization, Self-Efficacy, and suicidal ideation in adolescents

This study employs three waves of longitudinal data to perform a cross-lagged regression analysis of early bullying victimization, self-efficacy, and suicidal ideation among adolescents. Demographic factors, including gender, guardian status, and whether the adolescent is an only child, are controlled for as they may influence model fit.Model fit results indicate that the cross-lagged regression model for early bullying victimization, self-efficacy, and suicidal ideation exhibits a good fit. (χ²/df = 2.943, RMSEA = 0.044, CFI = 0.995, TLI = 0.970, SRMR = 0.015).

Autoregressive effects

The results of the cross-lagged analysis are shown in Fig. 1. The autoregressive coefficients indicate significant relationships across different time points, suggesting that prior scores can positively predict subsequent levels of the same variables, including bullying victimization, self-efficacy, and suicidal ideation.

Fig. 1.

Fig. 1

Cross-Lagged Effects Model of Early Bullying Victimization, Self-Efficacy, and Suicidal Ideation in Adolescents

Direct effects

The causal regression model indicates that T1 bullying victimization significantly predicts T2 self-efficacy and T2 suicidal ideation, whereas T2 bullying victimization significantly predicts T3 suicidal ideation but not T3 self-efficacy. Furthermore, T1 self-efficacy significantly predicts T2 bullying victimization and T2 suicidal ideation, and T2 self-efficacy significantly predicts T3 bullying victimization and T3 suicidal ideation. T1 suicidal ideation significantly predicts T2 self-efficacy but not T2 bullying victimization, while T2 suicidal ideation does not significantly predict T3 self-efficacy or T3 bullying victimization.

Indirect effects

As there were some significant direct paths between bullying victimization, self-efficacy, and suicidal ideation across consecutive waves, the hypothesized in direct effects were investigated. The Bootstrap method was utilized to test the mediating effect of self-efficacy; a 95% confidence interval not including zero supports the existence of a mediating effect. Results reveal that T2 self-efficacy mediates the relationship between T1 bullying victimization and T3 suicidal ideation (β = 0.012, 95% CI = 0.003–0.024, P < 0.05); T2 self-efficacy mediates the relationship between T3 bullying victimization and T1 suicidal ideation (β = 0.016, 95% CI = 0.004–0.035, P < 0.05).

Discussion

This study finds that early bullying victimization in adolescents has a unidirectional predictive relationship with suicidal ideation, indicating that the degree of bullying victimization can predict the level of suicidal thoughts. This result aligns with previous research [43], supporting hypothesis 1a while refuting 1b. Furthermore, this study addresses the limitations of prior cross-sectional research by employing a longitudinal design, revealing the persistent impact of bullying victimization on the development of suicidal ideation. Interpersonal theories of suicide suggest that feelings of alienation and perceptions of being a burden are crucial factors in the formation and escalation of suicidal thoughts [44, 45]. Adolescents who experience bullying may develop negative self-evaluations and perceptions of their environment, significantly affecting their sense of belonging and their ability to support intimate relationships. These negative cognitions can lead adolescents to perceive themselves as burdens in social contexts, heightening feelings of alienation and burden, thereby fulfilling the initial conditions for suicidal thoughts and behaviors [46, 47].

The mediation effect analysis reveals that early self-efficacy in adolescents serves as a complete mediator in the relationship between bullying victimization and suicidal ideation, supporting Hypothesis 2a. This indicates that bullying victimization increases suicidal ideation by diminishing individual self-efficacy, aligning with the Motivation-Volition Integration Model [48]. This model outlines three stages in the development of suicidal behavior: the pre-motivational stage, the motivational stage, and the volitional stage [49, 50]. In the pre-motivational stage, the focus is on factors that trigger suicidal ideation, including environmental influences and negative life events. Bullying, a common negative life event for adolescents, elicits strong feelings of frustration and humiliation, leading to a decline in life motivation and contributing to low self-esteem and self-efficacy, resulting in a sense of entrapment [51]. The motivational stage involves the formation of suicidal ideation, where prolonged negative psychological states heighten the likelihood of transitioning from a sense of entrapment to suicidal thoughts, influencing attitudes toward suicide and death [52]. Finally, the volitional stage describes the process of converting suicidal ideation into suicidal behavior; as psychological conditions worsen and suicidal thoughts intensify, these ideations can easily evolve into actual self-harm or suicide [53]. Overall, bullying victimization represents a significant negative event in early adolescence that leads to decreased self-efficacy. Individuals enduring prolonged low self-efficacy may experience reduced fear of death and increased tolerance for the pain associated with suicide, resulting in stronger suicidal ideations and placing adolescents at heightened risk for suicidal behaviors.

The mediation analysis reveals that early self-efficacy in adolescents fully mediates the relationship between suicidal ideation and bullying victimization. This suggests that although suicidal ideation in early adolescents does not directly affect the degree of bullying victimization, it can influence this through self-efficacy, supporting Hypothesis 2b. First, suicidal ideation predicts levels of self-efficacy, consistent with prior research [54]. Suicidal behavior may serve as a means of self-escape and avoidance. Due to their unique developmental stage, early adolescents often lack the problem-solving abilities and willpower seen in adults. Those with suicidal thoughts may resort to irrelevant and avoidant coping strategies, resulting in noticeably low self-efficacy in real-life situations [55, 56]. Second, self-efficacy further predicts the extent of individual bullying victimization. Research indicates that self-efficacy, as a form of psychological capital, can forecast the development of early bullying victimization among adolescents. Low self-efficacy often leads these individuals to endure rather than retaliate or seek help when faced with aggression, diminishing their social functioning and emotional regulation, while simultaneously increasing the frequency and severity of bullying experiences, trapping them in a deeper crisis [57]. Overall, self-efficacy plays a crucial role in the dynamic relationship between early bullying victimization and suicidal ideation in adolescents. As a mediator, bullying victimization can intensify suicidal thoughts, which may, in turn, increase the likelihood of further bullying. Over time, this may create a vicious cycle of “bullying victimization—intensified suicidal ideation—secondary victimization,” ultimately leading to concrete suicidal behaviors. This underscores the need to target self-efficacy in research and intervention strategies related to bullying victimization and suicidal ideation in adolescents, aiming to enhance their quality of life.

Strengths and limitations

In this study, we examines the longitudinal mediating role of early self-efficacy in adolescents between bullying victimization and suicidal ideation. The findings contribute theoretical insights and empirical evidence regarding the mechanisms linking early bullying victimization to suicidal thoughts in adolescents. Additionally, the research offers valuable guidance for fostering early self-efficacy and addressing both bullying victimization and suicidal ideation.

However, this study has several limitations. First, as the sample was drawn from public middle schools in a city in Hunan Province, its representativeness is limited. Future research should consider incorporating more diverse school settings, such as rural and private schools, to enhance the generalizability of the findings. Second, the influence of peer and family factors on the dynamic relationship between bullying victimization and suicidal ideation cannot be overlooked. Future studies should further examine the predictive roles of these factors to provide targeted interventions aimed at improving adolescents’ quality of life. Third, this study relied on self-report questionnaires, which may be subject to social desirability bias or response bias. Future research should broaden the sample scope and adopt more objective data collection methods.

Conclusion

Based on the research findings, this study presents the following conclusions: (1) The bullying victimization in early adolescents can directly predict the level of suicidal ideation and can also indirectly influence suicidal ideation by affecting self-efficacy; (2) Suicidal ideation does not directly predict the level of bullying victimization; rather, it can indirectly predict bullying victimization through its impact on self-efficacy.These results suggest that future research should consider two important aspects: first, strategies to curb early bullying victimization must be developed to mitigate its negative impacts on victims’ mental and physical health and to prevent self-harm and suicidal behaviors. Second, self-efficacy should be explored as an effective target for interventions aimed at controlling the relationship between bullying victimization and suicidal ideation. Enhancing adolescents’ self-efficacy can significantly improve their quality of life and promote healthy development.

Author contributions

Ziyi Chen, Jianhua Zhang, Tiancheng Zhang and Zeng Zhou conceived the study. Ziyi Chen, Yang Liu and Yuanyuan Ma designed and supervised the study. Jianhua Zhang, Tiancheng Zhang and Fulan Zhang participated in data collection. Ziyi Chen, Jianhua Zhang, Yuanyuan Ma and Yiyi Chen organized and analyzed the data, wrote the different sections of the manuscript. Ziyi Chen wrote the first draft of drafted the manuscript. Tiancheng Zhang, Yang Liu and Zeng Zhou improved the research and edited the manuscript. All authors read and approved the final manuscript. Hua Meng and Ting Pan contributed equally to this work. All authors contributed to manuscriptrevision and read and approved the submitted version.

Funding

Ministry of Education Humanities and Social Science Youth Project (23YJC890059). Hunan Province Education Science planning project (XJK23xt001).

Data availability

The datasets generated and/or analysed during the current study are not publicly available due [our experimental team’s policy] but are available from the corresponding author on reasonable request.

Declarations

Ethics approval and consent to participate

The study was approved by the Biomedicine Ethics Committee of Jishou University before the initiation of the project (Grant number: JSDX-2023-0034). And informed consent was obtained from the participants and their guardians before starting the program. We confirm that all the experiment is in accordance with the relevant guidelines and regulations such as the declaration of Helsinki.

Consent for publication

Not applicable.

Competing interests

The authors declare no competing interests.

Footnotes

Publisher’s note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Contributor Information

Jianhua Zhang, Email: zjh828288@163.com.

Yang Liu, Email: ldyedu@foxmail.com.

References

  • 1.World Health Organization. Suicide worldwide in 2019: Global Health Estimates[EB/OL]. https://www.who.int/publications/i/item/9789240026643
  • 2.Wu CZ, Ma N, Huang TT, Lu AF, Ren ZH, Yuan FH. Relationship between college students’ perceived stress and their suicidal ideation: multiple mediating effect of resilience and depression. J Xi’an Jiaotong University(Medical Sciences). 2024;45(3):371–5. 10.7652/jdyxb202403004. [Google Scholar]
  • 3.Geoffroy MC, Bouchard S, Per M, Khoury B, Chartrand E, Renaud J, Turecki G, Colman I, Orri M. Prevalence of suicidal ideation and self-harm behaviours in children aged 12 years and younger: a systematic review and meta-analysis. Lancet Psychiatry. 2022;9(9):703–14. 10.1016/S2215-0366(22)00193-6. [DOI] [PubMed] [Google Scholar]
  • 4.Kwon H, Lee JS, Kim AR, Hong HJ, Kweon YS. Risk factors for suicidal ideation and attempts in adolescents. Soa Chongsonyon Chongsin Uihak. 2018;29(3):114–21. 10.5765/jkacap.170010. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 5.Xu HQ, Wan YH, Xu SJ, Zhang SC, Wang W, Zeng HJ, Yang R, Tao FB. Associations of non-suicidal self-injury with suicidal ideation and suicide attempt among middle school students. Chin Mental Health J. 2019;33(10):774–8. 10.3969/j.issn.1000-6729.2019.10.010. [Google Scholar]
  • 6.Zhang ZX, Huang XX, Hu J, Xue YN, Jia LY, Tao FB, Wan YH, Zhang SC. Association of interaction between mental health literacy and non-suicidal self-injury with suicidal behaviors among middle school students: a cross- sectional survey in three China cities. Chin J Public Health. 2022;38(12):1517–22. 10.11847/zgggws1138596. [Google Scholar]
  • 7.Pu X, Yong ZT, Wang K, Wang LY, Chen J, Wang L, Bai T. Association between suicidal ideation and exposure to social-ecological risk factors among middle school students in Taiyuan City. Chin J Sch Health. 2023;44(10):1527–31. 10.16835/j.cnki.1000-9817.2023.10.020. [Google Scholar]
  • 8.Zhu XX, Tian LL, Huebner ES. Trajectories of suicidal ideation from middle childhood to early adolescence: risk and protective factors. J Youth Adolesc. 2019;48(9):1818–34. 10.1007/s10964-019-01087-y. [DOI] [PubMed] [Google Scholar]
  • 9.Lewinsohn PM, Rohde P, Seeley JR. Major depressive disorder in older adolescents: prevalence, risk factors, and clinical implications. Clin Psychol Rev. 1998;18(7):765–94. 10.1016/s0272-7358(98)00010-5. [DOI] [PubMed] [Google Scholar]
  • 10.Scardera S, Perret LC, Ouellet-Morin I, Gariépy G, Juster RP, Boivin M, et al. Association of social support during adolescence with depression, anxiety, and suicidal ideation in young adults. JAMA Netw Open. 2020;3(12):e2027491. 10.1001/jamanetworkopen.2020.27491. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 11.Wu ZH, Zhao ZF, Li GP. Childhood psychological maltreatment and peer victimization and their relationship with depressive symptoms and suicidal ideation in college students. Chin Mental Health J. 2023;37(07):596–602. 10.3969/j.issn.1000-6729.2023.07.009. [Google Scholar]
  • 12.Liu RT, Walsh RFL, Sheehan AE, Cheek SM, Sanzari CM. Prevalence and correlates of suicide and nonsuicidal Self-injury in children: A systematic review and Meta-analysis. JAMA Psychiatry. 2022;79(7):718–26. 10.1001/jamapsychiatry.2022.1256. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 13.Lannoy S, Mars B, Heron J, Edwards AC. Suicidal ideation during adolescence: the roles of aggregate genetic liability for suicide attempts and negative life events in the past year. J Child Psychol Psychiatry. 2022;63(10):1164–73. 10.1111/jcpp.13653. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 14.Savahl S, Montserrat C, Casas F, Adams S, Tiliouine H, Benninger E, Jackson K. Children’s experiences of bullying victimization and the influence on their subjective Well-Being: A multinational comparison. Child Dev. 2019;90(2):414–31. 10.1111/cdev.13135. [DOI] [PubMed] [Google Scholar]
  • 15.Feng YH, Yan K, Ge YC. The impact of bullying victimization on Self-injury behavior among middle school students:a moderated mediation model. Chin J Clin Psychol. 2024;32(2):350–5. 10.16128/j.cnki.1005-3611.2024.02.019. [Google Scholar]
  • 16.Estévez-García JF, Cañas E, Estévez E. Non-Disclosure and suicidal ideation in adolescent victims of bullying: an analysis from the family and school context. Psychosoc Interv. 2023;32(3):191–201. 10.5093/pi2023a13. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 17.Ji LQ. Causes and prevention of bullying in schools: a psychological perspective. Res Educational Dev. 2024;44(10):70–6. 10.14121/j.cnki.1008-3855.2024.10.009. [Google Scholar]
  • 18.Wang ZJ, Peng Y, Wang XZ, Liu CJ, He JK. Relationship of students bullying victimization and suicide risk from a junior high school in Luoyang City. Med Soc. 2023;36(10):120–5. 10.13723/j.yxysh.2023.10.020. [Google Scholar]
  • 19.Duan S, Duan Z, Li R, Wilson A, Wang Y, Jia Q, Yang Y, Xia M, Wang G, Jin T, et al. Bullying victimization, bullying witnessing, bullying perpetration and suicide risk among adolescents: A serial mediation analysis. J Affect Disord. 2020;273:274–9. 10.1016/j.jad.2020.03.143. [DOI] [PubMed] [Google Scholar]
  • 20.Zhang YY, Zhang X, Xu W, The Influence of Empathy on Bystander Defending Behaviors: The Mediating Role of Moral Identity and the Moderating Role of Social Self-efficacy. Chinese Journal of Clinical Psychology. 2023;31(5):1189–1193. 10.16128/j.cnki.1005-3611.2023.05.032.
  • 21.Zhang K, Zhang S, Dong YH. Positive psychological capital: measurement and relationship with mental health. Studies of Psychology and Behavior. 2010;8(1):58–64.
  • 22.Luthans F, Youssef CM,.Human. Social, and now positive psychological capital Management:[J].Organizational dynamics, 2004, 33(2):143–60.10.1016/j.orgdyn.2004.01.003 [DOI] [PMC free article] [PubMed]
  • 23.Harris LM, Huang XYN, Funsch KM, Fox KR, Ribeiro JD. Efficacy of interventions for suicide and self-injury in children and adolescents: a meta-analysis. Sci Rep. 2022;12(1):12313. 10.1038/s41598-022-16567-8. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 24.Isaac V, Wu CY, McLachlan CS, Lee MB. Associations between health-related self-efficacy and suicidality. BMC Psychiatry. 2018;18(1):126. 10.1186/s12888-018-1705-z. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 25.Haraldstad K, Kvarme LG, Christophersen KA, Helseth S. Associations between self-efficacy, bullying and health-related quality of life in a school sample of adolescents: a cross-sectional study. BMC Public Health. 2019;19(1):757. 10.1186/s12889-019-7115-4. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 26.Bussey K, Luo A, Fitzpatrick S, Allison K. Defending victims of cyberbullying: the role of self-efficacy and moral disengagement. J Sch Psychol. 2020;78:1–12. 10.1016/j.jsp.2019.11.006. [DOI] [PubMed] [Google Scholar]
  • 27.Fang J, Wen ZL, Qiu HZ. Mediation analysis of longitudinal data. J Psychol Sci. 2021;44(4):989–96. 10.16719/j.cnki.1671-6981.20210431. [Google Scholar]
  • 28.Preacher KJ. Advances in mediation analysis: a survey and synthesis of new developments. Annu Rev Psychol. 2015;66:825–52. 10.1146/annurev-psych-010814-015258. [DOI] [PubMed] [Google Scholar]
  • 29.Wen M, Lin D. Child development in rural China: children left behind by their migrant parents and children of nonmigrant families. Child Dev. 2012;83(1):120–36. 10.1111/j.1467-8624.2011.01698.x. [DOI] [PubMed] [Google Scholar]
  • 30.Zhao X, Chen J, Chen MC, Lv XL, Jiang YH, Sun YH. Left-behind children in rural China experience higher levels of anxiety and poorer living conditions. Acta Paediatr. 2014;103(6):665–70. 10.1111/apa.12602. [DOI] [PubMed] [Google Scholar]
  • 31.Falbo T, Poston DL Jr. The academic, personality, and physical outcomes of only children in China. Child Dev. 1993;64(1):18–35. 10.1111/j.1467-8624.1993.tb02893.x. [DOI] [PubMed] [Google Scholar]
  • 32.Cameron L, Erkal N, Gangadharan L, Meng X. Little emperors: behavioral impacts of China’s One-Child policy. Science. 2013;339(6122):953–7. 10.1126/science.1230221. [DOI] [PubMed] [Google Scholar]
  • 33.Ji YC. Comprehensive report on health related/dangerous behaviors of Chinese adolescents. 2005[M]. Peking University Medical Press; 2007.
  • 34.Schwarzer R, Jerusalem MG. Self-Efficacy Scale [M].Windsor:Nfer-Nelson,1995.
  • 35.Wang CK, Hu ZF, Liu Y. Evidences for reliability and validity of the Chinese version of general Self-Efficacy scale. Chin J Appl Psychol. 2001;7(1):37–40. 10.3969/j.issn.1006-6020.2001.01.007. [Google Scholar]
  • 36.Osman A, Barrios FX, Gutierrez PM, Wrangham JJ, Kopper BA, Truelove RS, Linden SC. The positive and negative suicide ideation (PANSI) inventory: psychometric evaluation with adolescent psychiatric inpatient samples. J Pers Assess. 2002;79(3):512–30. 10.1207/S15327752JPA7903_07. [DOI] [PubMed] [Google Scholar]
  • 37.Wang XZ, Gong HL, Kang XR, Liu WW, Dong XJ, Ma YF. Reliability and validity of Chinese revision of positive and negative suicide ideation in high school students. China J Health Psychol. 2011;19(8):964–6. 10.13342/j.cnki.cjhp.2011.08.014. [Google Scholar]
  • 38.Muthén LK, Muthén BO. Mplus user’s guide. 8th ed. Los Angeles: Muthén & Muthén; 2017. [Google Scholar]
  • 39.Hu L, Bentler PM. Cutoff criteria for fit indexes in covariance structure analysis: conventional criteria versus new alternatives. Struct Equ Model. 1999;6(1):1–55. 10.1080/10705519909540118. [Google Scholar]
  • 40.MacCallum RC, Austin JT. Applications of structural equation modeling in psychological research. Annu Rev Psychol. 2000;51:201–26. 10.1146/annurev.psych.51.1.201. [DOI] [PubMed] [Google Scholar]
  • 41.Podsakoff PM, MacKenzie SB, Lee JY, Podsakoff NP. Common method biases in behavioral research: a critical review of the literature and recommended remedies. J Appl Psychol. 2003;88(5):879–903. 10.1037/0021-9010.88.5.879. [DOI] [PubMed] [Google Scholar]
  • 42.Zhou H, Long LR. Statistical remedies for common method biases. Adv Psychol Sci. 2004;12(6):942–50. 10.3969/j.issn.1671-3710.2004.06.018. [Google Scholar]
  • 43.Benatov J, Brunstein Klomek A, Chen-Gal S. Bullying perpetration and victimization associations to suicide behavior: a longitudinal study. Eur Child Adolesc Psychiatry. 2022;31(9):1353–60. 10.1007/s00787-021-01776-9. [DOI] [PubMed] [Google Scholar]
  • 44.Joiner TE, Van Orden KA, Witte TK, Selby EA, Ribeiro JD, Lewis R, Rudd MD. Main predictions of the interpersonal-psychological theory of suicidal behavior: empirical tests in two samples of young adults. J Abnorm Psychol. 2009;118(3):634–46. 10.1037/a0016500. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 45.Van Orden KA, Witte TK, Cukrowicz KC, Braithwaite SR, Selby EA, Joiner TE Jr. The interpersonal theory of suicide. Psychol Rev. 2010;117(2):575–600. 10.1037/a0018697. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 46.Wei H, Li YY, Liu MT, He AM. Parental phubbing and adolescents’suicidal ideation:from the perspective of experiential avoidance model. Chin J Clin Psychol. 2023;31(1):246–9. 10.16128/j.cnki.1005-3611.2023.01.047. [Google Scholar]
  • 47.Meng FC, Zhu XX, Gao QQ, Li X, Chen J, Sa Q. Integrating the interpersonal theory of suicide into the relations between Cyber-Victimization and suicidality among adolescents: A Short-Term prospective study. J Interpers Violence. 2023;38(1–2):NP981–1006. 10.1177/08862605221086638. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 48.O’Connor RC, Rasmussen S, Hawton K. Distinguishing adolescents who think about self-harm from those who engage in self-harm. Br J Psychiatry. 2012;200(4):330–5. 10.1192/bjp.bp.111.097808. [DOI] [PubMed] [Google Scholar]
  • 49.Miao QF, Qiu LJ, Wang XN, Zhu L, Hu TT. A qualitative study of complex psychological experience among adolescents with suicide attempts. Med Philos. 2023;44(16):48–52. 10.12014/j.issn.1002-0772.2023.16.11. [Google Scholar]
  • 50.O’Connor RC, Nock MK. The psychology of suicidal behaviour. Lancet Psychiatry. 2014;1(1):73–85. 10.1016/S2215-0366(14)70222-6. [DOI] [PubMed] [Google Scholar]
  • 51.Liu YX, Yu XH, An F, Wang YJ. School bullying and self-efficacy in adolescence: A meta-analysis. J Adolesc. 2023;95(8):1541–52. 10.1002/jad.12245. [DOI] [PubMed] [Google Scholar]
  • 52.Han J, Wong I, Christensen H, Batterham PJ. Resilience to suicidal behavior in young adults: a cross-sectional study. Sci Rep. 2022;12(1):11419. 10.1038/s41598-022-15468-0. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 53.Ying MT, Jiang GR, Lu T, Wang L. From suicide ideation to suicide attempt: theoretical models and risk factors for the transition of suicidal action. Chin J Clin Psychol. 2024;32(2):314–22. 10.16128/j.cnki.1005-3611.2024.02.014. [Google Scholar]
  • 54.Qi JD, Huang DW, Liu X, Ying TZ. The status of suicidal ideation and the role of networking self-efficacy and loneliness among junior middle school students. Chin J Health Educ. 2020;36(5):450–4. 10.16168/j.cnki.issn.1002-9982.2020.05.014. [Google Scholar]
  • 55.Li Y, Kwok SYCL. A longitudinal network analysis of the interactions of risk and protective factors for suicidal potential in early adolescents. J Youth Adolesc. 2023;52(2):306–18. 10.1007/s10964-022-01698-y. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 56.Liu JJ, He XY, Li S, Ran GM. Social avoidance and adolescents’suicide ideation:a moderated mediation model. Stud Psychol Behav. 2023;21(5):675–81. 10.12139/j.1672-0628.2023.05.014. [Google Scholar]
  • 57.Dong YQ, Wang XX, Yuan WH, Gao JB, Li ZX, Zhong JW, Huang QS. Effect of physical exercise on school bullying among junior high school students:the chain mediating effect of psychological capital and self-control. China J Health Psychol. 2023;31(5):733–9. 10.13342/j.cnki.cjhp.2023.05.018. [Google Scholar]
  • 58.Liu, Yang et al. Anxiety mediated the relationship between bullying victimization and internet addiction in adolescents, and family support moderated the relationship. BMC pediatrics. 2025;25(1):8. 10.1186/s12887-024-05348-z. [DOI] [PMC free article] [PubMed]
  • 59.Liu, Yang et al. The chain mediating effect of anxiety and inhibitory control between bullying victimization and internet addiction in adolescents. Scientific reports. 2024;14(1):23350. 10.1038/s41598-024-74132-x. [DOI] [PMC free article] [PubMed]
  • 60.Liu, Yang et al. Physical activity moderated the mediating effect of self-control between bullying victimization and mobile phone addiction among college students. Scientific reports. 2024;14(1):20855. 10.1038/s41598-024-71797-2. [DOI] [PMC free article] [PubMed]

Associated Data

This section collects any data citations, data availability statements, or supplementary materials included in this article.

Data Availability Statement

The datasets generated and/or analysed during the current study are not publicly available due [our experimental team’s policy] but are available from the corresponding author on reasonable request.


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