Prevalence and pattern of self-harm among university students in Dhaka, Bangladesh

doi:10.21203/rs.3.rs-3767103/v1

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Prevalence and pattern of self-harm among university students in Dhaka, Bangladesh

https://doi.org/10.21203/rs.3.rs-3767103/v1

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Background

Self-harm is a global public health concern, particularly among university students. This study explores the prevalence and correlates of self-harm among university students in Dhaka, Bangladesh, within the context of global, regional, and local trends.

Methods

A cross-sectional study was conducted among 200 students from the University of Dhaka and the Bangladesh University of Business and Technology. Data were collected through face-to-face interviews, and analyses were performed using SPSS version 26.

Results

The study revealed a notable prevalence of self-harm at 17%, with a significant gender disparity—females reported a fourfold higher prevalence than males. Bivariate analyses showed no significant differences based on institutions, academic disciplines, habitat, or socioeconomic status. However, logistic regression identified significant associations; females had a higher likelihood of self-harm, and middle and high socioeconomic status were protective factors.

Discussion

Our findings contribute to the global discourse on self-harm among university students, aligning with regional trends while providing locally specific insights. The gender disparity emphasizes the need for gender-specific interventions, and the protective effect of socioeconomic status highlights the importance of addressing economic disparities.

Conclusion

This study underscores the urgency of tailored mental health initiatives for university students in Dhaka. The observed prevalence and associated factors guide future research and inform evidence-based interventions to mitigate the prevalence of self-harm and enhance mental well-being on university campuses.

Psychology

Psychiatry

mental health

self-harm

university students

public health

Bangladesh

Self-harm, a multifaceted manifestation of psychological distress, has emerged as a significant global public health concern, especially among university students. This issue not only affects individual well-being but also poses challenges to the overall mental health landscape of educational institutions.

Globally, the prevalence of self-harm among university students varies, with alarming rates documented across diverse cultural contexts. Studies from China (Li et al., 2020; Peng et al., 2023; Yu et al., 2022) and England (O’Connor et al., 2018) reported prevalence rates ranging from 7.5–16.2%, highlighting the pervasive nature of this phenomenon. The widespread impact of self-harm on university campuses is underscored by a recent nationwide study in China, emphasizing the need for comprehensive mental health strategies (Peng et al., 2023, 2023).

In the Asian region, the prevalence of self-harm among university students has been a subject of increasing concern. Hong Kong witnessed a substantial prevalence of 32.7% of students reporting at least one form of deliberate self-harm (Shek & Yu, 2013). Similarly, Malaysia recorded a prevalence of 7.3% among university students during the COVID-19 pandemic (Siddiqui & Qian, 2022). These regional trends emphasize the urgent need for targeted interventions to address the unique challenges faced by university students in diverse cultural and socioeconomic contexts.

Within the local context of Dhaka, Bangladesh, where mental health issues are gaining recognition, evidence on self-harm among university students has been limited. A clinical study reported a clinical prevalence of 16.4% among total mental and behavioral emergencies attended during a specific period (Singh et al., 2019). However, comprehensive research specific to university students in Dhaka has been sparse. Our study seeks to address this gap by investigating the prevalence and associated factors of self-harm among university students in Dhaka.

Understanding the factors contributing to self-harm among university students in Dhaka is crucial for several reasons. First and foremost, it enables the identification of at-risk groups, allowing for the development of targeted preventive and intervention strategies. Given the cultural nuances and unique stressors faced by students in Dhaka, our study aims to contribute context-specific insights that can inform mental health initiatives tailored to the local university population.

Moreover, the global and regional variations in self-harm prevalence underscore the need for localized interventions that consider the cultural and socioeconomic specificities of the Dhaka context. By shedding light on the prevalence and correlates of self-harm, this study strives to provide a foundation for evidence-based mental health programs that address the distinct challenges faced by university students in Dhaka.

This study aimed to gain a comprehensive understanding of self-harming behaviors among university students in Dhaka, contributing to the development of targeted prevention and intervention strategies. The study adheres to the STROBE guidelines for reporting cross-sectional studies.

Study Design and Setting

This cross-sectional study was conducted at the Department of Psychiatry, Bangabandhu Sheikh Mujib Medical University (BSMMU) in Dhaka, Bangladesh, spanning from February 2020 to August 2020.

Participants and Sampling

Participants, drawn from the University of Dhaka and the Bangladesh University of Business and Technology (BUBT), were selected using a convenient random sampling technique (Andrade, 2021). The sample size was 200 students, comprising 102 from the University of Dhaka (51 from computer science and 51 from sociology) and 98 from BUBT (51 computer science majors and 47 English majors). The sampling approach aimed to ensure representativeness within the constraints of the study's scope.

Ethical Considerations

This study received approval from the institutional review boards of both participating universities. Informed consent was obtained from all participants, emphasizing the voluntary nature of participation and confidentiality assurances. Ethical considerations were paramount throughout the study.

Data Collection

Data collection involved face-to-face interviews, where participants completed a sociodemographic questionnaire and the SHI-Bangla version. The interviews, conducted in private to protect participant confidentiality, were guided by a structured protocol. The instruments selected were chosen based on their relevance to the study's objectives.

Variables and Measurements

The sociodemographic questionnaire covered key variables, including age, gender, area of living (urban/rural), and family income, while the SHI-Bangla version assessed self-harming behaviors. The selection of these instruments aligns with the study's focus and aims.

Response Rate and Non-Participation

Of the 240 students contacted, 200 agreed to participate, yielding an 83% response rate. While specific reasons for non-participation were not systematically recorded, potential biases were considered in the analysis and interpretation of results.

Data Analysis

Statistical analyses were performed using SPSS version 23.0. Descriptive statistics were applied to sociodemographic variables, and appropriate statistical procedures were employed for comparative analyses. Assumptions made during the analysis are explicitly stated to enhance the transparency of the study's findings.

Confidentiality and Anonymity

Coding was implemented to ensure the confidentiality and anonymity of participant information. All study materials were anonymized, and data were securely stored.

Demographic Characteristics of Participants

The study included a diverse sample of university students from both the University of Dhaka and the Bangladesh University of Business and Technology (BUBT). The mean age of the participants was 21 years (SD: 1.95), reflecting a relatively homogenous age group. Participants were evenly distributed between the two universities, demonstrating a balanced representation of students from different academic environments. In terms of gender distribution, 65.5% of participants identified as male, while 34.5% identified as female. Academic disciplines varied within the sample, with 51% of participants majoring in Computer Science, 23.5% in English, and 25.5% in Sociology. This distribution allowed for the examination of self-harming behaviors across diverse academic backgrounds. Geographically, the majority of participants (55.5%) resided in urban areas, underscoring the urban-rural diversity within the sample. Socioeconomic status, a crucial factor in mental health research, revealed that 4% of participants belonged to the low-income group, 67% to the middle-income group, and 29% to the high-income group. This socioeconomically diverse composition enriches the study's ability to explore potential associations between socioeconomic factors and self-harm.

Table-1: Demographic characteristics of the participants

Characteristics	Frequency	Percentage
Sex
Male	131	65.5
Female	69	34.5
Institution
BUBT	98	49.0
DU	102	51.0
Subject
Computer Science	102	51.0
English	47	23.5
Sociology	51	25.5
Habitat
Urban	111	55.5
Rural	89	44.5
Socioeconomic Status
Low	8	4.0
Middle	134	67.0
High	58	29.0

Self-Harm Behaviors and associated factors

Among the 200 university students who participated in the study, 34 individuals reported a history of self-harm, resulting in an overall prevalence of 17% (95% CI: 12–22.5). This indicates a significant proportion of the student population engaging in self-harming behaviors.

Upon closer examination of gender differences, it was found that 9.9% of male participants (n = 13) and 30.4% of female participants had a history of self-harm. The prevalence of self-harm was significantly higher among female participants compared to their male counterparts (p = 0.001).

Bivariate analyses were conducted to explore potential differences in self-harm behaviors among various demographic and contextual factors. The results revealed that, when measured separately, there were no significant differences in self-harm behavior based on the institutions attended, academic disciplines, habitat (urban or rural), or socioeconomic status.

However, a notable gender disparity emerged as a significant factor influencing self-harm behaviors. The bivariate analysis demonstrated a statistically significant difference between male and female participants (p = 0.000). Female participants were approximately four times more likely to report a history of self-harm compared to their male counterparts (OR = 3.971, 95% CI: 1.841–8.566).

Table-2: Bivariate Analysis of Self-Harm Behaviors

Characteristics	DSH		OR (95% CI)	p-value
	Yes (n, %)	No (n, %)
Sex
Male	13, 9.9	118, 90.1
Female	21, 30.4	48, 69.6	3.971 (1.841–8.566)	0.000
Institution
BUBT	18, 18.4	80, 81.6
DU	16, 15.7	86, 84.3	0.827 (0.395–1.731)	0.614
Subject
Computer Science	15, 14.7	87, 85.3
English	9, 19.1	38, 80.9	1.415 (0.586–3.418)	0.441
Sociology	10, 19.6	41, 80.4	1.030 (0.378–2.807)	0.954
Habitat
Urban	12, 13.5	77, 86.5
Rural	22, 19.8	89, 80.2	0.630 (0.293–1.357)	.238
Socioeconomic Status
Low	2, 25.0	6, 75.0
Middle	25, 18.7	109, 81.3	0.412 (0.069–2.453)	.330
High	7, 12.1	51, 87.9	0.598 (0.243–1.474)	.264

To further explore the factors associated with self-harm behaviors while adjusting for potential confounders, a binary logistic regression analysis was conducted. The results revealed significant differences in self-harm among different groups of socioeconomic status and gender.

After adjusting for all variables, the Adjusted Odds Ratio (AOR) for male participants compared to female participants was 6.512 (95% CI: 2.343–18.095), with a p-value of 0.000. This suggests that, even when considering other variables, the likelihood of self-harm remained significantly higher among female participants.

Examining the impact of socioeconomic status, compared to the low-income group, the AOR for the middle-income group was 0.068 (95% CI: 0.008–0.592) with a p-value of 0.015. Similarly, the AOR for the high-income group was 0.297 (95% CI: 0.104–0.844) with a p-value of 0.023.

Table-3: Multivariate Analysis of Self-Harm Behaviors

	aOR	95% C.I.		p-value
		Lower	Upper
Sex
Male	1.000
Female	6.512	2.343	18.095	0.000
Socioeconomic status
Low
Middle	.068	.008	.592	.015
High	.297	.104	.844	.023
Constant	5.906			.002

The prevalence of self-harm among university students has been a growing concern worldwide. In our study, we observed a notable prevalence of 17% among the participating students. This finding aligns with global trends, where the rates of self-harm among university students vary widely across different regions and time periods.

Comparing our results with existing literature, our prevalence is notably higher than the 7.5% reported among university students in China (Peng et al., 2023), but closer to the 16.4% clinical prevalence of deliberate self-harm documented in mental and behavioral emergencies attended during the same period in India (Singh et al., 2019). These variations underscore the need for region-specific approaches and interventions to address the multifaceted nature of self-harm behaviors in university settings.

Consistent with previous research, our study revealed demographic patterns influencing self-harm behaviors. The age distribution of self-harm attempters was concentrated among the 18–39 age group, aligning with the findings of Singh et al. (2019). The dominance of females among self-harm cases in our study resonates with global patterns, as documented in studies from Hong Kong (Shek & Yu, 2013) and Norway (Tørmoen et al., 2020).

Notably, our study identified a stark gender difference, with female participants reporting a four times higher prevalence of self-harm compared to their male counterparts. This finding is consistent with a broader body of literature emphasizing the elevated risk of self-harm among females (Bresin & Schoenleber, 2015; Chao et al., 2016; Idig-Camuroglu & Gölge, 2018; Li et al., 2020; Sornberger et al., 2012; Victor et al., 2018; Yu et al., 2022). The observed gender disparity underscores the importance of gender-specific risk assessment and intervention strategies tailored to the unique challenges faced by female university students.

Our study uncovered a significant association between socioeconomic status and self-harm, with the logistic regression analysis indicating a protective effect of middle and high socioeconomic status. These results contrast with findings from a study in Malaysia, where the prevalence of self-harm among university students during the COVID-19 pandemic was 7.3% (Siddiqui & Qian, 2022). The variations in prevalence rates emphasize the importance of considering local socioeconomic contexts and stressors that may contribute to self-harm behaviors.

Furthermore, our results align with studies indicating an inverse association between socioeconomic status and self-harm, emphasizing the potential role of economic factors in shaping mental health outcomes among university students (Geulayov et al., 2022; Lodebo et al., 2017; McIntyre et al., 2021; Page et al., 2014; Park et al., 2022). The protective effect observed in middle and high-income groups highlights the need for targeted interventions addressing socioeconomic disparities and promoting mental health resilience among students from low-income backgrounds.

The complex interplay of gender and socioeconomic factors revealed in our study has critical implications for the design of preventive and intervention strategies. Tailoring mental health initiatives to address the unique challenges faced by female students and those from lower socioeconomic backgrounds is paramount. Considering the global and regional variations in self-harm prevalence, future research should delve deeper into the cultural, economic, and social determinants influencing self-harm among university students.

In conclusion, our study adds to the growing body of literature on self-harm among university students, providing insights into the demographic and socioeconomic factors associated with these behaviors. By understanding the unique risk profiles of subgroups within this population, we can inform targeted interventions to mitigate the prevalence of self-harm and promote mental well-being on university campuses.

While this study provides valuable insights into the prevalence and correlates of self-harm among university students in Dhaka, several limitations should be acknowledged. First, the cross-sectional design limits our ability to establish causation, and the data collected represent a snapshot in time, preventing the examination of temporal changes in self-harm behaviors. Second, the reliance on self-reported data introduces the potential for social desirability bias and underreporting of sensitive information. Additionally, the study was conducted in two specific institutions in Dhaka, limiting the generalizability of findings to other university populations in Bangladesh. Furthermore, the convenient random sampling technique may introduce selection bias, as students who chose not to participate may differ systematically from those who did. Lastly, the study's focus on university students may not capture the full spectrum of self-harm behaviors in the broader young adult population. Despite these limitations, this study provides a foundational understanding of self-harm in the Dhaka university context, paving the way for future research and targeted interventions.

Our study on self-harm among university students in Dhaka reveals a significant prevalence of 17%, with a fourfold higher rate among females. The logistic regression underscores the protective role of middle and high socioeconomic status. These findings emphasize the need for targeted interventions addressing gender-specific and socioeconomic factors. Our study serves as a critical step in understanding and addressing self-harm among university students in Dhaka, guiding the development of focused mental health initiatives for this population.

The authors of this paper affirm that they have no competing interests.

Andrade, C. (2021). The Inconvenient Truth About Convenience and Purposive Samples. Indian Journal of Psychological Medicine, 43(1), 86–88. https://doi.org/10.1177/0253717620977000
Bresin, K., & Schoenleber, M. (2015). Gender differences in the prevalence of nonsuicidal self-injury: A meta-analysis. Clinical Psychology Review, 38, 55–64. https://doi.org/10.1016/j.cpr.2015.02.009
Chao, Q., Yang, X., & Luo, C. (2016). Boy Crisis? Sex Differences in Self-Injurious Behaviors and the Effects of Gender Role Conflicts Among College Students in China. American Journal of Men’s Health, 10(6), NP1–NP10. https://doi.org/10.1177/1557988315579096
Geulayov, G., Casey, D., Bale, E., Brand, F., Clements, C., Farooq, B., Kapur, N., Ness, J., Waters, K., Patel, A., & Hawton, K. (2022). Socio-economic disparities in patients who present to hospital for self-harm: Patients’ characteristics and problems in the Multicentre Study of Self-harm in England. Journal of Affective Disorders, 318, 238–245. https://doi.org/10.1016/j.jad.2022.08.106
Idig-Camuroglu, M., & Gölge, Z. B. (2018). Non-Suicidal Self-Injury among University Students in Turkey: The Effect of Gender and Childhood Abuse. Psychiatria Danubina, 30(4), 410–420. https://doi.org/10.24869/psyd.2018.410
Li, C.-Q., Zhang, J.-S., Ma, S., Lv, R.-R., Duan, J.-L., Luo, D.-M., Yan, X.-J., Ma, N., & Song, Y. (2020). Gender differences in self-harm and drinking behaviors among high school students in Beijing, China. BMC Public Health, 20(1), 1892. https://doi.org/10.1186/s12889-020-09979-6
Lodebo, B. T., Möller, J., Larsson, J.-O., & Engström, K. (2017). Socioeconomic position and self-harm among adolescents: A population-based cohort study in Stockholm, Sweden. Child and Adolescent Psychiatry and Mental Health, 11, 46. https://doi.org/10.1186/s13034-017-0184-1
McIntyre, J., Elahi, A., Latham, C., Mullholland, H., Haines-Delmont, A., Saini, P., & Taylor, P. J. (2021). Does neighbourhood identification buffer against the effects of socioeconomic disadvantage on self-harm? Journal of Affective Disorders, 294, 857–863. https://doi.org/10.1016/j.jad.2021.07.103
O’Connor, R. C., Wetherall, K., Cleare, S., Eschle, S., Drummond, J., Ferguson, E., O’Connor, D. B., & O’Carroll, R. E. (2018). Suicide attempts and non-suicidal self-harm: National prevalence study of young adults. BJPsych Open, 4(3), 142–148. https://doi.org/10.1192/bjo.2018.14
Page, A., Lewis, G., Kidger, J., Heron, J., Chittleborough, C., Evans, J., & Gunnell, D. (2014). Parental socio-economic position during childhood as a determinant of self-harm in adolescence. Social Psychiatry and Psychiatric Epidemiology, 49(2), 193–203. https://doi.org/10.1007/s00127-013-0722-y
Park, H., In, S., & Hur, J.-W. (2022). Association of socioeconomic status with nonsuicidal self-injury and suicidal ideation in young Korean adults. The International Journal of Social Psychiatry, 68(5), 1127–1134. https://doi.org/10.1177/00207640221104691
Peng, S., Yang, T., Zhang, W., Cottrell, R. R., & Rockett, I. R. (2023). Contextual influences on deliberate self-harm among Chinese university undergraduates: A representative nationwide study. Journal of Affective Disorders, 335, 371–376.
Shek, T. L., & Yu, L. (2013). Self-harm and suicidal behaviors in Hong Kong adolescents. In Adolescence and Behavior Issues in a Chinese Context (pp. 119–140). Nova Science Publishers, Inc.
Siddiqui, F. S., & Qian, G. Y. (2022). Psychological impact of self-quarantine on malaysian dental students during COVID-19 pandemic. Medical Journal of Dr. DY Patil University, 15(Suppl 1), S30–S45.
Singh, S., Kumar, S., & Deep, R. (2019). Patients with deliberate self-harm attended in emergency setting at a tertiary care hospital: A 13-month analysis of clinical-psychiatric profile. The International Journal of Psychiatry in Medicine, 54(6), 363–376.
Sornberger, M. J., Heath, N. L., Toste, J. R., & McLouth, R. (2012). Nonsuicidal self-injury and gender: Patterns of prevalence, methods, and locations among adolescents. Suicide & Life-Threatening Behavior, 42(3), 266–278. https://doi.org/10.1111/j.1943-278X.2012.0088.x
Tørmoen, A. J., Myhre, M., Walby, F. A., Grøholt, B., & Rossow, I. (2020). Change in prevalence of self-harm from 2002 to 2018 among Norwegian adolescents. European Journal of Public Health, 30(4), 688–692. https://doi.org/10.1093/eurpub/ckaa042
Victor, S. E., Muehlenkamp, J. J., Hayes, N. A., Lengel, G. J., Styer, D. M., & Washburn, J. J. (2018). Characterizing gender differences in nonsuicidal self-injury: Evidence from a large clinical sample of adolescents and adults. Comprehensive Psychiatry, 82, 53–60. https://doi.org/10.1016/j.comppsych.2018.01.009
Yu, Q., Wu, S., Twayigira, M., Luo, X., Gao, X., Shen, Y., Long, Y., Huang, C., & Shen, Y. (2022). Prevalence and associated factors of school bullying among Chinese college students in Changsha, China. Journal of Affective Disorders, 297, 62–67. https://doi.org/10.1016/j.jad.2021.10.010

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Prevalence and pattern of self-harm among university students in Dhaka, Bangladesh

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Abstract

Background

Methods

Results

Discussion

Conclusion

Introduction

Method

Results

Demographic Characteristics of Participants

Self-Harm Behaviors and associated factors

Discussion

Limitations

Conclusion

Declarations

References

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