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Predicting Non-suicidal Self-Injury and Suicidal Ideation Among University Students: A Cross-Sectional Study.

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Title: Predicting Non-suicidal Self-Injury and Suicidal Ideation Among University Students: A Cross-Sectional Study.
Authors: Hasan, S. M. Rakibul1,2 (AUTHOR), Tamanna, Tasnim1,2 (AUTHOR), Hasan, Md. Emran1,3 (AUTHOR), Sadia, Mahjabin Tasnim4 (AUTHOR), Mahmud, Al4 (AUTHOR), Siddique, Abu Bakar4 (AUTHOR), Hiya, Most. Soudia Hamid4 (AUTHOR), Mahin, Tanzim Shahriar4 (AUTHOR), Khorshed, Sayeda Alvi4 (AUTHOR), Tripura, Bipin4 (AUTHOR), Dey, Alethea5 (AUTHOR), Islam, Md. Aminul6 (AUTHOR), Dey, Diptta7 (AUTHOR), Sultana, Sabiha4 (AUTHOR), Mawa, Kashfia8 (AUTHOR), Mostofa, Soma Binta9 (AUTHOR), Hossain, Shahed4 (AUTHOR), Hasan, Jahid10 (AUTHOR), Almerab, Moneerah Mohammad11 (AUTHOR), Habib, Abdullah Al1,4 (AUTHOR)
Source: Inquiry (00469580). 11/1/2025, Vol. 62, p1-16. 16p.
Subject Terms: *Universities & colleges, *Anxiety, *Eating disorders, *Psychology of college students, *Mental depression, Risk assessment, Cross-sectional method, Lifestyles, Scale analysis (Psychology), Suicidal ideation, Cyberbullying, Research funding, Questionnaires, Smoking, Mental illness, Statistical sampling, Logistic regression analysis, Disease prevalence, Chi-squared test, Descriptive statistics, Self-mutilation, Odds ratio, Statistics, Inferential statistics, Sociodemographic factors, Data analysis software, Confidence intervals, Psychosocial factors
Geographic Terms: Bangladesh
Abstract: Non-suicidal self-injury (NSSI) and suicidal ideation (SI) represent significant mental health challenges among university students. In low- and middle-income contexts like Bangladesh, there is limited understanding of how these behaviors differentially affect students with and without mental illness. This study addresses these gaps by investigating the prevalence and risk factors of NSSI and SI, with stratified analyses by mental illness status, to predict these behaviors. This cross-sectional study recruited 1401 university students between December 2024 and January 2025. Data was collected via a self-administered questionnaire assessing socio-demographics, and psychological factors. Traditional statistical analyses, including chi-square tests and logistic regression, were conducted in SPSS 27. The prevalence of NSSI and SI was 21.4% and 17.2%, respectively. Both NSSI and SI were more common among students with symptoms of depression or anxiety (mental illness) than those without. Multivariable analyses identified smoking, cyberbullying, and probable eating disorder as significant predictors of both NSSI and SI, with these associations persisting after stratification by mental illness status. Subgroup analyses showed that among students without mental illness, female gender, older age, smoking, cyberbullying, and eating disorder symptoms significantly predicted NSSI, while smoking, cyberbullying, eating disorder, and older age predicted SI. In students with mental illness, smoking and cyberbullying remained robust predictors of both NSSI and SI, while eating disorder was significantly associated with NSSI but not SI. The regression models explained 12.9% of the variance in NSSI and 16.6% in SI. The findings highlight the necessity to adopt interventions that address modifiable risk factors, with a strong emphasis on behavioral and mental health variables, to effectively reduce self-harming and suicidal behaviors in young adults. [ABSTRACT FROM AUTHOR]
Copyright of Inquiry (00469580) is the property of Sage Publications Inc. and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
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  Data: Non-suicidal self-injury (NSSI) and suicidal ideation (SI) represent significant mental health challenges among university students. In low- and middle-income contexts like Bangladesh, there is limited understanding of how these behaviors differentially affect students with and without mental illness. This study addresses these gaps by investigating the prevalence and risk factors of NSSI and SI, with stratified analyses by mental illness status, to predict these behaviors. This cross-sectional study recruited 1401 university students between December 2024 and January 2025. Data was collected via a self-administered questionnaire assessing socio-demographics, and psychological factors. Traditional statistical analyses, including chi-square tests and logistic regression, were conducted in SPSS 27. The prevalence of NSSI and SI was 21.4% and 17.2%, respectively. Both NSSI and SI were more common among students with symptoms of depression or anxiety (mental illness) than those without. Multivariable analyses identified smoking, cyberbullying, and probable eating disorder as significant predictors of both NSSI and SI, with these associations persisting after stratification by mental illness status. Subgroup analyses showed that among students without mental illness, female gender, older age, smoking, cyberbullying, and eating disorder symptoms significantly predicted NSSI, while smoking, cyberbullying, eating disorder, and older age predicted SI. In students with mental illness, smoking and cyberbullying remained robust predictors of both NSSI and SI, while eating disorder was significantly associated with NSSI but not SI. The regression models explained 12.9% of the variance in NSSI and 16.6% in SI. The findings highlight the necessity to adopt interventions that address modifiable risk factors, with a strong emphasis on behavioral and mental health variables, to effectively reduce self-harming and suicidal behaviors in young adults. [ABSTRACT FROM AUTHOR]
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  Data: <i>Copyright of Inquiry (00469580) is the property of Sage Publications Inc. and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.)
PLink https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=ehh&AN=189238043
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        Value: 10.1177/00469580251382395
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        Text: English
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      – SubjectFull: Bangladesh
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