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Fulltext Association of suicidal ideation with demographic, lifestyle and health factors in Malaysians

Cheah YK, Azahadi M, Phang SN, Abd Manaf NH

East Asian Arch Psychiatry, 2018 Sep;28(3):85-94.
PMID: 30146496

OBJECTIVE: To determine the association of suicidal ideation with demographic, lifestyle, and health factors, using data from National Health and Morbidity Survey 2011 (NHMS 2011) of Malaysia.
METHODS: The NHMS 2011 included 10,141 respondents. Independent variables of suicidal ideation were income, age, household size, sex, ethnicity, education, marital status, smoking, physical activity, and self-rated health. The risk factors of suicidal ideation were determined using logistic regression analysis.
RESULTS: In the pooled sample, suicidal ideation was associated with age, sex, ethnicity, and self-rated health, but not associated with income, household size, education, physical activity, or smoking.
CONCLUSION: The likelihood of having suicidal ideation is positively associated with young adults, women, Indians, and those with poor self-rated health.
Study name: National Health and Morbidity Survey (NHMS-2011)

Matched MeSH terms: Suicidal Ideation*
Fulltext Association between sexual orientation acceptance and suicidal ideation, substance use, and internalised homophobia amongst the pink carpet Y cohort study of young gay, bisexual, and queer men in Singapore

Ong C, Tan RKJ, Le D, Tan A, Tyler A, Tan C, et al.

BMC Public Health, 2021 05 22;21(1):971.
PMID: 34022843 DOI: 10.1186/s12889-021-10992-6

BACKGROUND: Gay, bisexual and queer (GBQ) men are frequently subjected to minority stressors that have negative impacts on their health. Milestones that include the acceptance and disclosure of sexual identity amongst GBQ men are hence key instruments in understanding the prevalence of internalised homophobia and predicting health outcomes. As such, this work takes a novel approach to deduce the correlates of delayed acceptance of sexual orientation in young GBQ men as a measure of internalised homophobia through retrospective self-reporting and age-based analysis.
METHODS: Participants were recruited as part of a cohort study exploring the syndemic risks associated with HIV acquisition among young GBQ men in Singapore. We examined their levels of internalised, perceived, experienced homophobia, as well as their health behaviours and suicidal tendencies. Two separate variables were also self-reported by the participants - the age of questioning of sexual orientation and the age of acceptance of sexual orientation. We subsequently recoded a new variable, delayed acceptance of sexual orientation, by taking the difference between these two variables, regressing it as an independent and dependent variable to deduce its psychosocial correlates, as well as its association with other measured instruments of health.
RESULTS: As a dependent variable, delayed acceptance of sexual orientation is positively associated with an increase of age and internalised homophobia, while being negatively associated with reporting as being gay, compared to being bisexual or queer. As an independent variable, delayed acceptance of sexual orientation was associated with a delayed age of coming out to siblings and parents, suicide ideation, historical use of substances including smoking tobacco cigarettes and consuming marijuana, as well as reporting higher levels of experienced, internalised and perceived homophobia.
CONCLUSION: Greater levels of early intervention and efforts are required to reduce the heightened experience of minority stress resulting from communal and institutional hostilities. Areas of improvement may include community-based counselling and psychological support for GBQ men, while not forsaking greater education of the social and healthcare sectors. Most importantly, disrupting the stigma narrative of a GBQ 'lifestyle' is paramount in establishing an accepting social environment that reduces the health disparity faced by GBQ men.

Matched MeSH terms: Suicidal Ideation
Fulltext Assessing Prevalence and Unique Risk Factors of Suicidal Ideation among First-Year University Students in China Using a Unique Multidimensional University Personality Inventor

Wu O, Lu X, Yeo KJ, Xiao Y, Yip P

Int J Environ Res Public Health, 2022 Aug 30;19(17).
PMID: 36078501 DOI: 10.3390/ijerph191710786

BACKGROUND: University students with suicidal ideation are at high risk of suicide, which constitutes a significant social and public health problem in China. However, little is known about the prevalence and associated risk factors of suicidal ideation among first-year university students in China, especially during the COVID-19 pandemic.
OBJECTIVES: To investigate the prevalence of suicidal ideation and its factors in first-year Chinese university students from a vocational college in Zhejiang during the COVID-19 pandemic.
METHODS: Using a cluster sampling technique, a university-wide survey was conducted of 686 first-year university students from Hangzhou in March 2020 using University Personality Inventory (UPI). UPI includes an assessment for suicidal ideation and possible risk factors. Suicidal ideation prevalence was calculated for males and females. Univariate analysis and multivariable logistic regression models were conducted, adjusting for age and sex. Analyses were carried out using the SPSS version 22.0 software.
RESULTS: The prevalence of 12-month suicidal ideation among first-year university students during March 2020 was 5.2%, and there was no significant difference between males and females (4.8% vs. 6.0%, x2 = 0.28, p = 0.597). Multivariable logistic regression analysis identified social avoidance (B = 0.78, OR = 2.17, p < 0.001) and emotional vulnerability (B = 0.71, OR = 2.02, p < 0.001) as positively associated with suicidal ideation.
CONCLUSIONS: Social avoidance and emotional vulnerabilities are unique factors associated with greater suicidal ideation among first-year university students during the COVID-19 pandemic. UPI serves as a validated tool to screen suicide risks among Chinese university students. Encouraging social engagement and improving emotional regulation skills are promising targets to reduce suicidal ideation among first-year university students.

Matched MeSH terms: Suicidal Ideation
Are reports of cognitive testing among older electroconvulsive therapy recipients clinically valid?

Plakiotis C, Chin LF, O'Connor DW

J ECT, 2014 Mar;30(1):26-9.
PMID: 24487645 DOI: 10.1097/YCT.0000000000000082

Electroconvulsive therapy (ECT) administration rises in frequency with age, with older depressed adults often showing clinical features predictive of good response. Recent reviews suggest that older people experience few if any long-term cognitive adverse effects after contemporary ECT, despite their increased vulnerability to these. However, the broader clinical validity of research findings is not assured as most studies of ECT-related cognitive effects do not discuss cognitive test nonparticipants. This study examines whether cognitive test participants and nonparticipants are comparable.

Matched MeSH terms: Suicidal Ideation
Are predictors of future suicide attempts and the transition from suicidal ideation to suicide attempts shared or distinct: a 12-month prospective study among patients with depressive disorders

Chan LF, Shamsul AS, Maniam T

Psychiatry Res, 2014 Dec 30;220(3):867-73.
PMID: 25240940 DOI: 10.1016/j.psychres.2014.08.055

Our study aimed to examine the interplay between clinical and social predictors of future suicide attempt and the transition from suicidal ideation to suicide attempt in depressive disorders. Sixty-six Malaysian inpatients with a depressive disorder were assessed at index admission and within 1 year for suicide attempt, suicidal ideation, depression severity, life event changes, treatment history and relevant clinical and socio-demographic factors. One-fifth of suicidal ideators transitioned to a future suicide attempt. All future attempters (12/66) had prior ideation and 83% of attempters had a prior attempt. The highest risk for transitioning from ideation to attempt was 5 months post-discharge. Single predictor models showed that previous psychiatric hospitalization and ideation severity were shared predictors of future attempt and ideation to attempt transition. Substance use disorders (especially alcohol) predicted future attempt and approached significance for the transition process. Low socio-economic status predicted the transition process while major personal injury/illness predicted future suicide attempt. Past suicide attempt, subjective depression severity and medication compliance predicted only future suicide attempt. The absence of prior suicide attempt did not eliminate the risk of future attempt. Given the limited sample, future larger studies on mechanisms underlying the interactions of such predictors are needed.

Matched MeSH terms: Suicidal Ideation*
Application of socio-ecological model in developing preventive strategies against suicidal ideation and suicidal attempt among youth in low and middle-income countries: A scoping review

Zulkiply SH, Rosliza AM

Med J Malaysia, 2022 Nov;77(6):755-763.
PMID: 36448396

INTRODUCTION: Suicide is recognized as an important public health concern, as it is the second leading cause of death among young people. About 80% of all suicide cases occur in low- and middle-income countries (LMICs). Understanding the risk factors for suicidal behaviours among young people in LMIC is important in developing preventive strategies; however, evidence on this is still lacking. Socio-ecological model (SEM) is a suitable framework in explaining the factors of suicidal behaviour. The aim of this review is to identify the factors associated with suicidal ideation and suicidal attempt among young people in LMIC, guided by the SEM model, and eventually develop its preventive strategies.
MATERIALS AND METHODS: This review has two parts. The first part is a scoping review of the factors associated with suicidal ideation and attempt among young people. The search was conducted in Pubmed, Scopus, and PsycInfo. The second part is the development of preventive strategies according to the identified factors. Both parts will be guided by the SEM model.
RESULTS: A total of ten studies with 45,278 participants that matched the criteria are included in this review. The review found that the risk factors for suicidal ideation among young people in LMIC are being female, psychiatric illness, psychology problem, smoking, alcohol intake, victim of abuse, bullied, and food insecurity. The preventive strategies include policy, mental healthcare services, awareness programme, and coping strategies.
CONCLUSION: More epidemiological studies are needed to evaluate the risk factors of suicide that are unique in LMIC, such as help-seeking behaviour and available mental healthcare services. Suicide prevention requires concerted effort of policymakers, healthcare services, community and individual; thus, SEM framework is suitable as a guidance for suicide prevention.

Matched MeSH terms: Suicidal Ideation
An explainable predictive model for suicide attempt risk using an ensemble learning and Shapley Additive Explanations (SHAP) approach

Nordin N, Zainol Z, Mohd Noor MH, Chan LF

Asian J Psychiatr, 2023 Jan;79:103316.
PMID: 36395702 DOI: 10.1016/j.ajp.2022.103316

Machine learning approaches have been used to develop suicide attempt predictive models recently and have been shown to have a good performance. However, those proposed models have difficulty interpreting and understanding why an individual has suicidal attempts. To overcome this issue, the identification of features such as risk factors in predicting suicide attempts is important for clinicians to make decisions. Therefore, the aim of this study is to propose an explainable predictive model to predict and analyse the importance of features for suicide attempts. This model can also provide explanations to improve the clinical understanding of suicide attempts. Two complex ensemble learning models, namely Random Forest and Gradient Boosting with an explanatory model (SHapley Additive exPlanations (SHAP)) have been constructed. The models are used for predictive interpretation and understanding of the importance of the features. The experiment shows that both models with SHAP are able to interpret and understand the nature of an individual's predictions with suicide attempts. However, compared with Random Forest, the results show that Gradient Boosting with SHAP achieves higher accuracy and the analyses found that history of suicide attempts, suicidal ideation, and ethnicity as the main predictors for suicide attempts.

Matched MeSH terms: Suicidal Ideation*
Age Changes and Suicidal Activity in Iran Over the Past Decade: A Systematic Review and Meta-Analysis

Sharif Nia H, Heidari M, Naghavi N, Lehto RH, Haghdoost AA, Jafari-Koulaee A, et al.

Omega (Westport), 2020 Oct 26.
PMID: 33106088 DOI: 10.1177/0030222820966934

This review study fills an important gap by aiming to determine the age changes in attempted and completed suicide in Iran during the past decade. A systematic review of related articles in international and Iranian databases from January 2008 to January 2020 was first conducted and relevant studies were extracted based on established criteria. Results showed that the mean age of suicide in Iran is 29.8 (range 27.7 - 31.8) years old for men and 27.4 (range 25.8 - 28.9) for women (P

Matched MeSH terms: Suicidal Ideation
Fulltext A comparative study of machine learning techniques for suicide attempts predictive model

Nordin N, Zainol Z, Mohd Noor MH, Lai Fong C

Health Informatics J, 2021 3 23;27(1):1460458221989395.
PMID: 33745355 DOI: 10.1177/1460458221989395

Current suicide risk assessments for predicting suicide attempts are time consuming, of low predictive value and have inadequate reliability. This paper aims to develop a predictive model for suicide attempts among patients with depression using machine learning algorithms as well as presents a comparative study on single predictive models with ensemble predictive models for differentiating depressed patients with suicide attempts from non-suicide attempters. We applied and trained eight different machine learning algorithms using a dataset that consists of 75 patients diagnosed with a depressive disorder. A recursive feature elimination was used to reduce the features via three-fold cross validation. An ensemble predictive models outperformed the single predictive models. Voting and bagging revealed the highest accuracy of 92% compared to other machine learning algorithms. Our findings indicate that history of suicide attempt, religion, race, suicide ideation and severity of clinical depression are useful factors for prediction of suicide attempts.

Matched MeSH terms: Suicidal Ideation*