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Predicting suicidal behavior outcomes: an analysis of key factors and machine learning models | BMC Psychiatry

Predicting suicidal behavior outcomes: an analysis of key factors and machine learning models | BMC Psychiatry
  • O’Connor E, Gaynes B, Burda BU, Williams C, Whitlock EP. Screening for suicide risk in primary care: A systematic evidence review for the US Preventive Services Task Force. 2013. PMID: 23678511.

  • Carrasco-Barrios MT, Huertas P, Martín P, Martín C, Castillejos MC, Petkari E, et al. Determinants of suicidality in the European general population: a systematic review and meta-analysis. Int J Environ Res Public Health. 2020;17(11):4115.

    Article 
    PubMed 
    PubMed Central 

    Google Scholar 

  • Hill NT, Robinson J, Pirkis J, Andriessen K, Krysinska K, Payne A, et al. Association of suicidal behavior with exposure to suicide and suicide attempt: a systematic review and multilevel meta-analysis. PLoS Med. 2020;17(3):e1003074.

    Article 
    PubMed 
    PubMed Central 

    Google Scholar 

  • Lovero KL, Dos Santos PF, Come AX, Wainberg ML, Oquendo MA. Suicide in global mental health. Curr Psychiatry Rep. 2023;25(6):255–62.

    Article 
    PubMed 
    PubMed Central 

    Google Scholar 

  • Organization WH. Suicide worldwide in 2019: global health estimates. 2021. ISBN: 9789240026643

  • Wu KC-C, Cai Z, Chang Q, Chang S-S, Yip PSF, Chen Y-Y. Criminalisation of suicide and suicide rates: an ecological study of 171 countries in the world. BMJ open. 2022;12(2):e049425.

    Article 
    PubMed 
    PubMed Central 

    Google Scholar 

  • Mirdamadi M. How does the death conscious culture of Iran affect experiences of depression? Cult Med Psychiatry. 2019;43(1):56–76.

    Article 
    PubMed 

    Google Scholar 

  • Bachmann S. Epidemiology of suicide and the psychiatric perspective. Int J Environ Res Public Health. 2018;15(7):1425.

    Article 
    PubMed 
    PubMed Central 

    Google Scholar 

  • Kiani Chalmardi A, Rashid S, Honarmand P, Tamook F. A structural test of the interpersonal theory of suicide model in students. Contemporary psychology. Biannual J Iran Psychol Association. 2018;13(1):50–61.

    Google Scholar 

  • Kim S, Park J, Lee H, Lee H, Woo S, Kwon R et al. Global public concern of childhood and adolescence suicide: a new perspective and new strategies for suicide prevention in the post-pandemic era. World J Pediatr. 2024:20(9):872–900.

  • Qin P, Syeda S, Canetto SS, Arya V, Liu B, Menon V, et al. Midlife suicide: a systematic review and meta-analysis of socioeconomic, psychiatric and physical health risk factors. J Psychiatr Res. 2022;154:233–41.

    Article 
    PubMed 

    Google Scholar 

  • Likhvar V, Honda Y, Ono M. Relation between temperature and suicide mortality in Japan in the presence of other confounding factors using time-series analysis with a semiparametric approach. Environ Health Prev Med. 2011;16:36–43.

    Article 
    PubMed 

    Google Scholar 

  • Vidal-Ribas P, Govender T, Sundaram R, Perlis RH, Gilman SE. Prenatal origins of suicide mortality: a prospective cohort study in the United States. Translational Psychiatry. 2022;12(1):14.

    Article 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar 

  • Ropper AH, Seena Fazel MD, Runeson B. MD Ph D N Engl J Med. 2020;382:266–74.

    Article 

    Google Scholar 

  • Ehtemam H, Sadeghi Esfahlani S, Sanaei A, Ghaemi MM, Hajesmaeel-Gohari S, Rahimisadegh R, et al. Role of machine learning algorithms in suicide risk prediction: a systematic review-meta analysis of clinical studies. BMC Med Inf Decis Mak. 2024;24(1):138.

    Article 

    Google Scholar 

  • Seyedsalehi A, Fazel S. Suicide risk assessment tools and prediction models: new evidence, methodological innovations, outdated criticisms. BMJ Ment Health. 2024;27:e300990.

  • Lee W, Lee J, Woo S-I, Choi SH, Bae J-W, Jung S, et al. Machine learning enhances the performance of short and long-term mortality prediction model in non-ST-segment elevation myocardial infarction. Sci Rep. 2021;11(1):12886.

    Article 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar 

  • Schafer KM, Kennedy G, Gallyer A, Resnik P. A direct comparison of theory-driven and machine learning prediction of suicide: a meta-analysis. PLoS ONE. 2021;16(4):e0249833.

    Article 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar 

  • Pigoni A, Delvecchio G, Turtulici N, Madonna D, Pietrini P, Cecchetti L, et al. Machine learning and the prediction of suicide in psychiatric populations: a systematic review. Translational Psychiatry. 2024;14(1):140.

    Article 
    PubMed 
    PubMed Central 

    Google Scholar 

  • Nordin N, Zainol Z, Noor MHM, Chan LF. Suicidal behaviour prediction models using machine learning techniques: a systematic review. Artif Intell Med. 2022;132:102395.

    Article 
    PubMed 

    Google Scholar 

  • Saravanan N, Moheshkumar G, Shaid VM, Purushothman S, Sanjai VG, editors. Accurate Prediction and Detection of Suicidal Risk using Random Forest Algorithm. 2024 4th International Conference on Pervasive Computing and Social Networking (ICPCSN); 2024: p. 287–92. https://doi.org/10.1109/ICPCSN62568.2024.00053.

  • Bae S-M. The prediction model of suicidal thoughts in Korean adults using decision tree analysis: a nationwide cross-sectional study. PLoS ONE. 2019;14(10):e0223220.

    Article 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar 

  • Su C, Aseltine R, Doshi R, Chen K, Rogers SC, Wang F. Machine learning for suicide risk prediction in children and adolescents with electronic health records. Translational Psychiatry. 2020;10(1):413.

    Article 
    PubMed 
    PubMed Central 

    Google Scholar 

  • Aslan H, Yılmaz AB, Jeong N, Lee S, Choi C, editors. Prediction of number of suicidal people based on KNN. 2022 International Conference on Electronics, Information, and Communication (ICEIC); 2022; p. 1–4. https://doi.org/10.1109/ICEIC54506.2022.9748557.

  • Indrawan G, Sudiarsa I, Agustini K, Sariyasa S. Smooth support vector machine for suicide-related behaviours prediction. Int J Electr Comput Eng. 2018;8(5):3399.

    Google Scholar 

  • Boudreaux ED, Rundensteiner E, Liu F, Wang B, Larkin C, Agu E, et al. Applying machine learning approaches to suicide prediction using healthcare data: overview and future directions. Front Psychiatry. 2021;12:707916.

    Article 
    PubMed 
    PubMed Central 

    Google Scholar 

  • Sidey-Gibbons JA, Sidey-Gibbons CJ. Machine learning in medicine: a practical introduction. BMC Med Res Methodol. 2019;19:1–18.

    Article 

    Google Scholar 

  • Villeneuve PJ, Huynh D, Lavigne É, Colman I, Anisman H, Peters C, et al. Daily changes in ambient air pollution concentrations and temperature and suicide mortality in Canada: findings from a national time-stratified case-crossover study. Environ Res. 2023;223:115477.

    Article 
    CAS 
    PubMed 

    Google Scholar 

  • Nie J, O’Neil A, Liao B, Lu C, Aune D, Wang Y. Risk factors for completed suicide in the general population: a prospective cohort study of 242, 952 people. J Affect Disord. 2021;282:707–11.

    Article 
    PubMed 

    Google Scholar 

  • Favril L, Yu R, Geddes JR, Fazel S. Individual-level risk factors for suicide mortality in the general population: an umbrella review. Lancet Public Health. 2023;8(11):e868–77.

    Article 
    PubMed 
    PubMed Central 

    Google Scholar 

  • Favril L, Yu R, Uyar A, Sharpe M, Fazel S. Risk factors for suicide in adults: systematic review and meta-analysis of psychological autopsy studies. BMJ Ment Health. 2022;25(4):148–55.

    Google Scholar 

  • Chau K, Kabuth B, Chau N. Gender and family disparities in suicide attempt and role of socioeconomic, School, and Health-related difficulties in early adolescence. Biomed Res Int. 2014;2014(1):314521.

    PubMed 
    PubMed Central 

    Google Scholar 

  • Breiman L. Random forests. Mach Learn. 2001;45:5–32.

    Article 

    Google Scholar 

  • Quinlan JR. Induction of decision trees. Mach Learn. 1986;1:81–106.

    Article 

    Google Scholar 

  • Stoltzfus JC. Logistic regression: a brief primer. Acad Emerg Med. 2011;18(10):1099–104.

    Article 
    PubMed 

    Google Scholar 

  • Altman NS. An introduction to kernel and nearest-neighbor nonparametric regression. Am Stat. 1992;46(3):175–85.

    Article 

    Google Scholar 

  • Cortes C, Vapnik V. Support-vector networks. Mach Learn. 1995;20:273–97.

    Article 

    Google Scholar 

  • Bergstra J, Bengio Y. Random search for hyper-parameter optimization. J Mach Learn Res. 2012;13:281−305.

  • Ling CX, Huang J, Zhang H, editors. AUC: a better measure than accuracy in comparing learning algorithms. Advances in Artificial Intelligence: 16th Conference of the Canadian Society for Computational Studies of Intelligence, AI 2003, Halifax, Canada, June 11–13, 2003, Proceedings 16; 2003: Springer.

  • Bakirarar B, Elhan AH. Class weighting technique to deal with Imbalanced Class Problem in Machine Learning: Methodological Research. Türkiye Klinikleri Biyoistatistik. 2023;15(1):19–29.

    Article 

    Google Scholar 

  • Salmi M, Atif D, Oliva D, Abraham A, Ventura S. Handling imbalanced medical datasets: review of a decade of research. Artif Intell Rev. 2024;57(10):273.

    Article 

    Google Scholar 

  • Daigle MS. Suicide prevention through means restriction: assessing the risk of substitution: a critical review and synthesis. Accid Anal Prev. 2005;37(4):625–32.

    Article 
    PubMed 

    Google Scholar 

  • Yip PS, Caine E, Yousuf S, Chang S-S, Wu KC-C, Chen Y-Y. Means restriction for suicide prevention. Lancet. 2012;379(9834):2393–9.

    Article 
    PubMed 
    PubMed Central 

    Google Scholar 

  • Beghi M, Rosenbaum JF, Cerri C, Cornaggia CM. Risk factors for fatal and nonfatal repetition of suicide attempts: a literature review. Neuropsychiatr Dis Treat. 2013:8:1725–36.

  • Chen I-M, Liao S-C, Lee M-B, Wu C-Y, Lin P-H, Chen WJ. Risk factors of suicide mortality among multiple attempters: a national registry study in Taiwan. J Formos Med Assoc. 2016;115(5):364–71.

    Article 
    PubMed 

    Google Scholar 

  • Haghparast-Bidgoli H, Rinaldi G, Shahnavazi H, Bouraghi H, Kiadaliri AA. Socio-demographic and economics factors associated with suicide mortality in Iran, 2001–2010: application of a decomposition model. Int J Equity Health. 2018;17(1):1–7.

    Article 

    Google Scholar 

  • Denney JT, Rogers RG, Krueger PM, Wadsworth T. Adult suicide mortality in the United States: marital status, family size, socioeconomic status, and differences by sex. Soc Sci Q. 2009;90(5):1167–85.

    Article 
    PubMed 
    PubMed Central 

    Google Scholar 

  • Yoshimasu K, Kiyohara C, Miyashita K, Hygiene SRGJS. Suicidal risk factors and completed suicide: meta-analyses based on psychological autopsy studies. Environ Health Prev Med. 2008;13:243–56.

    Article 
    PubMed 
    PubMed Central 

    Google Scholar 

  • Wu Y, Schwebel DC, Huang Y, Ning P, Cheng P, Hu G. Sex-specific and age-specific suicide mortality by method in 58 countries between 2000 and 2015. Injury prevention. 2021;27(1):61–70.

  • Graetz N, Preston SH, Peele M, Elo IT. Ecological factors associated with suicide mortality among non-hispanic whites. BMC Public Health. 2020;20:1–12.

    Article 

    Google Scholar 

  • Cai Z, Junus A, Chang Q, Yip PS. The lethality of suicide methods: a systematic review and meta-analysis. J Affect Disord. 2022;300:121–9.

    Article 
    PubMed 

    Google Scholar 

  • Elnour AA, Harrison J. Lethality of suicide methods. Inj Prev. 2008;14(1):39–45.

    Article 
    CAS 
    PubMed 

    Google Scholar 

  • Durkheim E. Suicide: a study in sociology. Routledge; 2005.

    Book 

    Google Scholar 

  • Joiner TE. Why people die by suicide. Harvard University Pres; 2005.

    Google Scholar 

  • Amini P, Ahmadinia H, Poorolajal J, Amiri MM. Evaluating the high risk groups for suicide: a comparison of logistic regression, support vector machine, decision tree and artificial neural network. Iran J Public Health. 2016;45(9):1179.

    PubMed 
    PubMed Central 

    Google Scholar 

  • Belsher BE, Smolenski DJ, Pruitt LD, Bush NE, Beech EH, Workman DE, et al. Prediction models for suicide attempts and deaths: a systematic review and simulation. JAMA Psychiatry. 2019;76(6):642–51.

    Article 
    PubMed 

    Google Scholar 

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