Azizpour Yosra, Sayehmiri Kourosh, Asadollahi Khairollah
Department of Epidemiology, School of Health, Ilam University of Medical Sciences, Ilam, Iran.
Department of Biostatistics, School of Health, Ilam University of Medical Sciences, Ilam, Iran.
Iran J Psychiatry. 2020 Oct;15(4):305-311. doi: 10.18502/ijps.v15i4.4296.
Suicide is a preventable social harm in the field of health. The present study aimed to design a prediction model for suicide incidence based on Box-Jenkins model in Ilam province. Using a retrospective method all completed and attempted suicide data were collected during 1993-2013. Then, using the autoregressive integrated moving average (ARIMA) model, the time series analysis of the Box-Jenkins model was conducted to predict suicide status in the coming years (2014-2015). According to the actual results obtained from the suicide data in 2014, a total of 1078 suicides were recorded and compared to the predicted results, according to the fitted model of the time series, which showed the selected model predicted 931 suicide cases, showing 86% accuracy of prediction. The series' prediction indicated 931 suicides in 2014 with a negative growth rate of 25.3% compared to 2013 and 969 suicide cases in 2015 with a positive growth rate of 3.93% compared to 2014. The results of this study showed the designed model provides a high diagnostic value to predict suicide rates. These types of models can help to predict suicide in future and plan to control and prevent suicide attempts.
自杀是健康领域一种可预防的社会危害。本研究旨在基于伊拉姆省的Box-Jenkins模型设计一个自杀发生率预测模型。采用回顾性方法收集了1993年至2013年期间所有完成的自杀和自杀未遂数据。然后,使用自回归积分滑动平均(ARIMA)模型,对Box-Jenkins模型进行时间序列分析,以预测未来几年(2014年至2015年)的自杀状况。根据2014年自杀数据获得的实际结果,共记录了1078例自杀事件,并与根据时间序列拟合模型得出的预测结果进行比较,结果显示所选模型预测了931例自杀病例,预测准确率为86%。该序列预测显示,2014年有931例自杀事件,与2013年相比负增长率为25.3%;2015年有969例自杀事件,与2014年相比正增长率为3.93%。本研究结果表明,所设计的模型对预测自杀率具有较高的诊断价值。这类模型有助于预测未来的自杀情况,并规划控制和预防自杀未遂的措施。