یک رویکرد اکتشافی مبتنی بر داده ها در مورد خودکشی های خوشه ای
ترجمه نشده

یک رویکرد اکتشافی مبتنی بر داده ها در مورد خودکشی های خوشه ای

عنوان فارسی مقاله: خودکشی های خوشه ای: یک رویکرد اکتشافی یادگیری ماشین مبتنی بر داده ها
عنوان انگلیسی مقاله: Clustering suicides: A data-driven, exploratory machine learning approach
مجله/کنفرانس: روانپزشکی اروپایی - European Psychiatry
رشته های تحصیلی مرتبط: روانشناسی، پزشکی
گرایش های تحصیلی مرتبط: روانشناسی بالینی، روانپزشکی
کلمات کلیدی فارسی: خودکشی، روشهای خودکشی، یادگیری ماشین، خودکشی خشونت آمیز، تجزیه و تحلیل خوشه ای
کلمات کلیدی انگلیسی: Suicide، Suicide methods، Machine-learning، Violent suicide، Cluster analysis
نوع نگارش مقاله: مقاله پژوهشی (Research Article)
نمایه: MedLine - Scopus - Master Journals List - JCR
شناسه دیجیتال (DOI): https://doi.org/10.1016/j.eurpsy.2019.08.009
دانشگاه: Clinical Division of General Psychiatry, Department of Psychiatry and Psychotherapy, Medical University of Vienna, Währinger Gürtel 18-20, 1090 Vienna, Austria
ناشر: الزویر - Elsevier
نوع ارائه مقاله: ژورنال
نوع مقاله: ISI
سال انتشار مقاله: 2019
ایمپکت فاکتور: 3/287 در سال 2019
شاخص H_index: 85 در سال 2020
شاخص SJR: 1/595 در سال 2019
شناسه ISSN: 0924-9338
شاخص Quartile (چارک): Q1 در سال 2019
فرمت مقاله انگلیسی: PDF
تعداد صفحات مقاله انگلیسی: 5
وضعیت ترجمه: ترجمه نشده است
قیمت مقاله انگلیسی: رایگان
آیا این مقاله بیس است: خیر
آیا این مقاله مدل مفهومی دارد: ندارد
آیا این مقاله پرسشنامه دارد: ندارد
آیا این مقاله متغیر دارد: ندارد
کد محصول: E13965
رفرنس: دارای رفرنس در داخل متن و انتهای مقاله
فهرست انگلیسی مطالب

Abstract


1- Introduction


2- Material and methods


3-  Results


4- Discussion


5- Conclusions


References

نمونه متن انگلیسی مقاله

Abstract


Methods of suicide have received considerable attention in suicide research. The common approach to differentiate methods of suicide is the classification into “violent” versus “non-violent” method. Interestingly, since the proposition of this dichotomous differentiation, no further efforts have been made to question the validity of such a classification of suicides. This study aimed to challenge the traditional separation into “violent” and “non-violent” suicides by generating a cluster analysis with a data-driven, machine learning approach. In a retrospective analysis, data on all officially confirmed suicides (N = 77,894) in Austria between 1970 and 2016 were assessed. Based on a defined distance metric between distributions of suicides over age group and month of the year, a standard hierarchical clustering method was performed with the five most frequent suicide methods. In cluster analysis, poisoning emerged as distinct from all other methods – both in the entire sample as well as in the male subsample. Violent suicides could be further divided into sub-clusters: hanging, shooting, and drowning on the one hand and jumping on the other hand. In the female sample, two different clusters were revealed – hanging and drowning on the one hand and jumping, poisoning, and shooting on the other. Our data-driven results in this large epidemiological study confirmed the traditional dichotomization of suicide methods into “violent” and “non-violent” methods, but on closer inspection “violent methods” can be further divided into sub-clusters and a different cluster pattern could be identified for women, requiring further research to support these refined suicide phenotypes.


Introduction


Suicide is a major public health issue accounting for over one million deaths per year making it the tenth leading cause of death worldwide [1] and the leading cause of preventable death in the elderly [2]. In 2016 the annual global age-standardized suicide rate of 10.5 per 100,000 population. Despite some progress and extensive research in the field of suicidology, predicting attempts and deaths by suicide still remains a challenge – both in a scientifically controlled setting and in clinical reality [3]. The lack of predictability makes preventive action difficult – both in clinical mental health care settings with individual patients as well as at aggregated levels for risk groups and entire populations. Additionally, the lethality of suicide methods differs greatly, which leads to restriction of lethal or violent means of suicide as the most recommended preventive measure [4–8]. In Austria, suicide rates have been steadily declining since the mid-80 s, from 1990 to 2000 the annual rate was 21.3 per 100,000 persons and from 2000 to 2010 it further decreased to 16.9. The only age-group showing increasing rates were males aged over 80. Women showed a more marked decrease than men [9,10]. Methods of suicide have received considerable attention in suicide research [11] especially regarding prevention and mean’s restriction [7,8].

  • اشتراک گذاری در

دیدگاه خود را بنویسید:

تاکنون دیدگاهی برای این نوشته ارسال نشده است

یک رویکرد اکتشافی مبتنی بر داده ها در مورد خودکشی های خوشه ای
نوشته های مرتبط
مقالات جدید
لوگوی رسانه های برخط

logo-samandehi

پیوندها