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用于研究自杀动态的马尔可夫链模型:罗斯定理的一个例证

A Markov chain model for studying suicide dynamics: an illustration of the Rose theorem.

作者信息

Yip Paul Siu Fai, So Bing Kwan, Kawachi Ichiro, Zhang Yi

机构信息

Department of Social Work and Social Administration, The University of Hong Kong, Hong Kong, Hong Kong.

出版信息

BMC Public Health. 2014 Jun 19;14:625. doi: 10.1186/1471-2458-14-625.

DOI:10.1186/1471-2458-14-625
PMID:24948330
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC4082176/
Abstract

BACKGROUND

High-risk strategies would only have a modest effect on suicide prevention within a population. It is best to incorporate both high-risk and population-based strategies to prevent suicide. This study aims to compare the effectiveness of suicide prevention between high-risk and population-based strategies.

METHODS

A Markov chain illness and death model is proposed to determine suicide dynamic in a population and examine its effectiveness for reducing the number of suicides by modifying certain parameters of the model. Assuming a population with replacement, the suicide risk of the population was estimated by determining the final state of the Markov model.

RESULTS

The model shows that targeting the whole population for suicide prevention is more effective than reducing risk in the high-risk tail of the distribution of psychological distress (i.e. the mentally ill).

CONCLUSIONS

The results of this model reinforce the essence of the Rose theorem that lowering the suicidal risk in the population at large may be more effective than reducing the high risk in a small population.

摘要

背景

高风险策略对人群自杀预防仅有适度效果。最好将高风险策略和基于人群的策略结合起来预防自杀。本研究旨在比较高风险策略和基于人群的策略在预防自杀方面的有效性。

方法

提出一个马尔可夫链疾病与死亡模型来确定人群中的自杀动态,并通过修改模型的某些参数来检验其在减少自杀人数方面的有效性。假设人群可更新,通过确定马尔可夫模型的最终状态来估计人群的自杀风险。

结果

该模型表明,针对全体人群进行自杀预防比降低心理困扰分布(即精神病患者)高风险尾部的风险更有效。

结论

该模型结果强化了罗斯定理的精髓,即降低总体人群的自杀风险可能比降低少数人群的高风险更有效。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e25b/4082176/9e5e27efb100/1471-2458-14-625-3.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e25b/4082176/14a21fdfde94/1471-2458-14-625-1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e25b/4082176/5e20b8149060/1471-2458-14-625-2.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e25b/4082176/9e5e27efb100/1471-2458-14-625-3.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e25b/4082176/14a21fdfde94/1471-2458-14-625-1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e25b/4082176/5e20b8149060/1471-2458-14-625-2.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e25b/4082176/9e5e27efb100/1471-2458-14-625-3.jpg

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