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基于多层感知器的边缘型人格障碍非线性预测模型

A Non-linear Predictive Model of Borderline Personality Disorder Based on Multilayer Perceptron.

作者信息

Maldonato Nelson M, Sperandeo Raffaele, Moretto Enrico, Dell'Orco Silvia

机构信息

Department of Neuroscience, Reproductive and Odontostomatological Sciences, University of Naples Federico II, Naples, Italy.

Scuola in Psicoterapia Gestaltica Integrata, Torre Annunziata, Italy.

出版信息

Front Psychol. 2018 Apr 4;9:447. doi: 10.3389/fpsyg.2018.00447. eCollection 2018.

Abstract

Borderline Personality Disorder is a serious mental disease, classified in Cluster B of DSM IV-TR personality disorders. People with this syndrome presents an anamnesis of traumatic experiences and shows dissociative symptoms. Since not all subjects who have been victims of trauma develop a Borderline Personality Disorder, the emergence of this serious disease seems to have the fragility of character as a predisposing condition. Infect, numerous studies show that subjects positive for diagnosis of Borderline Personality Disorder had scores extremely high or extremely low to some temperamental dimensions (harm Avoidance and reward dependence) and character dimensions (cooperativeness and self directedness). In a sample of 602 subjects, who have had consecutive access to an Outpatient Mental Health Service, it was evaluated the presence of Borderline Personality Disorder using the semi-structured interview for the DSM IV-TR personality disorders. In this population we assessed the presence of dissociative symptoms with the Dissociative Experiences Scale and the personality traits with the Temperament and Character Inventory developed by Cloninger. To assess the weight and the predictive value of these psychopathological dimensions in relation to the Borderline Personality Disorder diagnosis, a neural network statistical model called "multilayer perceptron," was implemented. This model was developed with a dichotomous dependent variable, consisting in the presence or absence of the diagnosis of borderline personality disorder and with five covariates. The first one is the taxonomic subscale of dissociative experience scale, the others are temperamental and characterial traits: Novelty-Seeking, Harm-Avoidance, Self-Directedness and Cooperativeness. The statistical model, that results satisfactory, showed a significance capacity (89%) to predict the presence of borderline personality disorder. Furthermore, the dissociative symptoms seem to have a greater influence than the character traits in the borderline personality disorder e disease. In conclusion, the results seem to indicate that to borderline personality disorder development, contribute both psychic factors, such as temperament and character traits, and environmental factors, such as traumatic events capable of producing dissociative symptoms. These factors interact in a nonlinear way in producing maladaptive behaviors typical of this disorder.

摘要

边缘性人格障碍是一种严重的精神疾病,归类于《精神疾病诊断与统计手册》第四版修订版(DSM IV-TR)人格障碍中的B类。患有这种综合征的人有创伤经历的病史,并表现出解离症状。由于并非所有受过创伤的人都会患上边缘性人格障碍,这种严重疾病的出现似乎以性格脆弱为 predisposing 条件。实际上,大量研究表明,被诊断为边缘性人格障碍呈阳性的受试者在某些气质维度(回避伤害和奖赏依赖)和性格维度(合作性和自我导向性)上得分极高或极低。在一个连续接受门诊心理健康服务的602名受试者样本中,使用针对DSM IV-TR人格障碍的半结构化访谈评估边缘性人格障碍的存在情况。在这个群体中,我们使用解离体验量表评估解离症状的存在情况,并使用克隆宁格开发的气质和性格量表评估人格特质。为了评估这些精神病理维度相对于边缘性人格障碍诊断的权重和预测价值,实施了一种名为“多层感知器”的神经网络统计模型。该模型是用一个二分因变量开发的,该因变量包括边缘性人格障碍诊断的存在与否以及五个协变量。第一个是解离体验量表的分类子量表,其他是气质和性格特质:寻求新奇、回避伤害、自我导向和合作性。结果令人满意的统计模型显示出预测边缘性人格障碍存在的显著能力(89%)。此外,解离症状在边缘性人格障碍疾病中似乎比性格特质有更大的影响。总之,结果似乎表明,对边缘性人格障碍的发展有贡献的既有心理因素,如气质和性格特质,也有环境因素,如能够产生解离症状的创伤性事件。这些因素在产生这种障碍典型的适应不良行为中以非线性方式相互作用。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c5ca/5893824/4b0dd2350d08/fpsyg-09-00447-g0001.jpg

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