Fassino S, Amianto F, Abbate Daga G, Leombruni P
Unit of Psychiatry, Department of Neurosciences, University of Turin, Turin, Italy.
Panminerva Med. 2007 Mar;49(1):7-15.
The dropout from care in public psychiatric units is a frequent event and strategies to reduce its incidence are still debated. This study aims to determine which personality and psychopathology dimensions influence the dropout in a psychiatric unit.
All new patients referred to a public psychiatric outpatient service were tested with self-administered inventories assessing personality traits (TCI), parental bonding (PBI), and psychopathology (SCL-90; BDI; STAXI). Completers were divided into nondropout, late dropout, and early dropout groups which were compared with each other with respect to diagnosis, referral, demographic data and the inventories. Logistic regression was performed between dropout and non dropout subjects with respect to the significantly differing variables.
No clinical or demographic characteristic predict dropout. Numerous SCL-90 psychopathology scales, state anger and some TCI personality facets distinguish dropout from in care subjects. Psychoticism and sentimentalism have been evidenced independent predictors of dropout.
In the present study dropout from the psychiatric unit is more related to personal characteristics than to sociodemographic variables or diagnosis. Dropout is related to personality and psychopathology characteristics which may reduce subject's relational skills and impair therapeutic alliance. These traits may also influence subjects' perception of the service quality and of the assessment procedure. The acknowledgement of such traits as possible determinants of dropout may orient service organization and personnel education to prevent this phenomenon in health care services. Strategies for preventing dropout are discussed.
公立精神科病房的失访情况屡见不鲜,降低其发生率的策略仍存在争议。本研究旨在确定哪些人格和精神病理学维度会影响精神科病房的失访情况。
所有转诊至公立精神科门诊服务的新患者均接受了自我管理的问卷调查,以评估人格特质(TCI)、父母养育方式(PBI)和精神病理学情况(SCL - 90;BDI;STAXI)。完成调查的患者被分为未失访组、晚期失访组和早期失访组,并就诊断、转诊、人口统计学数据和调查问卷进行相互比较。针对存在显著差异的变量,对失访和未失访受试者进行逻辑回归分析。
没有临床或人口统计学特征能够预测失访情况。众多SCL - 90精神病理学量表、状态愤怒以及一些TCI人格方面能够区分失访患者和在院患者。精神质和情感主义已被证明是失访的独立预测因素。
在本研究中,精神科病房的失访更多地与个人特征相关,而非社会人口统计学变量或诊断。失访与人格和精神病理学特征有关,这些特征可能会降低患者的社交技能并损害治疗联盟。这些特质还可能影响患者对服务质量和评估程序的认知。认识到这些特质可能是失访的决定因素,可为服务组织和人员培训提供方向,以预防医疗服务中的这一现象。文中讨论了预防失访的策略。