Cullen Alexis E, Jewell Amelia, Tully John, Coghlan Suzanne, Dean Kimberlie, Fahy Tom
Department of Forensic and Neurodevelopmental Sciences, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, United Kingdom.
PLoS One. 2015 Sep 24;10(9):e0138819. doi: 10.1371/journal.pone.0138819. eCollection 2015.
Incidents of absconsion in forensic psychiatric units can have potentially serious consequences, yet surprisingly little is known about the characteristics of patients who abscond from these settings. The few previous studies conducted to date have employed retrospective designs, and no attempt has been made to develop an empirically-derived risk assessment scale. In this prospective study, we aimed to identify predictors of absconsion over a two-year period and investigate the feasibility of developing a brief risk assessment scale.
The study examined a representative sample of 135 patients treated in forensic medium- and low-secure wards. At baseline, demographic, clinical, treatment-related, and offending/behavioural factors were ascertained from electronic medical records and the treating teams. Incidents of absconsion (i.e., failure to return from leave, incidents of escape, and absconding whilst on escorted leave) were assessed at a two-year follow-up. Logistic regression analyses were used to determine the strongest predictors of absconsion which were then weighted according to their ability to discriminate absconders and non-absconders. The predictive utility of a brief risk assessment scale based on these weighted items was evaluated using receiver operator characteristics (ROC).
During the two-year follow-up period, 27 patients (20%) absconded, accounting for 56 separate incidents. In multivariate analyses, four factors relating to offending and behaviour emerged as the strongest predictors of absconsion: history of sexual offending, previous absconsion, recent inpatient verbal aggression, and recent inpatient substance use. The weighted risk scale derived from these factors had moderate-to-good predictive accuracy (ROC area under the curve: 0.80; sensitivity: 067; specificity: 0.71), a high negative predictive value (0.91), but a low positive predictive value (0.34).
Potentially-targetable recent behaviours, such as inpatient verbal aggression and substance use, are strong predictors of absconsion in forensic settings; the absence of these factors may enable clinical teams to identify unnecessarily restricted low-risk individuals.
法医精神病科的患者潜逃事件可能会产生潜在的严重后果，但令人惊讶的是，对于从这些机构潜逃的患者的特征知之甚少。迄今为止进行的少数先前研究采用了回顾性设计，且未尝试制定基于实证的风险评估量表。在这项前瞻性研究中，我们旨在确定两年期间潜逃的预测因素，并研究制定简短风险评估量表的可行性。
该研究对在法医中低安全级病房接受治疗的135名患者的代表性样本进行了检查。在基线时，从电子病历和治疗团队中确定人口统计学、临床、治疗相关以及犯罪/行为因素。在两年随访时评估潜逃事件（即请假未归、逃跑事件以及在护送请假期间潜逃）。使用逻辑回归分析来确定潜逃的最强预测因素，然后根据其区分潜逃者和非潜逃者的能力进行加权。基于这些加权项目的简短风险评估量表的预测效用使用受试者工作特征（ROC）进行评估。
在两年随访期间，27名患者（20%）潜逃，发生了56起单独事件。在多变量分析中，与犯罪和行为相关的四个因素成为潜逃的最强预测因素：性犯罪史、先前潜逃、近期住院期间的言语攻击以及近期住院期间的物质使用。从这些因素得出的加权风险量表具有中等至良好的预测准确性（曲线下面积：0.80；敏感性：0.67；特异性：0.71），高阴性预测值（0.91），但阳性预测值低（0.34）。
近期可能可针对的行为，如住院期间的言语攻击和物质使用，是法医环境中潜逃的有力预测因素；这些因素的不存在可能使临床团队能够识别出限制不必要的低风险个体。
