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Inclusion of the other in the self as a potential risk factor for prolonged grief disorder: A comparison of patients with matched bereaved healthy controls
Clinical Psychology & Psychotherapy ( IF 3.198 ) Pub Date : 2021-11-25 , DOI: 10.1002/cpp.2697
Octavia Harrison 1 , Sabine Windmann 2 , Rita Rosner 3 , Regina Steil 1, 4
Affiliation  

Pathological grief has received increasing attention in recent years, as about 10% of the bereaved suffer from one kind of it. Pathological grief in the form of prolonged grief disorder (PGD) is a relatively new diagnostic category which will be included into the upcoming ICD-11. To date, various risk and protective factors, as well as treatment options for pathological grief, have been proposed. Nevertheless, empirical evidence in that area is still scarce. Our aim was to identify the association of interpersonal closeness with the deceased and bereavement outcome. Interpersonal closeness with the deceased in 54 participants (27 patients suffering from PGD and 27 bereaved healthy controls) was assessed as the overlap of pictured identities via the inclusion of the other in the self scale (IOS scale). In addition to that, data on PGD symptomatology, general mental distress and depression were collected. Patients suffering from PGD reported higher inclusion of the deceased in the self. By contrast, they reported feeling less close towards another living close person. Results of the IOS scale were associated with PGD severity, general mental distress and depression. Inclusion of the deceased in the self is a significant statistical predictor for PGD caseness.

中文翻译:

将他人纳入自我作为长期悲伤障碍的潜在风险因素:患者与匹配的失去亲人的健康对照者的比较

近年来,病理性悲痛越来越受到关注,大约 10% 的丧亲者患有一种病态悲痛。长期悲伤障碍 (PGD) 形式的病理性悲伤是一个相对较新的诊断类别,将被纳入即将发布的 ICD-11。迄今为止,已经提出了各种风险和保护因素,以及病理性悲伤的治疗方案。然而,该领域的经验证据仍然很少。我们的目的是确定人际亲密度与死者和丧亲结果之间的关系。54 名参与者(27 名患有 PGD 的患者和 27 名失去亲人的健康对照组)与死者的人际亲密度被评估为通过将另一个人纳入自我量表(IOS 量表)来评估身份的重叠。在此之上,收集了有关 PGD 症状、一般精神困扰和抑郁的数据。患有 PGD 的患者报告说,死者对自己的包容性更高。相比之下,他们报告说与另一个生活亲密的人感觉不太亲近。IOS量表的结果与PGD严重程度、一般精神困扰和抑郁相关。将死者纳入自我是 PGD 案例的重要统计预测指标。
更新日期:2021-11-25
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