JOURNAL ARTICLE
Examining the Basic Assumption of Psychoanalytic Theory Regarding Normal and Abnormal Grief: Roles of Unfinished Businesses and Bereavement Related Guilt.
Published In: Omega: Journal of Death & Dying, 2024, v. 90, n. 2. P. 783 1 of 3
Database: Academic Search Ultimate 2 of 3
Authored By: Keser, Emrah; Ar-Karci, Yagmur; Danışman, Ilgın Gökler 3 of 3
Abstract
This article investigates the role of bereavement-related guilt as a mediator between unresolved pre-death relational conflict and maladaptive grief outcomes, specifically prolonged grief disorder (PGD) and depressive symptoms, within a psychoanalytic framework. Using a sample of 447 adults who lost a first-degree family member within the past five years, the study employed the Unfinished Business in Bereavement Scale (UBBS), Bereavement Guilt Scale (BGS), Prolonged Grief Disorder Scale (PG-13), and Beck Depression Inventory (BDI). Results indicated that higher levels of unresolved conflict were associated with increased prolonged grief and depression symptoms, and these relationships were significantly mediated by feelings of guilt related to the bereavement. The findings support psychoanalytic theory's premise that ambivalent feelings and guilt stemming from conflictual pre-death relationships contribute to pathological grief, while also acknowledging limitations related to self-report measures and cross-sectional design. The study suggests clinical attention to unresolved relational conflicts and guilt may enhance grief interventions across therapeutic approaches.
Additional Information
- Source:Omega: Journal of Death & Dying. 2024/12, Vol. 90, Issue 2, p783
- Document Type:Article
- Subject Area:Psychology
- Publication Date:2024
- ISSN:0030-2228
- DOI:10.1177/00302228221111946
- Accession Number:180358125
- Copyright Statement:Copyright of Omega: Journal of Death & Dying is the property of Sage Publications Inc. and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
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