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A Cognitive Attachment Model of prolonged grief: Integrating attachments, memory, and identity

Overview of attention for article published in Clinical Psychology Review, May 2013
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Title
A Cognitive Attachment Model of prolonged grief: Integrating attachments, memory, and identity
Published in
Clinical Psychology Review, May 2013
DOI 10.1016/j.cpr.2013.05.001
Pubmed ID
Authors

Fiona Maccallum, Richard A. Bryant

Abstract

Prolonged grief (PG), otherwise known as complicated grief, has attracted much attention in recent years as a potentially debilitating condition that affects approximately 10% of bereaved people. We propose a model of PG that integrates processes of attachment, self-identity, and autobiographical memory. The paper commences with a discussion of the PG construct and reviews current evidence regarding the distinctiveness of PG from other bereavement related-outcomes. We then review the evidence regarding the dysfunctional attachments, appraisals, and coping styles that people with PG display. Recent evidence pertaining to the patterns of autobiographical memory in PG is described in the context of the self-memory system. This system provides a unifying framework to understand the roles of personal memories, identity, attachments, and coping responses in PG. The proposed model places emphasis on how one's sense of identity influences yearning, memories of the deceased, appraisals, and coping strategies, to maintain a focus on the loss. The model is discussed in relation to existing models of PG. The potential for shaping treatment strategies to shift perceptions of the self is then outlined. Finally, we outline future directions to test propositions stemming from the model and enhance our understanding of the mechanisms underlying PG.

Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 263 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United Kingdom 2 <1%
Sweden 1 <1%
Ireland 1 <1%
Canada 1 <1%
Unknown 258 98%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 50 19%
Student > Master 41 16%
Student > Bachelor 36 14%
Student > Doctoral Student 28 11%
Researcher 17 6%
Other 42 16%
Unknown 49 19%
Readers by discipline Count As %
Psychology 151 57%
Social Sciences 18 7%
Medicine and Dentistry 13 5%
Nursing and Health Professions 6 2%
Environmental Science 4 2%
Other 18 7%
Unknown 53 20%