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"Identity confusion in complicated grief: A closer look": Correction.

Benjamin W BelletNicole J LeBlancMarie-Christine NizziMikaela L CarterFlorentine H S van der DoesJacqueline PetersDonald J RobinaughRichard J McNally
Published in: Journal of abnormal psychology (2020)
Reports an error in "Identity confusion in complicated grief: A closer look" by Benjamin W. Bellet, Nicole J. LeBlanc, Marie-Christine Nizzi, Mikaela L. Carter, Florentine H. S. van der Does, Jacqueline Peters, Donald J. Robinaugh and Richard J. McNally (Journal of Abnormal Psychology, 2020[May], Vol 129[4], 397-407). In the original article, the following acknowledgment of funding was missing from the author note: "Donald J. Robinaugh's work on this article was supported by federal funding from the National Institute of Mental Health (Grant 1K23MH113805-01A1; principal investigator: Donald J. Robinaugh)." The online version of this article has been corrected. (The following abstract of the original article appeared in record 2020-23551-001). Complicated grief (CG) is characterized by a wide range of symptoms, including identity confusion or a sense that a part of oneself has died with the decedent. Although identity confusion is a commonly reported feature of CG, little is known about which specific aspects of self-concept are compromised. In the current study, we used qualitative coding methods to investigate which aspects of the sense of self differed between those with and without CG in a sample of 77 bereaved adults. Relative to individuals without CG, those with CG provided fewer descriptors of their self-concept overall (lower self-fluency), provided sets of descriptors that consisted of fewer categories (lower self-diversity), and had lower proportions of self-relevant preferences and activities. However, group differences were not observed for proportions of any other categories of self-concept descriptors, including references to the loss, the past, or distress-related self-statements. Directions for future research and clinical implications are discussed. (PsycInfo Database Record (c) 2020 APA, all rights reserved).
Keyphrases
  • mental health
  • machine learning
  • systematic review
  • social media
  • adverse drug
  • emergency department
  • depressive symptoms