JOURNAL ARTICLE

Navigating Loss: An In-Depth Exploration of Grief and Spiritual Resilience in Hispanic and Latino Cultures.

  • Published In: Urban Social Work, 2025, v. 9, n. 2. P. 80 1 of 3

  • Database: Sociology Source Ultimate 2 of 3

  • Authored By: Olivo, Angelica 3 of 3

Abstract

Background: This was a phenomenological study that highlighted how culture, spirituality, and coping mechanisms influenced Hispanic and Latino community grief. Objective: A purposively selected sample of recordings of participant life review interviews from client records at the end-of-life comfort home identified themes on death beliefs, traditional grieving practices, cultural taboos, family roles, and religious faith, providing rich data on cultural and spiritual factors in grief. Methods: The themes that emerged from the analysis were related to death beliefs, traditional grieving practices, cultural taboos, family roles, and religious faith. The theoretical framework mixed deduction-induction approaches and was culture-sensitive to social work interventions. Findings: Findings supported a second line of evidence that diverse subgroups and the longitudinal grief experience may better inform understandings of, and improve cultural competency in, bereavement support. Conclusions: This study adds to the body of knowledge on bereavement among Hispanic and Latino communities and, potentially, to the establishment of culturally adapted interventions. [ABSTRACT FROM AUTHOR]

Additional Information

  • Source:Urban Social Work. 2025/11, Vol. 9, Issue 2, p80
  • Document Type:Article
  • Subject Area:Health and Medicine
  • Publication Date:2025
  • ISSN:2474-8684
  • DOI:10.1891/USW-2024-0022
  • Accession Number:189061591
  • Copyright Statement:Copyright of Urban Social Work is the property of Springer Publishing Company, 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.)

Looking to go deeper into this topic? Look for more articles on EBSCOhost.