JOURNAL ARTICLE
Clinician Communication in Hospice: Constructions of Reality Throughout the End-of-Life Process.
Published In: Omega: Journal of Death & Dying, 2025, v. 90, n. 3. P. 1109 1 of 3
Database: Academic Search Ultimate 2 of 3
Authored By: Tenzek, Kelly E.; Grant, Pei C.; Depner, Rachel M.; Levy, Kathryn; Byrwa, David J. 3 of 3
Abstract
The article focuses on hospice clinicians' perspectives regarding language use in end-of-life (EOL) communication to identify challenges and opportunities for fostering a trajectory of dialogue that supports a good death experience. Using qualitative data from focus groups and interviews with interdisciplinary team members—including doctors, nurses, chaplains, social workers, expressive therapists, and a pharmacist—the study applied the Opportunity Model for Presence during the End-of-Life Process (OMP-EOLP) to analyze themes related to language choices, professional roles and responsibilities, and socio-cultural considerations. Findings highlight the tension between engaging in direct conversations about death and avoidance due to cultural taboos, the importance of reframing language to meet patients' and families' needs, and the critical role of nonverbal communication. The study underscores the need for early, ongoing, and culturally sensitive advance care planning, enhanced interdisciplinary education, and the use of diverse media tools to facilitate meaningful EOL discussions, while also addressing systemic barriers within healthcare.
Additional Information
- Source:Omega: Journal of Death & Dying. 2025/02, Vol. 90, Issue 3, p1109
- Document Type:Article
- Subject Area:Psychology
- Publication Date:2025
- ISSN:0030-2228
- DOI:10.1177/00302228221116719
- Accession Number:181653316
- 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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