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Record W7113682988

CARE THAT LISTENS: SHAPING INTENSIVE CARE UNIT BEREAVEMENT PROTOCOLS THROUGH THE POWER OF STORY

2025· article· en· W7113682988 on OpenAlexaboutno aff

Bibliographic record

VenueUniversity Library (University of Saskatchewan) · 2025
Typearticle
Languageen
FieldPsychology
TopicGrief, Bereavement, and Mental Health
Canadian institutionsnot available
Fundersnot available
KeywordsGriefInclusion (mineral)StorytellingIntervention (counseling)Health careUnit (ring theory)DocumentationAcute careIntensive care unit
DOInot available

Abstract

fetched live from OpenAlex

Complicated Grief (CG) is an intense and prolonged grief reaction that can significantly affect individuals’ well-being. While bereavement is a natural human experience and specific to an individual’s worldview, CG requires targeted support to mitigate long-term adverse outcomes. Bereavement care is a recognized intervention to address CG, yet there is limited guidance on effective bereavement care protocols which foster equitable, diverse, decolonized, and inclusive supports within healthcare settings, particularly in Intensive Care Units (ICUs). In Saskatchewan, no standardized or routine bereavement care protocols currently exist in ICUs, despite the demonstrated need realized from an increased risk of developing CG in the ICU. This thesis project contributes to a larger research project entitled Healing Together: Understanding and engaging healthcare providers to expand bereavement support in the ICU (Healing Together), led by a team of researchers at the University of Saskatchewan (USask), which aims to develop ICU-specific bereavement care protocols that prioritize equity, diversity, decolonization, and inclusion (EDDI). While the larger project invites ICU practitioners to develop these protocols in a co-creative workshop, this thesis research focuses on a method for sharing diverse lived experiences of bereavement with workshop attendees using a storytelling method to prompt self-reflection of power, privilege, and bias. Equity-deserving co-researchers were engaged using a storytelling method to record the lived experience of bereavement and reflect on how their worldview shaped their journey of grief. The researcher shared the stories with ICU practitioners ahead of the co-creative workshops to encourage self-reflexivity among the listeners as they later engaged in the facilitated workshop discussions. The larger ICU study shared preliminary findings with the researcher for use and translation in a knowledge mobilization (KMb) activity, where the research knowledge was returned to the storytellers, and demonstrates the larger study’s priority to champion patients as research partners. Following the online KMb activity, the researcher facilitated a sharing circle with the co-researchers to explore three research questions that addressed: how storytelling supports the expression of worldview and grief experiences; whether storytellers perceive their knowledge had an impact on co-creative workshops and ICU practitioners; and finally, how the storytellers respond to the KMb activity. Using poetic transcription to create co-researcher-voiced poems from sharing circle discussions, findings suggest that storytellers perceived sharing their stories with healthcare practitioners an effective method for evoking empathy with the listeners. Nurtured through a trusting relationship among the researcher and co-researchers, storytelling empowers co-researchers through self-determination and contributes to the co-creation of bereavement care that is culturally safe, inclusive, and responsive to diverse needs. This work offers a meaningful contribution to improving end-of-life practices in ICUs and creates a space for equity-deserving voices in healthcare transformation.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.105
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.001
Scholarly communication0.0000.001
Open science0.0010.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.038
GPT teacher head0.274
Teacher spread0.236 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designQualitative
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations0
Published2025
Admission routes1
Has abstractyes

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