Caring for Grievers: A Scoping Review of Bereavement Practice Approaches and Support Strategies
Bibliographic record
Abstract
Bereavement support is a foundational element of palliative care social work, yet practice approaches and support strategies remain varied. This scoping review was initiated in response to a Canadian children's hospice's interest in expanding its bereavement services. The aim was to identify and critically reflect on assessment strategies and professional approaches used with bereaved children, youth, and adults, and to consider how these align, or diverge, from the values and practices of palliative care social work. A review of evidence syntheses published between 2015 and September 2024 was conducted across four databases: MEDLINE, Embase, PsycINFO, and CINAHL. Seventy-one articles met inclusion criteria, identifying over 400 distinct assessment tools and a wide range of support approaches. This review also highlighted gaps in the literature, such as methodological limitations (risk of bias, lack of control groups, limited follow-up), conceptual ambiguity, and challenges in applying evidence to practice. Viewed through a palliative care social work lens, the findings underscore the need to understand grief as a uniquely human experience requiring systems of support. Expanding bereavement care involves individual service delivery in addition to building cohesive programming and integrated systems that acknowledge and support grief across contexts.
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 machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.013 | 0.040 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.004 |
| Bibliometrics | 0.019 | 0.020 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".