The Grief and Bereavement Experiences of Informal Caregivers: A Scoping Review of the North American Literature
Bibliographic record
Abstract
Background: Informal caregivers are a significant part of the hospice and palliative care landscape as members of the interdisciplinary care team. Despite this, little is known about the impact this responsibility has on informal caregivers’ experiences of grief and bereavement. Objective: To address this, a scoping review of the literature was conducted to explore the current state of knowledge toward grief and bereavement of informal caregivers of adult/geriatric patients in the hospice and palliative/end-of-life care realm within North America. Methods: Using Arksey and O’Malley's 5-step framework, key electronic health care and social sciences databases (eg, CINAHL, MEDLINE, ProQuest Sociological Abstracts, PsycINFO) alongside gray literature sources were searched and screened against inclusion and exclusion criteria. A thematic content analysis was used to identify key themes. Results: 29 articles met the final inclusion criteria with 3 central themes emerging: (1) mediators of grief, (2) grief experiences, and (3) types of grief. Discussion: Informal caregivers encounter unique grief and bereavement experiences: The range of psychosocial outcomes, both negative and positive, can be affected by various mediators such as caregiver burden, demographics, disease type of the patient being cared for, etc. Bereavement interventions must be designed with the mediators of grief in mind. Conclusions: Understanding the nuances of informal caregivers’ experiences with grief and bereavement will inform and advance practice, policy, and research. Practitioners/clinicians should be further educated on how to properly acknowledge the complexity of grief and bereavement for informal caregivers, specifically paying attention to mediators. Further research needs to consider the role of culture.
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 | 0.011 | 0.038 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.022 | 0.025 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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.
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".