The lived experience of family caregivers who provided end-of-life care to persons with advanced dementia
Bibliographic record
Abstract
OBJECTIVE: Dementia is a terminal illness, and family caregivers play a vital role in providing end-of-life care to their relative. The present study begins to address the paucity of research regarding end-of-life caregiving experience with dementia. METHOD: This study utilized Munhall's methodology for interpretive phenomenology. Seven women and four men were interviewed two to three times within a year of their relative's death; interviews were transcribed verbatim and hermeneutically analyzed. RESULTS: Findings reveal two essential aspects of end-of-life dementia caregiving: being-with and being-there. Further findings are organized according to the existential life worlds. Examination of the life worlds demonstrates that 1) spatiality provided a sense or lack of feeling welcome to provide end-of-life care; 2) temporality was an eternity or time melting away quickly, or the right or wrong time to die; 3) corporeality revealed feelings of exhaustion; and 4) relationality was felt as a closeness to others or in tension-filled relationships. SIGNIFICANCE OF RESULTS: An understanding from bereaved caregivers' perspectives will help healthcare practitioners better support and empathize with family caregivers. Further research is warranted that focuses on other places of death and differences in experience based on gender or relationship to the care receiver.
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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 | 0.003 | 0.011 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.006 | 0.005 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| 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".