Feeling like a burden to others: a systematic review focusing on the end of life
Bibliographic record
Abstract
Research into the burden of illness has focused predominantly on family caregivers, with little consideration of the other side of the caregiving relationship-care recipients' perspectives on having become a 'burden to others'. However, there is now a small but growing body of evidence to suggest that worry about creating burden to others is a common and troubling concern for people who are nearing the end of their lives. This concern is referred to as 'self-perceived burden'. The present study provides a systematic review of the literature, addressing self-perceived burden at the end of life. Using standard methods, literature was searched for relevant studies in palliative care and related fields. The review revealed that self-perceived burden is reported as a significant problem by 19- 65% of terminally ill patients. It is correlated with loss of dignity, suffering, and a 'bad death'. Self-perceived burden has also been identified as a relevant factor in death-hastening acts among patients with life-threatening illness, as well as in clinical decisions, such as the choice of place of care at the end of life, advance directives, and acceptance of treatment. Given the unique challenges faced by patients with advanced disease and their families, there is a need for further investigation into this under-researched area.
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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 | 0.004 | 0.021 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.006 | 0.003 |
| Bibliometrics | 0.008 | 0.013 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".