Sympathy, empathy, and compassion: A grounded theory study of palliative care patients’ understandings, experiences, and preferences
Bibliographic record
Abstract
BACKGROUND: Compassion is considered an essential element in quality patient care. One of the conceptual challenges in healthcare literature is that compassion is often confused with sympathy and empathy. Studies comparing and contrasting patients' perspectives of sympathy, empathy, and compassion are largely absent. AIM: The aim of this study was to investigate advanced cancer patients' understandings, experiences, and preferences of "sympathy," "empathy," and "compassion" in order to develop conceptual clarity for future research and to inform clinical practice. DESIGN: Data were collected via semi-structured interviews and then independently analyzed by the research team using the three stages and principles of Straussian grounded theory. SETTING/PARTICIPANTS: Data were collected from 53 advanced cancer inpatients in a large urban hospital. RESULTS: Constructs of sympathy, empathy, and compassion contain distinct themes and sub-themes. Sympathy was described as an unwanted, pity-based response to a distressing situation, characterized by a lack of understanding and self-preservation of the observer. Empathy was experienced as an affective response that acknowledges and attempts to understand individual's suffering through emotional resonance. Compassion enhanced the key facets of empathy while adding distinct features of being motivated by love, the altruistic role of the responder, action, and small, supererogatory acts of kindness. Patients reported that unlike sympathy, empathy and compassion were beneficial, with compassion being the most preferred and impactful. CONCLUSION: Although sympathy, empathy, and compassion are used interchangeably and frequently conflated in healthcare literature, patients distinguish and experience them uniquely. Understanding patients' perspectives is important and can guide practice, policy reform, and future research.
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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 | 0.014 | 0.016 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.006 | 0.008 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.002 | 0.004 |
| 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".