Compassion: a scoping review of the healthcare literature
Bibliographic record
Abstract
Background Recent concerns about suboptimal patient care and a lack of compassion have prompted policymakers to question the preparedness of clinicians for the challenging environment in which they practice. Compassionate care is expected by patients and is a professional obligation of clinicians; however, little is known about the state of research on clinical compassion. The purpose of this scoping review was to map the literature on compassion in clinical healthcare. Methods Searches of eight electronic databases and the grey literature were conducted to identify empirical studies published over the last 25 years. Eligible studies explored perceptions or interventions of compassionate care in clinical populations, healthcare professionals, and healthcare students. Following the title and abstract review, two reviewers independently screened full-texts articles, and extracted study data. A narrative approach to synthesizing and mapping the literature was used. Results and discussion Of 36,637 records, 648 studies were retrieved and 44 studies were included in the review. Less than one third of studies included patients. Six themes emerged from studies that explored perceptions of compassionate care: nature of compassion, development of compassion, interpersonal factors related to compassion, action and practical compassion, barriers and enablers of compassion, and outcomes of compassion. Intervention studies included two compassionate care trials with patients and eight educational programs that aimed to improve compassionate care in clinicians and students. Conclusions This review identifies the limited empirical understanding of compassion in healthcare, highlighting the lack of patient and family voices in compassion research. A deeper understanding of the key behaviors and attitudes that lead to improved patient-reported outcomes through compassionate care is necessary.
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 | 0.022 | 0.090 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.006 | 0.005 |
| Bibliometrics | 0.055 | 0.045 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.007 | 0.007 |
| Open science | 0.003 | 0.006 |
| Research integrity | 0.005 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 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".