The empathetic response in nurses who treat pain: concept analysis
Bibliographic record
Abstract
AIM: This paper is a report of a concept analysis of empathy. BACKGROUND: It is widely accepted that an empathetic response is necessary for nurses to deliver adequate pain relief and therapeutic care. Previous work suggests that empathy is a learned behaviour, and thus can be blocked if necessary to diminish personal distress. METHODS: A computerized search of the CINAHL, MEDLINE, PsycINFO, and Web of Science databases from 1980 to 2007 was conducted, using the keywords pain and empathy, both alone and in combination. Similar concepts such as sympathy, caring and compathy were included if the database distinguished between these concepts. Twenty-five relevant articles were reviewed and Rodgers evolutionary concept analysis process was used to clarify the concept. FINDINGS: The recent observation that a mirror-like neural response occurs in the brain of a person witnessing another in pain provides compelling evidence that empathetic arousal may occur independent of the previously described attributes of prior experience or learned cognitive appraisal. CONCLUSION: While the empathetic response of care providers plays a central role in the recognition and treatment of pain, nurses are taught that regulation of this response is important to protect themselves against the traumatic effects of seeing patients in pain. However, there is emerging evidence that some elements of empathetic arousal are autonomic and therefore unable to be fully controlled; this may have important implications for nurses' vulnerability.
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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 | 0.006 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.006 | 0.006 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".