Identification of empathic communication behaviors for enhancement of person center care: A blueprint
Bibliographic record
Abstract
Abstract Background The benefits of empathy in providing optimal healthcare have been reported in multiple studies. There has also been several studies and professional association statements identifying the need for “empathy in communicating” or “empathic communication” in delivering person‐centered‐care. However, an agreed upon definition of the components of “empathic communication” are unavailable. The purpose of this study was to create a blueprint and explore the use of empathic communication behaviors among nurses at a large skilled nursing facility. Method A multidisciplinary long‐term care team including stakeholders set out to identify the content and operationalize empathic communication behaviors. Through a systematic review 1, multiple iterations, and stakeholder input; the conceptualized empathic communication behaviors were identified and placed into three domains: Nonverbal Behaviors: Being present for others by maintaining eye contact; maintaining a welcoming and attentive body position and facial expression; observing the other person’s facial expression. Listening Skills: Asking questions to clarify the situation; repeating back what is heard. Imagination: Imagining what other people are experiencing if one were walking in their shoes, and how one would feel in a similar situation. To gauge their degree of empathic behaviors, participants were asked how often they performed specific activities. Data collected included demographics, eight empathic communication behaviors, and the Toronto Empathy Questionnaire (TEQ). Result 63 nurses (Certified Nursing Assistants: CNAs, Professional Nurses: PNs), primarily African American and Afro‐Caribbean women, completed the survey. There were significant differences in nonverbal communication skills between CNAs and PNs. We found the nurses TEQ scores were consistent with women’s scores in the general population. Conclusion These findings support the conceptualized “Eight Empathic Communication Behaviors” as a majority of respondents reported they frequently use these behaviors to gain understanding about what someone else (resident, visitor, or coworker) is communicating. Further research will include observation of nurses’ behaviors but has been delayed due to the pandemic. Exploration of strategies to foster a social environment that promotes empathic communication that promotes positive care outcomes is needed. 1. Brown, E.L., Agronin, M.E., Stein, J. (2020). A Systematic Review of Interventions to Enhance Empathy and Person‐Centered‐Care with Dementia. Res Gerontol Nurs, 13 (3):158‐168.
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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 | 0.025 | 0.030 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.010 | 0.006 |
| Science and technology studies | 0.002 | 0.005 |
| Scholarly communication | 0.006 | 0.006 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.002 | 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".