Clinicians’ Emotional Responses During Conversations About Serious Illness
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By
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Akira Kuriyama
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Rebecca Kuehn
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Deborah J. Cook
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October 29, 2026
Clinical Scorecard: Clinicians’ Emotional Responses During Conversations About Serious Illness
At a Glance
| Category | Detail |
|---|---|
| Condition | Clinician emotional expression and self-disclosure in serious illness conversations |
| Key Mechanisms | A factorial vignette survey assessed how physician self-disclosure, verbal sadness, and visible tears related to public ratings of comfort, trust, compassion, and professionalism. |
| Target Population | 1572 members of the Swiss general public; findings concern public responses to hypothetical scenarios, not patients’ experiences in actual clinical encounters. |
| Care Setting | Serious illness conversations, particularly when treatment fails or is unavailable; evidence is based on written vignettes rather than clinical encounters. |
Key Highlights
- Brief physician self-disclosure and verbal expressions of sadness were associated with higher ratings of comfort, trust, compassion, and professionalism.
- Sadness accompanied by tears was associated with greater comfort, trust, and compassion and did not significantly lower perceived professionalism.
- Ratings differed between language groups, indicating that responses may vary by linguistic and cultural context.
- The survey provides indirect, hypothesis-generating evidence because participants evaluated written hypothetical scenarios rather than real conversations.
- The authors advise against scripted emotional expression and emphasize keeping attention on the patient’s suffering and needs.
Guideline-Based Recommendations
Diagnosis
Management
- The authors advise against treating self-disclosure or emotional expression as scripted communication techniques.
- When expressing emotion or disclosing personal information, direct it toward meeting the patient’s needs rather than serving the clinician.
- Keep the focus on the patient’s suffering; avoid expressions that shift emotional responsibility to the patient or require the patient to comfort the clinician.
- The authors note that a concise remark such as “I am truly sorry that we have reached this point” may acknowledge the seriousness of the circumstances.
Monitoring & Follow-up
- Attend to how the patient responds, recognizing that the meaning and acceptability of clinician emotion may vary by individual and context.
Risks
- The source states that performed or clinician-focused emotion may be perceived as insincere or as sympathy rather than empathy or compassion.
- The study did not assess uncontrolled distress, prolonged crying, or situations in which patients felt obligated to comfort the clinician.
- Written vignettes cannot represent tone, silence, facial expression, eye contact, gestures, or other body language.
Patient & Prescribing Data
No treatment or prescribing population was studied. Survey respondents were members of the Swiss general public; 10.8% reported a chronic illness and 23.0% reported that someone close to them had one.
Not applicable: the article reports a communication survey, not a treatment or prescribing study.
Clinical Best Practices
- Recognize patients as people with fears, hopes, relationships, and sources of meaning.
- Use emotional expression, if appropriate, to acknowledge the patient’s experience without redirecting attention to the clinician.
- A patient-informed framework cited in the source distinguishes sympathy, described as a pity-based response focused on the observer, from empathy and compassion, which involve understanding suffering and a commitment to address the person’s needs.
- Interpret findings cautiously because responses to clinician emotion were context-dependent and the study did not involve actual clinical encounters.
Related Resources & Content
Based on findings from:
Clinician Emotion in Serious Illness Conversations
Akira Kuriyama, Rebecca Kuehn, Deborah J. Cook. Journal Of General Internal Medicine, 2026.
https://link.springer.com/article/10.1007/s11606-026-10887-5
This content is an AI-generated, fully rewritten summary based on a published scholarly article. It does not reproduce the original text and is not a substitute for the original publication. Readers are encouraged to consult the source for full context, data, and methodology.