Publication Cover
Journal of Communication in Healthcare
Strategies, Media and Engagement in Global Health
Volume 11, 2018 - Issue 2
836
Views
0
CrossRef citations to date
0
Altmetric
Papers

The consequences of diverse empathic responses in nurse-patient interactions: a discourse analysis

ORCID Icon, &
Pages 87-94 | Published online: 24 Mar 2018
 

ABSTRACT

Background: Empathy in healthcare interactions has been a focus of considerable research since the 1980s, and discourse analysis has been used more recently to identify how empathy is accomplished in interactions between healthcare professionals and their patients. However, there has been little research using naturally occurring nurse/patient interactions.

Method: This study employs discourse analysis from an interactional sociolinguistic approach to examine and describe the interactional consequences of empathy during nurse-patient interactions.

Results: The consequence of the display of empathy was an extended interaction with numerous affiliative responses by both parties, showing evidence of good rapport and a therapeutic relationship. This is compared to interactions where minimal affiliative responses are evident. The exchange with the patient is cut short with a quick return to the clinical agenda after a momentary acknowledgement of the patient’s concern. Where empathy is not displayed, the patient does not elaborate on concerns, thereby limiting the development of rapport and trust. The display of empathy has been linked to patient satisfaction and improved patient outcomes.

Conclusion: Examining natural nurse-patient interactions allows for a greater understanding of the consequences of various communicative approaches and levels of engagement. This awareness can enable the development of stronger communicative competence of health professionals, enhancing professional practice and patient satisfaction.

Ethical approval

The study was approved by the Macquarie University Human Research Ethics Committee (reference 5201400783) and the hospital concerned.

Disclosure statement

No potential conflict of interest was reported by the author(s).

Acknowledgements

The authors would like to thank the participants and patients who took part in this project, as well as the hospital managers who allowed the project to go ahead.

Notes on contributors

Tonia Crawford is a Registered Nurse and a PhD candidate in the linguistics department, Macquarie University. She is examining intercultural communication between Registered Nurses from diverse cultural and linguistic backgrounds with their patients in the Australian health care setting. She is also a lecturer in the Faculty of Nursing at the University of Sydney.

Peter Roger is Senior Lecturer in Linguistics at Macquarie University. He studied medicine at the University of Sydney and worked as a medical practitioner for several years before going on to complete a PhD in communication sciences and disorders. He is co-author (with Sally Candlin) of Communication and Professional Relationships in Healthcare Practice (Equinox, 2013).

Sally Candlin is Honorary Senior Research Fellow in the Linguistics Department at Macquarie University. Her current research interests lie in the areas of teaching and learning, and nurse patient interactions. She has authored Therapeutic Communication (Pearson, 2008) and co-authored (with Peter Roger) Communication and Professional Relationships in Healthcare Practice (Equinox, 2013).

Additional information

Funding

This project was conducted with the financial support of an Australian Postgraduate Award.

Log in via your institution

Log in to Taylor & Francis Online

PDF download + Online access

  • 48 hours access to article PDF & online version
  • Article PDF can be downloaded
  • Article PDF can be printed
USD 65.00 Add to cart

Issue Purchase

  • 30 days online access to complete issue
  • Article PDFs can be downloaded
  • Article PDFs can be printed
USD 314.00 Add to cart

* Local tax will be added as applicable

Related Research

People also read lists articles that other readers of this article have read.

Recommended articles lists articles that we recommend and is powered by our AI driven recommendation engine.

Cited by lists all citing articles based on Crossref citations.
Articles with the Crossref icon will open in a new tab.