Digital clinical empathy in a live chat: multiple findings from a formative qualitative study and usability tests
Hanna Luetke Lanfer1, Doreen Reifegerste2, Winja Weber3
1School of Public Health, Bielefeld University, Universitaetsstrasse 25, 33615, Bielefeld, Germany. hanna.luetkelanfer@uni-bielefeld.de.
Background:
Clinical empathy is considered a crucial element in patient-centered care. The advent of digital technology in healthcare has introduced new dynamics to empathy which needs to be explored in the context of the technology, particularly within the context of written live chats. Given the growing prevalence of written live chats, this study aimed to explore and evaluate techniques of digital clinical empathy within a familial cancer-focused live chat, focusing on how health professionals can (a) understand, (b) communicate, and (c) act upon users' perspectives and emotional states.
Methods:
The study utilized a qualitative approach in two research phases. It examined the expected and implemented techniques and effectiveness of digital clinical empathy in a live chat service, involving semi-structured interviews with health professionals (n = 9), focus group discussions with potential users (n = 42), and two rounds of usability tests between health professionals (n = 9) and users (n = 18). Data were examined using qualitative content analysis.
Results:
Expected techniques of digital clinical empathy, as articulated by both users and health professionals, involve reciprocal engagement, timely responses, genuine authenticity, and a balance between professionalism and informality, all while going beyond immediate queries to facilitate informed decision-making. Usability tests confirm these complexities and introduce new challenges, such as balancing timely, authentic responses with effective, personalized information management and carefully framed referrals.
Conclusions:
The study reveals that the digital realm adds layers of complexity to the practice of clinical empathy. It underscores the importance of ongoing adaptation and suggests that future developments could benefit from a hybrid model that integrates the strengths of both AI and human health professionals to meet evolving user needs and maintain high-quality, empathetic healthcare interactions.
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