I am interested in user experience design for digital healthcare, specialising in user research and translating insights into intuitive design. I aim to apply my expertise to projects that prioritise user-centred design and impactful digital healthcare solutions.
“The project evaluated the effect of formal and informal conversational styles in healthcare chatbots on user acceptance. The findings offered recommendations for designing chatbots that adapt their style based on the situation, improving both user satisfaction and system reliability.”
Healthcare chatbots need to balance formal and informal conversational styles to optimize user trust and engagement. Formal styles are effective in conveying professionalism, while informal styles can enhance user engagement and interaction. However, how these styles specifically influence user acceptance in healthcare contexts remains underexplored.
Understanding this balance is essential for designing chatbots that meet both informational and emotional needs.
The aim of this research is to examine the effect of formal and informal conversational styles of healthcare chatbots on acceptance.
What is the effect of chatbot conversational style (formal vs informal) on acceptance?
The Design Thinking approach was employed, with the Empathize and Define stages informed by key literature, including works by Chattaraman et al. (Chattaraman et al., 2019) and Huang & Ki (Huang and Ki, 2023). This literature review focused on understanding factors such as user trust, engagement, and the impact of different conversational styles in healthcare chatbots. By identifying the essential characteristics of formal and informal conversational styles, a solid foundation was established for the prototyping and testing phases that followed.
In the “Ideation” phase, two methods for generating chatbot scripts were explored. Option A used ChatGPT to directly create scripts based on the defined characteristics, while Option B generated a detailed guideline first, which was then used to produce the scripts. The content from both approaches was iteratively modified to align with the key features identified in the initial theory. After refining these low-fidelity prototypes, the text was placed into the Botsonic platform for high-fidelity dialogue production.
For both formal (toe pain) and informal (finger pain) styles, scripts were iteratively refined using two methods:
Four participants evaluated both chatbot versions, providing feedback on dialogue style and naturalness. They preferred Option A but noted that formal style needed clearer terminology and a simpler structure, leading to bullet point formatting. For the informal style, the tone was adjusted to be more conversational and relaxed.
A within-subjects design was used, focusing on conversational style. Twenty participants completed a background questionnaire before interacting with two chatbot prototypes—one formal, one informal—across easy and difficult tasks. The order was counterbalanced to avoid learning transfer effects.
Quantitative Analysis:
Descriptive analysis summarized trust, mental effort, perceived usefulness, and ease of use. Statistical Tests were used based on p-values to identify differences between styles.
Qualitative Analysis:
An inductive thematic analysis was conducted to extract key themes from participants’ experiences.
Quantitative Results:
Analysis indicated a general preference for the formal style in terms of trust and perceived usefulness, while mental effort and ease of use were similar for both styles. No statistically significant differences were found, suggesting both styles can be effective depending on the context.
Qualitative Results:
Two main themes emerged: the informal style was engaging and personal but raised concerns about authority with complex health information. The formal style conveyed trust and reliability but could feel less accessible if overly complex. A blend of both styles may optimize user experience and acceptance.
(All laptop interfaces shown in this project were generated using Botsonic)
Bronze Award | 2024 SGADC-Singapore Art Design Competition
MSc.User Experience Design | Loughborough University | 2023-2024
BA. Product Design | Central South University | 2019-2023
