Smart sheba: an investigation on the effectiveness of integrating LLM enabled chatbots and using a user-centred design strategy to enhance user experience of older adults
Abstract
Elderly users face physical, behavioral, and cognitive constraints as they age. As a
considerable portion of the world’s population comprises elderly people, the graphical
user interfaces (GUI) of commercial technology applications should be simplified
to mobilize this age bracket’s soft skills and technology consumption. Yet, the comfort
of this age range is often overlooked while designing smart technology interfaces.
Several studies indicate potential design strategies for different technologies.
The paper, subsequently, tests an e-health application designed using UCD strategies,
consisting of chatbots using AI, to meet the cognitive needs of the elderly
and to make their interactions with the application easy, intuitive, and comfortable.
The paper introduces the use of AI, specifically the Large Language Model (LLM)
of the Natural Language Processing (NLP) system, to create a friendly and humanlike
chatbot that will assist elderly individuals or their caretakers in determining
the nature of the illness, suggest the type of specialist to refer to, and list down
hospitals that provide the required care. This research aims to build an e-health
application to study the design methodologies that might assist elderly people with
intuitive instructions across all interfaces, explore new possibilities by incorporating
User-Centric Designs (UCD) and Artificial Intelligence (AI) in the application, and
propose findings to conclude a model design for conventional applications to exhibit
an elderly-friendly framework.
After testing out this application on elderly people (N = 18), the findings from the
data gathered suggest design strategies that can be implemented or have further
research done on them to empower the elderly population to use applications on
smartphones and other smart devices independently. To conclude, this research
seeks to suggest ways to optimize smartphones and smart devices for the cognitive
needs of the elderly. This research will address the specific needs and preferences
of elderly users and assist them with medical trepidations. By addressing this gap
in design, this research seeks to effectively design e-health interfaces that can be
altered and used in other such interface designs to make them elderly-friendly.