Research on Identifying and Optimizing Elderly Needs for Smart Elderly Care Service Platforms—An Empirical Analysis of Elderly Users Based on the Kano Model

As the world's population ages, a quiet revolution is taking place in how we care for our elders, shifting from traditional physical assistance to digital support systems. In China, where the number of older adults is growing rapidly, the government and technology companies are building "smart elderly care service platforms." These are digital hubs designed to connect seniors with safety monitoring, health management, and daily assistance through smartphones and tablets. However, a significant gap has emerged: while the technology exists, it often fails to connect with the people it is meant to serve. Many platforms are built with complex interfaces and features that assume a level of digital fluency that many older adults simply do not have. This disconnect leads to frustration, where seniors feel excluded rather than supported. To solve this, researchers must move beyond guessing what seniors need and instead listen carefully to their actual experiences. This requires a method that can distinguish between features that are merely nice to have, those that are essential for basic use, and those that provide a genuine sense of delight.

A team of researchers from Fujian Normal University and a local technology company set out to map these needs with precision. They focused on 27 specific functions that could be included in these digital care platforms, ranging from simple things like making text larger to complex services like AI voice companions. To understand how these features truly impact an older person's day, the team turned to a classic tool for understanding user satisfaction known as the Kano model. This approach does not assume that adding more features always makes a product better. Instead, it recognizes that some features are so basic that their absence causes anger, while their presence is taken for granted. Other features create a direct, linear boost in happiness the better they work, and a third group provides a surprising spark of joy that users didn't know they wanted until they experienced it. By applying this framework, the researchers aimed to sort the 27 potential functions into these distinct categories, creating a clear roadmap for developers.

The study began by gathering a group of 294 older adults who had already used smart care platforms. These participants, mostly between the ages of 60 and 70, were asked to evaluate each of the 27 functions in two ways: how they would feel if the feature existed, and how they would feel if it did not. This dual perspective allowed the researchers to see the full emotional weight of each feature. The results revealed a clear hierarchy of needs that challenges the common assumption that "more technology is better." The most critical findings centered on a group of eight features that the researchers identified as essential. These included the ability to adjust font and icon sizes, a streamlined interface that removes clutter, and robust safety measures like fraud warnings and emergency contact links. For these features, the data showed a stark reality: if they are missing, older users become deeply dissatisfied and may abandon the platform entirely. However, simply having them does not necessarily make users ecstatic; they are the baseline, the non-negotiable foundation upon which everything else rests.

Beyond the basics, the study uncovered a second layer of needs that directly correlate with user satisfaction. These are features that users expect to work well, and the better they perform, the happier the user becomes. This group included clear, simple language that avoids technical jargon, real-time step-by-step guidance during tasks, and secure ways to link devices to user accounts. The researchers found that improving these specific areas offers the most reliable path to increasing satisfaction. When a platform speaks plainly and guides the user through a process without confusion, it builds trust. Similarly, features that help seniors connect with family or manage offline services like meal delivery were highly valued. These are not surprises; they are the core services that users actively seek out, and their quality determines whether the platform feels helpful or burdensome.

Perhaps the most intriguing part of the research involved the "attractive" features—functions that users did not explicitly demand but which, when present, create a significant positive surprise. The study identified five such features: screen reading capabilities that speak text aloud, visual charts that turn health data into easy-to-read graphs, intelligent reminders for medication, personalized plans for managing chronic diseases, and AI voice companions that can chat and offer news. These features act as a differentiator. Their absence does not upset the user, but their presence can transform a functional tool into a beloved companion. For instance, an AI voice that can answer questions or simply chat can reduce loneliness and make the technology feel less cold and mechanical. The researchers noted that while these features are currently less common, they hold the potential to significantly enhance the emotional connection between the senior and the digital world.

The study also identified a group of features that currently have little impact on user satisfaction, known as indifferent requirements. These include things like vibration feedback when a button is pressed, specific color adjustments, and digital tutorials on how to use the phone. The data suggested that for the current generation of users, these features are neither helpful nor harmful. However, the researchers cautioned against dismissing them entirely. As technology evolves and older adults become more comfortable with digital tools, what is now indifferent could tomorrow become a source of delight or even a basic expectation. The researchers suggested that these features should be kept in reserve, ready to be activated when user needs shift.

To bring these findings into practice, the researchers proposed a four-stage optimization strategy for developers. The first and most urgent step is to secure the essential functions, ensuring that safety, fraud protection, and basic readability are flawless. Without this foundation, no amount of advanced features will matter. The second stage involves refining the expected services, making sure that guidance is clear and that family connections are seamless. The third stage is to explore the potential of the attractive features, introducing AI companions and health visualizations to create moments of joy. Finally, the fourth stage involves a careful review of the indifferent features, deciding whether to keep them, improve them, or remove them to reduce clutter. This approach moves away from the "kitchen sink" method of adding every possible feature and instead focuses on a targeted, user-centered design.

The researchers were careful to note the limits of their work. The study relied on the self-reported opinions of older adults who already had some experience with these platforms, mostly from urban areas. It did not include the vast number of seniors in rural regions or those who have never touched a smartphone, whose needs might be quite different. Furthermore, the data represents a snapshot in time; it does not track how needs might change as a person ages further or as the technology itself evolves. Despite these limitations, the study provides a vital, evidence-based guide for the future of elderly care technology. It suggests that the path to a truly age-friendly digital world is not about building more complex systems, but about understanding the specific, layered needs of the people who will use them. By prioritizing safety and clarity, then layering in features that offer genuine connection and surprise, developers can build platforms that do not just serve the elderly, but truly welcome them into the digital society.