## 3 Systematic Review Results
### Acceptance Models
The second phase is incorporation, involving further exploration and experimentation with the technology. The third phase is conversion, where individuals decide to accept or reject the technology based on real-life experience. Finally, the fourth phase is the intention to learn, which includes factors like self-efficacy and motivation to acquire new technological skills. These phases play a crucial role in determining the acceptance or rejection of technology by older individuals. The authors in [38] presented an integrated acceptance framework (IAF) for older users' acceptance of eHealth based on a systematic review of 43 studies. The framework consists of five dimensions: personal, user-technology relational, technological, service-related, and environmental, comprising a total of 23 factors. The study analysed the differences in these factors based on participants' health conditions, verification time, and year. The proposed framework aims to guide research on eHealth acceptance and emphasises the need for specific measures to facilitate acceptance among older adults. Acceptance models provide a foundational framework for researchers to explore the complex factors influencing technology adoption among older adults. These models, like TAM and UTAUT, offer a structured approach to understanding the motivations and challenges faced by this demographic. Examining extensions of these models, like STAM, reveals the importance of tailoring the models to specific contexts and incorporating culturally relevant factors like social influence. However, limitations exist, with criticisms highlighting the need for models to move beyond basic acceptance to inform actionable design principles. However, while models like TAM and UTAUT provide theoretical insights, their generality often limits the derivation of actionable design insights specific to the nuanced needs and preferences of specific demographics, such as pre-fail older adults in home settings. This gap directly informed the necessity of our co-design activities to gather more context-specific data. The concept of user experience goes beyond just perceived ease of use and usefulness. Studies exploring the four phases of technology acceptance (objectification, incorporation, conversion, and intention to learn) emphasise the importance of understanding how older adults interact with technology over time. Frameworks like the IAF delve even deeper, identifying 23 factors across five dimensions that influence technology adoption in older populations. These insights are crucial for designing technologies that cater to the unique needs and preferences of older adults, ultimately empowering them to embrace the benefits technology offers. In summary, acceptance models such as TAM, UTAUT, and STAM provide essential theoretical foundations for understanding technology adoption among older adults. However, their limitations, particularly the lack of actionable design insights, underscore the need for participatory approaches like co-design workshops and activities. The reviewed extensions of these models introduce critical contextual, emotional, and social factors, demonstrating the importance of tailoring acceptance frameworks to specific populations.