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Creators/Authors contains: "Du, Yang"

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  1. Free, publicly-accessible full text available April 1, 2026
  2. BackgroundReminiscence, a therapy that uses stimulating materials such as old photos and videos to stimulate long-term memory, can improve the emotional well-being and life satisfaction of older adults, including those who are cognitively intact. However, providing personalized reminiscence therapy can be challenging for caregivers and family members. ObjectiveThis study aimed to achieve three objectives: (1) design and develop the GoodTimes app, an interactive multimodal photo album that uses artificial intelligence (AI) to engage users in personalized conversations and storytelling about their pictures, encompassing family, friends, and special moments; (2) examine the app’s functionalities in various scenarios using use-case studies and assess the app’s usability and user experience through the user study; and (3) investigate the app’s potential as a supplementary tool for reminiscence therapy among cognitively intact older adults, aiming to enhance their psychological well-being by facilitating the recollection of past experiences. MethodsWe used state-of-the-art AI technologies, including image recognition, natural language processing, knowledge graph, logic, and machine learning, to develop GoodTimes. First, we constructed a comprehensive knowledge graph that models the information required for effective communication, including photos, people, locations, time, and stories related to the photos. Next, we developed a voice assistant that interacts with users by leveraging the knowledge graph and machine learning techniques. Then, we created various use cases to examine the functions of the system in different scenarios. Finally, to evaluate GoodTimes’ usability, we conducted a study with older adults (N=13; age range 58-84, mean 65.8 years). The study period started from January to March 2023. ResultsThe use-case tests demonstrated the performance of GoodTimes in handling a variety of scenarios, highlighting its versatility and adaptability. For the user study, the feedback from our participants was highly positive, with 92% (12/13) reporting a positive experience conversing with GoodTimes. All participants mentioned that the app invoked pleasant memories and aided in recollecting loved ones, resulting in a sense of happiness for the majority (11/13, 85%). Additionally, a significant majority found GoodTimes to be helpful (11/13, 85%) and user-friendly (12/13, 92%). Most participants (9/13, 69%) expressed a desire to use the app frequently, although some (4/13, 31%) indicated a need for technical support to navigate the system effectively. ConclusionsOur AI-based interactive photo album, GoodTimes, was able to engage users in browsing their photos and conversing about them. Preliminary evidence supports GoodTimes’ usability and benefits cognitively intact older adults. Future work is needed to explore its potential positive effects among older adults with cognitive impairment. 
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  3. The coronavirus disease 2019 (COVID-19) epidemic poses a threat to the everyday life of people worldwide and brings challenges to the global health system. During this outbreak, it is critical to find creative ways to extend the reach of informatics into every person in society. Although there are many websites and mobile applications for this purpose, they are insufficient in reaching vulnerable populations like older adults who are not familiar with using new technologies to access information. In this paper, we propose an AI-enabled chatbot assistant that delivers real-time, useful, context-aware, and personalized information about COVID-19 to users, especially older adults. To use the assistant, a user simply speaks to it through a mobile phone or a smart speaker. This natural and interactive interface does not require the user to have any technical background. The virtual assistant was evaluated in the lab environment through various types of use cases. Preliminary qualitative test results demonstrate a reasonable precision and recall rate. 
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  4. null (Ed.)