Enhancing Caregiver Empowerment Through the Story Mosaic System: Human-Centered Design Approach for Visualizing Older Adult Life Stories
Bibliographic record
Abstract
Background: Various older adult care settings have embraced the use of the life story approach to enhance the development of comprehensive care plans. However, organizing life stories and extracting useful information is labor-intensive, primarily due to the repetitive, fragmented, and redundant nature of life stories gathered from everyday communication scenarios. Existing life story systems, while available, do not adequately fulfill the requirements of users, especially in the application of care services. Objective: The objective of this study is to design, develop, and evaluate a digital system that provides caregivers with the necessary tools to view and manage the life stories of older adults, enabling expedited access to pertinent information effectively and visually. Methods: This study used a multidisciplinary, user-centered design approach across 4 phases: initial design requirements, prototyping, prototype refinement workshops, and usability testing. During the initial phase, we conducted field research in the Hefei Tianyu Senior Living Service Nursing Home, China, to discover how caregivers currently store and use life stories and their needs, challenges, and obstacles in organizing and retrieving information. Subsequently, we designed a low-fidelity prototype according to the users' requirements. A prototyping workshop involving 6 participants was held to collaboratively design and discuss the prototype's function and interaction. User feedback from the workshops was used to optimize the prototype, leading to the development of the system. We then designed 2 rounds of usability testing with 7 caregivers to evaluate the system's usability and effectiveness. Results: We identified 3 categories of functionalities that are necessary to include in the design of our initial low-fidelity prototype of life story visualizations: life story input, life story organization, and timeline generation. Subsequently, through the workshops, we identified 3 categories for functional optimization: feedback on user interface and usability, optimization suggestions for existing features, and the request for additional functionalities. Next, we designed a medium-fidelity prototype based on human-centered design. The Story Mosaic system underwent usability testing in the Hefei Tianyu Senior Living Service Nursing Home. Overall, 7 users recorded and organized 1123 life stories of 16 older adults. The usability testing results indicated that the system was accessible and easy to use for caregivers. Based on the feedback from the usability testing, we finalized the high-fidelity prototype. Conclusions: We designed, developed, and evaluated the Story Mosaic system to support the visual management of older adults' life stories. This system empowers caregivers through digital technology and innovative design, pioneering personal narrative integration in caregiving. This system can expand to include informal caregivers and family members for continued adaptability and empathy.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.005 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".