Tablet-Based Well-Being Check for the Elderly: Development and Evaluation of Usability and Acceptability
Bibliographic record
Abstract
BACKGROUND: Many elderly people prefer to live at home independently. One of the major concerns raised by the family members is the safety and well-being of their elderly family members when living independently in a home environment. To address this issue, assistive technology solutions have been available in the market. Despite their availability and proliferation, these types of solutions are not popular with the elderly due to their intrusive nature, privacy-related issues, social stigma, and fear of losing human interaction. This study shares the experience in the development of a digital photo frame system that helps family members to check the well-being of the elderly, exploiting their desire to remain socially connected. OBJECTIVES: The aim of this study was to iteratively design, implement, and assess the usability, user friendliness, and acceptability of a tablet-based system to check the well-being of the elderly. METHODS: Our study methodology comprises three separate stages: initial system development, contextual assessment, and comparative case study evaluation. RESULTS: In the first stage, requirements were elicited from the elderly to design a well-being check prototype. In the second stage, areas for improvements (eg, privacy features) were identified. Also, additional features (such as medication prompts or food reminders) were suggested to help aged and health care service providers with effective but subtle monitoring of the elderly. These would lower their operating cost by reducing visits by care providers to the homes of the elderly. In the third stage, the results highlighted the difference (between users in India and Australia) in the levels of familiarity of the elderly with this technology. Some elderly participants at the Kalyani Institute for Study, Planning and Action for Rural Change, India latched onto this technology quickly while a few refused to use the system. However, in all cases, the support of family members was crucial for their willingness to use the technology. CONCLUSIONS: This project has three major outcomes. First, a picture frame prototype was tested with the elderly to leverage the benefits of social communication. Second, the project helped us test and implement the "Silvercare" model for supporting the elderly through young retired people residing in the area. Finally, the project helped formalize the agile three-stage design methodology to develop information technology solutions for the elderly. Also, the project contributed to an ongoing European Union Project called Victoryahome, which involves more than 50 sites across 5 countries (Norway, Sweden, Netherlands, Portugal, and Australia) to assess the use of telepresence robots, wearable fall detectors, and medication dispensers for the elderly living independently.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.010 | 0.019 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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".