User Requirements for Technology to Assist Aging in Place: Qualitative Study of Older People and Their Informal Support Networks
Bibliographic record
Abstract
BACKGROUND: Informal support is essential for enabling many older people to age in place. However, there is limited research examining the information needs of older adults' informal support networks and how these could be met through home monitoring and information and communication technologies. OBJECTIVE: The purpose of this study was to investigate how technologies that connect older adults to their informal and formal support networks could assist aging in place and enhance older adults' health and well-being. METHODS: Semistructured interviews were conducted with 10 older adults and a total of 31 members of their self-identified informal support networks. They were asked questions about their information needs and how technology could support the older adults to age in place. The interviews were transcribed and thematically analyzed. RESULTS: The analysis identified three overarching themes: (1) the social enablers theme, which outlined how timing, informal support networks, and safety concerns assist the older adults' uptake of technology, (2) the technology concerns theme, which outlined concerns about cost, usability, information security and privacy, and technology superseding face-to-face contact, and (3) the information desired theme, which outlined what information should be collected and transferred and who should make decisions about this. CONCLUSIONS: Older adults and their informal support networks may be receptive to technology that monitors older adults within the home if it enables aging in place for longer. However, cost, privacy, security, and usability barriers would need to be considered and the system should be individualizable to older adults' changing needs. The user requirements identified from this study and described in this paper have informed the development of a technology that is currently being prototyped.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".