Investigating the Integration and the Long-Term Use of Smart Speakers in Older Adults’ Daily Practices: Qualitative Study
Bibliographic record
Abstract
BACKGROUND: As smart speakers become more popular, there have been an increasing number of studies on how they may benefit older adults or how older adults perceive them. Despite the increasing ownership rates of smart speakers among older adults, studies that examine their integration and the long-term use in older adults' daily practices are scarce. OBJECTIVE: This study aims to uncover the integration of smart speakers into the daily practices of older adults over the long term, contributing to an in-depth understanding of maintained technology use among this demographic. METHODS: To achieve these objectives, the study interviewed 20 older adults who had been using smart speakers for over 6 months. These semistructured interviews enabled participants to share their insights and experiences regarding the maintained use of smart speakers in the long term. RESULTS: We identified 4 dimensions of the long-term use of smart speakers among older adults, including functional integration, spatial integration, cognitive integration, and semantic integration. For the functional integration of smart speakers, the study reported different types of use, including entertainment, information collection, medication reminders, companionship, environment modification, and emergency calls. For the spatial integration of smart speakers, the study showed older adults' agency in defining, changing, and reshaping daily practices through the spatial organization of smart speakers. For the cognitive integration of smart speakers, the findings showed the cognitive processes involved in adapting to and incorporating smart speakers into daily habits and routines. For the semantic integration of smart speakers, the findings revealed that older adults' enjoyable user experience and strong bonds with the device contributed to their acceptance of occasional functional errors. Finally, the study proposed several suggestions for designers and developers to better design smart speakers that promote maintainable use behaviors among older adults. CONCLUSIONS: On the basis of the findings, this study highlighted the importance of understanding how older adults use smart speakers and the practices through which they integrate them into their daily routines. The findings suggest that smart speakers can provide significant benefits for older adults, including increased convenience and improved quality of life. However, to promote maintainable use behaviors, designers and developers should consider more about the technology use contexts and the specific needs and preferences of older adults when designing these devices.
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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 | 0.005 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".