Effectiveness of a co‐designed technology package on perceptions of safety in community‐dwelling older adults
Bibliographic record
Abstract
OBJECTIVES: Increasing numbers of older people are living longer, often alone, in their own homes. Services and products that enable older people to remain safely in their own homes are required. The My Smart Home project recruited 30 community-dwelling people aged 65+ to co-design a package of technology to address their individual goals for safety and security at home. The technology package, up to the value of $4000, included installation of health monitoring, communication and entertainment devices, and security alarms, with 6 hours of technology coaching. METHODS: Participants completed the Personal Wellbeing Index (PWI), the Australian Quality of Life-8 Dimensions (AQoL-8D) and the Canadian Occupational Performance Measure (COPM) at baseline, and after 4 weeks' use of the technology package. Semi-structured interviews were also used to qualitatively understand the challenges, enablers and outcomes of the project with respect to safety and security in the home. RESULTS: Significant improvements in PWI (p < 0.01), AQoL-8D (p < 0.001) and COPM for goal performance (p < 0.001) and goal satisfaction (p < 0.001) were reported. Participants also reported feeling safer and more secure in their own homes. Common barriers to adoption of technology, cost, integration with already-owned technology and lack of confidence were overcome with this technology and coaching package. CONCLUSIONS: An individualised package of technology, with coaching, that supports older people to realise their personal goals with technology resulted in improved well-being, quality of life and sense of safety and security in community-dwelling older people. Ultimately, this should support a longer and better quality of life at home.
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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 | 0.004 | 0.013 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".