Genuine partnership and equitable research: Working "with" older people for the development of a smart activity monitoring system
Bibliographic record
Abstract
Recent UK government policy has highlighted the value of user involvement in service development, particularly concerning assistive technologies and their role in providing care. This article illustrates the case of a person-centred, participatory project involving older people in the design, implementation and development of innovative technological solutions to enable older people to live independently and age-in-place within their homes and communities. The research aims and objectives included: the identification of technological, psychological and social needs of older people; the definition of user requirements to inform an activity monitoring system for use in private homes and residential care settings; and the analysis of the ways in which such systems impact on the everyday lives of older adults in different settings. The innovative aspects of the user-driven, participatory approach illustrated in this paper concern the involvement of older people as co-researchers throughout the research process. This article reports the reflexive accounts which emerged during the project and provides viable and practical pathways to facilitate participatory research in the development of assistive technology for older adults. It provides practical guidelines for future user-driven, participatory research involving older adults in the design, development and implementation of assistive technologies. Our findings show that developing authentic, non-tokenistic research partnerships and including older people’s ideas, motivations and perspectives in the design and development of these types of technology can lead to productive forms of mutual inspiration and technological solutions grounded in the experiences of older people.
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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 | 0.060 | 0.042 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.013 | 0.012 |
| Scholarly communication | 0.011 | 0.012 |
| Open science | 0.002 | 0.027 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 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".