“That’s me at my best”: perspectives of older adults on involvement in technology research
Bibliographic record
Abstract
Creating assistive technology for older adults requires a deep understanding of their needs, values and preferences. Human-centred approaches can be used to engage older adults in technology research to help ensure that end solutions are ethically aligned, relevant and responsive to their priorities. However, the value of cocreation is not universally acknowledged. Older adults continue to receive negative stereotyping and are limited from engaging in research. With the growing demand for assistive technologies that effectively meet end-user needs, it is important that we deepen our knowledge about engagement and promote inclusion of older adults in technology research. To learn more, we asked members of a research advisory group for assistive technologies, specifically social robots, to tell us about their experiences of engagement and the impact it has on their lives, to speculate whether participation in research may promote human flourishing. Our findings reveal that engagement is more than knowledge exchange: it is a multifaceted, dynamic process that creates rich and meaningful experiences for older adults. Experiences of engagement dovetail with interpretations of flourishing and improved well-being, which include outcomes related to empowerment, autonomy and connectedness to self and others. Older adults also report finding purpose and satisfaction in knowing that their contributions to research may be used to develop technologies that can benefit others. This work amplifies the voice of lived experiences to deepen our understanding of the impacts of participation and prompts us to reimagine how older adults may be meaningfully engaged in technology research.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.005 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 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".