User Involvement in Research on Aging and Health: Creating Knowledge and Technologies With Older Adults
Bibliographic record
Abstract
Abstract Although, user involvement is largely recognized as instrumental when developing relevant knowledge, services as well as products - aging populations are still likely to be sparsely involved in such processes. Surprisingly, many gerontechnologies are still developed based on a technological perspective rather than a gerontological perspective. Consequently, age-related changes as well as needs, actual use or perceptions of older adults are disregarded or neglected. Similar problems apply to public and private environments with potentially negative implications on accessibility. The present symposium includes four presentations that address user involvement, by capturing older adults’ and aging populations’ use as well as perceptions of emerging technologies, successful development of gerontechnologies, and a multigenerational mass-experiment on housing accessibility in later life. The first study from Germany captures the everyday situation of smartphone use as well as aspects of user experience, affect and social context among older adults. The second study addresses perceptions and attitudes of three generations in Sweden related to continuous technological advancement of products intended to support active and healthy aging. The third presentation will describe the iterative development process of the 2020 mass-experiment – the Housing Experiment -- involving older adults, stakeholders in the housing sector, teachers and pupils in Sweden. The fourth presentation from Canada explores the benefits, challenges, and solutions to support older adult engagement in research that leads to the successful development of technologies for and with older adults. Finally, our discussant will further elaborate on the respective study findings and summarize the symposium.
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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 | 0.062 | 0.028 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.006 | 0.005 |
| Scholarly communication | 0.008 | 0.006 |
| Open science | 0.001 | 0.011 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 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".