Conducting Co-Design with Older People in a Digital Setting: Methodological Reflections and Recommendations
Bibliographic record
Abstract
Introduction: Co-design has been identified as a participatory method to create person-centred integrated healthcare services that align with older people's values and lived experiences. Description: Existing guidelines on conducting co-design primarily focus on in-person methods with limited guidance on using digital methods to collect data. This gap in knowledge is particularly pertinent when co-designing with older people who can experience challenges with digital literacy and accessibility. This article uses the exemplar of a pilot site within a European co-design research project, aiming to create digital health technology to support integrated care, to describe the steps and considerations required when collaborating with older people in an online environment. Focus groups and one-to-one interviews were conducted utilising digital mediums of teleconferencing and telephone calls to engage and collaborate with older people. Discussion: Several preparatory steps are required to effectively bridge the digital divide and conduct co-design with older people including engaging gatekeepers, relationship and trust-building, assessing digital literacy levels, education and providing technological support. Conclusion: This article highlights the steps and considerations that researchers should be aware of when embarking on co-designing with older people in a digital setting. The authors describe their methods that promotes inclusivity and the empowerment of older people as equal collaborators in the research process. The co-design approach and recommendations can be applied to various research settings and wider areas of integrated care with this population.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| 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".