Considerations When Designing Inclusive Digital Health Solutions for Older Adults Living With Frailty or Impairments
Bibliographic record
Abstract
This viewpoint is written by authors with industrial, clinical, and academic backgrounds within medical and social sciences. The purpose is to share our experiences with digital health innovation from a sociotechnical perspective. The audience for the viewpoint is innovators, researchers, service designers, and project managers with little or some experience with theory-informed programs, complex interventions, and implementation or reorganization of sociotechnical ecosystems in health care. In digital health innovation projects, barriers related to traditions and cultures among researchers, clinicians, and industry may arise. Moreover, the final digital solutions may not always fit into existing digital ecosystems and may thus require a reorganization of how health care is provided at horizontal and vertical levels. The collaborating researchers have experience working in the field of digital health innovation for more than a decade, and we have developed and used 4 frameworks and models that are particularly relevant for theory-based complex interventions and can be used to inform inclusive co-design of digital health solutions with a sociotechnical perspective. These are (1) the 4E, a matrix to include, engage, empower, and emancipate marginalized people; (2) the GO-TO model, which can be used as a design navigator; (3) the Epital Care Model, to inform infrastructure; and (4) the Readiness and Enablement Index for Health Technology instrument, to stratify service users. From January 2021 to September 2024, we had the opportunity to apply these into practice in 4 living labs located in Denmark, Norway, the Netherlands, and Canada as a part of a European Union-funded project on "Smart Inclusive Living Environments." The goal was to cocreate a digital solution and reorganize health care services to reduce social isolation, increase health literacy, and enhance well-being for older adults living with frailty or impairments. Based on our experiences with the Smart Inclusive Living Environments project, we have formed a proposal for how design guidelines for sociotechnical innovation projects can be structured, backed up with reflections based on our experiences. With that, design guidelines should include three areas: (1) a common vocabulary including theories, frameworks, and models; (2) templates and protocols for methods, including detailed guidelines and templates for the planned development of the technologies; and (3) methods to implement and provide education and training of service users and informal and formal caregivers. In the design process, we emphasize the importance of involving relevant stakeholders in the implementation of the created design guidelines to obtain preparedness in the organizations, as well as including putative service users to ensure the likelihood of adoption. Moreover, it is important to align expectations, have a common understanding of the applied frameworks and methods, and have access to the necessary resources to reach successful results.
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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 | 0.004 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| 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".