Ethical and Quality of Care–Related Challenges of Digital Health Twins in Care Settings for Older Adults: Scoping Review
Bibliographic record
Abstract
Background: Digital health twins (DHTs) have been evolving with their diverse applications in medicine, particularly in care settings for older adults, in response to the increasing demands of older adults. Despite its numerous benefits, the optimal implementation of DHTs has faced several challenges, particularly in terms of ethics and quality of care. Given the continuous rise in the need for such care and the evident potential for DHTs to meet these needs, this review seeks to identify and address the gaps in research knowledge to enhance DHT implementation. Objective: The review aims to compile and synthesize the best available evidence regarding the issues associated with quality of care, the ethical implications of DHTs, and the strategies undertaken to overcome those challenges in care settings for older adults. Methods: The review followed the Joanna Briggs Institute (JBI) methodology as a guide. The published studies were searched through CINAHL, MEDLINE, JBI, and Web of Science. The unpublished studies were searched through Mednar, Trove, OCLC WorldCat, and Dissertations and Theses. Studies published in English from 2016 were considered. This review included studies of older individuals (aged 60 years and older) undergoing care delivery associated with DHTs and respective care providers. The concept involved the application of technology, and the context included studies based on care settings for older adults. A broad scope of evidence, including quantitative, qualitative, text, and opinion studies, was considered. In addition, 2 independent reviewers screened the titles and abstracts and reviewed the full text. Results: The results will be presented in a PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) flow diagram. A total of 2 draft charting tables were developed and presented. A summary of the characteristics of the included studies was then described in terms of location, study sites, timing, participants, and outcomes measured or phenomena of interest. A result-based convergent (integrated) synthesis design was used to identify 5 key challenges. Those challenges included (1) data security and privacy concerns, (2) equity and accessibility of health care, (3) effectiveness concerning context, timing, and location, (4) ethical implications regarding autonomy, consent, and overdiagnosis, and (5) the impact of DHTs on health care workflows and provider workload. Conclusions: The studies reviewed reveal several critical characteristics regarding the implementation of DHT technologies and their associated ethical considerations, particularly in terms of safety, equity, timing, location, participant characteristics, and workflow impact. The implications of these challenges emphasize the necessity for more practical ethical guidelines and policy frameworks to mitigate the potential risks associated with DHT application in older care. Further research should be conducted to examine other dimensions of the quality of care, such as access, timeliness, acceptability, and appropriateness.
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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 | 0.000 |
| 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".