Providing Medical Information to Older Adults in a Web-Based Environment: Systematic Review (Preprint)
Bibliographic record
Abstract
BACKGROUND Cancer is a disease that predominantly affects older adults, and several organizations recommend the completion of a geriatric assessment to help with cancer treatment decision-making. Owing to a shortage of geriatric teams and the vast number of older adults diagnosed with cancer each year, a web-based geriatric assessment may improve access to geriatric assessment for older adults. We systematically reviewed the literature to obtain the latest evidence for the design of our web-based geriatric assessment tool Comprehensive Health Assessment for My Plan. OBJECTIVE This review aimed to probe the following questions: what is the impact of providing health test results to older adults in a web-based environment without the presence of a health care provider for patient-centered outcomes, including satisfaction, perceived harm, empowerment, quality of life, and health care use (eg, hospitalization, physician visits, emergency room visits, and costs), and what recommendations do older adults and developers have for designing future apps or websites for older adults? METHODS This systematic review was guided by the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-analysis) statement. Studies were limited to publications in English that examined a web-based tool that provided test results to older adults (aged ≥65 years) without the presence of a health care provider. A health sciences librarian performed the search on November 29, 2019, on the following electronic databases: MEDLINE, Embase, CINAHL, PsycINFO, and the Cochrane Library. The quality of the included studies was assessed using the Mixed Methods Appraisal Tool Version 2018. The findings are summarized narratively and in tabular format. RESULTS A total of 26,898 titles and abstracts were screened by 2 independent reviewers, of which 94 studies were selected for a full-text review, and 9 studies were included in this review. There were only 2 randomized controlled trials of high quality that explored the effects of receiving health care results on the web via eHealth tools for older adults or provided evidence-based recommendations for designing such tools. Older adults were generally satisfied with receiving screening results via eHealth tools, and several studies suggested that receiving health screening results electronically improved participants’ quality of life. However, user interfaces that were not designed with older adults in mind and older adults’ lack of confidence in navigating eHealth tools proved challenging to eHealth uptake and use. All 9 studies included in this systematic review made recommendations on how to design eHealth tools that are intuitive and useful for older adults. CONCLUSIONS eHealth tools should incorporate specific elements to ensure usability for older adults. However, more research is required to fully elucidate the impact of receiving screening and results via eHealth tools without the presence of a health care provider for patient-centered outcomes in this target population.
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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 | 0.010 | 0.058 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.007 | 0.008 |
| Bibliometrics | 0.008 | 0.012 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.004 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.018 | 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".