A systematic review of gerontechnologies to support aging in place among community-dwelling older adults and their family caregivers
Bibliographic record
Abstract
Objective: Paucity of information concerning the efficacy of gerontechnologies to support aging in place among community-dwelling older adults prevents potential users, healthcare professionals, and policymakers from making informed decisions on their use. The goal of this study was to identify gerontechnologies tested for home support in dyads of community-dwelling older adults with unimpaired cognition and their family caregivers, including their benefits and challenges. We also provide the level of evidence of the studies and recommendations to address the specific challenges preventing their use, dissemination, and implementation. Methods: We conducted a systematic review of the literature published between 2016 and 2021 on gerontechnologies tested for home support in dyads. Two independent reviewers screened the abstracts according to the inclusion/exclusion criteria. A third reviewer resolved eligibility discrepancies. Data extraction was conducted by two independent reviewers. Results: Of 1,441 articles screened, only 13 studies met the inclusion criteria with studies of moderate quality. Mostly, these gerontechnologies were used to monitor the older adult or the environment, to increase communication with family caregivers, to assist in daily living activities, and to provide health information. Benefits included facilitating communication, increasing safety, and reducing stress. Common challenges included difficulties using the technologies, technical problems, privacy issues, increased stress and dissatisfaction, and a mismatch between values and needs. Conclusion: Only a few gerontechnologies have proven efficacy in supporting community-dwelling older adults and their family caregivers. The inclusion of values and preferences, co-creation with end users, designing easy-to-use technologies, and assuring training are strongly recommended to increase acceptability and dissemination. Systematic review registration: https://www.crd.york.ac.uk/prospero/display_record.php?RecordID=310803, identifier CRD42022310803.
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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 | 0.011 | 0.050 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.007 | 0.006 |
| Bibliometrics | 0.010 | 0.010 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.003 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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 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".