The influence of assistive technology and home modifications on falls in community-dwelling older adults: a systematic review protocol
Bibliographic record
Abstract
BACKGROUND: Fall-related injuries can reduce older adults' independence and result in economic burdens. The assistive technologies and home modifications explored in this review are suggested to reduce the risk of falls of community-dwelling older people. However, the location of the in-home assistive technology being used, and the in-home modification likely interact and influence fall reduction and injury prevention of community-dwelling older adults. This interactive effect is poorly understood. A better understanding of the impact of assistive technologies and modifications in the homes of older adults is needed to support the appropriate application of these devices. OBJECTIVE: The objective of this systematic review is to detail the contribution of assistive technology and home modification on falls, fall frequency, fall severity, and fall location within the homes of community-dwelling older adults. METHODS: We will source articles from 3 databases (MEDLINE, CINAHL, Web of Science Core Collection) and will assess them using a set of pre-defined inclusion and exclusion criteria. Reporting will be in accordance with PRISMA 2020. Two independent reviewers will screen each study at the title and abstract and full-text level. We are managing citations within the Covidence software. Data extraction and analysis will be reported in a systematic review. DISCUSSION: The outcome variables of interest are fall frequency, fall location, injury, mortality, and hospitalization. These variables of interest all relate to falls, their severity, and their locations in the home. We are seeking a better understanding of how these outcomes vary with the use of different assistive technologies and home modifications as reported in the literature. This will help us understand where falls occur which may inform how different assistive technologies can be used by community-dwelling older adults to prevent falls and adverse outcomes in different areas of their homes. Our review will provide a basis for more intentional prescription of ambulatory assistive technologies and evidence-based recommendations of home modifications. It may also inform adaptations to existing technologies to foster safer mobility in the homes of community-dwelling older adults. SYSTEMATIC REVIEW REGISTRATION: This protocol has been submitted for registration in PROSPERO CRD42022370172 on October 24, 2022.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.061 | 0.076 |
| Meta-epidemiology (narrow) | 0.006 | 0.006 |
| Meta-epidemiology (broad) | 0.022 | 0.017 |
| Bibliometrics | 0.020 | 0.016 |
| Science and technology studies | 0.005 | 0.006 |
| Scholarly communication | 0.008 | 0.010 |
| Open science | 0.006 | 0.006 |
| Research integrity | 0.007 | 0.005 |
| Insufficient payload (model declined to judge) | 0.057 | 0.008 |
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".