JMIR Publications

ABSTRACT

Background:

Falls among older adults represent a major public health challenge, frequently leading to hospitalization, functional decline, loss of independence, and increased healthcare costs. Advances in digital health technologies and medical devices have created new opportunities to improve fall-risk assessment, prediction, and prevention through personalized and technology-assisted approaches. However, the development of clinically relevant and implementable solutions requires the integration of scientific evidence, predictive modelling, and end-user perspectives.

Objective:

This research protocol describes Stage 1 of the Sustainable and Accessible Fall-Prevention Medical Device Technologies for Older Adults’ Health (S@FHe-RP) project. Stage 1 comprises four complementary and sequential studies designed to generate the scientific, methodological, and user-centered evidence required to support the future development of an accessible and sustainable digital medical device for fall prevention in older adults across community and long-term care settings.

Methods:

Stage 1 comprises four interconnected studies. Study 1 is a scoping review conducted according to the Joanna Briggs Institute methodology and the PRISMA-ScR guidelines to map existing digital technologies and identify knowledge gaps related to fall-risk assessment and prevention. Study 2 is systematic review synthesizing evidence on traditional and technology-adapted physical-functional assessments used for fall-risk evaluation. Study 3 adopts a mixed-methods approach, guided by the User-Centered Design framework and the Technology Acceptance Model, to explore end-users’ perspectives regarding usability, acceptability, and implementation requirements of digital fall-prevention technologies. Building upon the evidence generated in the preceding studies, Study 4 aims to develop and internally validate a predictive model based on bio-sociodemographic, clinical, and functional indicators associated with fall risk in older adults recruited from both community and long-term care settings. Collectively, these four studies constitute an integrated evidence-generation pathway in which each study informs the subsequent stage, supporting the future development, validation, and implementation of the proposed digital medical device.

Results:

Stage 1 is expected to generate complementary evidence regarding existing digital technologies, validated physical-functional assessments, end-user requirements, and clinically relevant predictors of fall risk. Together, these findings are expected to provide the scientific and methodological basis for the future development and validation of an evidence-based digital medical device applicable across community and long-term care settings.

Conclusions:

The S@FHe-RP proposes a structured translational framework integrating evidence synthesis, user-centered design, and predictive modelling to support the future development of accessible, sustainable, and clinically relevant digital health solutions for fall prevention across diverse ageing settings.