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Accepted for/Published in: JMIR Research Protocols

Date Submitted: Jan 22, 2021
Date Accepted: Feb 19, 2021

The final, peer-reviewed published version of this preprint can be found here:

Technology-Based Fall Risk Assessments for Older Adults in Low-Income Settings: Protocol for a Cross-sectional Study

Thiamwong L, Stout JR, Park JH, Yan X

Technology-Based Fall Risk Assessments for Older Adults in Low-Income Settings: Protocol for a Cross-sectional Study

JMIR Res Protoc 2021;10(4):e27381

DOI: 10.2196/27381

PMID: 33825688

PMCID: 8060859

Warning: This is an author submission that is not peer-reviewed or edited. Preprints - unless they show as "accepted" - should not be relied on to guide clinical practice or health-related behavior and should not be reported in news media as established information.

Technology-based fall risk assessments for older adults in low-income settings: A cross-sectional study protocol

  • Ladda Thiamwong; 
  • Jeffrey R. Stout; 
  • Joon-Hyuk Park; 
  • Xin Yan

ABSTRACT

Background:

One-third of older adults have maladaptive fall risk appraisal (FRA), a condition in which there is a discrepancy between a level of fear of falling (FOF) and physiological fall risk (balance performance). Older adults who overestimate their physiological fall risk and report high fear of falling are less likely to participate in physical activity. Limited data suggest the association between fear of falling, body composition, and physical activity intensity differs by fear severity.

Objective:

This study examines the associations among fall risk appraisal, body composition, and physical activity using Assistive Health Technology, including the BTrackS Balance System (BBS), Bioelectrical Impedance Analysis, and activity monitoring devices. This study also aims to examine the feasibility of recruitment and acceptability of technologies and procedures for use among older adults in low-income settings.

Methods:

This is a cross-sectional study. This study will be conducted at older adults’ homes/apartments in low-income settings in Central Florida, USA. Following consent, participants will be contacted, and our team will have two visits with them. The first visit includes questionnaires completion (e.g., socio-demographic, FOF) and the balance performance test using the BBS. Participants will be stratified by the FRA matrix. Also, they will perform the hand-grip strength and dynamic balance performance tests. Participants will then be asked to wear the ActiGraph GT9X Link wireless activity monitor on the non-dominant wrist for 7 consecutive days. The second visit includes body composition testing and a structured interview about the acceptability of technologies and procedures.

Results:

The ethical approval was obtained from the institutional review board, University of Central Florida (Protocol No. 2189; September 10, 2020). As of December 2020, the enrollment of participating is ongoing.

Conclusions:

Accurate fall risk appraisal is essential in implementing physical activity programs, especially in low-income older adults. This study will provide data for developing technology-based fall risk assessments for improving participation in physical activity, thus enhancing healthy longevity among older adults in low-income settings.


 Citation

Please cite as:

Thiamwong L, Stout JR, Park JH, Yan X

Technology-Based Fall Risk Assessments for Older Adults in Low-Income Settings: Protocol for a Cross-sectional Study

JMIR Res Protoc 2021;10(4):e27381

DOI: 10.2196/27381

PMID: 33825688

PMCID: 8060859

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