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Performance of digital technologies in assessing fall risks among older adults with cognitive impairment: a systematic review

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Abstract

Older adults with cognitive impairment (CI) are twice as likely to fall compared to the general older adult population. Traditional fall risk assessments may not be suitable for older adults with CI due to their reliance on attention and recall. Hence, there is an interest in using objective technology-based fall risk assessment tools to assess falls within this population. This systematic review aims to evaluate the features and performance of technology-based fall risk assessment tools for older adults with CI. A systematic search was conducted across several databases such as PubMed and IEEE Xplore, resulting in the inclusion of 22 studies. Most studies focused on participants with dementia. The technologies included sensors, mobile applications, motion capture, and virtual reality. Fall risk assessments were conducted in the community, laboratory, and institutional settings; with studies incorporating continuous monitoring of older adults in everyday environments. Studies used a combination of technology-based inputs of gait parameters, socio-demographic indicators, and clinical assessments. However, many missed the opportunity to include cognitive performance inputs as predictors to fall risk. The findings of this review support the use of technology-based fall risk assessment tools for older adults with CI. Further advancements incorporating cognitive measures and additional longitudinal studies are needed to improve the effectiveness and clinical applications of these assessment tools. Additional work is also required to compare the performance of existing methods for fall risk assessment, technology-based fall risk assessments, and the combination of these approaches.

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Data availability

Data utilised for this study is available at the Health Services and Systems Signature Research Programme of DUke-NUS Medical School. De-identified data can be made available upon reasonable request.

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Acknowledgements

The research was conducted at the Future Health Technologies at the Singapore-ETH Centre, which was established collaboratively between ETH Zurich and the National Research Foundation Singapore. This research is supported by the National Research Foundation, Singapore under its Campus for Research Excellence and Technological Enterprise (CREATE) programme. The authors would also like express gratitude to the Centre for Ageing Research & Education (CARE) at Duke-NUS Medical School. Data collected for the study can be made available upon reasonable request and permission from CARE at Duke-NUS Medical School.

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Authors and Affiliations

  1. Programme in Health Services and Systems Research (HSSR), Duke-NUS Medical School, Singapore, Singapore

    Vanessa Koh, Lai Wei Xuan, David B. Matchar & Angelique Chan

  2. Centre for Ageing Research and Education (CARE), Duke-NUS Medical School, 8 College Road, Singapore, 169857, Singapore

    Vanessa Koh & Angelique Chan

  3. Future Health Technologies Programme, Singapore-ETH Centre, Singapore, Singapore

    Tan Kai Zhe, Navrag Singh, David B. Matchar & Angelique Chan

  4. Laboratory for Movement Biomechanics, Institute for Biomechanics, ETH Zurich, Zurich, Switzerland

    Navrag Singh

  5. Department of Medicine (General Internal Medicine), Duke University Medical Center, Durham, NC, USA

    David B. Matchar

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  1. Vanessa Koh
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Contributions

Conceptualisation: V.J.W Koh; systematic search: V.J.W Koh, W.X. Lai; data synthesis: V.J.W Koh, W.X. Lai, K.Z. Tan; writing—original draft preparation: V.J.W Koh; writing—review and editing: V.J.W Koh, W.X. Lai, K.Z. Tan, N. Singh, D.B Matchar, A.W.M Chan; supervision, resources and funding acquisition: D.B Matchar, A.W.M Chan; All authors have read and reviewed the manuscript.

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Correspondence to Vanessa Koh.

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Table 6

Table 6 Full search strategy utilised on 27 July 2022, and an update was conducted on 20 July 2023
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Koh, V., Xuan, L.W., Zhe, T.K. et al. Performance of digital technologies in assessing fall risks among older adults with cognitive impairment: a systematic review. GeroScience 46, 2951–2975 (2024). https://doi.org/10.1007/s11357-024-01098-z

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