Cargando…
Development and validation of an algorithm to assess risk of first-time falling among home care clients
BACKGROUND: The falls literature focuses on individuals with previous falls, so little is known about individuals who have not experienced a fall in the past. Predicting falls in those without a prior event is critical for primary prevention of injuries. Identifying and intervening before the first...
Autores principales: | Kuspinar, Ayse, Hirdes, John P., Berg, Katherine, McArthur, Caitlin, Morris, John N. |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2019
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6792181/ https://www.ncbi.nlm.nih.gov/pubmed/31610776 http://dx.doi.org/10.1186/s12877-019-1300-2 |
Ejemplares similares
-
Examining the Effect of the First Wave of the COVID-19 Pandemic on Home Care Recipients’ Instrumental Activities of Daily Living Capacity
por: McArthur, Caitlin, et al.
Publicado: (2022) -
Associations with rates of falls among home care clients in Ontario, Canada: a population-based, cross-sectional study
por: Manis, Derek R., et al.
Publicado: (2020) -
Using machine learning algorithms to guide rehabilitation planning for home care clients
por: Zhu, Mu, et al.
Publicado: (2007) -
Social Engagement and Distress Among Home Care Recipients During the COVID-19 Pandemic in Ontario, Canada: A Retrospective Cohort Study
por: McArthur, Caitlin, et al.
Publicado: (2022) -
The Community Rehabilitation Assessment: patient and clinician-reported outcomes in ambulatory rehabilitation
por: Turcotte, Luke Andrew, et al.
Publicado: (2023)