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Special Issue "Health Services and Rehabilitation Research of Older Adults"

A special issue of International Journal of Environmental Research and Public Health (ISSN 1660-4601). This special issue belongs to the section "Health Behavior, Chronic Disease and Health Promotion".

Deadline for manuscript submissions: 1 December 2023 | Viewed by 984

Special Issue Editors

Laboratory of Movement, Institute of Orthopedics and Traumatology, Clinics Hospital, Medicine School, University of Sao Paulo, Sao Paulo 01246-000, Brazil
Interests: rehabilitation; locomotor system; biomechanics; disabilities and spine
1. Graduate Program in Aging Sciences, Universidade São Judas Tadeu (USJT), São Paulo 03166-000, Brazil
2. Laboratory Study of Movement, Instituto de Ortopedia e Traumatologia do Hospital das Clínicas (IOT-HC) da Faculdade de Medicina da Universidade de São Paulo (FMUSP), São Paulo 01246-000, Brazil
Interests: osteoporosis; balance; rehabilitation
Special Issues, Collections and Topics in MDPI journals
Programa de Mestrado Ciências do Envelhecimento, Universidade São Judas Tadeu, São Paulo 03166-000, Brazil
Interests: biomechanics; ageing; rehabilitation; diabetes mellitus
Special Issues, Collections and Topics in MDPI journals
1. Laboratório de Lípides (LIM-10), Hospital das Clínicas (HCFMUSP) da Faculdade de Medicina da Universidade de São Paulo, São Paulo 01246-000, Brazil
2. Programa de Pós-Graduação em Ciências do Envelhecimento, Universidade São Judas Tadeu, São Paulo 03166-000, Brazil
Interests: ageing; nutrition; diabetes mellitus; advanced glycation end-products
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

The world's population is ageing rapidly, and it is critical that health services are ready for the treatment of these patients and the prevention of disabilities. Senescence produces physiological losses with decreased functional capacity in all systems of the organism, so even healthier ageing could cause incapacity, frailty, falls and deaths. Rehabilitation services should be prepared to receive patients with different types and levels of disabilities, including frailty, sequelae of vascular accidents, musculoskeletal diseases, sensory and cognitive losses, and others, who require multidisciplinary treatments that meet all the needs of this population. This Special Issue aims to publish original articles and systematic reviews of disabilities related to senescence and senility: frailty, sarcopenia, osteoporosis, musculoskeletal diseases, metabolic syndrome, neurological diseases, and cognitive losses. Additionally, articles on mental health, nutrition, physical activity, sports, and community life will be included, as well as those on the theme of ageing with some physical incapacity. Articles on rehabilitation units aimed at the care of the elderly are also expected, including models and programs.

Dr. Júlia Maria D́. Andréa Greve
Dr. Guilherme Carlos Brech
Dr. Angélica Castilho Alonso
Dr. Adriana Machado-Lima
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. International Journal of Environmental Research and Public Health is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2500 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • ageing
  • frailty
  • sarcopenia
  • rehabilitation
  • exercise
  • osteoporosis
  • cognition
  • prevention of falls
  • balance
  • sports
  • physical activity

Published Papers (1 paper)

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Research

Article
Crash Risk Predictors in Older Drivers: A Cross-Sectional Study Based on a Driving Simulator and Machine Learning Algorithms
Int. J. Environ. Res. Public Health 2023, 20(5), 4212; https://doi.org/10.3390/ijerph20054212 - 27 Feb 2023
Viewed by 786
Abstract
The ability to drive depends on the motor, visual, and cognitive functions, which are necessary to integrate information and respond appropriately to different situations that occur in traffic. The study aimed to evaluate older drivers in a driving simulator and identify motor, cognitive [...] Read more.
The ability to drive depends on the motor, visual, and cognitive functions, which are necessary to integrate information and respond appropriately to different situations that occur in traffic. The study aimed to evaluate older drivers in a driving simulator and identify motor, cognitive and visual variables that interfere with safe driving through a cluster analysis, and identify the main predictors of traffic crashes. We analyzed the data of older drivers (n = 100, mean age of 72.5 ± 5.7 years) recruited in a hospital in São Paulo, Brazil. The assessments were divided into three domains: motor, visual, and cognitive. The K-Means algorithm was used to identify clusters of individuals with similar characteristics that may be associated with the risk of a traffic crash. The Random Forest algorithm was used to predict road crash in older drivers and identify the predictors (main risk factors) related to the outcome (number of crashes). The analysis identified two clusters, one with 59 participants and another with 41 drivers. There were no differences in the mean of crashes (1.7 vs. 1.8) and infractions (2.6 vs. 2.0) by cluster. However, the drivers allocated in Cluster 1, when compared to Cluster 2, had higher age, driving time, and braking time (p < 0.05). The random forest performed well (r = 0.98, R2 = 0.81) in predicting road crash. Advanced age and the functional reach test were the factors representing the highest risk of road crash. There were no differences in the number of crashes and infractions per cluster. However, the Random Forest model performed well in predicting the number of crashes. Full article
(This article belongs to the Special Issue Health Services and Rehabilitation Research of Older Adults)
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