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An Interactive Home-Based Cognitive-Motor Step Training Program to Reduce Fall Risk in Older Adults: Qualitative Descriptive Study of Older Adults’ Experiences and Requirements

An Interactive Home-Based Cognitive-Motor Step Training Program to Reduce Fall Risk in Older Adults: Qualitative Descriptive Study of Older Adults’ Experiences and Requirements

IntroductionBackgroundAccidental falls are a major contributor to the burden of disease in older adults and a major public health problem. One-third of people aged 65 years and above fall every year [1].

Trinidad Valenzuela, Husna Razee, Daniel Schoene, Stephen Ronald Lord, Kim Delbaere

JMIR Aging 2018;1(2):e11975

Re-Enactment as a Method to Reproduce Real-World Fall Events Using Inertial Sensor Data: Development and Usability Study

Re-Enactment as a Method to Reproduce Real-World Fall Events Using Inertial Sensor Data: Development and Usability Study

In contrast, video data facilitates the possibility of estimating the kinematics of falls as well as the fall-related movements before and after the fall event [10].

Kim Sarah Sczuka, Lars Schwickert, Clemens Becker, Jochen Klenk

J Med Internet Res 2020;22(4):e13961

Natural Language Processing of Medical Alert Service Notes Reveals Reasons for Emergency Admissions

Natural Language Processing of Medical Alert Service Notes Reveals Reasons for Emergency Admissions

For example, the incidents labeled as falls (n=37,842) were split into several subclusters corresponding to falls with bone fracture (n=1437), falls with bleeding (n=4137), falls caused by dizziness (n=519), etc.ConclusionsThe combination of state-of-the-art

Felipe Masculo, Jorn op den Buijs, Mariana Simons, Aki Harma

iproc 2019;5(1):e15225

Predicting Inpatient Falls Using Natural Language Processing of Nursing Records Obtained From Japanese Electronic Medical Records: Case-Control Study

Predicting Inpatient Falls Using Natural Language Processing of Nursing Records Obtained From Japanese Electronic Medical Records: Case-Control Study

After analyzing data from 1263 hospitals, Bouldin et al [1] reported that the rate of falls in the United States was 3.56 per 1000 patient-days during a 27-month study period and that 26.1% of these falls (0.93 per 1000 patient-days) resulted in injury.

Hayao Nakatani, Masatoshi Nakao, Hidefumi Uchiyama, Hiroyoshi Toyoshiba, Chikayuki Ochiai

JMIR Med Inform 2020;8(4):e16970

A Population-Based Intervention for the Prevention of Falls and Fractures in Home Dwelling People 65 Years and Older in South Germany: Protocol

A Population-Based Intervention for the Prevention of Falls and Fractures in Home Dwelling People 65 Years and Older in South Germany: Protocol

The development and implementation of strategies to prevent falls and fall-related injuries have therefore been recognized as an urgent public health challenge.A variety of risk factors for falls have been identified, and a number of interventions have shown

Diana Klein, Kilian Rapp, Michaela Küpper, Clemens Becker, Torben Fischer, Gisela Büchele, Petra Benzinger

JMIR Res Protoc 2014;3(1):e19

Reduction in Fall Rate in Dementia Managed Care Through Video Incident Review: Pilot Study

Reduction in Fall Rate in Dementia Managed Care Through Video Incident Review: Pilot Study

Falls are the leading cause of both fatal and nonfatal injuries among people aged 65 and older, with estimated yearly direct medical costs of US $637.2 million for fatal falls and US $31.3 billion for nonfatal falls in the United States alone [2].

Eleonore Bayen, Julien Jacquemot, George Netscher, Pulkit Agrawal, Lynn Tabb Noyce, Alexandre Bayen

J Med Internet Res 2017;19(10):e339

A Protocol-Driven, Bedside Digital Conversational Agent to Support Nurse Teams and Mitigate Risks of Hospitalization in Older Adults: Case Control Pre-Post Study

A Protocol-Driven, Bedside Digital Conversational Agent to Support Nurse Teams and Mitigate Risks of Hospitalization in Older Adults: Case Control Pre-Post Study

As a result, the falls data on the second intervention unit represent a mixed unit, with the first half of the quarterly falls data not including participants receiving the intervention.

Nicholas Bott, Sharon Wexler, Lin Drury, Chava Pollak, Victor Wang, Kathleen Scher, Sharon Narducci

J Med Internet Res 2019;21(10):e13440

Fall Risk Classification in Community-Dwelling Older Adults Using a Smart Wrist-Worn Device and the Resident Assessment Instrument-Home Care: Prospective Observational Study

Fall Risk Classification in Community-Dwelling Older Adults Using a Smart Wrist-Worn Device and the Resident Assessment Instrument-Home Care: Prospective Observational Study

A functional decline and a higher level of frailty caused by the muscular atrophy would escalate the risk for falls in older population [8,10,11]. The occurrence of falls increases with frailty level [4,11].

Yang Yang, John P Hirdes, Joel A Dubin, Joon Lee

JMIR Aging 2019;2(1):e12153