I have a very specialpodcast to tell you about today. My digital twin, created withNotebookLM from Google, has recorded a podcast for me.
And the topic is no less exciting: it's about our latestpublication, which is based onreal-world data and thecorrelation between fall risk and actualfalls in older adults.
Imagine we're moving as a company, unpacking the boxes, setting up the desks - and a podcast on a deeply technical topic is being created along the way. Because the renownedJMIR Aging Journal (Impact Factor 5.0) has published our submission:
"Evaluating the prognostic and clinical validity of the Fall Risk Scorederived from an AI-based mHealth application for fall prevention: a retrospective real-world data analysis"
My digital twin sat down with one of the authors of the World Fall Guidelines, a globally recognized expert on fall prevention, and discussed my recently published study on fall risk assessment.
In the study, we examined an artificial intelligence-based mHealth application (LINDERA Mobility Analysis) for fall prevention.
The app was used in German care facilities and calculates afall risk score(FRS).
The special feature: the app records the user's gait parameters via a smartphone-based video analysis and records additional risk factors using a questionnaire.
The rejection shows once again that the care sector cannot be assessed using criteria from the field of pharmacology. Simply looking at scientific evidence without incorporating nursing expertise leaves no room for the realities of everyday nursing care.
In nursing practice, there are unavoidable influencing factors that cannot be fully taken into account in scientific study designs.
At the same time, the urgency to find innovative solutions for care remains unaffected - because the number of fatal falls at home has doubled in the last ten years according to the NRW State Statistical Office.