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Descriptive Evaluation and Accuracy of a Mobile App to Assess Fall Risk in Seniors: Retrospective Case-Control Study.

Sophie RabeArash AzhandWolfgang PommerSwantje MüllerAnika Steinert
Published in: JMIR aging (2020)
Descriptive statistics for the dataset were provided as comparison and reference values. The fall-risk score exhibited a high discriminative ability to distinguish fallers from nonfallers, irrespective of the learning model evaluated. The models had an average AUC of 0.86, an average sensitivity of 93%, and an average specificity of 58%. Average overall accuracy was 73%. Thus, the fall-risk app has the potential to support caretakers in easily conducting a valid fall-risk assessment. The fall-risk score's prospective accuracy will be further validated in a prospective trial.
Keyphrases
  • risk assessment
  • cross sectional
  • human health
  • randomized controlled trial
  • heavy metals
  • phase iii
  • climate change