title: Prediction of falls in older adults with cancer: a preliminary study
abstract: To determine the extent to which falls occur in older adult patients with cancer; to identify how falls relate to depression, age, functional status, and cognition; and to develop a model for predicting falls.
  
  
  
  Descriptive, prospective, quantitative.
  
  
  
  Patients in the Senior Adult Oncology Program at the H. Lee Moffitt Cancer Center and Research Institute.
  
  
  
  165 patients aged 70 years or older with any diagnosis of cancer, treatment type, and stage.
  
  
  
  Data were collected during a one-time interview using a comprehensive geriatric assessment consisting of the Instrumental Activities of Daily Living (IADL) Scale, Activities of Daily Living (ADL) Scale, Geriatric Depression Scale, Mini-Mental State Examination, and a fall assessment.
  
  
  
  Falls, functional status, depression, cognition, age, and gender.
  
  
  
  IADL scores were found to be a predictor of falls while controlling for age and ADL status. An IADL score of 22 predicts a 21% risk of a fall. Fall risk increases to 81% at an IADL score of 9.
  
  
  
  IADL score is a predictor of falls in this older adult population with cancer. ADL scores are not a predictor of falls when IADL is included in the model.
  
  
  
  Nurses must play a vital role in conducting fall screening and risk assessments for older adults with cancer.
authors.affiliation: College of Nursing, University of South Florida, Tampa, FL, USA. jovercas@hsc.usf.edu
authors.forename: Janine
authors.identifier: 0000-0002-0717-5263
authors.initials: J
authors.lastname: Overcash
mesh_terms: D000058:Accidental Falls / Q000706:statistics & numerical data*; D000203:Activities of Daily Living; D000367:Age Factors; D000368:Aged; D015984:Causality; D015897:Comorbidity; D005260:Female; D005431:Florida / Q000453:epidemiology; D006801:Humans; D008137:Longitudinal Studies; D008297:Male; D008609:Mental Status Schedule; D009369:Neoplasms / Q000453:epidemiology*; D011446:Prospective Studies; D012044:Regression Analysis; D017678:Sex Distribution