title: Is the pain of activity log-books worth the gain in precision when distinguishing wear and non-wear time for tri-axial accelerometers?
abstract: OBJECTIVE
  To compare three methods for assessing wear time from accelerometer data: automated, log-books and a combination of the two.
  
  
  METHODS
  Cross-sectional study.
  
  
  METHODS
  Forty-five office workers wore an Actigraph GT3X accelerometer and kept a detailed activity log-book for 7 days. The automated method used six algorithms to determine non-wear time (20, 60, or 90 min of consecutive zero counts with and without 2-min interruptions); the log-book method used participant recorded on/off times; the combined method used the 60-min automated filter (with ≤2 min interruptions) plus detailed log-book data. Outcomes were number of participants with valid data, number of valid days, estimates of wear time and time spent in sedentary, light, moderate and vigorous activity. Percentage misclassification, sensitivity, specificity, and area under the receiver-operating curve were compared for each method, with the combined method as the reference.
  
  
  RESULTS
  Using the combined method, 34 participants met criteria for valid wear time (≥10 h/day, ≥4 days). Mean wear times ranged from 891 to 925 min/day and mean sedentary time s from 438 to 490 min/day. Percentage misclassification was higher and area under the receiver-operating curve was lower for the log-book method than for the automated methods. Percentage misclassification was lowest and area under the receiver-operating curve highest for the 20-min filter without interruptions, but this method had fewer valid days and participants than the 60 and 90-min filters without interruptions.
  
  
  CONCLUSIONS
  Automated filters are as accurate as a combination of automated filters and log-books for filtering wear time from accelerometer data. Automated filters based on 90-min of consecutive zero counts without interruptions are recommended for future studies.
authors.affiliation: School of Human Movement Studies, The University of Queensland, Brisbane, Australia; School of Population Health, The University of Queensland, Brisbane, Australia. Electronic address: g.peeters@uq.edu.au.
authors.forename: Geeske
authors.initials: G
authors.lastname: Peeters
authors.forename: Yolanda
authors.initials: Y
authors.lastname: van Gellecum
authors.forename: Gemma
authors.initials: G
authors.lastname: Ryde
authors.forename: Nicolas Aguilar
authors.initials: NA
authors.lastname: Farías
authors.forename: Wendy J
authors.initials: WJ
authors.lastname: Brown
mesh_terms: D061725:Accelerometry / Q000592:standards*; D000328:Adult; D003430:Cross-Sectional Studies; D005260:Female; D006801:Humans; D008297:Male; D008875:Middle Aged; D010865:Pilot Projects; D057566:Self Report / Q000592:standards
keywords: Actigraphy; Methods; Motor activity; Reproducibility of results