title: Comparing GPS, Log, Survey, and Accelerometry to Measure Physical Activity.
abstract: OBJECTIVE
  We explored how objectively measured global positioning system (GPS) and accelerometer data match with travel logs and questionnaires in predicting trip duration and physical activity (PA).
  
  
  METHODS
  99 participants wore GPS devices and accelerometers, and recorded all trips in a log for 5 consecutive days. Participants also completed a self-administered questionnaire on PA and travel behaviors.
  
  
  RESULTS
  There was good agreement between GPS and log for assessment of trip duration, although log measures overestimated trip duration (concordance correlation coefficient 0.53 [0.47, 0.59]; Bland-Altman estimate 0.76 [0.16, 3.71] comparing GPS to log). Log measures underestimated light PA and overestimated moderate PA compared to accelerometry when greater than zero moderate PA was reported.
  
  
  CONCLUSIONS
  It is often not feasible to deploy accelerometry or GPS devices in population research because these devices are expensive and require technical expertise and data processing. Questionnaires and logs provide inexpensive tools to assess PA and travel with reasonable concordance with objective measures. However, they have shortcomings in evaluating the presence and amount of light and moderate PA. Future questionnaires and logs should be developed to evaluate sensitivity to light and moderate PA.
authors.affiliation: Harvard TH Chan School of Public Health, Department of Epidemiology, Boston, MA, USA. pjames@hsph.harvard.edu.
authors.forename: Peter
authors.initials: P
authors.lastname: James
authors.affiliation: Emory University, Rollins School of Public Health, Atlanta, GA, USA.
authors.forename: Jennifer
authors.initials: J
authors.lastname: Weissman
authors.affiliation: Westat Geostats Services, Atlanta, GA, USA.
authors.forename: Jean
authors.initials: J
authors.lastname: Wolf
authors.affiliation: Watershed Institute for Collaborative Environmental Studies, University of Wisconsin-Eau Claire, Eau Claire, WI, USA.
authors.forename: Karen
authors.initials: K
authors.lastname: Mumford
authors.affiliation: Advancing Your Strengths Consulting, Eau Claire, WI, USA.
authors.forename: Cheryl K
authors.initials: CK
authors.lastname: Contant
authors.affiliation: University of Pennsylvania Perelman School of Medicine, Department of Biostatistics, Philadelphia, PA, USA.
authors.forename: Wei-Ting
authors.initials: WT
authors.lastname: Hwang
authors.affiliation: University of Pennsylvania Perelman School of Medicine, Department of Biostatistics, Philadelphia, PA, USA.
authors.forename: Lynne
authors.initials: L
authors.lastname: Taylor
authors.affiliation: University of Pennsylvania Perelman School of Medicine, Department of Biostatistics and Epidemiology, Philadelphia, PA, USA.
authors.forename: Karen
authors.initials: K
authors.lastname: Glanz
mesh_terms: D061725:Accelerometry / Q000592:standards*; D000328:Adult; D005260:Female; D040362:Geographic Information Systems / Q000592:standards*; D006306:Health Surveys / Q000592:standards*; D006801:Humans; D008297:Male; D009043:Motor Activity; D057566:Self Report / Q000592:standards*