title: Using participant event monitoring in a cohort study of unintentional injuries among children and adolescents.
abstract: OBJECTIVE
  We conducted a 3-year cohort study of 407 youths aged 9 to 18 years to develop multivariable risk prediction models of agriculture-related injuries.
  
  
  METHODS
  Data were obtained via participant event monitoring, with youths self-reporting injuries and exposures in daily diaries over a 13-week period. We evaluated data quality by comparing injury self-reports with other injury data.
  
  
  RESULTS
  Semilogarithmic plots of rates of all unintentional injuries combined (US data from 2000) as well as of agriculture-related injuries (US and Canadian data from 19 previous studies) graphed as a function of injury severity exhibited linearity, as did plots based on the present results. Severity-specific unintentional injury rates were 1.4- to 4.3-times higher than national rates, suggesting that our methodology can significantly reduce injury underreporting. In addition, at each severity level, estimated agriculture-related injury rates were 5.8- to 9.3-times higher than rates from previous national, regional, and state-based studies.
  
  
  CONCLUSIONS
  Our approach to participant event monitoring can be implemented with youths aged 9 to 18 years and will yield reliable daily data on unintentional injuries.
authors.affiliation: Division of Epidemiology, School of Public Health, The Ohio State University, Columbus, OH 43210, USA. wilkins.2@osu.edu
authors.forename: J R
authors.initials: JR
authors.lastname: Wilkins
authors.forename: J Mac
authors.initials: JM
authors.lastname: Crawford
authors.forename: Lorann
authors.initials: L
authors.lastname: Stallones
authors.forename: Kathleen M
authors.initials: KM
authors.lastname: Koechlin
authors.forename: Lei
authors.initials: L
authors.lastname: Shen
authors.forename: John
authors.initials: J
authors.lastname: Hayes
authors.forename: Thomas L
authors.initials: TL
authors.lastname: Bean
mesh_terms: D000062:Accidents, Occupational / Q000706:statistics & numerical data*; D000293:Adolescent; D000383:Agriculture / Q000706:statistics & numerical data*; D002170:Canada / Q000453:epidemiology; D002648:Child; D015331:Cohort Studies; D004651:Employment / Q000706:statistics & numerical data*; D005260:Female; D006801:Humans; D038801:International Classification of Diseases; D008297:Male; D008499:Medical Records; D015999:Multivariate Analysis; D011159:Population Surveillance / Q000379:methods*; D018570:Risk Assessment; D012307:Risk Factors; D015599:Trauma Severity Indices; D014481:United States / Q000453:epidemiology; D014947:Wounds and Injuries / Q000453:epidemiology* / Q000209:etiology