title: Transaction logfile analysis in health communication research: challenges and opportunities.
abstract: OBJECTIVE
  To investigate the individualized nature of eHealth communication, it is necessary for us to go beyond the conventional approach to explain the effect of eHealth initiatives. The current article proposes transaction logfile analysis as a unique method to probe the process by which individuals locate needed information and obtains benefits out of it.
  
  
  METHODS
  This article discusses the background of logfile analysis along with practical and methodological issues related to the analysis of log data.
  
  
  RESULTS
  This article recommends potential solutions to resolve issues discussed in the Section 2.
  
  
  CONCLUSIONS
  This article discusses how transaction logfile analysis could benefit eHealth researchers, along with its relevance and application in health communication research. Logfile analysis could provide rich knowledge on how eHealth applications and tools work if performed on a regular basis, incorporated with appropriate measurement techniques and research design, and interpreted carefully.
  
  
  CONCLUSIONS
  Logfile analysis can point toward important design implications for more effective eHealth applications. Further, interventions employing logfile analysis require not only well-designed research models but also interdisciplinary research team to handle the multifaceted work involved in the process.
authors.affiliation: Department of Telecommunications, University of Georgia Henry W. Grady College of Journalism and Mass Communication, Athens, GA 30602-3018, USA. jeonghan@uga.edu
authors.forename: Jeong Yeob
authors.initials: JY
authors.lastname: Han
mesh_terms: D003191:Comprehensive Health Care; D058015:Health Communication; D006801:Humans; D057226:Information Seeking Behavior; D007256:Information Systems; D020407:Internet; D008490:Medical Informatics; D010353:Patient Education as Topic; D018802:Patient-Centered Care; D012107:Research Design; D014152:Transactional Analysis / Q000379:methods*