title: Improving knowledge of patient skills thanks to automatic analysis of online discussions.
abstract: OBJECTIVE
  Automatically analyze the online discussions related to diabetes and extract information on patient skills for managing this disease.
  
  
  METHODS
  Two collections of about 7000 and 23,000 messages from online discussion fora and 174 skills from an available taxonomy are processed with Natural Language Processing methods and semantically enriched. Skills are projected on the messages to detect those skills which are mentioned by patients. Quantitative and qualitative evaluation is performed.
  
  
  RESULTS
  The method recognizes almost all the aimed skills in fora. The quality of the skills' recognition varies with the method's parameters. Most of the selected messages are relevant to at least one of the associated skills. Manual analysis shows a substantial number of messages is dedicated to daily self-care and psychosocial skills.
  
  
  CONCLUSIONS
  Study of real exchanges between patients leads to a better understanding of their skills in daily self-management of diabetes.
  
  
  CONCLUSIONS
  Our experiments can be useful for a better understanding and better knowledge of self-management of diseases by patients. They can also refine existing patient education programs.
authors.affiliation: Laboratory of Medical Informatics and BioInformatics (EA3969), University Paris 13, Bobigny, France. thierry.hamon@univ-paris13.fr
authors.forename: Thierry
authors.initials: T
authors.lastname: Hamon
authors.forename: Rémi
authors.initials: R
authors.lastname: Gagnayre
mesh_terms: D003920:Diabetes Mellitus / Q000628:therapy*; D019468:Disease Management; D034742:Electronic Mail; D005260:Female; D007722:Health Knowledge, Attitudes, Practice; D006801:Humans; D020407:Internet; D008297:Male; D009323:Natural Language Processing; D012648:Self Care
keywords: Natural Language Processing; Online discussion fora; Patient skills; Taxonomy of patient skills; Text mining; Therapeutic patient education