title: Leveraging cues from person-generated health data for peer matching in online communities.
abstract: Online health communities offer a diverse peer support base, yet users can struggle to identify suitable peer mentors as these communities grow. To facilitate mentoring connections, we designed a peer-matching system that automatically profiles and recommends peer mentors to mentees based on person-generated health data (PGHD). This study examined the profile characteristics that mentees value when choosing a peer mentor.
  
  
  
  Through a mixed-methods user study, in which cancer patients and caregivers evaluated peer mentor recommendations, we examined the relative importance of four possible profile elements: health interests, language style, demographics, and sample posts. Playing the role of mentees, the study participants ranked mentors, then rated both the likelihood that they would hypothetically contact each mentor and the helpfulness of each profile element in helping the make that decision. We analyzed the participants' ratings with linear regression and qualitatively analyzed participants' feedback for emerging themes about choosing mentors and improving profile design.
  
  
  
  Of the four profile elements, only sample posts were a significant predictor for the likelihood of a mentee contacting a mentor. Communication cues embedded in posts were critical for helping the participants choose a compatible mentor. Qualitative themes offer insight into the interpersonal characteristics that mentees sought in peer mentors, including being knowledgeable, sociable, and articulate. Additionally, the participants emphasized the need for streamlined profiles that minimize the time required to choose a mentor.
  
  
  
  Peer-matching systems in online health communities offer a promising approach for leveraging PGHD to connect patients. Our findings point to interpersonal communication cues embedded in PGHD that could prove critical for building mentoring relationships among the growing membership of online health communities.
authors.affiliation: Group Health Research Institute, Seattle, USA hartzler.a@ghc.org.
authors.forename: Andrea L
authors.initials: AL
authors.lastname: Hartzler
authors.affiliation: Human Centered Design and Engineering, University of Washington, Seattle, USA.
authors.forename: Megan N
authors.initials: MN
authors.lastname: Taylor
authors.affiliation: Department of Biomedical Informatics and Medical Education, University of Washington, Seattle, USA.
authors.forename: Albert
authors.initials: A
authors.lastname: Park
authors.affiliation: The Information School, University of Washington, Seattle, USA.
authors.forename: Troy
authors.initials: T
authors.lastname: Griffiths
authors.affiliation: Department of Biomedical Informatics and Medical Education, University of Washington, Seattle, USA.
authors.forename: Uba
authors.initials: U
authors.lastname: Backonja
authors.affiliation: Human Centered Design and Engineering, University of Washington, Seattle, USA.
authors.forename: David W
authors.initials: DW
authors.lastname: McDonald
authors.affiliation: The Information School, University of Washington, Seattle, USA.
authors.forename: Sam
authors.initials: S
authors.lastname: Wahbeh
authors.affiliation: The Information School, University of Washington, Seattle, USA.
authors.forename: Cory
authors.initials: C
authors.lastname: Brown
authors.affiliation: The Information School, University of Washington, Seattle, USA.
authors.forename: Wanda
authors.initials: W
authors.lastname: Pratt
mesh_terms: D000328:Adult; D005260:Female; D006801:Humans; D020407:Internet; D008297:Male; D000071252:Mentoring; D008611:Mentors; D008875:Middle Aged; D010379:Peer Group; D012657:Self-Help Groups; D012944:Social Support
keywords: data display; human-computer interaction; online health communities; peer mentoring; peer support; user interfaces