title: Improving older adults' experience with interactive voice response systems.
abstract: BACKGROUND
  Interactive voice response (IVR) systems use computer-based voice recognition and software algorithms to conduct human/computer interactions. In recent years, there has been a proliferation of IVR applications in business and healthcare. The available evidence suggests that older people have negative attitudes towards IVR and experience significant difficulties using these systems.
  
  
  OBJECTIVE
  The goal of this project was to identify areas of difficulties in IVR use by older people and propose strategies for improvement.
  
  
  METHODS
  During two focus groups, we examined older people's perceptions of IVR systems and the most common difficulties experienced by seniors in interacting with these systems. We also recorded their suggestions for improvement of IVR.
  
  
  RESULTS
  Frequency and chi square analyses were performed on the focus groups data. Some of the difficulties reported by participants in this study were congruent with previous findings, but we also uncovered some additional problems, such as frustration for not being able to reach an operator, being asked to wait too long on hold, being unable to recover from mistakes, and an absence of shortcuts in the systems. In addition, significant number of participants indicated that they prefer a system that adjusts to them automatically as opposed to a system that allows for adjustment.
  
  
  CONCLUSIONS
  Generally, our findings suggest that the poor acceptability of IVR systems by older people could be improved by designing IVR algorithms that detect difficulties during an ongoing IVR exchange and direct people to different algorithms adapted for each person.
authors.affiliation: School of Psychology, University of Ottawa, Ontario, Canada.
authors.forename: Delyana Ivanova
authors.initials: DI
authors.lastname: Miller
authors.forename: Halina
authors.initials: H
authors.lastname: Bruce
authors.forename: Michèle
authors.initials: M
authors.lastname: Gagnon
authors.forename: Vincent
authors.initials: V
authors.lastname: Talbot
authors.forename: Claude
authors.initials: C
authors.lastname: Messier
mesh_terms: D000368:Aged; D000369:Aged, 80 and over; D004522:Educational Status; D005260:Female; D017144:Focus Groups; D006801:Humans; D008297:Male; D017060:Patient Satisfaction; D049250:Speech Recognition Software / Q000592:standards / Q000639:trends*; D017216:Telemedicine / Q000379:methods / Q000592:standards / Q000639:trends*; D014584:User-Computer Interface