Cited by 60Social Robot Interaction and HRITechnology Use by Older AdultsRobotics and Automated Systems

Robots in Older People’s Homes to Improve Medication Adherence and Quality of Life: A Randomised Cross-Over Trial

Broadbent, Elizabeth, Peri, Kathy, Kerse, Ngaire, Jayawardena, Chandimal, Kuo, IHan, Datta, Chandan, MacDonald, Bruce·2014·Lecture Notes in Computer Science

Integrity signals

Registry

Crossref · 10.1007/978-3-319-11973-1_7

Cites

22 of 22 references verified0 citation errors · 0 not checkable

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  • Speech is largely considered the most powerful communication mode for social robots to engage with end users.

    “Speech is largely considered the most powerful communication mode for social robots to engage with end users [31].”

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Authors
Broadbent, E., Peri, K., Kerse, N., Jayawardena, C., Kuo, I., Datta, C., & MacDonald, B.
Affiliations
University of Auckland (NZ)
Venue
Lecture Notes in Computer Science
Published
2014
Pages
64-73
ISSN
  • 0302-9743 (ISSN-L)
  • 1611-3349
OpenAlex
W1558982838
Cited by
60
References
22
Citations by year
2026: 8 · 2025: 3 · 2024: 3 · 2023: 6 · 2022: 13 · 2021: 5 · 2020: 8 · 2019: 3 · 2018: 4 · 2017: 3 · 2016: 2 · 2015: 2
FWCI
4.49
Type
conference paper
Language
en
Open access
closed
Locations
  • Lecture notes in computer science (publishedVersion)
  • Unitec Research Bank (Unitec Institute of Technology) (submittedVersion)
Topics
  • Social Sciences › Psychology › Social Psychology › Social Robot Interaction and HRI
  • Social Sciences › Demography › Technology Use by Older Adults
  • Physical Sciences › Engineering › Control and Systems Engineering › Robotics and Automated Systems
Keywords
healthcare robots, older adults, medication adherence, quality of life, depression, retirement communities, medication reminders, social robots, acceptability, feasibility, perceived agency, independent living

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Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

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