Evidence map›Paper›PMID 37081106›Full record

ArticleScientific reports2023

Exploring the role of human-following robots in supporting the mobility and wellbeing of older people.

Shuo Li, Kirsty Milligan, Phil Blythe, Yanghanzi Zhang, Simon Edwards, Nic Palmarini, Lynne Corner, Yanjie Ji, Fan Zhang, Anil Namdeo

Open access · goldAbstract read
In one paragraph

Article in Scientific reports, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed, 1 pooled it
5.3field-weighted citation impact, top 4% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

5 citing papers in PubMed, 1 synthesis or guideline pooled it, 16 citations in OpenAlex.

  1. Pooled it
  2. Article
  3. Article
  4. Article
  5. Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

10 authors at 4 institutions in 2 countries.

Shuo LiSchool of Engineering, Newcastle University, Cassie Building, Claremont Road, Newcastle Upon Tyne, NE1 7RU, UK. shuo.li@newcastle.ac.uk.
Kirsty MilliganSchool of Engineering, Newcastle University, Cassie Building, Claremont Road, Newcastle Upon Tyne, NE1 7RU, UK.
Phil BlytheSchool of Engineering, Newcastle University, Cassie Building, Claremont Road, Newcastle Upon Tyne, NE1 7RU, UK.
Yanghanzi ZhangSchool of Engineering, Newcastle University, Cassie Building, Claremont Road, Newcastle Upon Tyne, NE1 7RU, UK.
Simon EdwardsSchool of Engineering, Newcastle University, Cassie Building, Claremont Road, Newcastle Upon Tyne, NE1 7RU, UK.
Nic PalmariniUK's National Innovation Centre for Ageing, The Catalyst, 3 Science Square, Newcastle Upon Tyne, NE4 5TG, UK.
Lynne CornerUK's National Innovation Centre for Ageing, The Catalyst, 3 Science Square, Newcastle Upon Tyne, NE4 5TG, UK.
Yanjie JiJiangsu Key Laboratory of Urban ITS, Jiangsu Province Collaborative Innovation Centre of Modern Urban Traffic Technologies, School of Transportation, Southeast University, Southeast University Road 2, Nanjing, 211189, China.
Fan ZhangJiangsu Key Laboratory of Urban ITS, Jiangsu Province Collaborative Innovation Centre of Modern Urban Traffic Technologies, School of Transportation, Southeast University, Southeast University Road 2, Nanjing, 211189, China.
Anil NamdeoDepartment of Geography and Environmental Sciences, Northumbria University, Ellison Place, Newcastle Upon Tyne, NE1 8ST, UK.
Newcastle University · GBNewcastle Hospitals - Campus for Ageing and Vitality · GBSoutheast University · CNNorthumbria University · GB

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

With the ever-pressing challenges of societal ageing, robotic technologies for older people are increasingly portrayed as a solution for better independent living for longer. However, the application of human-following robots for elderly citizens has not yet been considered, and any prospective benefits offered by the technology for active ageing have previously been overlooked. This qualitative research aimed to explore older people's needs and requirements towards the human-following robot through the reflexive thematic analysis of semi-structured interview data from 17 independent older adults, supported by a video-based demonstration of the robot. The results indicate that older people believed that human-following robot has the potential to provide social benefits to an independent older adult by encouraging walking trips and prompting social interaction with others in the community. Practical limitations and cost of the robot are barriers to adoption at present. The findings indicate that there is potential for human-following robots to support active ageing, through increasing opportunities for the social participation of an older adult, but further development of the robot is needed for this potential to be realised.

Indexed as

RoboticsAgedAgingHumansIndependent LivingQualitative ResearchTechnology

Identifiers

PMID37081106
PMCPMC10119299
OpenAlexW4366548426

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.