Evidence map›Paper›PMID 33776608›Full record

ArticleGerontechnology : international journal on the fundamental aspects of technology to serve the ageing society2020

Learning-Enabled Robotic Assistive Support: Understanding Older Adult Opinions and Comparing Them to Younger Adult Opinions.

Nisha Raghunath, Christopher Pereyda, Justin F Frow, Diane Cook, Maureen Schmitter-Edgecombe

Abstract read
In one paragraph

Article in Gerontechnology : international journal on the fundamental aspects of technology to serve the ageing society, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
–field-weighted citation impact
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

4 citing papers in PubMed.

  1. Article
  2. Evaluating Human-Robot Interactions to Support Healthy Aging-in-Place.Journal of applied gerontology : the official journal of the Southern Gerontological Society · 2025
    Review
  3. Article
  4. Article
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

5 authors.

Nisha RaghunathWashington State University Department of Psychology, Pullman, USA.
Christopher PereydaWashington State University School of EECS, Pullman, USA.
Justin F FrowWashington State University Department of Psychology, Pullman, USA.
Diane CookWashington State University School of EECS, Pullman, USA.
Maureen Schmitter-EdgecombeWashington State University Department of Psychology, Pullman, USA.

Funding

Multidisciplinary undergraduate training program in Health-assistive Smart EnvironmentsR25AG046114 · NIA · WASHINGTON STATE UNIVERSITY · PI COOK, DIANE JOYCE, MINOR, BRYAN · 2014 to 2025
$3.4M
Smart Technologies for Health Assessment and AssistanceR01EB009675 · NIBIB · WASHINGTON STATE UNIVERSITY · PI COOK, DIANE JOYCE, SCHMITTER-EDGECOMBE, MAUREEN · 2010 to 2017
$2.6M
NIA NIH HHS R25 AG046114NIBIB NIH HHS R01 EB009675
6 · The paper itself

Abstract

backgroundAs older adults age, they may require assistance completing activities of daily living (ADLs). Robotic assistance can offset healthcare costs and allow older adults to preserve their autonomy. Younger adults are often involved in the design and purchase of these robotic technologies, and must take into account the needs and expectations of the target population (i.e., older adults) to create a robot that the end-user will adopt. RESEARCH AIM/QUESTIONS: This study evaluated the opinions of both younger and older adults regarding the design and performance of the Robot Activity Support (RAS) system. It is important to understand points of agreement and divergence between these populations' perspectives so that effective robotic aids are created for older adults.

methodsFifty-two younger and older adults completed three scripted tasks with the RAS robot in a smart home environment. Each participant made task errors to cue the robot to offer help via three prompt modalities (guide to the object, video of forgotten step, and video of the full task). After interacting with the robot, participants completed questionnaires to evaluate their opinions of and satisfaction with the robot.

resultsThere were no differences between younger and older adults' perceptions of the robot across a variety of factors (e.g., likability, cognitive demand), with both age groups expressing generally neutral opinions. Both groups rated the Full Video prompt as least helpful, effective, and liked. Participants recommended the robot's response accuracy, movement speed, alerting style and system flexibility be improved. Younger adults overestimated how much older adults would want a robot like this.

conclusionsThis study underscores the importance of testing technology with the end-user, as older adults were less interested in having a similar robot in their home than younger counterparts expected. Future studies will show if older adults' opinions can be improved after making the recommended changes.

Indexed as

activities of daily livingassistanceautonomousmild cognitive impairmentrobotsmart home

Identifiers

PMID33776608
PMCPMC7993754

What OpenQuestion holds

Textmetadata
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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.