Evidence map›Paper›PMID 30894423›Full record

Trial reportBMJ quality & safety2019

Robot for health data acquisition among older adults: a pilot randomised controlled cross-over trial.

Roel Boumans, Fokke van Meulen, Koen Hindriks, Mark Neerincx, Marcel G M Olde Rikkert

Abstract readRandomized Controlled Trial
In one paragraph

Trial report in BMJ quality & safety, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
16citing papers in PubMed, 2 pooled it
–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

16 citing papers in PubMed, 2 syntheses or guidelines pooled it.

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4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

5 authors.

Roel BoumansDepartment of Geriatrics, Radboud University Medical Center, Nijmegen, The Netherlands roel.boumans@radboudumc.nl.ORCID 0000-0002-1287-6363
Fokke van MeulenDepartment of Geriatrics, Radboud University Medical Center, Nijmegen, The Netherlands.
Koen HindriksFaculty of Electrical Engineering, Mathematics and Computer Science, Delft University of Technology, Delft, The Netherlands.
Mark NeerincxFaculty of Electrical Engineering, Mathematics and Computer Science, Delft University of Technology, Delft, The Netherlands.
Marcel G M Olde RikkertDepartment of Geriatrics, Radboud University Medical Center, Nijmegen, The Netherlands.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

BACKGROUND /

objectivesHealthcare professionals (HCP) are confronted with an increased demand for assessments of important health status measures, such as patient-reported outcome measurements (PROM), and the time this requires. The aim of this study was to investigate the effectiveness and acceptability of using an HCP robot assistant, and to test the hypothesis that a robot can autonomously acquire PROM data from older adults.

designA pilot randomised controlled cross-over study where a social robot and a nurse administered three PROM questionnaires with a total of 52 questions.

settingA clinical outpatient setting with community-dwelling older adults.

participantsForty-two community-dwelling older adults (mean age: 77.1 years, SD: 5.7 years, 45% female). MEASUREMENTS: The primary outcome was the task time required for robot-patient and nurse-patient interactions. Secondary outcomes were the similarity of the data and the percentage of robot interactions completed autonomously. The questionnaires resulted in two values (robot and nurse) for three indexes of frailty, well-being and resilience. The data similarity was determined by comparing these index values using Bland-Altman plots, Cohen's kappa (κ) and intraclass correlation coefficients (ICC). Acceptability was assessed using questionnaires.

resultsThe mean robot interview duration was 16.57 min (SD=1.53 min), which was not significantly longer than the nurse interviews (14.92 min, SD=8.47 min; p=0.19). The three Bland-Altman plots showed moderate to substantial agreement between the frailty, well-being and resilience scores (κ=0.61, 0.50 and 0.45, and ICC=0.79, 0.86 and 0.66, respectively). The robot autonomously completed 39 of 42 interviews (92.8%).

conclusionSocial robots may effectively and acceptably assist HCPs by interviewing older adults.

Indexed as

Interviews as TopicPatient Reported Outcome MeasuresAgedAged, 80 and overCross-Over StudiesFemaleHumansMaleNetherlandsPatient SatisfactionPilot ProjectsRoboticsSurveys and QuestionnairesTimeolder adultspatient-reported outcome measurementquestionnairessocial robot

Identifiers

PMID30894423
PMCPMC6860647

What OpenQuestion holds

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LicenceCC BY-NC
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Registered trials

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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.