Evidence map›Paper›PMID 36622738›Full record

ArticleJournal of medical Internet research2023

Enhancing Nurse-Robot Engagement: Two-Wave Survey Study.

Gen-Yih Liao, Tzu-Ling Huang, May-Kuen Wong, Yea-Ing Lotus Shyu, Lun-Hui Ho, Chi Wang, T C E Cheng, Ching-I Teng

Abstract read
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Article in Journal of medical Internet research, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing 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

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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

6 citing papers in PubMed.

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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

8 authors.

Gen-Yih LiaoDepartment of Information Management, Chang Gung University, Taoyuan, Taiwan.ORCID 0000-0002-6712-1400
Tzu-Ling HuangDepartment of Information Management, National Central University, Taoyuan, Taiwan.ORCID 0000-0002-3358-6779
May-Kuen WongDepartment of Physical Medicine and Rehabilitation, Chang Gung Memorial Hospital, Linkou, Taoyuan, Taiwan.ORCID 0000-0003-3586-1292
Yea-Ing Lotus ShyuSchool of Nursing, College of Medicine, Chang Gung University, Taoyuan, Taiwan.ORCID 0000-0002-9697-535X
Lun-Hui HoDepartment of Nursing, Chang Gung Memorial Hospital, Linkou, Taoyuan, Taiwan.ORCID 0000-0001-9110-0530
Chi WangSchool of Nursing, College of Medicine, Chang Gung University, Taoyuan, Taiwan.ORCID 0000-0002-2033-0870
T C E ChengDepartment of Logistics and Maritime Studies, The Hong Kong Polytechnic University, Kowloon, Hong Kong.ORCID 0000-0001-5127-6419
Ching-I TengDepartment of Physical Medicine and Rehabilitation, Chang Gung Memorial Hospital, Linkou, Taoyuan, Taiwan.ORCID 0000-0002-3976-5399

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundRobots are introduced into health care contexts to assist health care professionals. However, we do not know how the benefits and maintenance of robots influence nurse-robot engagement.

objectiveThis study aimed to examine how the benefits and maintenance of robots and nurses' personal innovativeness impact nurses' attitudes to robots and nurse-robot engagement.

methodsOur study adopted a 2-wave follow-up design. We surveyed 358 registered nurses in operating rooms in a large-scale medical center in Taiwan. The first-wave data were collected from October to November 2019. The second-wave data were collected from December 2019 to February 2020. In total, 344 nurses participated in the first wave. We used telephone to follow up with them and successfully followed-up with 331 nurses in the second wave.

resultsRobot benefits are positively related to nurse-robot engagement (β=.13, P<.05), while robot maintenance requirements are negatively related to nurse-robot engagement (β=-.15, P<.05). Our structural model fit the data acceptably (comparative fit index=0.96, incremental fit index=0.96, nonnormed fit index=0.95, root mean square error of approximation=0.075).

conclusionsOur study is the first to examine how the benefits and maintenance requirements of assistive robots influence nurses' engagement with them. We found that the impact of robot benefits on nurse-robot engagement outweighs that of robot maintenance requirements. Hence, robot makers should consider emphasizing design and communication of robot benefits in the health care context.

Indexed as

RoboticsCross-Sectional StudiesHealth PersonnelHospitalsHumansSurveys and QuestionnairesAsiaattitudebenefitdigital heatheHealthengagementhealth carehealthcarehealthcare professionalhealth technologyintelligent technologynursenursingpersonal innovativenessrobotroboticssmart technologystructural equation modelingsurveyTaiwan

Identifiers

PMID36622738
PMCPMC9893885

What OpenQuestion holds

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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.