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Enhancing Nurse–Robot Engagement: Two-Wave Survey Study
BACKGROUND: Robots 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. OBJECTIVE: This study aimed to examine how the benefits and maintenance of robots and nurses’ personal...
Autores principales: | , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
JMIR Publications
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9893885/ https://www.ncbi.nlm.nih.gov/pubmed/36622738 http://dx.doi.org/10.2196/37731 |
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author | Liao, Gen-Yih Huang, Tzu-Ling Wong, May-Kuen Shyu, Yea-Ing Lotus Ho, Lun-Hui Wang, Chi Cheng, T C E Teng, Ching-I |
author_facet | Liao, Gen-Yih Huang, Tzu-Ling Wong, May-Kuen Shyu, Yea-Ing Lotus Ho, Lun-Hui Wang, Chi Cheng, T C E Teng, Ching-I |
author_sort | Liao, Gen-Yih |
collection | PubMed |
description | BACKGROUND: Robots 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. OBJECTIVE: This study aimed to examine how the benefits and maintenance of robots and nurses’ personal innovativeness impact nurses’ attitudes to robots and nurse–robot engagement. METHODS: Our 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. RESULTS: Robot 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). CONCLUSIONS: Our 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. |
format | Online Article Text |
id | pubmed-9893885 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | JMIR Publications |
record_format | MEDLINE/PubMed |
spelling | pubmed-98938852023-02-03 Enhancing Nurse–Robot Engagement: Two-Wave Survey Study Liao, Gen-Yih Huang, Tzu-Ling Wong, May-Kuen Shyu, Yea-Ing Lotus Ho, Lun-Hui Wang, Chi Cheng, T C E Teng, Ching-I J Med Internet Res Original Paper BACKGROUND: Robots 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. OBJECTIVE: This study aimed to examine how the benefits and maintenance of robots and nurses’ personal innovativeness impact nurses’ attitudes to robots and nurse–robot engagement. METHODS: Our 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. RESULTS: Robot 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). CONCLUSIONS: Our 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. JMIR Publications 2023-01-09 /pmc/articles/PMC9893885/ /pubmed/36622738 http://dx.doi.org/10.2196/37731 Text en ©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. Originally published in the Journal of Medical Internet Research (https://www.jmir.org), 09.01.2023. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work, first published in the Journal of Medical Internet Research, is properly cited. The complete bibliographic information, a link to the original publication on https://www.jmir.org/, as well as this copyright and license information must be included. |
spellingShingle | Original Paper Liao, Gen-Yih Huang, Tzu-Ling Wong, May-Kuen Shyu, Yea-Ing Lotus Ho, Lun-Hui Wang, Chi Cheng, T C E Teng, Ching-I Enhancing Nurse–Robot Engagement: Two-Wave Survey Study |
title | Enhancing Nurse–Robot Engagement: Two-Wave Survey Study |
title_full | Enhancing Nurse–Robot Engagement: Two-Wave Survey Study |
title_fullStr | Enhancing Nurse–Robot Engagement: Two-Wave Survey Study |
title_full_unstemmed | Enhancing Nurse–Robot Engagement: Two-Wave Survey Study |
title_short | Enhancing Nurse–Robot Engagement: Two-Wave Survey Study |
title_sort | enhancing nurse–robot engagement: two-wave survey study |
topic | Original Paper |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9893885/ https://www.ncbi.nlm.nih.gov/pubmed/36622738 http://dx.doi.org/10.2196/37731 |
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