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评估医院环境中访客对 AI 护理机器人的期望:使用 Kano 模型的横断面研究。

Assessing Visitor Expectations of AI Nursing Robots in Hospital Settings: Cross-Sectional Study Using the Kano Model.

机构信息

Department of Nursing, Wuhan Asia Heart Hospital Affiliated to Wuhan University of Science and Technology, Wuhan, China.

Institute of Nursing Research, School of Medicine, Wuhan University of Science and Technology, Wuhan, China.

出版信息

JMIR Nurs. 2024 Nov 27;7:e59442. doi: 10.2196/59442.

DOI:10.2196/59442
PMID:39602413
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC11612591/
Abstract

BACKGROUND

Globally, the rates at which the aging population and the prevalence of chronic diseases are increasing are substantial. With declining birth rates and a growing percentage of older individuals, the demand for nursing staff is steadily rising. However, the shortage of nursing personnel has been a long-standing issue. In recent years, numerous researchers have advocated for the implementation of nursing robots as a substitute for traditional human labor.

OBJECTIVE

This study analyzes hospital visitors' attitudes and priorities regarding the functional areas of artificial intelligence (AI) nursing robots based on the Kano model. Building on this analysis, recommendations are provided for the functional optimization of AI nursing robots, aiming to facilitate their adoption in the nursing field.

METHODS

Using a random sampling method, 457 hospital visitors were surveyed between December 2023 and March 2024 to compare the differences in demand for AI nursing robot functionalities among the visitors.

RESULTS

A comparative analysis of the Kano attribute quadrant diagrams showed that visitors seeking hospitalization prioritized functional aspects that enhance medical activities. In contrast, visitors attending outpatient examinations focused more on functional points that assist in medical treatment. Additionally, visitors whose purpose was companionship and care emphasized functional aspects that offer psychological and life support to patients.

CONCLUSIONS

AI nursing robots serve various functional areas and cater to diverse audience groups. In the future, it is essential to thoroughly consider users' functional needs and implement targeted functional developments to maximize the effectiveness of AI nursing robots.

摘要

背景

在全球范围内,人口老龄化和慢性病患病率的增长速度都非常快。随着出生率的下降和老年人口比例的增加,对护理人员的需求正在稳步上升。然而,护理人员短缺一直是一个长期存在的问题。近年来,许多研究人员提倡使用护理机器人来代替传统的人工劳动。

目的

本研究基于 Kano 模型分析了医院访客对人工智能(AI)护理机器人功能领域的态度和优先事项。在此分析的基础上,为 AI 护理机器人的功能优化提供了建议,旨在促进其在护理领域的采用。

方法

2023 年 12 月至 2024 年 3 月期间,采用随机抽样方法对 457 名医院访客进行了调查,以比较访客对 AI 护理机器人功能的需求差异。

结果

对 Kano 属性象限图的比较分析表明,住院访客优先考虑增强医疗活动的功能方面。相比之下,门诊就诊访客更关注有助于医疗的功能点。此外,以陪伴和护理为目的的访客则强调为患者提供心理和生活支持的功能方面。

结论

AI 护理机器人服务于各种功能领域,并迎合不同的受众群体。未来,必须充分考虑用户的功能需求,并实施有针对性的功能开发,以最大限度地发挥 AI 护理机器人的效果。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ee9a/11612591/fc8efab46653/nursing-v7-e59442-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ee9a/11612591/fec710c35b98/nursing-v7-e59442-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ee9a/11612591/b7b31290ff6e/nursing-v7-e59442-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ee9a/11612591/396a26e4a4ef/nursing-v7-e59442-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ee9a/11612591/0b8fdd0ff57d/nursing-v7-e59442-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ee9a/11612591/fc8efab46653/nursing-v7-e59442-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ee9a/11612591/fec710c35b98/nursing-v7-e59442-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ee9a/11612591/b7b31290ff6e/nursing-v7-e59442-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ee9a/11612591/396a26e4a4ef/nursing-v7-e59442-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ee9a/11612591/0b8fdd0ff57d/nursing-v7-e59442-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ee9a/11612591/fc8efab46653/nursing-v7-e59442-g005.jpg

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JMIR Aging. 2024 Aug 27;7:e55257. doi: 10.2196/55257.
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Asian Pac Isl Nurs J. 2024 Aug 14;8:e59484. doi: 10.2196/59484.
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Spiritual care needs and their attributes among Chinese inpatients with advanced breast cancer based on the Kano model: a descriptive cross-sectional study.
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BMC Palliat Care. 2024 Feb 22;23(1):50. doi: 10.1186/s12904-024-01377-8.
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Int J Nurs Stud. 2023 Dec;148:104612. doi: 10.1016/j.ijnurstu.2023.104612. Epub 2023 Sep 29.
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