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在人工智能时代评估巴基斯坦医疗保健社区对扩展现实(XR)技术的知识、态度和认知。

Assessing the knowledge, attitude and perception of Extended Reality (XR) technology in Pakistan's Healthcare community in an era of Artificial Intelligence.

作者信息

Khan Zoha, Adil Talha, Oduoye Malik Olatunde, Khan Bareerah Shaukat, Ayyazuddin Meher

机构信息

Azad Jammu Kashmir Medical College, Muzzaffarad, Pakistan.

Medical Research Circle, Bukavu, Democratic Republic of Congo.

出版信息

Front Med (Lausanne). 2024 Oct 16;11:1456017. doi: 10.3389/fmed.2024.1456017. eCollection 2024.


DOI:10.3389/fmed.2024.1456017
PMID:39478829
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC11521847/
Abstract

BACKGROUND AND OBJECTIVES: The Extended Reality (XR) technology was established by combining elements of Virtual Reality and Augmented Reality, offering users the advantage of working in a virtual environment. The study aimed to evaluate medical professionals' and students' knowledge, attitudes, and practices regarding using XR technology in Pakistan's healthcare system and identify its benefits, drawbacks, and implications for the system's future. METHODOLOGY: A cross-sectional study was executed by circulating a self-structured online questionnaire among the Medical Community across Major Cities of Pakistan using various social media platforms as available sampling. The sample size was calculated to be 385 using RAOSOFT. Cronbach's alpha was calculated as 0.74. The Exploratory Factor Analysis (EFA) conducted on the dataset was validated using the Kaiser-Meyer-Olkin (KMO) measure and Bartlett's Test of Sphericity. The KMO value of 0.752 indicates adequate sampling, and Bartlett's Test was significant (χ (435) = 2809.772, < 0.001), confirming the suitability of the data for factor analysis. Statistical analysis was done using SPSS-25, and data description was done as frequency and percentage. Pearson correlation and regression analysis kept -value < 0.05% significant. RESULTS: Approximately 54.8% of 406 participants conveyed their familiarity with XR technologies. The majority of participants (83.8%) believed that using XR technology effectively enhanced medical education and patient care in Pakistan. Regarding clinical outcomes, 70.8% believed XR improved the efficiency of procedures and 52.8% agreed XR would lead to more device-dependent systems and eradicating human error (32.4%). Major barriers to XR integration included ethical and privacy issues (63.9%), lack of technological advancements in Pakistan (70%), and lack of ample knowledge and training of XR among health care professionals (45.8%). Hypothesis testing revealed a low positive but significant correlation between the use of AI-based healthcare systems and the increasing speed and accuracy of procedures ( = 0.342, < 0.001), supporting Hypothesis 1. Similarly, a very low positive yet significant correlation was observed between the augmentation of diagnostic and surgical procedures and addressing data security and ethical issues for implementing XR ( = 0.298, < 0.001), supporting Hypothesis 2. Lastly, a correlation between the mean Attitude (MA) score and the mean Perception (MP) score was found to be moderately positive and significant ( = 0.356, < 0.001). Hence, the hypothesis 3 was supported. CONCLUSION: XR technology has the potential to enhance medical education and patient care in Pakistan, but its adoption faces significant challenges, including ethical concerns, technological gaps, and inadequate training. The study's findings highlight the need to address these issues to maximize the benefits of XR in healthcare.

摘要

背景与目的:扩展现实(XR)技术是通过融合虚拟现实和增强现实的元素而建立的,为用户提供了在虚拟环境中工作的优势。本研究旨在评估巴基斯坦医疗系统中医疗专业人员和学生对使用XR技术的知识、态度和实践,并确定其对该系统的益处、缺点及对未来的影响。 方法:采用横断面研究方法,通过各种社交媒体平台,在巴基斯坦主要城市的医疗群体中发放一份自行设计的在线问卷,作为可用抽样。使用RAOSOFT计算样本量为385。Cronbach's alpha系数计算为0.74。对数据集进行的探索性因子分析(EFA)使用Kaiser-Meyer-Olkin(KMO)度量和Bartlett球形检验进行验证。KMO值为0.752表明抽样充分,Bartlett检验具有显著性(χ(435)=2809.772,<0.001),证实数据适合进行因子分析。使用SPSS-25进行统计分析,数据描述采用频率和百分比形式。Pearson相关性和回归分析将p值<0.05%视为显著。 结果:406名参与者中约54.8%表示熟悉XR技术。大多数参与者(83.8%)认为使用XR技术能有效提升巴基斯坦的医学教育和患者护理水平。关于临床结果,70.8%的人认为XR提高了手术效率,52.8%的人同意XR将导致更多依赖设备的系统并消除人为错误(32.4%)。XR整合的主要障碍包括伦理和隐私问题(63.9%)、巴基斯坦缺乏技术进步(70%)以及医疗保健专业人员对XR缺乏足够的知识和培训(45.8%)。假设检验显示,基于人工智能的医疗系统的使用与手术速度和准确性的提高之间存在低正相关但显著相关(r = 0.342,p < 0.001),支持假设1。同样,在诊断和外科手术的增强与实施XR时解决数据安全和伦理问题之间观察到非常低的正相关但显著相关(r = 0.298,p < 0.001),支持假设2。最后,发现平均态度(MA)得分与平均认知(MP)得分之间存在中度正相关且显著(r = 0.356,p < 0.001)。因此,假设3得到支持。 结论:XR技术有潜力提升巴基斯坦的医学教育和患者护理水平,但其应用面临重大挑战,包括伦理问题、技术差距和培训不足。该研究结果凸显了解决这些问题以最大化XR在医疗保健中益处的必要性。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9eb2/11521847/600f17cb9758/fmed-11-1456017-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9eb2/11521847/600f17cb9758/fmed-11-1456017-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9eb2/11521847/600f17cb9758/fmed-11-1456017-g001.jpg

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本文引用的文献

[1]
Editorial: The use of extended realities providing better patient outcomes in healthcare.

Front Med (Lausanne). 2024-2-19

[2]
Knowledge, attitude and practice among pharmacy students and faculty members towards artificial intelligence in pharmacy practice: A multinational cross-sectional study.

PLoS One. 2024

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Immersive distance simulation: Exploring the educational impact of stereoscopic extended reality (XR) video in remote learning environments.

Med Teach. 2024-9

[4]
The Role of Artificial Intelligence in Anterior Cruciate Ligament Injuries: Current Concepts and Future Perspectives.

Healthcare (Basel). 2024-1-24

[5]
Problems and Opportunities of a Smartphone-Based Care Management Platform: Application of the Wald Principles to a Survey-Based Analysis of Patients' Perception in a Pilot Center.

Healthcare (Basel). 2024-1-9

[6]
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Arch Dermatol Res. 2024-1-9

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Exploring knowledge, attitudes, and practices towards artificial intelligence among health professions' students in Jordan.

BMC Med Inform Decis Mak. 2023-12-14

[8]
Using XR (Extended Reality) for Behavioral, Clinical, and Learning Sciences Requires Updates in Infrastructure and Funding.

Policy Insights Behav Brain Sci. 2023-10

[9]
Artificial Intelligence, Computational Simulations, and Extended Reality in Cardiovascular Interventions.

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