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农村急诊医学的数字化转型:工作满意度和工作量对沟通和技术接受的影响。

Digital transition in rural emergency medicine: Impact of job satisfaction and workload on communication and technology acceptance.

机构信息

Steinbeis University, Berlin, Germany.

Curacon Ltd., Muenster, Germany.

出版信息

PLoS One. 2023 Jan 24;18(1):e0280956. doi: 10.1371/journal.pone.0280956. eCollection 2023.

DOI:10.1371/journal.pone.0280956
PMID:36693080
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC9873191/
Abstract

BACKGROUND

Tele-emergency physicians (TEPs) take an increasingly important role in the need-oriented provision of emergency patient care. To improve emergency medicine in rural areas, we set up the project 'Rural|Rescue', which uses TEPs to restructure professional rescue services using information and communication technologies (ICTs) in order to reduce the therapy-free interval. Successful implementation of ICTs relies on user acceptance and knowledge sharing behavior.

METHOD

We conducted a factorial design with active knowledge transfer and technology acceptance as a function of work satisfaction (high vs. low), workload (high vs. low) and point in time (prior to vs. after digitalization). Data were collected via machine readable questionnaires issued to 755 persons (411 pre, 344 post), of which 304 or 40.3% of these persons responded (194 pre, 115 post).

RESULTS

Technology acceptance was higher after the implementation of TEP for nurses but not for other professions, and it was higher when the workload was high. Regarding active communication and knowledge sharing, employees with low work satisfaction are more likely to share their digital knowledge as compared to employees with high work satisfaction. This is an effect of previous knowledge concerning digitalization: After implementing the new technology, work satisfaction increased for the more experienced employees, but not for the less experienced ones.

CONCLUSION

Our research illustrates that employees' workload has an impact on the intention of using digital applications. The higher the workload, the more people are willing to use TEPs. Regarding active knowledge sharing, we see that employees with low work satisfaction are more likely to share their digital knowledge compared to employees with high work satisfaction. This might be attributed to the Dunning-Kruger effect. Highly knowledgeable employees initially feel uncertain about the change, which translates into temporarily lower work satisfaction. They feel the urge to fill even small knowledge gaps, which in return leads to higher work satisfaction. Those responsible need to acknowledge that digital change affects their employees' workflow and work satisfaction. During such times, employees need time and support to gather information and knowledge in order to cope with digitally changed tasks.

摘要

背景

远程急诊医师(TEP)在满足需求的急诊患者护理中发挥着越来越重要的作用。为了改善农村地区的急诊医学,我们设立了“农村救援”项目,该项目使用 TEP 使用信息和通信技术(ICT)来重组专业救援服务,以减少治疗前的间隔时间。成功实施 ICT 依赖于用户接受度和知识共享行为。

方法

我们采用了因子设计,将主动知识转移和技术接受作为工作满意度(高与低)、工作量(高与低)和时间点(数字化之前与之后)的函数。通过向 755 人(411 人之前,344 人之后)发放机器可读问卷收集数据,其中 304 人或 40.3%的人做出了回应(194 人之前,115 人之后)。

结果

TEP 实施后,护士对技术的接受程度更高,但其他职业并非如此,而且当工作量较高时,接受程度也更高。关于主动沟通和知识共享,与工作满意度高的员工相比,工作满意度低的员工更有可能分享他们的数字知识。这是数字化相关知识的先前影响:实施新技术后,经验丰富的员工的工作满意度增加,但经验不足的员工则不然。

结论

我们的研究表明,员工的工作量会影响使用数字应用程序的意图。工作量越大,人们就越愿意使用 TEP。关于主动知识共享,我们发现,与工作满意度高的员工相比,工作满意度低的员工更有可能分享他们的数字知识。这可能归因于邓宁-克鲁格效应。高知识员工最初对变化感到不确定,这转化为暂时较低的工作满意度。他们感到有必要填补哪怕是很小的知识空白,这反过来又会导致更高的工作满意度。相关负责人需要认识到数字变革会影响员工的工作流程和工作满意度。在这种时候,员工需要时间和支持来收集信息和知识,以应对数字化工作任务。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/388d/9873191/378997c7ad54/pone.0280956.g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/388d/9873191/e82f9d6b3b9c/pone.0280956.g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/388d/9873191/5f8c8944e7e1/pone.0280956.g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/388d/9873191/409a9baa118c/pone.0280956.g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/388d/9873191/378997c7ad54/pone.0280956.g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/388d/9873191/e82f9d6b3b9c/pone.0280956.g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/388d/9873191/5f8c8944e7e1/pone.0280956.g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/388d/9873191/409a9baa118c/pone.0280956.g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/388d/9873191/378997c7ad54/pone.0280956.g004.jpg

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