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一种使用综合健康模型的关键工作者自我监测健康筛查方法,名为“我的个人健康”。

A self-monitoring wellbeing screening methodology for keyworkers, 'My Personal Wellbeing', using an integrative wellbeing model.

机构信息

Department of Computer and Information Sciences, University of Northumbria, Ellison Building, Newcastle Upon Tyne, NE1 8ST, UK.

Department of Computer and Information Sciences, University of Northumbria, Newcastle Upon Tyne, UK.

出版信息

BMC Health Serv Res. 2023 Mar 14;23(1):250. doi: 10.1186/s12913-023-09213-0.

Abstract

BACKGROUND

The detrimental impact of Covid-19 has led to an urgent need to support the wellbeing of UK National Health Service and care workers. This research develops an online diary to support the wellbeing of staff in public healthcare in real-time, allowing the exploration of population wellbeing and pro-active responses to issues identified.

METHODS

The diary was co-produced by NHS and care stakeholders and university researchers. It was based on an integrative model monitoring mental health symptoms as well as wellbeing indicators. Diary users were encouraged to reflect on their experience confidentially, empowering them to monitor their wellbeing. The data collected was analysed using Mann-Whitney-Wilcoxon and Kruskal-Wallis statistical tests to determine any significant wellbeing trends and issues.

RESULTS

A statistically significant decline in wellbeing (P < 2.2E-16), and a significant increase in symptoms (P = 1.2E-14) was observed. For example, indicators of post-traumatic stress, including, flashbacks, dissociation, and bodily symptoms (Kruskal-Wallis P = 0.00081, 0.0083, and 0.027, respectively) became significantly worse and users reported issues with sleeping (51%), levels of alertness (46%), and burnout (41%).

CONCLUSIONS

The wellbeing diary indicated the value of providing ways to distinguish trends and wellbeing problems, thus, informing how staff wellbeing services can determine and respond to need with timely interventions. The results particularly emphasised the pressing need for interventions that help staff with burnout, self-compassion, and intrusive memories.

摘要

背景

Covid-19 的不利影响导致人们迫切需要支持英国国民保健制度和护理人员的福祉。这项研究开发了一个在线日记,以实时支持公共医疗保健人员的福祉,允许探索人口福祉,并对发现的问题做出积极响应。

方法

该日记由 NHS 和护理利益相关者以及大学研究人员共同制作。它基于一个综合模型,监测心理健康症状以及幸福感指标。鼓励日记使用者机密地反思自己的经历,使他们能够监测自己的幸福感。使用 Mann-Whitney-Wilcoxon 和 Kruskal-Wallis 统计检验分析收集的数据,以确定任何显著的幸福感趋势和问题。

结果

观察到幸福感显著下降(P < 2.2E-16),症状显著增加(P = 1.2E-14)。例如,创伤后应激的指标,包括闪回、分离和身体症状(Kruskal-Wallis P = 0.00081、0.0083 和 0.027,分别)明显恶化,用户报告睡眠问题(51%)、警觉水平问题(46%)和倦怠问题(41%)。

结论

幸福感日记表明提供区分趋势和幸福感问题的方法的价值,从而告知员工福祉服务如何确定和及时干预需求。结果特别强调了干预措施的迫切需要,这些措施有助于员工应对倦怠、自我同情和侵入性记忆。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1106/10012443/d75989d1410d/12913_2023_9213_Figa_HTML.jpg

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