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探索个体对一款营养筛查移动应用程序的看法和反馈:定性焦点小组研究。

Exploring Individuals' Views and Feedback on a Nutritional Screening Mobile App: Qualitative Focus Group Study.

作者信息

Jones Debra, Sowerbutts Anne Marie, Burden Sorrel

机构信息

School of Health Sciences, University of Manchester, Manchester, United Kingdom.

出版信息

JMIR Form Res. 2024 Dec 18;8:e63680. doi: 10.2196/63680.

Abstract

BACKGROUND

Malnutrition is a major global health challenge. Worldwide, approximately 390 million adults are underweight, while 2.5 billion are overweight. The Malnutrition Universal Screening Tool (MUST) has been implemented successfully in the United Kingdom to assess the nutritional status of patients in health care settings. Currently, MUST is available as a web-based tool or as a paper-based version, However, the paper tool can lead to calculation errors, and web-based tools require internet access, limiting use in some communities. The MUST app uses clear and simple navigation and processes information precisely, so could potentially improve the accuracy and accessibility of malnutrition screening for health care professionals (HCP) in all settings.

OBJECTIVE

This study aimed to explore the views of HCPs on the content, functionality, and usability of a newly developed mobile app for MUST.

METHODS

We performed a qualitative study using deductive and inductive framework analysis. A series of online focus groups (~1 hour each) were conducted, exploring potential users' views on the app's content design, functionality, and usefulness, which was set in demonstration mode and not available for direct use with patients. Each focus group used a semistructured approach and predefined topic guide. Participants were recruited consecutively and United Kingdom-wide using advertisements through emails, newsletters, and on social media across appropriate local and national networks. Participants had the opportunity to look at the app on their phones before giving feedback and an on-screen demonstration of the app was provided during the focus group. Data were analyzed using deductive and inductive framework analysis.

RESULTS

In total, 8 online focus groups were conducted between August 2022 and January 2023. Participants (n=32) were dietetic and nutrition HCPs or educators with experience in using MUST in clinical or community settings. Data analysis revealed three broad themes: (1) improving the app for better use in practice, (2) user experience of design, and (3) barriers and facilitators in different settings. Overall feedback for the app was positive with potential users considering it to be very useful for improving routine and accurate screening, particularly in the community, and mainly because of the automatic calculation feature, which may help with improving discrepancies. Participants generally considered the app to be for professional use only, stating that patients may find it too clinical or technical. Participants also made suggestions for app sustainability and improvements, such as incentives to complete the demographics section or the option to skip questions, and the addition of more subjective measures and instructions on measuring ulna length.

CONCLUSIONS

The MUST app was positively evaluated by potential users, who reported it was user-friendly and an accessible way to screen for malnutrition risk, whilst improving the accuracy of screening and availability in community settings.

摘要

背景

营养不良是一项重大的全球健康挑战。在全球范围内,约有3.9亿成年人体重过轻,而超重人数达25亿。营养不良通用筛查工具(MUST)已在英国成功实施,用于评估医疗环境中患者的营养状况。目前,MUST有基于网络的工具版本和纸质版本。然而,纸质工具可能会导致计算错误,而基于网络的工具需要联网,这限制了其在一些社区的使用。MUST应用程序导航清晰简单,信息处理精确,因此有可能提高所有环境下医疗保健专业人员(HCP)进行营养不良筛查的准确性和可及性。

目的

本研究旨在探讨医疗保健专业人员对新开发的MUST移动应用程序的内容、功能和可用性的看法。

方法

我们采用演绎和归纳框架分析法进行了一项定性研究。开展了一系列在线焦点小组讨论(每组约1小时),探讨潜在用户对该应用程序内容设计、功能和实用性的看法,该应用程序设置为演示模式,不能直接用于患者。每个焦点小组采用半结构化方法和预定义的主题指南。通过电子邮件、时事通讯以及在适当的地方和国家网络的社交媒体上发布广告,在全英国范围内连续招募参与者。参与者在给出反馈之前有机会在手机上查看该应用程序,并且在焦点小组讨论期间提供了该应用程序的屏幕演示。使用演绎和归纳框架分析法对数据进行分析。

结果

2022年8月至2023年1月期间共开展了8次在线焦点小组讨论。参与者(n = 32)为饮食和营养方面的医疗保健专业人员或教育工作者,他们在临床或社区环境中使用过MUST。数据分析揭示了三个广泛的主题:(1)改进应用程序以便在实践中更好地使用;(2)设计的用户体验;(3)不同环境中的障碍和促进因素。对该应用程序的总体反馈是积极的,潜在用户认为它对改进常规和准确筛查非常有用,特别是在社区中,主要是因为自动计算功能,这可能有助于减少差异。参与者普遍认为该应用程序仅供专业人员使用,称患者可能会觉得它过于临床化或技术化。参与者还对应用程序的可持续性和改进提出了建议,例如完成人口统计部分的激励措施或跳过问题的选项,以及增加更多主观测量方法和尺骨长度测量说明。

结论

潜在用户对MUST应用程序给予了积极评价,他们报告称该应用程序用户友好,是一种易于使用的营养不良风险筛查方式,同时提高了筛查的准确性以及在社区环境中的可及性。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/547d/11694050/1e342c763bb2/formative_v8i1e63680_fig1.jpg

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