• 文献检索
  • 文档翻译
  • 深度研究
  • 学术资讯
  • Suppr Zotero 插件Zotero 插件
  • 邀请有礼
  • 套餐&价格
  • 历史记录
应用&插件
Suppr Zotero 插件Zotero 插件浏览器插件Mac 客户端Windows 客户端微信小程序
定价
高级版会员购买积分包购买API积分包
服务
文献检索文档翻译深度研究API 文档MCP 服务
关于我们
关于 Suppr公司介绍联系我们用户协议隐私条款
关注我们

Suppr 超能文献

核心技术专利:CN118964589B侵权必究
粤ICP备2023148730 号-1Suppr @ 2026

文献检索

告别复杂PubMed语法,用中文像聊天一样搜索,搜遍4000万医学文献。AI智能推荐,让科研检索更轻松。

立即免费搜索

文件翻译

保留排版,准确专业,支持PDF/Word/PPT等文件格式,支持 12+语言互译。

免费翻译文档

深度研究

AI帮你快速写综述,25分钟生成高质量综述,智能提取关键信息,辅助科研写作。

立即免费体验

了解新冠疫情期间及之后的全人健康与恢复力:一项横断面描述性相关性研究。

Understanding Whole-Person Health and Resilience During the COVID-19 Pandemic and Beyond: A Cross-sectional and Descriptive Correlation Study.

作者信息

Rajamani Sripriya, Austin Robin, Geiger-Simpson Elena, Jantraporn Ratchada, Park Suhyun, Monsen Karen A

机构信息

University of Minnesota, Minneapolis, MN, United States.

出版信息

JMIR Nurs. 2022 May 16;5(1):e38063. doi: 10.2196/38063.

DOI:10.2196/38063
PMID:35576563
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC9152721/
Abstract

BACKGROUND

The COVID-19 pandemic has prompted an interest in whole-person health and emotional well-being. Informatics solutions through user-friendly tools such as mobile health apps offer immense value. Prior research developed a consumer-facing app MyStrengths + MyHealth using Simplified Omaha System Terms (SOST) to assess whole-person health. The MyStrengths + MyHealth app assesses strengths, challenges, and needs (SCN) for 42 concepts across four domains (My Living, My Mind and Networks, My Body, My Self-care; eg, Income, Emotions, Pain, and Nutrition, respectively). Given that emotional well-being was a predominant concern during the COVID-19 pandemic, we sought to understand whole-person health for participants with/without Emotions challenges.

OBJECTIVE

This study aims to use visualization techniques and data from attendees at a Midwest state fair to examine SCN overall and by groups with/without Emotions challenges, and to explore the resilience of participants.

METHODS

This cross-sectional and descriptive correlational study surveyed adult attendees at a 2021 Midwest state fair. Data were visualized using Excel and analyzed using descriptive and inferential statistics using SPSS.

RESULTS

The study participants (N=182) were primarily female (n=123, 67.6%), aged ≥45 years (n=112, 61.5%), White (n=154, 84.6%), and non-Hispanic (n=177, 97.3%). Compared to those without Emotions challenges, those with Emotions challenges were aged 18-44 (P<.001) years, more often female (P=.02), and not married (P=.01). Overall, participants had more strengths (mean 28.6, SD 10.5) than challenges (mean 12, SD 7.5) and needs (mean 4.2, SD 7.5). The most frequent needs were in Emotions, Nutrition, Income, Sleeping, and Exercising. Compared to those without Emotions challenges, those with Emotions challenges had fewer strengths (P<.001), more challenges (P<.001), and more needs (P<.001), along with fewer strengths for Emotions (P<.001) and for the cluster of health-related behaviors domain concepts, Sleeping (P=.002), Nutrition (P<.001), and Exercising (P<.001). Resilience was operationalized as correlations among strengths for SOST concepts and visualized for participants with/without an Emotions challenge. Those without Emotions challenges had more positive strengths correlations across multiple concepts/domains.

CONCLUSIONS

This survey study explored a large community-generated data set to understand whole-person health and showed between-group differences in SCN and resilience for participants with/without Emotions challenges. It contributes to the literature regarding an app-aided and data-driven approach to whole-person health and resilience. This research demonstrates the power of health informatics and provides researchers with a data-driven methodology for additional studies to build evidence on whole-person health and resilience.

摘要

背景

新冠疫情引发了人们对全人健康和情绪幸福感的关注。通过移动健康应用等用户友好型工具提供的信息学解决方案具有巨大价值。先前的研究开发了一款面向消费者的应用程序“MyStrengths + MyHealth”,使用简化奥马哈系统术语(SOST)来评估全人健康。“MyStrengths + MyHealth”应用程序评估了四个领域(我的生活、我的思想与社交网络、我的身体、我的自我护理;例如,分别为收入、情绪、疼痛和营养)中42个概念的优势、挑战和需求(SCN)。鉴于在新冠疫情期间情绪幸福感是一个主要关注点,我们试图了解有/无情绪挑战的参与者的全人健康状况。

目的

本研究旨在使用可视化技术和来自中西部州博览会参与者的数据,总体上以及按有/无情绪挑战的群体来检查SCN,并探索参与者的恢复力。

方法

这项横断面描述性相关研究对2021年中西部州博览会的成年参与者进行了调查。数据使用Excel进行可视化处理,并使用SPSS进行描述性和推断性统计分析。

结果

研究参与者(N = 182)主要为女性(n = 123,67.6%),年龄≥45岁(n = 112,61.5%),白人(n = 154,84.6%),非西班牙裔(n = 177,97.3%)。与无情绪挑战的人相比,有情绪挑战的人年龄在18 - 44岁(P <.001),女性比例更高(P =.02),且未婚(P =.01)。总体而言,参与者的优势(平均28.6,标准差10.5)多于挑战(平均12,标准差7.5)和需求(平均4.2,标准差7.5)。最常见的需求集中在情绪、营养、收入、睡眠和锻炼方面。与无情绪挑战的人相比,有情绪挑战的人优势更少(P <.001),挑战更多(P <.001),需求更多(P <.001),情绪方面的优势更少(P <.001),与健康相关行为领域概念集群(睡眠(P =.002)、营养(P <.001)和锻炼(P <.001))的优势也更少。恢复力通过SOST概念的优势之间的相关性来衡量,并针对有/无情绪挑战的参与者进行可视化展示。无情绪挑战的人在多个概念/领域的优势相关性更积极。

结论

这项调查研究探索了一个由社区生成的大型数据集以了解全人健康,并显示了有/无情绪挑战的参与者在SCN和恢复力方面的组间差异。它为有关全人健康和恢复力的应用辅助及数据驱动方法的文献做出了贡献。这项研究展示了健康信息学的力量,并为研究人员提供了一种数据驱动的方法,用于进一步的研究,以建立关于全人健康和恢复力的证据。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/dd6b/9152721/cbe63f0daea7/nursing_v5i1e38063_fig9.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/dd6b/9152721/ef97e763527a/nursing_v5i1e38063_fig1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/dd6b/9152721/d529d142ee87/nursing_v5i1e38063_fig2.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/dd6b/9152721/fe5da0d07ebc/nursing_v5i1e38063_fig3.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/dd6b/9152721/9667b7f63f3e/nursing_v5i1e38063_fig4.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/dd6b/9152721/f77b9d0ee531/nursing_v5i1e38063_fig5.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/dd6b/9152721/fa72d9c1819d/nursing_v5i1e38063_fig6.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/dd6b/9152721/3e049d5a6e7b/nursing_v5i1e38063_fig7.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/dd6b/9152721/077678b1298f/nursing_v5i1e38063_fig8.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/dd6b/9152721/cbe63f0daea7/nursing_v5i1e38063_fig9.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/dd6b/9152721/ef97e763527a/nursing_v5i1e38063_fig1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/dd6b/9152721/d529d142ee87/nursing_v5i1e38063_fig2.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/dd6b/9152721/fe5da0d07ebc/nursing_v5i1e38063_fig3.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/dd6b/9152721/9667b7f63f3e/nursing_v5i1e38063_fig4.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/dd6b/9152721/f77b9d0ee531/nursing_v5i1e38063_fig5.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/dd6b/9152721/fa72d9c1819d/nursing_v5i1e38063_fig6.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/dd6b/9152721/3e049d5a6e7b/nursing_v5i1e38063_fig7.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/dd6b/9152721/077678b1298f/nursing_v5i1e38063_fig8.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/dd6b/9152721/cbe63f0daea7/nursing_v5i1e38063_fig9.jpg

相似文献

1
Understanding Whole-Person Health and Resilience During the COVID-19 Pandemic and Beyond: A Cross-sectional and Descriptive Correlation Study.了解新冠疫情期间及之后的全人健康与恢复力:一项横断面描述性相关性研究。
JMIR Nurs. 2022 May 16;5(1):e38063. doi: 10.2196/38063.
2
Exploring Large Community- and Clinically-Generated Datasets to Understand Resilience Before and During the COVID-19 Pandemic.探索大型社区和临床生成的数据集,以了解 COVID-19 大流行前后的韧性。
J Nurs Scholarsh. 2021 May;53(3):262-269. doi: 10.1111/jnu.12634. Epub 2021 Apr 3.
3
Thriving Through Pain: A Whole-Person and Resilience Comparative Study Using Mobile Health Application Technology for Individuals With Self-Reported Pain Challenges.在疼痛中茁壮成长:一项针对自我报告有疼痛挑战的个体,使用移动健康应用技术进行的全人及复原力比较研究。
Pain Manag Nurs. 2025 Feb;26(1):55-64. doi: 10.1016/j.pmn.2024.09.004. Epub 2024 Oct 18.
4
Using data visualization to characterize whole-person health of public health nurses.利用数据可视化描述公共卫生护士的全人健康状况。
Public Health Nurs. 2023 Sep-Oct;40(5):612-620. doi: 10.1111/phn.13224. Epub 2023 Jul 9.
5
Examining standardized consumer-generated social determinants of health and resilience data supported by Omaha System terminology.检查标准化的消费者生成的健康和适应力社会决定因素数据,这些数据得到了奥马哈系统术语的支持。
J Am Med Inform Assoc. 2023 Oct 19;30(11):1852-1857. doi: 10.1093/jamia/ocad143.
6
Understanding Women's Cardiovascular Health Using MyStrengths+MyHealth: A Patient-Generated Data Visualization Study of Strengths, Challenges, and Needs Differences.利用 MyStrengths+MyHealth 理解女性心血管健康:一项基于患者生成数据的优势、挑战和需求差异的可视化研究。
J Nurs Scholarsh. 2021 Sep;53(5):634-642. doi: 10.1111/jnu.12674. Epub 2021 May 16.
7
Machine learning methods to discover hidden patterns in well-being and resilience for healthy aging.用于发现健康老龄化中幸福感和恢复力隐藏模式的机器学习方法。
J Nurs Scholarsh. 2025 Jan;57(1):72-81. doi: 10.1111/jnu.13025. Epub 2024 Sep 9.
8
Incorporating a Whole-Person Perspective in Consumer-Generated Data: Social Determinants, Resilience, and Hidden Patterns.在消费者生成的数据中纳入全人视角:社会决定因素、韧性和隐藏模式。
Comput Inform Nurs. 2021 Apr 8;39(8):402-410. doi: 10.1097/CIN.0000000000000730.
9
An International Research Collaborative to Examine Global Health Resilience Using the MyStrengths+MyHealth Application.利用 MyStrengths+MyHealth 应用程序开展全球健康韧性国际研究协作。
Stud Health Technol Inform. 2022 Jun 6;290:1128-1129. doi: 10.3233/SHTI220301.
10
Folic acid supplementation and malaria susceptibility and severity among people taking antifolate antimalarial drugs in endemic areas.在流行地区,服用抗叶酸抗疟药物的人群中,叶酸补充剂与疟疾易感性和严重程度的关系。
Cochrane Database Syst Rev. 2022 Feb 1;2(2022):CD014217. doi: 10.1002/14651858.CD014217.

引用本文的文献

1
Machine learning methods to discover hidden patterns in well-being and resilience for healthy aging.用于发现健康老龄化中幸福感和恢复力隐藏模式的机器学习方法。
J Nurs Scholarsh. 2025 Jan;57(1):72-81. doi: 10.1111/jnu.13025. Epub 2024 Sep 9.
2
Exploring behavioral intention to use telemedicine services post COVID-19: a cross sectional study in Saudi Arabia.探究新冠肺炎疫情后使用远程医疗服务的行为意愿:沙特阿拉伯的一项横断面研究。
Front Public Health. 2024 Apr 16;12:1385713. doi: 10.3389/fpubh.2024.1385713. eCollection 2024.
3
Advantages and disadvantages of using theory-based versus data-driven models with social and behavioral determinants of health data.

本文引用的文献

1
An International Research Collaborative to Examine Global Health Resilience Using the MyStrengths+MyHealth Application.利用 MyStrengths+MyHealth 应用程序开展全球健康韧性国际研究协作。
Stud Health Technol Inform. 2022 Jun 6;290:1128-1129. doi: 10.3233/SHTI220301.
2
Toward Clinical Adoption of Standardized mHealth Solutions: The Feasibility of Using MyStrengths+MyHealth Consumer-Generated Health Data for Knowledge Discovery.迈向标准化移动健康解决方案的临床应用:利用MyStrengths+MyHealth消费者生成的健康数据进行知识发现的可行性。
Comput Inform Nurs. 2022 Feb 1;40(2):71-79. doi: 10.1097/CIN.0000000000000862.
3
使用基于理论和数据驱动的模型来分析健康相关社会行为决定因素的优缺点。
J Am Med Inform Assoc. 2023 Oct 19;30(11):1818-1825. doi: 10.1093/jamia/ocad148.
4
Examining standardized consumer-generated social determinants of health and resilience data supported by Omaha System terminology.检查标准化的消费者生成的健康和适应力社会决定因素数据,这些数据得到了奥马哈系统术语的支持。
J Am Med Inform Assoc. 2023 Oct 19;30(11):1852-1857. doi: 10.1093/jamia/ocad143.
Mapping a Strength-Oriented Approach to a Standardized Terminology: A Case Study.
将以优势为导向的方法映射到标准化术语:一个案例研究。
Stud Health Technol Inform. 2021 Dec 15;284:379-383. doi: 10.3233/SHTI210751.
4
Mental health in relation to changes in sleep, exercise, alcohol and diet during the COVID-19 pandemic: examination of four UK cohort studies.新冠大流行期间睡眠、锻炼、饮酒和饮食变化与心理健康的关系:四项英国队列研究的考察。
Psychol Med. 2023 May;53(7):2748-2757. doi: 10.1017/S0033291721004657. Epub 2021 Dec 16.
5
Digital health needs for implementing high-quality primary care: recommendations from the National Academies of Sciences, Engineering, and Medicine.数字健康在实施高质量初级保健中的需求:美国国家科学院、工程院和医学院的建议。
J Am Med Inform Assoc. 2021 Nov 25;28(12):2738-2742. doi: 10.1093/jamia/ocab190.
6
Sleep, Physical Activity, and Diet of Adults during the Second Lockdown of the COVID-19 Pandemic in Greece.希腊新冠疫情第二次封锁期间成年人的睡眠、身体活动及饮食情况
Int J Environ Res Public Health. 2021 Jul 8;18(14):7292. doi: 10.3390/ijerph18147292.
7
Effect of Inadequate Sleep on Frequent Mental Distress.睡眠不足对频繁精神困扰的影响。
Prev Chronic Dis. 2021 Jun 17;18:E61. doi: 10.5888/pcd18.200573.
8
Understanding Women's Cardiovascular Health Using MyStrengths+MyHealth: A Patient-Generated Data Visualization Study of Strengths, Challenges, and Needs Differences.利用 MyStrengths+MyHealth 理解女性心血管健康:一项基于患者生成数据的优势、挑战和需求差异的可视化研究。
J Nurs Scholarsh. 2021 Sep;53(5):634-642. doi: 10.1111/jnu.12674. Epub 2021 May 16.
9
Health and Disease Are Dynamic Complex-Adaptive States Implications for Practice and Research.健康与疾病是动态复杂适应状态:对实践和研究的启示
Front Psychiatry. 2021 Mar 29;12:595124. doi: 10.3389/fpsyt.2021.595124. eCollection 2021.
10
Incorporating a Whole-Person Perspective in Consumer-Generated Data: Social Determinants, Resilience, and Hidden Patterns.在消费者生成的数据中纳入全人视角:社会决定因素、韧性和隐藏模式。
Comput Inform Nurs. 2021 Apr 8;39(8):402-410. doi: 10.1097/CIN.0000000000000730.