• 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

与肥胖相关行为改变的动机和身体活动相关的推文:描述性分析。

Tweets Related to Motivation and Physical Activity for Obesity-Related Behavior Change: Descriptive Analysis.

机构信息

Department of Software and Information Systems, College of Computing and Informatics, University of North Carolina-Charlotte, Charlotte, NC, United States.

出版信息

J Med Internet Res. 2022 Jul 20;24(7):e15055. doi: 10.2196/15055.

DOI:10.2196/15055
PMID:35857347
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC9350819/
Abstract

BACKGROUND

Obesity is one of the greatest modern public health problems, due to the associated health and economic consequences. Decreased physical activity is one of the main societal changes driving the current obesity pandemic.

OBJECTIVE

Our goals are to fill a gap in the literature and study whether users organically utilize a social media platform, Twitter, for providing motivation. We examine the topics of messages and social network structures on Twitter. We discuss social media's potential for providing peer support and then draw insights to inform the development of interventions for long-term health-related behavior change.

METHODS

We examined motivational messages related to physical activity on Twitter. First, we collected tweets related to physical activity. Second, we analyzed them using (1) a lexicon-based approach to extract and characterize motivation-related tweets, (2) a thematic analysis to examine common themes in retweets, and (3) topic models to understand prevalent factors concerning motivation and physical activity on Twitter. Third, we created 2 social networks to investigate organically arising peer-support network structures for sustaining physical activity and to form a deeper understanding of the feasibility of these networks in a real-world context.

RESULTS

We collected over 1.5 million physical activity-related tweets posted from August 30 to November 6, 2018. A relatively small percentage of the tweets mentioned the term motivation; many of these were made on Mondays or during morning or late morning hours. The analysis of retweets showed that the following three themes were commonly conveyed on the platform: (1) using a number of different types of motivation (self, process, consolation, mental, or quotes), (2) promoting individuals or groups, and (3) sharing or requesting information. Topic models revealed that many of these users were weightlifters or people trying to lose weight. Twitter users also naturally forged relations, even though 98.12% (2824/2878) of these users were in different physical locations.

CONCLUSIONS

This study fills a knowledge gap on how individuals organically use social media to encourage and sustain physical activity. Elements related to peer support are found in the organic use of social media. Our findings suggest that geographical location is less important for providing peer support as long as the support provides motivation, despite users having few factors in common (eg, the weather) affecting their physical activity. This presents a unique opportunity to identify successful motivation-providing peer support groups in a large user base. However, further research on the effects in a real-world context, as well as additional design and usability features for improving user engagement, are warranted to develop a successful intervention counteracting the current obesity pandemic. This is especially important for young adults, the main user group for social media, as they develop lasting health-related behaviors.

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c179/9350819/a189527e1624/jmir_v24i7e15055_fig2.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c179/9350819/8731afd76956/jmir_v24i7e15055_fig1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c179/9350819/a189527e1624/jmir_v24i7e15055_fig2.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c179/9350819/8731afd76956/jmir_v24i7e15055_fig1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c179/9350819/a189527e1624/jmir_v24i7e15055_fig2.jpg
摘要

背景

肥胖是现代最大的公共卫生问题之一,因为它会带来健康和经济方面的后果。体力活动减少是导致当前肥胖流行的主要社会变化之一。

目的

我们的目标是填补文献中的空白,并研究用户是否会自然地利用社交媒体平台 Twitter 来提供动力。我们检查了 Twitter 上的信息主题和社交网络结构。我们讨论了社交媒体提供同伴支持的潜力,然后从中汲取了一些见解,为长期与健康相关的行为改变干预措施的开发提供信息。

方法

我们检查了 Twitter 上与体力活动相关的激励信息。首先,我们收集了与体力活动相关的推文。其次,我们使用了以下方法对这些推文进行了分析:(1)基于词汇的方法,用于提取和描述与激励相关的推文;(2)主题分析,用于检查转发中的常见主题;(3)主题模型,用于了解与 Twitter 上的激励和体力活动相关的普遍因素。第三,我们创建了 2 个社交网络,以调查自然产生的维持体力活动的同伴支持网络结构,并深入了解这些网络在真实环境中的可行性。

结果

我们收集了 2018 年 8 月 30 日至 11 月 6 日期间与 150 多万条体力活动相关的推文。提到“动机”一词的推文比例相对较小;其中许多推文是在周一或早上或上午晚些时候发布的。对转发的分析表明,该平台上通常传达了以下三个主题:(1)使用多种不同类型的激励(自我激励、过程激励、安慰激励、心理激励或引语);(2)推广个人或团体;(3)分享或请求信息。主题模型显示,这些用户中有很多人是举重运动员或试图减肥的人。Twitter 用户还自然地建立了关系,尽管 98.12%(2824/2878)的用户位于不同的地理位置。

结论

本研究填补了关于个人如何利用社交媒体来鼓励和维持体力活动的知识空白。在社交媒体的自然使用中发现了与同伴支持相关的元素。我们的研究结果表明,只要支持提供动力,地理位置对于提供同伴支持就不那么重要,尽管用户之间几乎没有共同的因素(例如天气)影响他们的体力活动。这为在大型用户群中识别成功的提供激励的同伴支持群体提供了一个独特的机会。然而,为了开发一种成功的干预措施来对抗当前的肥胖流行,还需要对现实世界环境中的效果以及提高用户参与度的其他设计和可用性功能进行进一步的研究。对于社交媒体的主要用户群体——年轻人来说,这一点尤为重要,因为他们正在养成持久的与健康相关的行为。

相似文献

1
Tweets Related to Motivation and Physical Activity for Obesity-Related Behavior Change: Descriptive Analysis.与肥胖相关行为改变的动机和身体活动相关的推文:描述性分析。
J Med Internet Res. 2022 Jul 20;24(7):e15055. doi: 10.2196/15055.
2
Exploring Discussions About Virtual Reality on Twitter to Inform Brain Injury Rehabilitation: Content and Network Analysis.探索 Twitter 上关于虚拟现实的讨论以了解脑损伤康复:内容和网络分析。
J Med Internet Res. 2024 Jan 19;26:e45168. doi: 10.2196/45168.
3
Examining Tweet Content and Engagement of Canadian Public Health Agencies and Decision Makers During COVID-19: Mixed Methods Analysis.研究 COVID-19 期间加拿大公共卫生机构和决策者的推文内容和参与度:混合方法分析。
J Med Internet Res. 2021 Mar 11;23(3):e24883. doi: 10.2196/24883.
4
Seeking and Providing Social Support on Twitter for Trauma and Distress During the COVID-19 Pandemic: Content and Sentiment Analysis.在 COVID-19 大流行期间,通过 Twitter 寻求和提供创伤与痛苦的社会支持:内容和情感分析。
J Med Internet Res. 2023 Aug 31;25:e46343. doi: 10.2196/46343.
5
Social Media and Research Publication Activity During Early Stages of the COVID-19 Pandemic: Longitudinal Trend Analysis.社交媒体与 COVID-19 大流行早期阶段的研究出版活动:纵向趋势分析。
J Med Internet Res. 2021 Jun 17;23(6):e26956. doi: 10.2196/26956.
6
Exploring the Behavior of Users With Attention-Deficit/Hyperactivity Disorder on Twitter: Comparative Analysis of Tweet Content and User Interactions.探索 Twitter 上注意力缺陷多动障碍用户的行为:推文内容和用户互动的比较分析。
J Med Internet Res. 2023 May 17;25:e43439. doi: 10.2196/43439.
7
Top Concerns of Tweeters During the COVID-19 Pandemic: Infoveillance Study.新冠疫情期间推特用户的主要担忧:信息监测研究
J Med Internet Res. 2020 Apr 21;22(4):e19016. doi: 10.2196/19016.
8
The Mutual Influence of the World Health Organization (WHO) and Twitter Users During COVID-19: Network Agenda-Setting Analysis.世界卫生组织(WHO)与推特用户在 COVID-19 期间的相互影响:网络议程设置分析。
J Med Internet Res. 2022 Apr 26;24(4):e34321. doi: 10.2196/34321.
9
The Spread of COVID-19 Crisis Communication by German Public Authorities and Experts on Twitter: Quantitative Content Analysis.德国公共当局和专家在 Twitter 上传播 COVID-19 危机信息:定量内容分析。
JMIR Public Health Surveill. 2021 Dec 22;7(12):e31834. doi: 10.2196/31834.
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
Prevalence and Predictors of Posting Health-Related Content Among US Facebook Users: A Cross-Sectional Survey Study.美国脸书用户发布健康相关内容的患病率及预测因素:一项横断面调查研究。
Int J Environ Res Public Health. 2025 Jun 10;22(6):918. doi: 10.3390/ijerph22060918.
2
Whose tweets about obesity and weight loss gain the most attention: celebrities, political, or medical authorities?关于肥胖和减肥的推文,哪些人最受关注:名人、政治人物还是医学权威?
Int J Obes (Lond). 2025 Apr;49(4):673-681. doi: 10.1038/s41366-024-01689-y. Epub 2024 Nov 26.
3
Investigating Older Adults' Use of a Socially Assistive Robot via Time Series Clustering and User Profiling: Descriptive Analysis Study.

本文引用的文献

1
Understanding user responses to the COVID-19 pandemic on Twitter from a terror management theory perspective: Cultural differences among the US, UK and India.从恐惧管理理论视角理解推特用户对新冠疫情的反应:美国、英国和印度之间的文化差异
Comput Human Behav. 2022 Mar;128:107087. doi: 10.1016/j.chb.2021.107087. Epub 2021 Nov 1.
2
Web-Based Digital Health Interventions for Weight Loss and Lifestyle Habit Changes in Overweight and Obese Adults: Systematic Review and Meta-Analysis.基于网络的数字健康干预对超重和肥胖成年人减肥及生活方式习惯改变的影响:系统评价与荟萃分析
J Med Internet Res. 2019 Jan 8;21(1):e298. doi: 10.2196/jmir.9609.
3
基于时间序列聚类和用户画像的老年人对社交机器人使用情况的调查:描述性分析研究。
JMIR Form Res. 2024 Sep 19;8:e41093. doi: 10.2196/41093.
4
Pediatric Cancer Communication on Twitter: Natural Language Processing and Qualitative Content Analysis.推特上的儿科癌症交流:自然语言处理与定性内容分析
JMIR Cancer. 2024 May 7;10:e52061. doi: 10.2196/52061.
5
A Novel Approach to Characterize State-level Food Environment and Predict Obesity Rate Using Social Media Data: Correlational Study.一种利用社交媒体数据描述州级食品环境并预测肥胖率的新方法:相关性研究。
J Med Internet Res. 2022 Dec 13;24(12):e39340. doi: 10.2196/39340.
Creating Engaging Health Promotion Campaigns on Social Media: Observations and Lessons From Fitbit and Garmin.
在社交媒体上开展引人入胜的健康促进活动:来自Fitbit和佳明的观察与经验教训。
J Med Internet Res. 2018 Dec 10;20(12):e10911. doi: 10.2196/10911.
4
Temporal and spatiotemporal investigation of tourist attraction visit sentiment on Twitter.基于 Twitter 的旅游景点访问情绪的时间和时空调查。
PLoS One. 2018 Jun 14;13(6):e0198857. doi: 10.1371/journal.pone.0198857. eCollection 2018.
5
Tracking Health Related Discussions on Reddit for Public Health Applications.在Reddit上追踪与健康相关的讨论以用于公共卫生应用。
AMIA Annu Symp Proc. 2018 Apr 16;2017:1362-1371. eCollection 2017.
6
Harnessing Reddit to Understand the Written-Communication Challenges Experienced by Individuals With Mental Health Disorders: Analysis of Texts From Mental Health Communities.利用Reddit了解精神健康障碍患者所面临的书面沟通挑战:对心理健康社区文本的分析
J Med Internet Res. 2018 Apr 10;20(4):e121. doi: 10.2196/jmir.8219.
7
Examining Thematic Similarity, Difference, and Membership in Three Online Mental Health Communities from Reddit: A Text Mining and Visualization Approach.审视来自Reddit的三个在线心理健康社区的主题相似性、差异性及成员关系:一种文本挖掘与可视化方法。
Comput Human Behav. 2018 Jan;78:98-112. doi: 10.1016/j.chb.2017.09.001. Epub 2017 Sep 6.
8
Time2bHealthy - An online childhood obesity prevention program for preschool-aged children: A randomised controlled trial protocol.Time2bHealthy——一项针对学龄前儿童的在线儿童肥胖预防计划:一项随机对照试验方案。
Contemp Clin Trials. 2017 Oct;61:73-80. doi: 10.1016/j.cct.2017.07.022. Epub 2017 Jul 22.
9
Using social media to deliver weight loss programming to young adults: Design and rationale for the Healthy Body Healthy U (HBHU) trial.利用社交媒体为年轻人提供减肥计划:健康身体 健康的你(HBHU)试验的设计与原理
Contemp Clin Trials. 2017 Sep;60:1-13. doi: 10.1016/j.cct.2017.06.007. Epub 2017 Jun 10.
10
Economic Burden of Obesity: A Systematic Literature Review.肥胖的经济负担:一项系统的文献综述
Int J Environ Res Public Health. 2017 Apr 19;14(4):435. doi: 10.3390/ijerph14040435.