Suppr超能文献

基于推特的成人戒烟支持网络中的参与度映射

Mapping Engagement in Twitter-Based Support Networks for Adult Smoking Cessation.

作者信息

Lakon Cynthia M, Pechmann Cornelia, Wang Cheng, Pan Li, Delucchi Kevin, Prochaska Judith J

机构信息

Cynthia M. Lakon is with the Department of Population Health and Disease Prevention, Program in Public Health, University of California, Irvine. Cornelia Pechmann is with The Paul Merage School of Business, University of California, Irvine. Cheng Wang is with the Department of Sociology, University of Notre Dame, Notre Dame, IN. Li Pan is with the Shanghai Jiao Tong University, Antai College of Economics and Management, Shanghai, China. Kevin Delucchi is with the Department of Psychiatry, University of California, San Francisco. Judith J. Prochaska is with the Stanford Prevention Research Center, Stanford University, Palo Alto, CA.

出版信息

Am J Public Health. 2016 Aug;106(8):1374-80. doi: 10.2105/AJPH.2016.303256. Epub 2016 Jun 16.

Abstract

We examined engagement in novel quit-smoking private social support networks on Twitter, January 2012 to April 2014. We mapped communication patterns within 8 networks of adult smokers (n = 160) with network ties defined by participants' tweets over 3 time intervals, and examined tie reciprocity, tie strength, in-degree centrality (popularity), 3-person triangles, 4-person cliques, network density, and abstinence status. On average, more than 50% of ties were reciprocated in most networks and most ties were between abstainers and nonabstainers. Tweets formed into more aggregated patterns especially early in the study. Across networks, 35.00% (7 days after the quit date), 49.38% (30 days), and 46.88% (60 days) abstained from smoking. We demonstrated that abstainers and nonabstainers engaged with one another in dyads and small groups. This study preliminarily suggests potential for Twitter as a platform for adult smoking-cessation interventions.

摘要

我们于2012年1月至2014年4月期间,研究了推特上新型戒烟私人社交支持网络中的参与情况。我们绘制了8个成年吸烟者网络(n = 160)内的交流模式,网络联系由参与者在3个时间间隔内发布的推文定义,并研究了联系的互惠性、联系强度、入度中心性(受欢迎程度)、三人三角关系、四人小团体、网络密度和戒烟状态。平均而言,大多数网络中超过50%的联系是互惠的,且大多数联系存在于戒烟者和非戒烟者之间。推文形成了更多聚合模式,尤其是在研究早期。在各个网络中,35.00%(戒烟日期后7天)、49.38%(30天)和46.88%(60天)的人成功戒烟。我们证明了戒烟者和非戒烟者在二元组和小团体中相互交流。这项研究初步表明推特作为成人戒烟干预平台的潜力。

相似文献

1
Mapping Engagement in Twitter-Based Support Networks for Adult Smoking Cessation.
Am J Public Health. 2016 Aug;106(8):1374-80. doi: 10.2105/AJPH.2016.303256. Epub 2016 Jun 16.
5
A prospective examination of online social network dynamics and smoking cessation.
PLoS One. 2017 Aug 23;12(8):e0183655. doi: 10.1371/journal.pone.0183655. eCollection 2017.
6
Vape, quit, tweet? Electronic cigarettes and smoking cessation on Twitter.
Int J Public Health. 2016 Mar;61(2):249-56. doi: 10.1007/s00038-016-0791-2. Epub 2016 Feb 3.
7
A Multirelational Social Network Analysis of an Online Health Community for Smoking Cessation.
J Med Internet Res. 2016 Aug 25;18(8):e233. doi: 10.2196/jmir.5985.
9
Social Network Behavior and Engagement Within a Smoking Cessation Facebook Page.
J Med Internet Res. 2016 Aug 2;18(8):e205. doi: 10.2196/jmir.5574.
10
Twitter=quitter? An analysis of Twitter quit smoking social networks.
Tob Control. 2012 Jul;21(4):447-9. doi: 10.1136/tc.2010.042507. Epub 2011 Jul 5.

引用本文的文献

1
Social network tie functions of social support and social influence and adult smoking abstinence.
PLoS One. 2024 Mar 7;19(3):e0296458. doi: 10.1371/journal.pone.0296458. eCollection 2024.
3
Perceived Costs versus Actual Benefits of Demographic Self-Disclosure in Online Support Groups.
J Consum Psychol. 2021 Jul;31(3):450-477. doi: 10.1002/jcpy.1200. Epub 2020 Oct 19.
4
Application of Automated Text Analysis to Examine Emotions Expressed in Online Support Groups for Quitting Smoking.
J Assoc Consum Res. 2021 Jul;6(3):315-323. doi: 10.1086/714517. Epub 2021 May 24.
8
Toward Real-Time Infoveillance of Twitter Health Messages.
Am J Public Health. 2018 Aug;108(8):1009-1014. doi: 10.2105/AJPH.2018.304497. Epub 2018 Jun 21.
9
A prospective examination of online social network dynamics and smoking cessation.
PLoS One. 2017 Aug 23;12(8):e0183655. doi: 10.1371/journal.pone.0183655. eCollection 2017.
10
Systematic review of social media interventions for smoking cessation.
Addict Behav. 2017 Oct;73:81-93. doi: 10.1016/j.addbeh.2017.05.002. Epub 2017 May 2.

本文引用的文献

1
Efficacy of SMS Text Message Interventions for Smoking Cessation: A Meta-Analysis.
J Subst Abuse Treat. 2015 Sep;56:1-10. doi: 10.1016/j.jsat.2015.01.011. Epub 2015 Feb 2.
2
Text messaging-based smoking cessation intervention: a narrative review.
Addict Behav. 2014 May;39(5):907-17. doi: 10.1016/j.addbeh.2013.11.024. Epub 2013 Dec 4.
3
Methodological considerations in analyzing Twitter data.
J Natl Cancer Inst Monogr. 2013 Dec;2013(47):140-6. doi: 10.1093/jncimonographs/lgt026.
4
Inferring tie strength from online directed behavior.
PLoS One. 2013;8(1):e52168. doi: 10.1371/journal.pone.0052168. Epub 2013 Jan 2.
5
Happy ending: a randomized controlled trial of a digital multi-media smoking cessation intervention.
Addiction. 2008 Mar;103(3):478-84; discussion 485-6. doi: 10.1111/j.1360-0443.2007.02119.x.
6
Do popular students smoke? The association between popularity and smoking among middle school students.
J Adolesc Health. 2005 Oct;37(4):323-9. doi: 10.1016/j.jadohealth.2004.10.016.
8
Automated e-mail messaging as a tool for improving quit rates in an internet smoking cessation intervention.
J Am Med Inform Assoc. 2004 Jul-Aug;11(4):235-40. doi: 10.1197/jamia.M1464. Epub 2004 Apr 2.
9
Design and pilot evaluation of an internet smoking cessation program.
J Am Med Inform Assoc. 2003 Jan-Feb;10(1):16-20. doi: 10.1197/jamia.m1128.
10
Biochemical verification of tobacco use and cessation.
Nicotine Tob Res. 2002 May;4(2):149-59. doi: 10.1080/14622200210123581.

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验