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A prospective examination of online social network dynamics and smoking cessation

Overview of attention for article published in PLOS ONE, August 2017
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About this Attention Score

  • In the top 5% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (95th percentile)
  • High Attention Score compared to outputs of the same age and source (94th percentile)

Mentioned by

news
5 news outlets
blogs
1 blog
twitter
7 X users
podcasts
1 podcast

Readers on

mendeley
94 Mendeley
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Article details
Title
A prospective examination of online social network dynamics and smoking cessation
Published in
PLOS ONE, August 2017
DOI 10.1371/journal.pone.0183655
Pubmed ID
Authors
Abstract

Use of online social networks for smoking cessation has been associated with abstinence. Little is known about the mechanisms through which the formation of social ties in an online network may influence smoking behavior. Using dynamic social network analysis, we investigated how temporal changes of an individual's number of social network ties are prospectively related to abstinence in an online social network for cessation. In a network where quitting is normative and is the focus of communications among members, we predicted that an increasing number of ties would be positively associated with abstinence. Participants were N = 2,657 adult smokers recruited to a randomized cessation treatment trial following enrollment on BecomeAnEX.org, a longstanding Internet cessation program with a large and mature online social network. At 3-months post-randomization, 30-day point prevalence abstinence was assessed and website engagement metrics were extracted. The social network was constructed with clickstream data to capture the flow of information among members. Two network centrality metrics were calculated at weekly intervals over 3 months: 1) in-degree, defined as the number of members whose posts a participant read; and 2) out-degree-aware, defined as the number of members who read a participant's post and commented, which was subsequently viewed by the participant. Three groups of users were identified based on social network engagement patterns: non-users (N = 1,362), passive users (N = 812), and active users (N = 483). Logistic regression modeled 3-month abstinence by group as a function of baseline variables, website utilization, and network centrality metrics. Abstinence rates varied by group (non-users = 7.7%, passive users = 10.7%, active users = 20.7%). Significant baseline predictors of abstinence were age, nicotine dependence, confidence to quit, and smoking temptations in social situations among passive users (ps < .05); age and confidence to quit among active users. Among centrality metrics, positive associations with abstinence were observed for in-degree increases from Week 2 to Week 12 among passive and active users, and for out-degree-aware increases from Week 2 to Week 12 among active users (ps < .05). This study is the first to demonstrate that increased tie formation among members of an online social network for smoking cessation is prospectively associated with abstinence. It also highlights the value of using individuals' activities in online social networks to predict their offline health behaviors.

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X Demographics

X Demographics

The data shown below were collected from the profiles of 7 X users who shared this research output. Click here to find out more about how the information was compiled.
Mendeley demographics

Mendeley demographics

The data shown below were compiled from readership statistics for 94 Mendeley readers of this research output. Click here to see the associated Mendeley record.
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Geographical breakdown

Geographical breakdown
Country Count As %
Unknown 94 100%

Demographic breakdown

Readers by professional status
Readers by professional status Count As %
Student > Ph. D. Student 14 15%
Student > Master 13 14%
Researcher 10 11%
Student > Doctoral Student 7 7%
Student > Postgraduate 5 5%
Other 15 16%
Unknown 30 32%
Readers by discipline
Readers by discipline Count As %
Psychology 14 15%
Medicine and Dentistry 11 12%
Social Sciences 8 9%
Nursing and Health Professions 7 7%
Computer Science 6 6%
Other 17 18%
Unknown 31 33%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 53. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 15 January 2023.
All research outputs
#983,146
of 32,919,153 outputs
Outputs from PLOS ONE
#11,841
of 218,669 outputs
Outputs of similar age
#15,314
of 346,915 outputs
Outputs of similar age from PLOS ONE
#230
of 4,032 outputs
Altmetric has tracked 32,919,153 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 97th percentile: it's in the top 5% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 218,669 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 17.1. This one has done particularly well, scoring higher than 94% of its peers.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 346,915 tracked outputs that were published within six weeks on either side of this one in any source. This one has done particularly well, scoring higher than 95% of its contemporaries.
We're also able to compare this research output to 4,032 others from the same source and published within six weeks on either side of this one. This one has done particularly well, scoring higher than 94% of its contemporaries.