title: An observational study of social and emotional support in smoking cessation Twitter accounts: content analysis of tweets.
abstract: BACKGROUND
  Smoking continues to be the number one preventable cause of premature death in the United States. While evidence for the effectiveness of smoking cessation interventions has increased rapidly, questions remain on how to effectively disseminate these findings. Twitter, the second largest online social network, provides a natural way of disseminating information. Health communicators can use Twitter to inform smokers, provide social support, and attract them to other interventions. A key challenge for health researchers is how to frame their communications to maximize the engagement of smokers.
  
  
  OBJECTIVE
  Our aim was to examine current Twitter activity for smoking cessation.
  
  
  METHODS
  Active smoking cessation related Twitter accounts (N=18) were identified. Their 50 most recent tweets were content coded using a schema adapted from the Roter Interaction Analysis System (RIAS), a theory-based, validated coding method. Using negative binomial regression, the association of number of followers and frequency of individual tweet content at baseline was assessed. The difference in followership at 6 months (compared to baseline) to the frequency of tweet content was compared using linear regression. Both analyses were adjusted by account type (organizational or not organizational).
  
  
  RESULTS
  The 18 accounts had 60,609 followers at baseline and 68,167 at 6 months. A total of 24% of tweets were socioemotional support (mean 11.8, SD 9.8), 14% (mean 7, SD 8.4) were encouraging/engagement, and 62% (mean 31.2, SD 15.2) were informational. At baseline, higher frequency of socioemotional support and encouraging/engaging tweets was significantly associated with higher number of followers (socioemotional: incident rate ratio [IRR] 1.09, 95% CI 1.02-1.20; encouraging/engaging: IRR 1.06, 95% CI 1.00-1.12). Conversely, higher frequency of informational tweets was significantly associated with lower number of followers (IRR 0.95, 95% CI 0.92-0.98). At 6 months, for every increase by 1 in socioemotional tweets, the change in followership significantly increased by 43.94 (P=.027); the association was slightly attenuated after adjusting by account type and was not significant (P=.064).
  
  
  CONCLUSIONS
  Smoking cessation activity does exist on Twitter. Preliminary findings suggest that certain content strategies can be used to encourage followership, and this needs to be further investigated.
authors.affiliation: Division of Health Informatics and Implementation Science, Quantitative Health Sciences, University of Massachusetts Medical School, Worcester, MA, United States.
authors.forename: Mary
authors.identifier: http://orcid.org/0000-0003-3795-5735
authors.initials: M
authors.lastname: Rocheleau
authors.forename: Rajani Shankar
authors.identifier: http://orcid.org/0000-0001-8406-6207
authors.initials: RS
authors.lastname: Sadasivam
authors.forename: Kate
authors.identifier: http://orcid.org/0000-0002-5239-0771
authors.initials: K
authors.lastname: Baquis
authors.forename: Hannah
authors.identifier: http://orcid.org/0000-0002-0547-5035
authors.initials: H
authors.lastname: Stahl
authors.forename: Rebecca L
authors.identifier: http://orcid.org/0000-0001-6752-5715
authors.initials: RL
authors.lastname: Kinney
authors.forename: Sherry L
authors.identifier: http://orcid.org/0000-0002-2462-8797
authors.initials: SL
authors.lastname: Pagoto
authors.forename: Thomas K
authors.identifier: http://orcid.org/0000-0002-2909-4018
authors.initials: TK
authors.lastname: Houston
mesh_terms: D003142:Communication; D006293:Health Promotion; D006801:Humans; D033181:Information Dissemination; D020407:Internet / Q000145:classification; D012189:Retrospective Studies; D012907:Smoking; D016540:Smoking Cessation / Q000523:psychology*; D012944:Social Support
keywords: Internet; Twitter; smoking cessation; social network