Literature DB >> 30016519

Egocentric social networks and smoking among adults with serious mental illness.

Kelly A Aschbrenner1,2, Carly Bobak3, Emily J Schneider4, John A Naslund5, Mary F Brunette2, A James O'Malley1,6.   

Abstract

Evidence-based smoking cessation treatment is safe and effective for smokers with serious mental illness (SMI); however, quit rates remain low in this population. We explored how social networks influence smoking outcomes among people with SMI who participated in smoking cessation treatment at community mental health centers. We conducted egocentric social network interviews with 41 individuals with SMI who participated in a statewide Medicaid demonstration project of smoking cessation treatment. We estimated the proportions of current smokers, former smokers, and never smokers in participants' (i.e., egos') networks and examined support for quitting from alters, defined as family, friends, peers, or significant others. We used logistic regression and mixed-effect logistic regression to explore the relationship between social network variables and ego's smoking status following cessation treatment. Egos reported an average of 5.9 ± 2.2 alters; 52% of alters were current smokers; 18% were former smokers; and 30% never smoked. The majority (57%) of alters helped an ego quit smoking. The presence of former smokers in the network was associated with decreased odds that the ego was smoking post-treatment. Egos whose friends were highly interconnected were less likely to smoke after treatment. Former smokers in the network may be a valuable resource for quitting particularly for vulnerable groups where there is a high prevalence and acceptability of smoking. Our initial findings suggest that a highly interconnected friendship network structure may be beneficial for people with SMI who are trying to quit smoking.

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Year:  2018        PMID: 30016519      PMCID: PMC6065543          DOI: 10.1093/tbm/ibx014

Source DB:  PubMed          Journal:  Transl Behav Med        ISSN: 1613-9860            Impact factor:   3.046


  32 in total

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2.  A 5-Factor Framework for Assessing Tobacco Use Disorder.

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3.  Pragmatics to Reveal Intent in Social Media Peer Interactions: Mixed Methods Study.

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