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Social networks of people with serious mental illness who smoke: potential role in a smoking cessation intervention.
Journal of Mental Health 2024 April 9
BACKGROUND: Smoking is a major contributor to morbidity and mortality among individuals with serious mental illness (SMI) and social networks may play an important role in smoking behaviors.
AIMS: Our objectives were to (1) describe the network characteristics of adults with SMI who smoke tobacco (2) explore whether network attributes were associated with nicotine dependence.
METHODS: We performed a secondary analysis of baseline data from a tobacco smoking cessation intervention trial among 192 participants with SMI. A subgroup ( n = 75) completed questions on the characteristics of their social network members. The network characteristics included network composition (e.g. proportion who smoke) and network structure (e.g. density of connections between members). We used multilevel models to examine associations with nicotine dependence.
RESULTS: Participant characteristics included: a mean age 50 years, 49% women, 48% Black, and 41% primary diagnosis of schizophrenia/schizoaffective disorder. The median personal network proportion of active smokers was 22%, active quitters 0%, and non-smokers 53%. The density of ties between actively smoking network members was greater than between non-smoking members (55% vs 43%, p = .02). Proportion of network smokers was not associated with nicotine dependence.
CONCLUSIONS: We identified potential social network challenges and assets to smoking cessation and implications for network interventions among individuals with SMI.
AIMS: Our objectives were to (1) describe the network characteristics of adults with SMI who smoke tobacco (2) explore whether network attributes were associated with nicotine dependence.
METHODS: We performed a secondary analysis of baseline data from a tobacco smoking cessation intervention trial among 192 participants with SMI. A subgroup ( n = 75) completed questions on the characteristics of their social network members. The network characteristics included network composition (e.g. proportion who smoke) and network structure (e.g. density of connections between members). We used multilevel models to examine associations with nicotine dependence.
RESULTS: Participant characteristics included: a mean age 50 years, 49% women, 48% Black, and 41% primary diagnosis of schizophrenia/schizoaffective disorder. The median personal network proportion of active smokers was 22%, active quitters 0%, and non-smokers 53%. The density of ties between actively smoking network members was greater than between non-smoking members (55% vs 43%, p = .02). Proportion of network smokers was not associated with nicotine dependence.
CONCLUSIONS: We identified potential social network challenges and assets to smoking cessation and implications for network interventions among individuals with SMI.
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