ArticleRural mental health2017
Depression, Smoking, and Ego-Centric Social Network Characteristics in Ohio Appalachian Women.
Article in Rural mental health, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
5 citing papers in PubMed, 10 citations in OpenAlex.
- Social network structure and depression by gender in rural Honduras: a cross-sectional study.BMJ open · 2026Observational
- Web-Based Social Networks of Individuals With Adverse Childhood Experiences: Quantitative Study.Journal of medical Internet research · 2023Article
- Associations between cancer history, social distancing behaviors, and loneliness in adults during the COVID-19 pandemic.PloS one · 2023Article
- Review
- The impact of smoking cessation attempts on stress levels.BMC public health · 2019Article
Corrections and comments
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Authors and funding
7 authors at 1 institution in 1 country.
Funding
Abstract
Depression is a serious, costly, and debilitating disorder that is understudied in rural women. Studies show that depression is associated with low social integration and support, but few studies investigate the relationship between depression and social network characteristics. This study examined the associations among women from three Ohio Appalachian counties enrolled in a health study, which aimed to collect information for a future social network smoking cessation intervention. An address-based sampling method was used to randomly select and recruit 404 women. A cross-sectional survey and interview were used to collect information about demographic, psychosocial, behavioral factors, and ego-centric social network characteristics, which are variables derived from an individual (ego) and her first degree contacts (alters). The CES-D scale assessed depressive symptoms. A multivariable logistic regression analysis described the association between these factors and participants with depression (defined as CES-D≥16). Higher network density, or greater number of relationships among alters divided by the total amount of alters, reduced the risk for depression (OR = 0.84, 95% confidence interval [CI] 0.73-0.95). Additionally, women with a high percentage of smoking alters were at greater risk for depression (OR = 1.19, 95% CI 1.02-1.39). Other factors associated with risk for depression included perceived stress score (OR = 1.34, 95% CI 1.24-1.45), loneliness score (OR = 1.37, 95% CI 1.05-1.80), and days with poor physical health (OR = 1.06, 95% CI 1.02-1.11). Findings suggest that psychosocial factors and social networks should be considered when addressing depression in clinical practice.
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Registered trials
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