ArticleSubstance use & misuse2015
Bidirectional Influence: A Longitudinal Analysis of Size of Drug Network and Depression Among Inner-City Residents in Baltimore, Maryland.
Article in Substance use & misuse, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
What it found
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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, 4 citations in OpenAlex.
- Injection Drug Network Characteristics Are Important Markers of HIV Risk Behavior and Lack of Viral Suppression.Journal of acquired immune deficiency syndromes (1999) · 2017Trial
- Incidence of substance use disorders and comorbidities in the All of Us Research Program.Drug and alcohol dependence · 2026Article
- Pandemic Associated Changes in Personal Substance Use and Perceptions of Changes to Peer Substance Use among College Students: A Retrospective Assessment.Journal of drug education · 2025Article
- Success4life Youth Empowerment for Promoting Well-being and Boosting Mental Health: Protocol for an Experimental Study.JMIR research protocols · 2022Article
- The role of perceived friend depression and perceived stigma on self-reported depression among individuals who use drugs.Journal of community psychology · 2018Article
Corrections and comments
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Authors and funding
4 authors at 2 institutions in 1 country.
Funding
Abstract
backgroundThe prevalence of depression among drug users is high. It has been recognized that drug use behaviors can be influenced and spread through social networks.
objectivesWe investigated the directional relationship between social network factors and depressive symptoms among a sample of inner-city residents in Baltimore, MD.
methodsWe performed a longitudinal study of four-wave data collected from a network-based HIV/STI prevention intervention for women and network members, consisting of both men and women. Our primary outcome and exposure were depression using CESD scale and social network characteristics, respectively. Linear-mixed model with clustering adjustment was used to account for both repeated measurement and network design.
resultsOf the 746 participants, those who had high levels of depression tended to be female, less educated, homeless, smokers, and did not have a main partner. In the univariate longitudinal model, larger size of drug network was significantly associated with depression (OR = 1.38, p < .001). This relationship held after controlling for age, gender, homeless in the past 6 months, college education, having a main partner, cigarette smoking, perceived health, and social support network (aOR = 1.19, p = .001). In the univariate mixed model using depression to predict size of drug network, the data suggested that depression was associated with larger size of drug network (coef. = 1.23, p < .001) and the same relation held in multivariate model (adjusted coef. = 1.08, p = .001).
conclusionsThe results suggest that larger size of drug network is a risk factor for depression, and vice versa. Further intervention strategies to reduce depression should address social networks factors.
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.