Evidence map›Paper›PMID 38778422›Full record

ArticleAddiction science & clinical practice2024

A social network analysis approach to assess COVID19-related disruption to substance use treatment and informal social interactions among people who use drugs in Scotland.

Mark McCann, Federica Bianchi, Srebrenka Letina, Samantha Stewart, Katy McLeod, Mark Tranmer

Abstract read
In one paragraph

Article in Addiction science & clinical practice, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

What it found

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2 · The registry

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3 · Its place in the literature

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4 · The record

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5 · Who and what money

Authors and funding

6 authors.

Mark McCannMRC/CSO Social & Public Health Sciences Unit, University of Glasgow, Glasgow, Scotland. Mark.McCann@Glasgow.ac.uk.ORCID 0000-0002-6100-1416
Federica BianchiInstitute of Computing, Università della Svizzera Italiana, Viganello, Switzerland.
Srebrenka LetinaMRC/CSO Social & Public Health Sciences Unit, University of Glasgow, Glasgow, Scotland.
Samantha StewartScottish Drugs Forum, Glasgow, Scotland.
Katy McLeodScottish Drugs Forum, Glasgow, Scotland.
Mark TranmerCollege of Social Sciences, Institute of Health and Wellbeing, University of Glasgow, Glasgow, Scotland.

Funding

Chief Scientist Office, Scottish Government Health and Social Care Directorate SPHSU18Medical Research Council MC_UU_00022/3
6 · The paper itself

Abstract

aimsTo assess the extent of Coronavirus-related disruption to health and social care treatment and social interactions among people with lived or living experience of substance use in Scotland, and explore potential reasons for variations in disruption.

designCross sectional mixed methods interview, incorporating a social network 'egonet interview' approach asking about whether participants had interactions with a range of substance use, health, social care or third sector organisations, or informal social interactions.

settingFive Alcohol and Drug Partnership Areas in Scotland.

participants57 (42% women) participants were involved in the study, on average 42 years old. MEASUREMENTS: Five-point Likert scale reporting whether interactions with a range of services and people had gotten much better, better, no different (or no change), worse, or much worse since COVID19 and lockdown. Ratings were nested within participants (Individuals provided multiple ratings) and some ratings were also nested within treatment service (services received multiple ratings). The nested structure was accounted for using cross classified ordinal logistic multilevel models.

findingsWhile the overall average suggested only a slight negative change in interactions (mean rating 2.93), there were substantial variations according to type of interaction, and between individuals. Reported change was more often negative for mental health services (Adjusted OR = 0.93 95% CI 0.17,0.90), and positive for pharmacies (3.03 95% CI 1.36, 5.93). The models found between-participant variation of around 10%, and negligible between-service variation of around 1% in ratings. Ratings didn't vary by individual age or gender but there was variation between areas.

conclusionsSubstance use treatment service adaptations due to COVID19 lockdown led to both positive and negative service user experiences. Social network methods provide an effective way to describe complex system-wide interaction patterns, and to measure variations at the individual, service, and area level.

Indexed as

COVID-19Social InteractionSocial Network AnalysisSubstance-Related DisordersAdultCross-Sectional StudiesFemaleHumansMaleMiddle AgedSARS-CoV-2ScotlandCOVID19EgonetHealth services evaluationMultilevel modelSocial network analysis

Identifiers

PMID38778422
PMCPMC11110318

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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.