Evidence map›Paper›PMID 25952354›Full record

Trial reportLancet (London, England)2015

Social network targeting to maximise population behaviour change: a cluster randomised controlled trial.

David A Kim, Alison R Hwong, Derek Stafford, D Alex Hughes, A James O'Malley, James H Fowler, Nicholas A Christakis

3 registry-linked trialsAbstract readRandomized Controlled Trial
In one paragraph

Trial report in Lancet (London, England), 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to 3 registered trials, which are not on this map. Cited by 130 papers, 5 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
130citing papers in PubMed, 5 pooled it
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

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.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

NCT01672580 nacompletednot on this map

Diffusion of Health Interventions Across Social Networks in Honduran Villages

TypeinterventionalSponsorHarvard UniversityRan2012 to 2014Enrolled5,773ConditionsMalnutrition, Dysentery, Social Transmission of Health BehaviorsArmsexposure to vitamin use, exposure to water chlorination, high in-degree, nominated by random
NCT04166097 naunknown statusnot on this mapstarted 2020, after this paper: background citation

Primary Prevention of Cardiovascular Disease Among Female Hospital Employees: The Heart Smart for Women Intervention

TypeinterventionalSponsorNorthwell HealthRan2020 to 2023Enrolled46ConditionsCardiovascular Risk FactorArmsHeart Smart Interventional Program
NCT04772469 nacompletednot on this mapstarted 2021, after this paper: background citation

Self-Test Strategies and Linkage Incentives to Improve ART and PrEP Uptake in Men

TypeinterventionalSponsorUniversity of California, San FranciscoRan2021 to 2023Enrolled934ConditionsHuman Immunodeficiency Virus, Acquired Immunodeficiency Syndrome, HIV Infections, Sexually Transmitted Diseases, ViralArmsProvision of multiple self-tests, Small monetary incentives, Use of SMS/text reminders to motivate adherence to ART or PrEP
3 · Its place in the literature

Who cites it

130 citing papers in PubMed, 5 syntheses or guidelines pooled it.

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70 more citing papers are in PubMed but not listed here.

4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

7 authors.

David A KimInterfaculty Initiative in Health Policy, Harvard University, Cambridge, MA, USA.
Alison R HwongInterfaculty Initiative in Health Policy, Harvard University, Cambridge, MA, USA.
Derek StaffordYale Institute for Network Science, Yale University, New Haven, CT, USA.
D Alex HughesDepartment of Political Science, University of California, San Diego, La Jolla, CA, USA.
A James O'MalleyDartmouth Institute of Health Policy and Clinical Practice, Geisel School of Medicine at Dartmouth, Lebanon, NH, USA.
James H FowlerDepartments of Political Science and Medical Genetics, University of California, San Diego, La Jolla, CA, USA.
Nicholas A ChristakisDepartments of Medicine, Ecology and Evolutionary Biology, Biomedical Engineering, and Sociology, Yale University, New Haven, CT, USA. Electronic address: nicholas.christakis@yale.edu.

Funding

The Spread of Health Behaviors in the Framingham Heart Study Social NetworkP01AG031093 · NIA · YALE UNIVERSITY · PI CHRISTAKIS, NICHOLAS A · 2008 to 2012
$10.7M
Roybal Center for Translational Research on AgingP30AG034420 · NIA · YALE UNIVERSITY · PI CHRISTAKIS, NICHOLAS A · 2009 to 2018
$3.3M
Network-based Health Interventions in Rural HondurasF30AG046978 · NIA · HARVARD MEDICAL SCHOOL · PI HWONG, ALISON R · 2013 to 2015
$136k
Canadian Institutes of Health ResearchNIA NIH HHS F30 AG046978NIA NIH HHS P-01 AG031093NIA NIH HHS P01 AG031093NIA NIH HHS P-30 AG034420NIA NIH HHS P30 AG034420
6 · The paper itself

Abstract

backgroundInformation and behaviour can spread through interpersonal ties. By targeting influential individuals, health interventions that harness the distributive properties of social networks could be made more effective and efficient than those that do not. Our aim was to assess which targeting methods produce the greatest cascades or spillover effects and hence maximise population-level behaviour change.

methodsIn this cluster randomised trial, participants were recruited from villages of the Department of Lempira, Honduras. We blocked villages on the basis of network size, socioeconomic status, and baseline rates of water purification, for delivery of two public health interventions: chlorine for water purification and multivitamins for micronutrient deficiencies. We then randomised villages, separately for each intervention, to one of three targeting methods, introducing the interventions to 5% samples composed of either: randomly selected villagers (n=9 villages for each intervention); villagers with the most social ties (n=9); or nominated friends of random villagers (n=9; the last strategy exploiting the so-called friendship paradox of social networks). Participants and data collectors were not aware of the targeting methods. Primary endpoints were the proportions of available products redeemed by the entire population under each targeting method. This trial is registered with ClinicalTrials.gov, number NCT01672580.

findingsBetween Aug 4, and Aug 14, 2012, 32 villages in rural Honduras (25-541 participants each; total study population of 5773) received public health interventions. For each intervention, nine villages (each with 1-20 initial target individuals) were randomised, using a blocked design, to each of the three targeting methods. In nomination-targeted villages, 951 (74·3%) of 1280 available multivitamin tickets were redeemed compared with 940 (66·2%) of 1420 in randomly targeted villages and 744 (61·0%) of 1220 in indegree-targeted villages. All pairwise differences in redemption rates were significant (p<0·01) after correction for multiple comparisons. Targeting nominated friends increased adoption of the nutritional intervention by 12·2% compared with random targeting (95% CI 6·9-17·9). Targeting the most highly connected individuals, by contrast, produced no greater adoption of either intervention, compared with random targeting.

interpretationIntroduction of a health intervention to the nominated friends of random individuals can enhance that intervention's diffusion by exploiting intrinsic properties of human social networks. This method has the additional advantage of scalability because it can be implemented without mapping the network. Deployment of certain types of health interventions via network targeting, without increasing the number of individuals targeted or the resources used, could enhance the adoption and efficiency of those interventions, thereby improving population health.

fundingNational Institutes of Health, The Bill & Melinda Gates Foundation, Star Family Foundation, and the Canadian Institutes of Health Research.

Indexed as

Health BehaviorSocial NetworkingAdultDisinfectionDrug MonitoringFemaleHealth Knowledge, Attitudes, PracticeHealth PromotionHondurasHumansMaleMicronutrientsMiddle AgedPublic HealthRural HealthSocial ChangeMicronutrientsSodium HypochloriteVitamins

Identifiers

PMID25952354
PMCPMC4638320

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Read underepoch 390

Registered trials

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.