Industry influenced evidence production in collaborative research communities: a network analysis.

Adam G Dunn, Blanca Gallego, Enrico Coiera
Author Information
  1. Adam G Dunn: Centre for Health Informatics, Australian Institute of Health Innovation, University of New South Wales, Sydney, NSW 2052, Australia. a.dunn@unsw.edu.au

Abstract

OBJECTIVE: To measure the relative influence that industry authors have on collaborative research communities and evidence production.
STUDY DESIGN AND SETTING: Using 22 commonly prescribed drugs, 6,711 randomized controlled trials (RCTs), and 28,104 authors, 22 collaboration networks were constructed and analyzed. The directly industry-affiliated (DIA) authors were identified in the networks according to their published affiliations. Measures of influence (network centrality) and impact (citations) were determined for every author. Network-level measures of community structure and collaborative preference were used to further characterize the groups.
RESULTS: Six percent (1,741 of 28,104) of authors listed a direct affiliation with the manufacturer of a drug evaluated in the RCT. These authors received significantly more citations (P<0.05 in 19 networks) and were significantly more central in the networks (P<0.05 in 20 networks). The networks show that DIA authors tend to have greater reach in the networks and collaborate more often with non-DIA authors despite a preference toward their own group. Potential confounders include publication bias, trial sizes, and conclusions.
CONCLUSIONS: Industry-based authors are more central in their networks and are deeply embedded within highly connected drug research communities. As a consequence, they have the potential to influence information flow in the production of evidence.

MeSH Term

Authorship
Community Networks
Cooperative Behavior
Drug Industry
Evidence-Based Medicine
Humans
Information Dissemination
Journal Impact Factor
Models, Organizational
Organizational Affiliation
Pharmaceutical Preparations
Publication Bias
Publishing
Randomized Controlled Trials as Topic
Research Personnel

Chemicals

Pharmaceutical Preparations

Word Cloud

Created with Highcharts 10.0.0authorsnetworksinfluencecollaborativeresearchevidenceproductioncommunities2228104DIAnetworkcitationspreferencedrugsignificantlyP<005centralOBJECTIVE:measurerelativeindustrySTUDYDESIGNANDSETTING:Usingcommonlyprescribeddrugs6711randomizedcontrolledtrialsRCTscollaborationconstructedanalyzeddirectlyindustry-affiliatedidentifiedaccordingpublishedaffiliationsMeasurescentralityimpactdeterminedeveryauthorNetwork-levelmeasurescommunitystructureusedcharacterizegroupsRESULTS:Sixpercent1741listeddirectaffiliationmanufacturerevaluatedRCTreceived1920showtendgreaterreachcollaborateoftennon-DIAdespitetowardgroupPotentialconfoundersincludepublicationbiastrialsizesconclusionsCONCLUSIONS:Industry-baseddeeplyembeddedwithinhighlyconnectedconsequencepotentialinformationflowIndustryinfluencedcommunities:analysis

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