Evidence map›Paper›PMID 26327931›Full record

ArticleTranslational behavioral medicine2015

Influence networks among substance abuse treatment clinics: implications for the dissemination of innovations.

Kimberly Johnson, Andrew Quanbeck, Adam Maus, David H Gustafson, James W Dearing

Abstract read
In one paragraph

Article in Translational behavioral medicine, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
–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.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

2 citing papers in PubMed.

  1. Article
  2. Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors.

Kimberly JohnsonUniversity of Wisconsin, Madison, WI USA.
Andrew QuanbeckUniversity of Wisconsin, Madison, WI USA.
Adam MausUniversity of Wisconsin, Madison, WI USA.
David H GustafsonUniversity of Wisconsin, Madison, WI USA.
James W DearingUniversity of Wisconsin, Madison, WI USA.

Funding

Institutional Clinical and Translational Science AwardUL1TR000427 · NCATS · UNIVERSITY OF WISCONSIN-MADISON · PI DREZNER, MARC KENNETH · 2012 to 2016
$32.2M
RCT Evaluating Improvement Strategies for Addiction TxR01DA020832 · NIDA · UNIVERSITY OF WISCONSIN-MADISON · PI GUSTAFSON, DAVID H · 2006 to 2010
$7.3M
Impact on opioid use of bundling medication-assisted treatment with mHealthR01DA040449 · NIDA · UNIVERSITY OF WISCONSIN-MADISON · PI GUSTAFSON, DAVID H · 2015 to 2019
$3.4M
Implementing Technology-Assisted Drug Treatment and relapse prevention in FQHCsR01DA034279 · NIDA · UNIVERSITY OF WISCONSIN-MADISON · PI GUSTAFSON, DAVID H, MARSCH, LISA A. · 2012 to 2016
$3.3M
To Test A Payer/Treatment Agency Intervention to Increase Use of BuprenorphineR01DA030431 · NIDA · UNIVERSITY OF WISCONSIN-MADISON · PI MOLFENTER, TODD DAVID · 2012 to 2016
$2.9M
Conceptualizing the problem of implementation: a systems engineering perspective applied in substance abuse treatmentK01DA039336 · NIDA · UNIVERSITY OF WISCONSIN-MADISON · PI QUANBECK, ANDREW · 2015 to 2019
$741k
Physician coaching to reduce opioid-related harmsR34DA036720 · NIDA · UNIVERSITY OF WISCONSIN-MADISON · PI BROWN, RANDALL T, QUANBECK, ANDREW · 2014 to 2016
$683k
"Community Infrastructure" Grants ProgramRC4DA029975 · NIDA · UNIVERSITY OF WISCONSIN-MADISON · PI GUSTAFSON, DAVID H, JOHNSON, KIMBERLY ANN · 2010 to 2010
$400k
NCATS NIH HHS UL1 TR000427NIDA NIH HHS K01 DA039336NIDA NIH HHS R01 DA020832NIDA NIH HHS R01 DA030431NIDA NIH HHS R01 DA034279NIDA NIH HHS R01 DA040449NIDA NIH HHS R34 DA036720NIDA NIH HHS RC4 DA029975
6 · The paper itself

Abstract

Understanding influence networks among substance abuse treatment clinics may speed the diffusion of innovations. The purpose of this study was to describe influence networks in Massachusetts, Michigan, New York, Oregon, and Washington and test two expectations, using social network analysis: (1) Social network measures can identify influential clinics; and (2) Within a network, some weakly connected clinics access out-of-network sources of innovative evidence-based practices and can spread these innovations through the network. A survey of 201 clinics in a parent study on quality improvement provided the data. Network measures and sociograms were obtained from adjacency matrixes created by UCINet. We used regression analysis to determine whether network status relates to clinics' adopting innovations. Findings suggest that influential clinics can be identified and that loosely linked clinics were likely to join the study sooner than more influential clinics but were not more likely to have improved outcomes than other organizations. Findings identify the structure of influence networks for SUD treatment organizations and have mixed results on how those structures impacted diffusion of the intervention under study. Further study is necessary to test whether use of knowledge of the network structure will have an effect on the pace and breadth of dissemination of innovations.

Indexed as

Addiction treatmentDiffusion of innovationsNetwork analysisSocial networksSociometrics

Identifiers

PMID26327931
PMCPMC4537466

What OpenQuestion holds

Textmetadata
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Registered trials

None linked

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.