Evidence map›Paper›PMID 25285047›Full record

ArticleField methods2014

A Mixed Methods Approach to Network Data Collection.

Eric Rice, Ian W Holloway, Anamika Barman-Adhikari, Dahlia Fuentes, C Hendricks Brown, Lawrence A Palinkas

Abstract read
In one paragraph

Article in Field methods, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.

0numbers the graph read from it
0cells of the map it votes in
10citing 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

10 citing papers in PubMed.

  1. Trial
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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

6 authors.

Eric RiceSchool of Social Work at the University of Southern California.
Ian W HollowayDepartment of Social Welfare at the University of California, Los Angeles.
Anamika Barman-AdhikariSchool of Social Work at the University of Southern California.
Dahlia FuentesSchool of Social Work at the University of Southern California.
C Hendricks BrownDepartments of Epidemiology and Biostatistics, Miller School of Medicine, University of Miami.
Lawrence A PalinkasSchool of Social Work at the University of Southern California.

Funding

INNOVATIVE IMPLEMENTATION RESEARCH METHODS COREP30DA027828 · NIDA · UNIVERSITY OF MIAMI SCHOOL OF MEDICINE · PI BROWN, C. HENDRICKS · 2011 to 2020
$11.4M
Community Development Teams to Scale-Up MTFC in CaliforniaR01MH076158 · NIMH · CENTER FOR RESEARCH TO PRACTICE, INC. · PI CHAMBERLAIN, PATRICIA · 2006 to 2011
$5.7M
NIDA NIH HHS P30 DA027828NIMH NIH HHS R01 MH076158
6 · The paper itself

Abstract

There is a growing interest in examining network processes with a mix of qualitative and quantitative network data. Research has consistently shown that free recall name generators entail recall bias and result in missing data that affects the quality of social network data. This study describes a mixed methods approach for collecting social network data, combining a free recall name generator in the context of an online survey with network relations data coded from transcripts of semi-structured qualitative interviews. The combined network provides substantially more information about the network space, both quantitatively and qualitatively. While network density was relatively stable across networks generated from different data collection methodologies, there were noticeable differences in centrality and component structure across networks. The approach presented here involved limited participant burden and generated more complete data than either technique alone could provide. We make suggestions for further development of this method.

Identifiers

PMID25285047
PMCPMC4184035

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Registered trials

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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.