Investigating Social Network Peer Effects on HIV Care Engagement Using a Fuzzy-Like Matching Approach: Cross-Sectional Secondary Analysis of the N2 Cohort Study

Using alternative sources of network data allowed us to fuzzy match a more complete network: fuzzy matching may identify hidden ties among participants that were missed by examining alternative sources of network data separately. Although sociocentric studies require significant resources to implement, more complete sociocentric-like networks may be generated using a fuzzy match approach that leverages egocentric, peer referral, and digital networks. Enriching offline networks with digital network data may provide insights into characteristics and norms that egocentric approaches may not be able to capture.

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Publication Details

Journal
JMIR Public Health and Surveillance
Published
2025-03-18
DOI
https://doi.org/10.2196/64497
Primary Topic
Social Media and Politics
Type
article
Field-Weighted Citation Impact
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article

Investigating Social Network Peer Effects on HIV Care Engagement Using a Fuzzy-Like Matching Approach: Cross-Sectional Secondary Analysis of the N2 Cohort Study

John A. Schneider, Justin Knox, Kayo Fujimoto, Britt Skaathun et al.
JMIR Public Health and Surveillance
Social Media and Politics
article

Investigating Social Network Peer Effects on HIV Care Engagement Using a Fuzzy-Like Matching Approach: Cross-Sectional Secondary Analysis of the N2 Cohort Study

John A. Schneider, Justin Knox, Kayo Fujimoto, Britt Skaathun, Raymond L. Moody, Dustin T. Duncan, Natascha Del Vecchio, Yen‐Tyng Chen, Redd Driver, Cho‐Hee Shrader, Juan G Arroyo-Flores, Mariano Kanamori, Lindsay E. Young, Makella S. Coudray
article en

Abstract

Using alternative sources of network data allowed us to fuzzy match a more complete network: fuzzy matching may identify hidden ties among participants that were missed by examining alternative sources of network data separately. Although sociocentric studies require significant resources to implement, more complete sociocentric-like networks may be generated using a fuzzy match approach that leverages egocentric, peer referral, and digital networks. Enriching offline networks with digital network data may provide insights into characteristics and norms that egocentric approaches may not be able to capture.

JMIR Public Health and SurveillanceVol. 11
Rutgers, The State University of New Jersey (US), University of Central Florida (US), University of Southern California (US), New York City Department of Health and Mental Hygiene (US), University of Connecticut (US), University of Miami (US), University of Hartford (US), Chicago Department of Public Health (US), Columbia University Irving Medical Center (US), New York Psychoanalytic Society and Institute (US), University of California San Diego (US), University of Chicago (US), New York State Psychiatric Institute, Arizona State University (US), Seattle University (US), Columbia University (US), The University of Texas Health Science Center at Houston (US)
Gender equality
Openalex Percentile: Top 94%
Social Media and Politics
DOIOpen Access PDFOpenAlex
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