In:
PLOS ONE, Public Library of Science (PLoS), Vol. 17, No. 10 ( 2022-10-27), p. e0276439-
Abstract:
This study examines how broad attitude networks are affected by tailored interventions aimed at variables selected based on their connectiveness with other variables. We first computed a broad attitude network based on a large-scale cross-sectional COVID-19 survey ( N = 6,093). Over a period of approximately 10 weeks, participants were invited five times to complete this survey, with the third and fifth wave including interventions aimed at manipulating specific variables in the broad COVID-19 attitude network. Results suggest that targeted interventions that yield relatively strong effects on variables central to a broad attitude network have downstream effects on connected variables, which can be partially explained by the variables the interventions were aimed at. We conclude that broad attitude network structures can reveal important relations between variables that can help to design new interventions.
Type of Medium:
Online Resource
ISSN:
1932-6203
DOI:
10.1371/journal.pone.0276439
DOI:
10.1371/journal.pone.0276439.g001
DOI:
10.1371/journal.pone.0276439.g002
DOI:
10.1371/journal.pone.0276439.g003
DOI:
10.1371/journal.pone.0276439.g004
DOI:
10.1371/journal.pone.0276439.g005
DOI:
10.1371/journal.pone.0276439.t001
DOI:
10.1371/journal.pone.0276439.t002
DOI:
10.1371/journal.pone.0276439.t003
DOI:
10.1371/journal.pone.0276439.s001
DOI:
10.1371/journal.pone.0276439.s002
DOI:
10.1371/journal.pone.0276439.s003
DOI:
10.1371/journal.pone.0276439.r001
DOI:
10.1371/journal.pone.0276439.r002
DOI:
10.1371/journal.pone.0276439.r003
DOI:
10.1371/journal.pone.0276439.r004
DOI:
10.1371/journal.pone.0276439.r005
DOI:
10.1371/journal.pone.0276439.r006
Language:
English
Publisher:
Public Library of Science (PLoS)
Publication Date:
2022
detail.hit.zdb_id:
2267670-3
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