Tailored interventions into broad attitude networks towards the COVID-19 pandemic

PLoS One. 2022 Oct 27;17(10):e0276439. doi: 10.1371/journal.pone.0276439. eCollection 2022.

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.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Attitude
  • COVID-19* / epidemiology
  • Cross-Sectional Studies
  • Humans
  • Pandemics
  • Surveys and Questionnaires

Grants and funding

This research was funded by The Dutch Research Council (NWO grant 440.20.019). J.D.'s work was supported by an EU Horizon 2020 Marie Curie Global Fellowship (no. 889682). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.