Abstract

Contact tracing is one of the oldest social network health interventions used to reduce the diffusion of various infectious diseases. However, some infectious diseases like COVID-19 amass at such a great scope that traditional methods of conducting contact tracing (e.g., face-to-face interviews) remain difficult to implement, pointing to the need to develop reliable and valid survey approaches. The purpose of this research is to test the effectiveness of three different egocentric survey methods for extracting contact tracing data: (1) a baseline approach, (2) a retrieval cue approach, and (3) a context-based approach. A sample of 397 college students were randomized into one condition each. They were prompted to anonymously provide contacts and populated places visited from the past four days depending on what condition they were given. After controlling for various demographic, social identity, psychological, and physiological variables, participants in the context-based condition were significantly more likely to recall more contacts (medium effect size) and places (large effect size) than the other two conditions. Theoretically, the research supports suggestions by field theory that assume network recall can be significantly improved by activating relevant activity foci. Practically, the research contributes to the development of innovative social network data collection methods for contract tracing survey instruments.

Document Type

Article

Publication Date

2-4-2021

Notes/Citation Information

Published in International Journal of Environmental Research and Public Health, v. 18, issue 4, 1466.

© 2021 by the authors. Licensee MDPI, Basel, Switzerland.

This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).

Digital Object Identifier (DOI)

https://doi.org/10.3390/ijerph18041466

Funding Information

This research was supported by the National Center for Research Resources and the National Center for Advancing Translational Sciences, National Institutes of Health, through Grant UL1TR001998.

Related Content

Anonymous link to dataset: https://osf.io/u7bda/?view_only=0394755b34a843808ac5cf34e8369b11.

The following are available online at https://www.mdpi.com/1660-4601/18/4/1466/s1, File S1: Questionnaire. It is also available for download as the additional file listed at the end of this record.

ijerph-18-01466-s001.pdf (104 kB)
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