Please use this identifier to cite or link to this item: https://hdl.handle.net/10356/164379
Title: The influence of normative perceptions on the uptake of the COVID-19 tracetogether digital contact tracing system: cross-sectional study
Authors: Lee, Jeong Kyu
Lin, Lavinia
Kang, Hyunjin
Keywords: Social sciences::Communication
Issue Date: 2021
Source: Lee, J. K., Lin, L. & Kang, H. (2021). The influence of normative perceptions on the uptake of the COVID-19 tracetogether digital contact tracing system: cross-sectional study. JMIR Public Health and Surveillance, 7(11), e30462-. https://dx.doi.org/10.2196/30462
Project: 2019-T1-002-115
Journal: JMIR Public Health and Surveillance
Abstract: Background: In 2020, the Singapore government rolled out the TraceTogether program, a digital system to facilitate contact tracing efforts in response to the COVID-19 pandemic. This system is available as a smartphone app and Bluetooth-enabled token to help identify close contacts. As of February 1, 2021, more than 80% of the population has either downloaded the mobile app or received the token in Singapore. Despite the high adoption rate of the TraceTogether mobile app and token (ie, device), it is crucial to understand the role of social and normative perceptions in uptake and usage by the public, given the collective efforts for contact tracing. Objective: This study aimed to examine normative influences (descriptive and injunctive norms) on TraceTogether device use for contact tracing purposes, informed by the theory of normative social behavior, a theoretical framework to explain how perceived social norms are related to behaviors. Methods: From January to February 2021, cross-sectional data were collected by a local research company through emailing their panel members who were (1) Singapore citizens or permanent residents aged 21 years or above; (2) able to read English; and (3) internet users with access to a personal email account. The study sample (n=1137) was restricted to those who had either downloaded the TraceTogether mobile app or received the token. Results: Multivariate (linear and ordinal logistic) regression analyses were carried out to assess the relationships of the behavioral outcome variables (TraceTogether device usage and intention of TraceTogether device usage) with potential correlates, including perceived social norms, perceived community, and interpersonal communication. Multivariate regression analyses indicated that descriptive norms (unstandardized regression coefficient β=0.31, SE=0.05; P<.001) and injunctive norms (unstandardized regression coefficient β=0.16, SE=0.04; P<.001) were significantly positively associated with the intention to use the TraceTogether device. It was also found that descriptive norms were a significant correlate of TraceTogether device use frequency (adjusted odds ratio [aOR] 2.08, 95% CI 1.66-2.61; P<.001). Though not significantly related to TraceTogether device use frequency, injunctive norms moderated the relationship between descriptive norms and the outcome variable (aOR 1.12, 95% CI 1.03-1.21; P=.005). Conclusions: This study provides useful implications for the design of effective intervention strategies to promote the uptake and usage of digital methods for contact tracing in a multiethnic Asian population. Our findings highlight that influence from social networks plays an important role in developing normative perceptions in relation to TraceTogether device use for contact tracing. To promote the uptake of the TraceTogether device and other preventive behaviors for COVID-19, it would be useful to devise norm-based interventions that address these normative perceptions by presenting high prevalence and approval of important social referents, such as family and close friends.
URI: https://hdl.handle.net/10356/164379
ISSN: 2369-2960
DOI: 10.2196/30462
Rights: ©Jeong Kyu Lee, Lavinia Lin, Hyunjin Kang. Originally published in JMIR Public Health and Surveillance (https://publichealth.jmir.org), 12.11.2021. This is an open-access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work, first published in JMIR Public Health and Surveillance, is properly cited. The complete bibliographic information, a link to the original publication on https://publichealth.jmir.org, as well as this copyright and license information must be included.
Fulltext Permission: open
Fulltext Availability: With Fulltext
Appears in Collections:WKWSCI Journal Articles

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