Adoption of a COVID-19 Contact Tracing App by Czech Youth: Cross-Cultural Replication Study

被引:0
|
作者
Dolezel, Michal [1 ,2 ]
Smutny, Zdenek [1 ]
机构
[1] Prague Univ Econ & Business, Fac Informat & Stat, Prague, Czech Republic
[2] Prague Univ Econ & Business, Fac Informat & Stat, W Churchill Sq 4, Prague 13067, Czech Republic
来源
JMIR HUMAN FACTORS | 2023年 / 10卷
关键词
contact tracing; proximity tracing; digital contact tracing; Health Belief Model; technology adoption; COVID-19; qualitative verification; Health Belief Model approach; pandemic crisis; eRouska; eMask; HEALTH; BEHAVIOR; INFORMATION; SEEKING; MODEL;
D O I
10.2196/45481
中图分类号
R19 [保健组织与事业(卫生事业管理)];
学科分类号
摘要
Background: During the worldwide COVID-19 pandemic crisis, the role of digital contact tracing (DCT) intensified. However, the uptake of this technology expectedly differed among age cohorts and national cultures. Various conceptual tools were introduced to strengthen DCT research from a theoretical perspective. However, little has been done to compare theory-supported findings across different cultural contexts and age cohorts.Objective: Building on the original study conducted in Belgium in April 2020 and theoretically underpinned by the Health Belief Model (HBM), this study attempted to confirm the predictors of DCT adoption in a cultural environment different from the original setting, that is, the Czech Republic. In addition, by using brief qualitative evidence, it aimed to shed light on the possible limitations of the HBM in the examined context and to propose certain extensions of the HBM.Methods: A Czech version of the original instrument was administered to a convenience sample of young (aged 18-29 y) Czech adults in November 2020. After filtering, 519 valid responses were obtained and included in the quantitative data analysis, which used structural equation modeling and followed the proposed structure of the relationships among the HBM constructs. Furthermore, a qualitative thematic analysis of the free-text answers was conducted to provide additional insights about the model's validity in the given context.Results: The proposed measurement model exhibited less optimal fit (root mean square error of approximation=0.065, 90% CI 0.060-0.070) than in the original study (root mean square error of approximation=0.036, 90% CI 0.033-0.039). Nevertheless, perceived benefits and perceived barriers were confirmed as the main, statistically significant predictors of DCT uptake, consistent with the original study (beta=.60, P<.001 and beta=-.39; P<.001, respectively). Differently from the original study, self-efficacy was not a significant predictor in the strict statistical sense (beta=.12; P=.003). In addition, qualitative analysis demonstrated that in the given cohort, perceived barriers was the most frequent theme (166/354, 46.9% of total codes). Under this category, psychological fears and concerns was a subtheme, notably diverging from the original operationalization of the perceived barriers construct. In a similar sense, a role for social influence in DCT uptake processes was suggested by some respondents (12/354, 1.7% of total codes). In summary, the quantitative and qualitative results indicated that the proposed quantitative model seemed to be of limited value in the examined context.Conclusions: Future studies should focus on reconceptualizing the 2 underperforming constructs (ie, perceived severity and cues to action) by considering the qualitative findings. This study also provided actionable insights for policy makers and app developers to mitigate DCT adoption issues in the event of a future pandemic caused by unknown viral agents.
引用
收藏
页数:22
相关论文
共 50 条
  • [31] Sentiment analysis of user feedback on the HSE's Covid-19 contact tracing app
    Rekanar, Kaavya
    O'Keeffe, Ian R.
    Buckley, Sarah
    Abbas, Manzar
    Beecham, Sarah
    Chochlov, Muslim
    Fitzgerald, Brian
    Glynn, Liam
    Johnson, Kevin
    Laffey, John
    McNicholas, Bairbre
    Nuseibeh, Bashar
    O'Connell, James
    O'Keeffe, Derek
    O'Callaghan, Mike
    Razzaq, Abdul
    Richardson, Ita
    Simpkin, Andrew
    Storni, Cristiano
    Tsvyatkova, Damyanka
    Walsh, Jane
    Welsh, Thomas
    Buckley, Jim
    IRISH JOURNAL OF MEDICAL SCIENCE, 2022, 191 (01) : 103 - 112
  • [32] To Use or Not to Use a COVID-19 Contact Tracing App: Mixed Methods Survey in Wales
    Jones, Kerina
    Thompson, Rachel
    JMIR MHEALTH AND UHEALTH, 2021, 9 (11):
  • [33] Digital Health Innovation: Exploring Adoption of COVID-19 Digital Contact Tracing Apps
    Sharma, Shavneet
    Singh, Gurmeet
    Sharma, Rashmini
    Jones, Paul
    Kraus, Sascha
    Dwivedi, Yogesh K.
    IEEE TRANSACTIONS ON ENGINEERING MANAGEMENT, 2024, 71 : 12272 - 12288
  • [34] Understanding the perceptions of UK COVID-19 contact tracing app in the BAME community in Leicester
    Akintoye, Simisola
    Ogoh, George
    Krokida, Zoi
    Nnadi, Juliana
    Eke, Damian
    JOURNAL OF INFORMATION COMMUNICATION & ETHICS IN SOCIETY, 2021, 19 (04) : 521 - 536
  • [35] Deciding if and How to Use a COVID-19 Contact Tracing App: Influences of Social Factors on Individual Use in Japan
    Jamieson J.
    Yamashita N.
    Epstein D.A.
    Chen Y.
    Proceedings of the ACM on Human-Computer Interaction, 2021, 5 (CSCW2)
  • [36] Fundamental limitations of contact tracing for COVID-19
    Tupper, Paul
    Otto, Sarah P.
    Colijn, Caroline
    FACETS, 2021, 6 : 1993 - 2001
  • [37] COVID-19 contact tracing: The Welsh experience
    Bright, Diana
    Brown, Graham
    Roberts, Richard J.
    Cottrell, Simon
    Gould, Ashley
    Jesurasa, Amrita
    Daniels, Philip
    Davies, Llion
    PUBLIC HEALTH IN PRACTICE, 2020, 1
  • [38] From contact tracing to COVID-19 pass holder; the tortured journey of the French TousAntiCovid contact tracing app
    Schultz, Emilien
    Touzani, Rajae
    Mancini, Julien
    Ward, Jeremy K.
    PUBLIC HEALTH, 2022, 206 : 5 - 7
  • [39] Preferences in the Willingness to Download a COVID-19 Contact Tracing App in the Netherlands and Turkey: Experimental Study
    Folkvord, Frans
    Peschke, Lutz
    Agca, Yasemin Gumus
    van Houten, Karlijn
    Stazi, Giacomo
    Lupianez-Villanueva, Francisco
    JMIR FORMATIVE RESEARCH, 2022, 6 (07)
  • [40] A Survey of COVID-19 Contact Tracing Apps
    Ahmed, Nadeem
    Michelin, Regio A.
    Xue, Wanli
    Ruj, Sushmita
    Malaney, Robert
    Kanhere, Salil S.
    Seneviratne, Aruna
    Hu, Wen
    Janicke, Helge
    Jha, Sanjay K.
    IEEE ACCESS, 2020, 8 (08): : 134577 - 134601