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
  • [1] Adoption of a Contact Tracing App for Containing COVID-19: A Health Belief Model Approach
    Walrave, Michel
    Waeterloos, Cato
    Ponnet, Koen
    JMIR PUBLIC HEALTH AND SURVEILLANCE, 2020, 6 (03): : 488 - 497
  • [2] Examining the cultural dimension of contact-tracing app adoption during the COVID-19 pandemic: a cross-country study in Singapore and Switzerland
    Geber, Sarah
    Ho, Shirley S.
    INFORMATION COMMUNICATION & SOCIETY, 2023, 26 (11) : 2229 - 2249
  • [3] Acceptability of App-Based Contact Tracing for COVID-19: Cross-Country Survey Study
    Altmann, Samuel
    Milsom, Luke
    Zillessen, Hannah
    Blasone, Raffaele
    Gerdon, Frederic
    Bach, Ruben
    Kreuter, Frauke
    Nosenzo, Daniele
    Toussaert, Severine
    Abeler, Johannes
    JMIR MHEALTH AND UHEALTH, 2020, 8 (08):
  • [4] The Adoption of a COVID-19 Contact-Tracing App: Cluster Analysis
    Hengst, Tessi M.
    Lechner, Lilian
    van der Laan, Laura Nynke
    Hommersom, Arjen
    Dohmen, Daan
    Hooft, Lotty
    Metting, Esther
    Ebbers, Wolfgang
    Bolman, Catherine A. W.
    JMIR FORMATIVE RESEARCH, 2023, 7
  • [5] Public Adoption of and Trust in the NHS COVID-19 Contact Tracing App in the United Kingdom: Quantitative Online Survey Study
    Dowthwaite, Liz
    Fischer, Joel
    Vallejos, Elvira Perez
    Portillo, Virginia
    Nichele, Elena
    Goulden, Murray
    McAuley, Derek
    JOURNAL OF MEDICAL INTERNET RESEARCH, 2021, 23 (09)
  • [6] Barriers to the Large-Scale Adoption of a COVID-19 Contact Tracing App in Germany: Survey Study
    Blom, Annelies G.
    Wenz, Alexander
    Cornesse, Carina
    Rettig, Tobias
    Fikel, Marina
    Friedel, Sabine
    Moehring, Katja
    Naumann, Elias
    Reifenscheid, Maximiliane
    Krieger, Ulrich
    JOURNAL OF MEDICAL INTERNET RESEARCH, 2021, 23 (03)
  • [7] Adoption of Covid-19 contact tracing app by extending UTAUT theory: Perceived disease threat as moderator
    Chopdar, Prasanta Kr
    HEALTH POLICY AND TECHNOLOGY, 2022, 11 (03)
  • [8] Examining the Prediction of COVID-19 Contact-Tracing App Adoption Using an Integrated Model and Hybrid Approach Analysis
    Alkhalifah, Ali
    Bukar, Umar Ali
    FRONTIERS IN PUBLIC HEALTH, 2022, 10
  • [9] The adoption of contact tracing applications of COVID-19 by European governments
    Jacob, Steve
    Lawaree, Justin
    POLICY DESIGN AND PRACTICE, 2021, 4 (01) : 44 - 58
  • [10] What makes people install a COVID-19 contact-tracing app? Understanding the influence of app design and individual difference on contact-tracing app adoption intention
    Li, Tianshi
    Cobb, Camille
    Yang, Jackie
    Baviskar, Sagar
    Agarwal, Yuvraj
    Li, Beibei
    Bauer, Lujo
    Hong, Jason I.
    PERVASIVE AND MOBILE COMPUTING, 2021, 75