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采用 COVID-19 接触者追踪应用程序的捷克青年:跨文化复制研究。

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

机构信息

Faculty of Informatics and Statistics, Prague University of Economics and Business, Prague, Czech Republic.

出版信息

JMIR Hum Factors. 2023 Nov 16;10:e45481. doi: 10.2196/45481.


DOI:10.2196/45481
PMID:37971804
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC10655852/
Abstract

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 (β=.60, P<.001 and β=-.39; P<.001, respectively). Differently from the original study, self-efficacy was not a significant predictor in the strict statistical sense (β=.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.

摘要

背景:在全球 COVID-19 大流行期间,数字接触追踪(DCT)的作用得到了加强。然而,这项技术的采用情况在不同的年龄组和国家文化中预计会有所不同。各种概念工具被引入,从理论角度加强 DCT 研究。然而,在不同的文化背景和年龄组之间比较理论支持的发现方面,几乎没有什么工作。

目的:本研究以 2020 年 4 月在比利时进行的原始研究为基础,并以健康信念模型(HBM)为理论基础,试图在与原始研究不同的文化环境(捷克共和国)中验证 DCT 采用的预测因素。此外,通过使用简短的定性证据,旨在阐明 HBM 在研究背景下的可能局限性,并提出对 HBM 的某些扩展。

方法:在 2020 年 11 月,对年轻(18-29 岁)捷克成年人的便利样本进行了原始工具的捷克语版本测试。经过筛选,共获得 519 份有效回复,用于定量数据分析,该分析使用结构方程建模,并遵循 HBM 结构之间关系的建议结构。此外,对自由文本答案进行了主题定性分析,以提供有关该模型在特定背景下有效性的更多见解。

结果:与原始研究相比(均方根误差逼近值=0.036,90%CI 0.033-0.039),所提出的测量模型的拟合度较差(均方根误差逼近值=0.065,90%CI 0.060-0.070)。然而,与原始研究一致,感知益处和感知障碍被确认为 DCT 采用的主要、统计学显著预测因素(β=0.60,P<.001 和β=-0.39;P<.001)。与原始研究不同的是,自我效能感在严格的统计学意义上不是一个显著的预测因素(β=0.12;P=.003)。此外,定性分析表明,在给定的队列中,感知障碍是最常见的主题(总代码的 46.9%,即 166/354)。在这个类别下,心理恐惧和担忧是一个亚主题,与原始感知障碍结构的操作化明显不同。同样,一些受访者提出了社会影响在 DCT 采用过程中的作用(总代码的 1.7%,即 12/354)。总之,定量和定性结果表明,在所研究的背景下,拟定量模型的似乎价值有限。

结论:未来的研究应专注于通过考虑定性发现,重新概念化两个表现不佳的结构(即感知严重程度和线索作用)。本研究还为政策制定者和应用程序开发者提供了可操作的见解,以减轻未来由未知病毒引起的大流行期间 DCT 采用问题。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8e63/10655852/5a8277863729/humanfactors_v10i1e45481_fig1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8e63/10655852/5a8277863729/humanfactors_v10i1e45481_fig1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8e63/10655852/5a8277863729/humanfactors_v10i1e45481_fig1.jpg

相似文献

[1]
Adoption of a COVID-19 Contact Tracing App by Czech Youth: Cross-Cultural Replication Study.

JMIR Hum Factors. 2023-11-16

[2]
Adoption of a Contact Tracing App for Containing COVID-19: A Health Belief Model Approach.

JMIR Public Health Surveill. 2020-9-1

[3]
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JMIR Hum Factors. 2024-6-25

[4]
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[5]
Utilizing Health Behavior Change and Technology Acceptance Models to Predict the Adoption of COVID-19 Contact Tracing Apps: Cross-sectional Survey Study.

J Med Internet Res. 2021-5-19

[6]
Understanding Trust and Changes in Use After a Year With the NHS COVID-19 Contact Tracing App in the United Kingdom: Longitudinal Mixed Methods Study.

J Med Internet Res. 2022-10-14

[7]
Acceptability of App-Based Contact Tracing for COVID-19: Cross-Country Survey Study.

JMIR Mhealth Uhealth. 2020-8-28

[8]
Ready or Not for Contact Tracing? Investigating the Adoption Intention of COVID-19 Contact-Tracing Technology Using an Extended Unified Theory of Acceptance and Use of Technology Model.

Cyberpsychol Behav Soc Netw. 2021-6

[9]
The Roles of General Health and COVID-19 Proximity in Contact Tracing App Usage: Cross-sectional Survey Study.

JMIR Public Health Surveill. 2021-8-18

[10]
Public Adoption of and Trust in the NHS COVID-19 Contact Tracing App in the United Kingdom: Quantitative Online Survey Study.

J Med Internet Res. 2021-9-17

本文引用的文献

[1]
Normative positions towards COVID-19 contact-tracing apps: findings from a large-scale qualitative study in nine European countries.

Crit Public Health. 2021-6-2

[2]
Why Individuals Do (Not) Use Contact Tracing Apps: A Health Belief Model Perspective on the German Corona-Warn-App.

Healthcare (Basel). 2023-2-15

[3]
Breaking the chain with individual gain? Investigating the moral intensity of COVID-19 digital contact tracing.

Comput Human Behav. 2023-6

[4]
COVID-19 and contact tracing apps: The importance of theory and conceptual models.

Int J Med Inform. 2023-2

[5]
Explaining citizens' resistance to use digital contact tracing apps: A mixed-methods study.

Int J Inf Manage. 2022-4

[6]
Continued Use of Contact-Tracing Apps in the United States and the United Kingdom: Insights From a Comparative Study Through the Lens of the Health Belief Model.

JMIR Form Res. 2022-12-8

[7]
Barriers and enablers of weight management after breast cancer: a thematic analysis of free text survey responses using the COM-B model.

BMC Public Health. 2022-8-20

[8]
Effects of strict containment policies on COVID-19 pandemic crisis: lessons to cope with next pandemic impacts.

Environ Sci Pollut Res Int. 2023-1

[9]
Analysis of mHealth research: mapping the relationship between mobile apps technology and healthcare during COVID-19 outbreak.

Global Health. 2022-6-28

[10]
Factors Influencing the Adoption of Contact Tracing Applications: Systematic Review and Recommendations.

Front Digit Health. 2022-5-3

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