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The Adoption of a COVID-19 Contact-Tracing App: Cluster Analysis
Tessi M Hengst
*
,
Lilian Lechner
, Laura Nynke van der Laan
,
Arjen Hommersom
, Daan Dohmen
, Lotty Hooft
, Esther Metting
, Wolfgang Ebbers
,
Catherine A W Bolman
*
Corresponding author for this work
Research Line Health psychology (part of UHC program)
Research Line Resilience (part of LIRS program)
Research Program Towards High-quality and Intelligent Systems (THIS)
Research Program Learning and Innovation for Resilience and Sustainability (LIRS)
Research output
:
Contribution to journal
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Article
›
Academic
›
peer-review
Overview
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Dive into the research topics of 'The Adoption of a COVID-19 Contact-Tracing App: Cluster Analysis'. Together they form a unique fingerprint.
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Keyphrases
Cluster Analysis
100%
Contact Tracing Apps
100%
COVID-19 Contact Tracing
100%
Intention to Use
77%
Psychosocial Variables
22%
Self-efficacy
11%
Dutch
11%
Information Communication Technology
11%
Access to Information
11%
Social Norms
11%
Positive Perceptions
11%
COVID-19 Pandemic
11%
Personal Data
11%
Public Health
11%
Higher Education Levels
11%
Vulnerable People
11%
Old Age
11%
Non-adopters
11%
Low Socioeconomic Status
11%
Cluster Solutions
11%
Longitudinal Data
11%
Negative Perception
11%
Health Disparities
11%
Trust in Government
11%
Societal Benefits
11%
Health Apps
11%
Low Adoption
11%
Distinguishable Cluster
11%
Intenders
11%
COVID-19 Virus
11%
Health Literacy
11%
Psychosocial Perception
11%
Benefit-risk Perception
11%
App Adoption
11%
Perceived Personal Benefits
11%
Computer Science
Cluster Analysis
100%
COVID-19
100%
Personal Data
50%
Vulnerable People
50%
Longitudinal Data
50%
Socioeconomic Position
50%
Information and Communication Technology
50%
COVID 19 Epidemic
50%
Psychology
Cluster Analysis
100%
COVID-19
100%
Self-Efficacy
33%
Social Norms
33%
Risk Perception
33%
Public Health
33%
Health Disparity
33%
Health Literacy
33%
Nursing and Health Professions
Cluster Analysis
100%
Contact Examination
100%
COVID-19
100%
Patient Social Context
22%
Self-Efficacy
11%
Health Literacy
11%
Health Disparity
11%
Personal Data
11%
Public Health
11%
Neuroscience
Self-Efficacy
100%
Behavior (Neuroscience)
100%