Predicted Adoption Rates of Contact Tracing App Configurations - Insights from a Choice-Based Conjoint Study with a Representative Sample of the UK population

Wiertz, Caroline; Banerjee, Aneesh; Acar, Oguz Ali; Ghosh, Adi

doi:10.2139/ssrn.3589199

Cited by 39 publications

(42 citation statements)

References 3 publications

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“…The context that respondents were offered in this study (ie, that the app would comply with privacy and security legislations) is likely to have contributed to the high adoption rates. Nevertheless, the only other choice-based study about COVID-19 apps published so far has reported even higher adoption rates, despite the fact that they did include attributes like using the app to enforce self-isolation, anonymity, length of data storage, and responsibility for the app project [ 22 ]. In this UK-wide study, the app with recommended specifications had a 73.5% adoption rate compared with 64.1% in our study.…”

Section: Discussionmentioning

confidence: 99%

COVID-19 Contact Tracing Apps: Predicted Uptake in the Netherlands Based on a Discrete Choice Experiment

Jonker¹,

Bekker‐Grob²,

Veldwijk³

et al. 2020

JMIR Mhealth Uhealth

109

129

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Background Smartphone-based contact tracing apps can contribute to reducing COVID-19 transmission rates and thereby support countries emerging from lockdowns as restrictions are gradually eased. Objective The primary objective of our study is to determine the potential uptake of a contact tracing app in the Dutch population, depending on the characteristics of the app. Methods A discrete choice experiment was conducted in a nationally representative sample of 900 Dutch respondents. Simulated maximum likelihood methods were used to estimate population average and individual-level preferences using a mixed logit model specification. Individual-level uptake probabilities were calculated based on the individual-level preference estimates and subsequently aggregated into the sample as well as subgroup-specific contact tracing app adoption rates. Results The predicted app adoption rates ranged from 59.3% to 65.7% for the worst and best possible contact tracing app, respectively. The most realistic contact tracing app had a predicted adoption of 64.1%. The predicted adoption rates strongly varied by age group. For example, the adoption rates of the most realistic app ranged from 45.6% to 79.4% for people in the oldest and youngest age groups (ie, ≥75 years vs 15-34 years), respectively. Educational attainment, the presence of serious underlying health conditions, and the respondents’ stance on COVID-19 infection risks were also correlated with the predicted adoption rates but to a lesser extent. Conclusions A secure and privacy-respecting contact tracing app with the most realistic characteristics can obtain an adoption rate as high as 64% in the Netherlands. This exceeds the target uptake of 60% that has been formulated by the Dutch government. The main challenge will be to increase the uptake among older adults, who are least inclined to install and use a COVID-19 contact tracing app.

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Section: Discussionmentioning

confidence: 99%

COVID-19 Contact Tracing Apps: Predicted Uptake in the Netherlands Based on a Discrete Choice Experiment

Jonker¹,

Bekker‐Grob²,

Veldwijk³

et al. 2020

JMIR Mhealth Uhealth

109

129

View full text Add to dashboard Cite

show abstract

“…Some studies are based on surveys assessing the uptake of these apps among different population samples. These studies mostly refer to a hypothetical app and the intention to use it [ 16 - 24 ], and only a few collect information on the use of an existing tool like StopCovid [ 25 - 27 ]. The majority of documents reporting the real uptake of contact tracing apps are national statistics without a scientific and theoretical background.…”

Section: Introductionmentioning

confidence: 99%

Health Care Students’ Knowledge of and Attitudes, Beliefs, and Practices Toward the French COVID-19 App: Cross-sectional Questionnaire Study

Montagni¹,

Roussel²,

Thiébaut³

et al. 2021

J Med Internet Res

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Background Many countries worldwide have developed mobile phone apps capable of supporting instantaneous contact tracing to control the COVID-19 pandemic. In France, a few people have downloaded and are using the StopCovid contact tracing app. Students in the health domain are of particular concern in terms of app uptake. Exploring their use and opinions about the app can inform improvements and diffusion of StopCovid among young people. Objective The aim of this study is to investigate health care students’ knowledge of and attitudes, beliefs, and practices (KABP) toward the StopCovid app. Methods A field survey was conducted among 318 students at the health sciences campus of the University of Bordeaux, France, between September 25 and October 16, 2020. A quota sampling method was used, and descriptive statistics and univariate analyses were performed. Results Of the 318 respondents, 77.3% (n=246) had heard about the app, but only 11.3% (n=36) had downloaded it, and 4.7% (n=15) were still using it at the time of the survey. Among the 210 participants who had heard about the app but did not download it, the main reasons for not using the app were a belief that it was not effective given its limited diffusion (n=37, 17.6%), a lack of interest (n=37, 17.6%), and distrust in the data security and fear of being geolocated (n=33, 15.7%). Among the 72 students who had not heard of the app and were given a brief description of its functioning and confidentiality policy, 52.7% (n=38) said they would use it. Participants reported that the main solution for increasing the use of the app would be better communication about it (227/318, 71.4%). Conclusions Even among health students, the contact tracing app was poorly used. The findings suggest that improved communication about its advantages and simplicity of use as well as clarifying false beliefs about it could help improve uptake.

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“…People’s preferences for a DCT app have been examined through 3 discrete choice experiments (DCEs). 6 , 7 , 8 Nevertheless, these studies all adopted an individualistic approach toward investigating preferences of potential app users in the sense that they focused on the positive and negative impacts that potential app users would experience themselves 6 , 7 , 8 (eg, What are the personal benefits that I gain from installing the app? 6 ).…”

Section: Introductionmentioning

confidence: 99%

Societal Effects Are a Major Factor for the Uptake of the Coronavirus Disease 2019 (COVID-19) Digital Contact Tracing App in The Netherlands

et al. 2021

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Objectives Our study investigates the extent to which uptake of a COVID-19 digital contact-tracing (DCT) app among the Dutch population is affected by its configurations, its societal effects, and government policies toward such an app. Methods We performed a discrete choice experiment among Dutch adults including 7 attributes, that is, who gets a notification, waiting time for testing, possibility for shops to refuse customers who have not installed the app, stopping condition for contact tracing, number of people unjustifiably quarantined, number of deaths prevented, and number of households with financial problems prevented. The data were analyzed by means of panel mixed logit models. Results The prevention of deaths and financial problems of households had a very strong influence on the uptake of the app. Predicted app uptake rates ranged from 24% to 78% for the worst and best possible app for these societal effects. We found a strong positive relationship between people’s trust in government and people’s propensity to install the DCT app. Conclusions The uptake levels we find are much more volatile than the uptake levels predicted in comparable studies that did not include societal effects in their discrete choice experiments. Our finding that the societal effects are a major factor in the uptake of the DCT app results in a chicken-or-the-egg causality dilemma. That is, the societal effects of the app are severely influenced by the uptake of the app, but the uptake of the app is severely influenced by its societal effects.

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Predicted Adoption Rates of Contact Tracing App Configurations - Insights from a Choice-Based Conjoint Study with a Representative Sample of the UK population

Cited by 39 publications

References 3 publications

COVID-19 Contact Tracing Apps: Predicted Uptake in the Netherlands Based on a Discrete Choice Experiment

COVID-19 Contact Tracing Apps: Predicted Uptake in the Netherlands Based on a Discrete Choice Experiment

Health Care Students’ Knowledge of and Attitudes, Beliefs, and Practices Toward the French COVID-19 App: Cross-sectional Questionnaire Study

Societal Effects Are a Major Factor for the Uptake of the Coronavirus Disease 2019 (COVID-19) Digital Contact Tracing App in The Netherlands

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