Assessing the level of acceptance of a crowdsourcing solution to monitor infectious diseases propagation

Cruz, Matheus; Oliveira, Roberta S.; Beltrão, Augusto Pizano Vieira; Lopes, Paulo H. B.; Viterbo, José; Trevisan, Daniela; Bernardini, Flávia

doi:10.1109/isc251055.2020.9239069

Cited by 15 publications

(27 citation statements)

References 19 publications

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“…The first risk of bias is sample size. While some of the studies [e.g., ( 15 , 16 )] have relatively large sample sizes over 1,000, others [e.g., ( 17 , 18 )] have small sample sizes <300. The studies with larger samples sizes that presented structural equation models (SEMs) are more likely to have statistically significant relationships between constructs, compared with those with smaller sample sizes, due to an increased level of confidence in the presented result which larger sample sizes foster.…”

Section: Resultsmentioning

confidence: 99%

“…Approximately, two-third of the included studies [e.g., ( 15 , 16 , 20 )] were carried out during the first half of 2020 when many were yet to be familiar with CTAs. The other one-third of the studies [e.g., ( 17 , 21 , 22 )] were carried out in the second half of the same year when people were more familiar with CTAs and their potential benefits due to the marketing campaigns and the availability of more information on traditional and social media. The difference in times in the conduct of the studies may have influenced the various findings.…”

Section: Resultsmentioning

confidence: 99%

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Factors Influencing the Adoption of Contact Tracing Applications: Systematic Review and Recommendations

Oyibo¹,

Sahu²,

Oetomo³

et al. 2022

Front. Digit. Health

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BackgroundThe emergence of new variants of COVID-19 causing breakthrough infections and the endemic potential of the coronavirus are an indication that digital contact tracing apps (CTAs) may continue to be useful for the long haul. However, the uptake of these apps in many countries around the world has been low due to several factors militating against their adoption and usage.ObjectiveIn this systematic review, we set out to uncover the key factors that facilitate or militate against the adoption of CTAs, which researchers, designers and other stakeholders should focus on in future iterations to increase their adoption and effectiveness in curbing the spread of COVID-19.Data SourcesSeven databases, including PubMed, CINAHL, Scopus, Web of Service, IEEE Xplore, ACM Digital Library, and Google Scholar, were searched between October 30 and January 31, 2020. A total of 777 articles were retrieved from the databases, with 13 of them included in the systematic review after screening.Study Eligibility Criteria, Participants, and InterventionThe criteria for including articles in the systematic review were that they could be user studies from any country around the world, must be peer-reviewed, written in English, and focused on the perception and adoption of COVID-19 contact tracing and/or exposure notification apps. Other criteria included user study design could be quantitative, qualitative, or mixed, and must have been conducted during the COVID-19 pandemic, which began in the early part of 2020.Study Appraisal and Synthesis MethodsThree researchers searched seven databases (three by the first author, and two each by the second and third authors) and stored the retrieved articles in a collaborative Mendeley reference management system online. After the removal of duplicates, each researcher independently screened one third of the articles based on title/abstract. Thereafter, all three researchers collectively screened articles that were in the borderline prior to undergoing a full-text review. Then, each of the three researchers conducted a full-text review of one-third of the eligible articles to decide the final articles to be included in the systematic review. Next, all three researchers went through the full text of each borderline article to determine their appropriateness and relevance. Finally, each researcher extracted the required data from one-third of the included articles into a collaborative Google spreadsheet and the first author utilized the data to write the review.ResultsThis review identified 13 relevant articles, which found 56 factors that may positively or negatively impact the adoption of CTAs. The identified factors were thematically grouped into ten categories: privacy and trust, app utility, facilitating conditions, social-cognitive factors, ethical concerns, perceived technology threats, perceived health threats, technology familiarity, persuasive design, and socio-demographic factors. Of the 56 factors, privacy concern turned out to be the most frequent factor of CTA adoption (12/13), followed by perceived benefit (7/13), perceived trust (6/13), and perceived data security risk (6/13). In the structural equation models presented by the authors of the included articles, a subset of the 56 elicited factors (e.g., perceived benefit and privacy concern) explains 16 to 77% of the variance of users' intention to download, install, or use CTAs to curb the spread of COVID-19. Potential adoption rates of CTA range from 19% (in Australia) to 75% (in France, Italy, Germany, United Kingdom, and United States). Moreover, actual adoption rates range from 37% (in Australia) to 50% (in Germany). Finally, most of the studies were carried out in Europe (66.7%), followed by North America (13.3%), and Australia, Asia, and South America (6.7% each).ConclusionThe results suggest that future CTA iterations should give priority to privacy protection through minimal data collection and transparency, improving contact tracing benefits (personal and social), and fostering trust through laudable gestures such as delegating contact tracing to public health authorities, making source code publicly available and stating who will access user data, when, how, and what it will be used for. Moreover, the results suggest that data security and tailored persuasive design, involving reward, self-monitoring, and social-location monitoring features, have the potential of improving CTA adoption. Hence, in addition to addressing issues relating to utility, privacy, trust, and data security, we recommend the integration of persuasive features into future designs of CTAs to improve their motivational appeal, adoption, and the user experience.Systematic Review Registrationhttps://www.crd.york.ac.uk/prospero/display_record.php?ID=CRD42021259080 PROSPERO, identifier CRD42021259080.

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Section: Resultsmentioning

confidence: 99%

Section: Resultsmentioning

confidence: 99%

Factors Influencing the Adoption of Contact Tracing Applications: Systematic Review and Recommendations

Oyibo¹,

Sahu²,

Oetomo³

et al. 2022

Front. Digit. Health

View full text Add to dashboard Cite

show abstract

“…Regarded as the cornerstone of persuasive apps, self-monitoring fosters self-awareness and commitment, among other advantages shown in Figure 7 [ 46 ]. In the context of contact tracing apps, Cruz et al [ 47 ] found that over 50% of their surveyed participants wanted to know how many infected people they have come in contact with and how many infected people have passed through a given location. Reward provides users with something to strive for and reinforces behaviors [ 48 ].…”

Section: Persuasive Designmentioning

confidence: 99%

Designing Better Exposure Notification Apps: The Role of Persuasive Design

Oyibo¹,

Morita²

2021

JMIR Public Health Surveill

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Background Digital contact tracing apps have been deployed worldwide to limit the spread of COVID-19 during this pandemic and to facilitate the lifting of public health restrictions. However, due to privacy-, trust-, and design-related issues, the apps are yet to be widely adopted. This calls for an intervention to enable a critical mass of users to adopt them. Objective The aim of this paper is to provide guidelines to design contact tracing apps as persuasive technologies to make them more appealing and effective. Methods We identified the limitations of the current contact tracing apps on the market using the Government of Canada’s official exposure notification app (COVID Alert) as a case study. Particularly, we identified three interfaces in the COVID Alert app where the design can be improved. The interfaces include the no exposure status interface, exposure interface, and diagnosis report interface. We propose persuasive technology design guidelines to make them more motivational and effective in eliciting the desired behavior change. Results Apart from trust and privacy concerns, we identified the minimalist and nonmotivational design of exposure notification apps as the key design-related factors that contribute to the current low uptake. We proposed persuasive strategies such as self-monitoring of daily contacts and exposure time to make the no exposure and exposure interfaces visually appealing and motivational. Moreover, we proposed social learning, praise, and reward to increase the diagnosis report interface’s effectiveness. Conclusions We demonstrated that exposure notification apps can be designed as persuasive technologies by incorporating key persuasive features, which have the potential to improve uptake, use, COVID-19 diagnosis reporting, and compliance with social distancing guidelines.

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“…Since the sensitivity of shared data, such as posts on social networks and GPS locations, the authors try to find a trade-off between the privacy of participants and the profit that the society derives from the accuracy and number of data collected. The authors of [22] propose a study for the acceptance of crowdsensing campaigns aimed at tracking infected people. The participatory and opportunistic capabilities of this idea allow to the creation of a city map about the places visited by infected citizens in order to identify location that need a more accurate disinfection, such as metro stops, squares, commercial business, offices.…”

Section: Mcs and Blockchain For Pandemia Managementmentioning

confidence: 99%

Edge-enabled Mobile Crowdsensing to Support Effective Rewarding for Data Collection in Pandemic Events

2021

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Smart cities use Information and Communication Technologies (ICT) to enrich existing public services and to improve citizens’ quality of life. In this scenario, Mobile CrowdSensing (MCS) has become, in the last few years, one of the most prominent paradigms for urban sensing. MCS allow people roaming around with their smart devices to collectively sense, gather, and share data, thus leveraging the possibility to capture the pulse of the city. That can be very helpful in emergency scenarios, such as the COVID-19 pandemic, that require to track the movement of a high number of people to avoid risky situations, such as the formation of crowds. In fact, using mobility traces gathered via MCS, it is possible to detect crowded places and suggest people safer routes/places. In this work, we propose an edge-anabled mobile crowdsensing platform, called ParticipAct, that exploits edge nodes to compute possible dangerous crowd situations and a federated blockchain network to store reward states. Edge nodes are aware of all critical situation in their range and can warn the smartphone client with a smart push notification service that avoids firing too many messages by adapting the warning frequency according to the transport and the specific subarea in which clients are located.

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Assessing the level of acceptance of a crowdsourcing solution to monitor infectious diseases propagation

Cited by 15 publications

References 19 publications

Factors Influencing the Adoption of Contact Tracing Applications: Systematic Review and Recommendations

Factors Influencing the Adoption of Contact Tracing Applications: Systematic Review and Recommendations

Designing Better Exposure Notification Apps: The Role of Persuasive Design

Edge-enabled Mobile Crowdsensing to Support Effective Rewarding for Data Collection in Pandemic Events

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