The crucial role of user's perceived trust in the orchestration and adoption of IT-ecosystems

Wiedmann, Klaus–Peter; Reeh, Marc-Oliver; Varelmann, Dieter; Hennigs, Nadine

doi:10.1145/1643823.1643894

Cited by 2 publications

(1 citation statement)

References 24 publications

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“…Prior research confirms that technology acceptance and adoption are affected by the level of trust users have in the technology [ 11 , 20 - 23 ]. However, evidence shows that designing trustworthy technologies is complex and needs to be better understood.…”

Section: Introductionmentioning

confidence: 97%

Modeling Trust in COVID-19 Contact-Tracing Apps Using the Human-Computer Trust Scale: Online Survey Study

Sousa¹,

Kalju²

2022

JMIR Hum Factors

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Background The COVID-19 pandemic has caused changes in technology use worldwide, both socially and economically. This pandemic crisis has brought additional measures such as contact-tracing apps (CTAs) to help fight against spread of the virus. Unfortunately, the low adoption rate of these apps affected their success. There could be many reasons for the low adoption, including concerns of security and privacy, along with reported issues of trust in CTAs. Some concerns are related with how CTAs could be used as surveillance tools or their potential threats to privacy as they involve health data. For example, in Estonia, the CTA named HOIA had approximately 250,000 downloads in the middle of January 2021. However, in 2021, only 4.7% of the population used HOIA as a COVID-19 CTA. The reasons for the low adoption include lack of competency, and privacy and security concerns. This lower adoption and the lack of trustworthiness persist despite efforts of the European Union in building ethics and trustworthy artificial intelligence (AI)-based apps. Objective The aim of this study was to understand how to measure trust in health technologies. Specifically, we assessed the usefulness of the Human-Computer Trust Scale (HCTS) to measure Estonians’ trust in the HOIA app and the causes for this lack of trust. Methods The main research question was: Can the HCTS be used to assess citizens’ perception of trust in health technologies? We established four hypotheses that were tested with a survey. We used a convenience sample for data collection, including sharing the questionnaire on social network sites and using the snowball method to reach all potential HOIA users in the Estonian population. Results Among the 78 respondents, 61 had downloaded the HOIA app with data on usage patterns. However, 20 of those who downloaded the app admitted that it was never opened despite most claiming to regularly use mobile apps. The main reasons included not understanding how it works, and privacy and security concerns. Significant correlations were found between participants’ trust in CTAs in general and their perceived trust in the HOIA app regarding three attributes: competency (P<.001), risk perception (P<.001), and reciprocity (P=.01). Conclusions This study shows that trust in the HOIA app among Estonian residents did affect their predisposition to use the app. Participants did not generally believe that HOIA could help to control the spread of the virus. The result of this work is limited to HOIA and health apps that use similar contact-tracing methods. However, the findings can contribute to gaining a broader understanding and awareness of the need for designing trustworthy technologies. Moreover, this work can help to provide design recommendations that ensure trustworthiness in CTAs, and the ability of AI to use highly sensitive data and serve society.

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Section: Introductionmentioning

confidence: 97%

Modeling Trust in COVID-19 Contact-Tracing Apps Using the Human-Computer Trust Scale: Online Survey Study

Sousa¹,

Kalju²

2022

JMIR Hum Factors

View full text Add to dashboard Cite

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Modeling Trust in COVID-19 Contact-Tracing Apps Using the Human-Computer Trust Scale: Online Survey Study (Preprint)

Sousa¹,

Kalju²

2021

Preprint

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BACKGROUND The COVID-19 pandemic has caused changes on how we use technology across the world, both socially and economically. Due to the urgency and severity of the crisis different virus control measures were explored. One of the means how technology could help in this situation was by helping trace the contacts of people to prevent the spread of the disease. Many governments and public health authorities across the world have launched a number of contact tracing mobile apps (CTA). By the end of 2020, there are more than 50 contact tracing apps in both Google Play and iOS App Store [1]. Despite the wide availability, the download rates are low and usage rates are even lower [2][3]. There could be many reasons why the adoption is so low, but most certainly one variable that has been overlooked is the level of trust that potential users need to feel comfortable using an app. In Estonia, the CTA named HOIA has been developed as a means of digital contact tracing. By the middle of January 2021, there have been approximately 250 000 downloads but only 1763 (around 4,7% of all COVID-19 positive in Estonia by that time) people have registered as being tested COVID-19 positive [4]. It shows that HOIA has not proved to be efficient means to reduce the spread of the pandemic. Modeling evidence suggests that in order to be effective, the use of contact tracing apps would need to be very high, at least 80% of smartphone users to stop the pandemic [5]. 40% of Estonian people who don’t have HOIA do not believe that HOIA is effective and does what is promised. The concern about security and privacy was in the second place [6]. OBJECTIVE The goal of this study was to assess Estonian's trust towards the HOIA app and what has caused the shortage in trust. Namely, assess how much Estonians trust Covid-19 contact tracing app HOIA and what aspects are perceived as distrust by them. The study contributes to designers' understanding and awareness of designing trustworthy technology. METHODS The study comprised of measuring trust in HOIA CTA application using human-computer Trust psychometric scale [22]. A convenience sample was used in data collection, this includes all potential HOIA among the Estonian population. RESULTS Results indicate significant positive correlations between participants' trust towards the Estonian COVID tracing application (HOIA) and their perceptions of risk (p-value 0.000), competency (P-value 0.000), Benevolence (P-value=0.025), and reciprocity (P-value 0.015). CONCLUSIONS With the COVID-19 crisis, the new phenomenon of contact tracing apps was introduced to fight against the pandemic. CTAs were hoped to be a technological breakthrough to decrease the spread of the virus. However, this has not happened around the world. The same has happened in Estonia and evidence shows, that one of the reasons could be the low level of trust. The results of the study confirm, that trust in HOIA among Estonian habitants does affect their predisposition to use and indicated that participants do not believe HOIA is able to fulfill the main goal and decrease the spread of the virus. The result of this work is not only limited to HOIA but can be implemented by other CTAs as well. The results of this study contribute to designers' understanding and awareness of designing trustworthy technology. Eventually helps to provide design recommendations that ensure trustworthiness in the CTAs AI ability to use highly sensitive data and serve society. Regarding the limitations of this study, the survey was able to gather insight about the perceptions of HOIA, was enough to make a statistical generalization about the users’ perception and usage habits but more data needs to be collected if the intention is to generalize the results to the whole population of Estonia. Also, we should pay attention to the different minority groups to reach a valid conclusion. CLINICALTRIAL no trial registration.

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The crucial role of user's perceived trust in the orchestration and adoption of IT-ecosystems

Cited by 2 publications

References 24 publications

Modeling Trust in COVID-19 Contact-Tracing Apps Using the Human-Computer Trust Scale: Online Survey Study

Modeling Trust in COVID-19 Contact-Tracing Apps Using the Human-Computer Trust Scale: Online Survey Study

Modeling Trust in COVID-19 Contact-Tracing Apps Using the Human-Computer Trust Scale: Online Survey Study (Preprint)

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