Kovid-19 İzleme Uygulamalarında Ödül Mekanizmaları ve Sürdürülebilir Yenilik Süreçlerinde Gönüllü Kamusal Katılım Üzerinde Etkileri

Öz

Kovid-19 salgını akıllı telefonların küresel anlamda toplumları etkisi altına almasından sonra yaşanan ilk salgındır. Bu nedenle, kişilerin bilimsel ihtiyaçlara göre kamusal farkındalık ve sorumluluk duygusu oluşturan bilgi ve bilimsel süreçlere nasıl dahil edilebileceği konusunda, yeterli anlayış ve deneyim henüz oluşmamıştır. Salgın kriziyle sürdürülebilir bir biçimde mücadele için, akademi, ekonomi, kültür ve basın merkezli kamu ile siyaset arasında oluşturulacak etkili bir işbirliği oldukça önemlidir. Değerlendirmede Mobil Uygulamalarda Derecelendirme Ölçeği (MUDÖ) yardımı ile farklı ülkelerdeki Kovid-19 izleme uygulamaları ödül mekanizmalarına göre niteliksel içerik analiz yöntemi kullanılarak incelenmiştir. Bu analiz farklı ödüllerin gönüllü katılıma etkileşimini içerir. Mobil Uygulamalarda Değerlendirme Ölçeği etkileşim, işlevsel estetik ve bilgi kalitesi unsurlarından oluşmaktadır. Gönüllülüğün korunması, bu uygulamaların etiğe uygun bir şekilde kullanılmasında, en temel ihtiyaç olarak anlaşılmaktadır. Buna göre, gönüllülük modelleri, seçilen kovid izleme uygulamalarının hukuki, etik, mahremiyet ve güvenlik politikaları dikkate alınarak incelenmiştir. Bu çerçevede, bu makale izleme uygulamalarının kamu içerisinde kullanımını artırmak için gereken özellik ve fonksiyonelliği kavramayı amaçlamakla birlikte kovid izleme uygulamalarının kullanımı açısından sınıflandırma yapmayı ve kriter oluşturmayı ve bunun kişilerin beşli sarmal işbirliği süreçlerine katılımına etkisini incelemektedir.

Anahtar Kelimeler

• Kovid-19
• izleme uygulamaları
• ödül mekanizması
• gönüllülük
• Beşli Sarmal İnovasyon Modeli

Reward Mechanisms in COVID-19 Tracking Apps and Its Impact on the Voluntary Participation of the Public in Sustainable Innovation Processes

Öz

The COVID-19 pandemic is the first pandemic after smartphones penetrated society globally. Consequently, there are not sufficient experiences and understanding of how to engage citizens in information and scientific processes that create public awareness and responsibilities according to scientific needs. For effective measures aiming to sustain the pandemic crisis, an efficient collaboration of academia, economy, culture-based, and media-based public and politics is crucial. With help of the Mobile Application Rating Scale (MARS) approach for assessment, COVID-19 tracking apps (CTAs) of different countries are analysed with help of a qualitative content analysis according to their reward mechanisms. The analysis includes correlation different rewards to voluntary participation. The MARS approach consists of engagement, functionality aesthetics and information quality. The protection of voluntariness is understood as the fundamental need for the ethical use of CTAs. Accordingly, patterns of voluntariness are examined in the context of legal, ethical privacy and security policies of selected CTAs. In this context, this paper will provide categories and criteria for CTA usage and its impact on citizen engagement in the Quintuple Helix collaboration process aiming to get insights into features and functionalities needed in CTAs and increased voluntary use of the public.

Anahtar Kelimeler

• COVID-19
• contact tracing
• reward mechanism
• voluntariness
• Quintuple Helix Innovation model

Kaynakça

1. Altmann, S., Milsom, L., Zillessen, H., Blasone, R., Gerdon, F., Bach, R., Kreuter, F., Nosenzo, D., Toussaert, S., & Abeler, J. (2020). Acceptability of app-based contact tracing for COVID-19: a cross-country survey study. JMIR mHealth and uHealth, 8(8), e19857. https://doi.org/10.2196/19857
2. Binnewies, C., & Groening, C. (2019). Achievement unlocked! The impact of digital achievements as a gamification element on motivation and performance. Computers in Human Behavior, 97, 151-166.
3. Bracken, C. C., Jeffres, L. W., & Neuendorf, K. A. (2004). Criticism or praise? The impact of verbal versus text-only computer feedback on social presence, intrinsic motivation, and recall. CyberPsychology& Behaviour, 7(3), 349–357.
4. Bygrave, L. A. (2002). Data protection law, approaching its rationale, logic and limits. The Hague/New York: Kluwer Law International.
5. Carayannis, E. G., Barth, T., & Campbell, D. F. J. (2012). The quintuple helix innovation model: global warming as a challenge and driver for innovation. Journal of Innovation and Entrepreneurship 1(2). https://doi. org/10.1186/2192-5372-1-2.
6. Csikszentmihalyi, M. (1990). Flow: The Psychology of Optimal Experience. New York: Harper & Row. Davalbhakta, S., Advani, S., Kumar, S., Agarwal, V., Bhoyar, S., Fedirko, E., Misra, D. P., Goel, A., Gupta, L., &
7. Agarwal, V. A. (2020). A systematic review of smartphone applications available for coronavirus disease 2019 (COVID19) and the assessment of their quality using the mobile application rating scale (MARS).” Journal of Medical Systems, 44(9).
8. Deci, E. L. (1972). Intrinsic motivation, extrinsic reinforcement, and inequity. Journal of Personality and Social Psychology, 22(1), 113–120.

9. Ertiö, T. P., Ruoppila, S., Thie,l S. K. (2016). Motivations to Use a Mobile Participation Application. In: Tambouris, E. et al. (eds) Electronic Participation. ePart 2016. Lecture Notes in Computer Science (Vol 9821). Cham: Springer. https://doi.org/10.1007/978-3-319-45074-2_11.
10. European Data Protection Board. (2021). Retrieved from https://edpb.europa.eu/sites/default/files/files/file1/ edpb_guidelines_20200420_contact_tracing_COVID_with_annex_en.pdf last access 25.11.2021
11. Gallego, A., Gaeta, E., Karinsalo, A., Ollikainen, V., Koskela, P., Peschke, L., Folkvord, F., Kaldoudi, E., Jämsä, T., Lupiáñez-Villanueva, F., Pecchia, L., & Fico, G. (2021). HCI challenges in designing pandemic trace applications for the effective knowledge transfer between science and society inside the quadruple helix collaboration. In Kurosu, M. (Ed.) Human-Computer Interaction. Interaction Techniques and Novel Applications (pp. 390-401). Berlin: Springer (ISBN: 978-3-030-78464-5).
12. Hsia, T.-L., Chiang, A.-J., Wu, J.-H, Teng, N.N.R., & Rubin, A. D. (2019). What drives e-health usage? Integrated institutional forces and top management perspectives. Computers in Human Behavior, 97, 260-270.
13. Hayat Eve Sığar (2020). HES kodu nedir. Retrieved from https://hayatevesigar.saglik.gov.tr/hes.html
14. Jelinek, A. (2020). Letter to the Head of Unit European Commission to Oliver Micol. Retrieved from https:// edpb.europa.eu/sites/default/files/files/file1/edpbletterecadvisecodiv-appguidance_final.pdf
15. Klar, R., & Lanzerath, D. (2020). The ethics of COVID-19 tracking apps – challenges and voluntariness. Research Ethics 16(3-4), 1-9.
16. Kiili, K., de Freitas, S., Arnab, S., & Lainema, T. (2012). The design principles for flow experience in educational games. Procedia Computer Science, 15, 78-91.
17. Koster, R. (2005). A theory of fun for game design. Scottsdale, AZ: Paraglyph Press.
18. Lopez, S. J., & Snyder, C. R. (2009) The Oxford Handbook of Positive Psychology (2nd ed.). Oxford, GB: Oxford University Press, 88-102.
19. Ming, L. C., Untong, N., Aliudin, N. A., Osili, N., Kifli, N., Tan, C. S., Goh, K. W., Ng, P. W., Al-Worafi, Y. M., Lee, K. S., & Goh, H. P. (2020). Mobile health apps on COVID-19 launched in the early days of the pandemic: Content analysis and review. JMIR mHealth and uHealth 8(9). https://doi.org/10.2196/19796.
20. Peng, W., Kanthawala, S., Yuan, S., & Hussain, S. A. (2016) A qualitative study of user perceptions of mobile health apps. BMC Public Health 16, 1158. https://doi.org/10.1186/s12889.016.3808-0
21. Peschke, L., Çataloğlu, B., Ceylan, N., Dionio, P., Dündar, I., Folkvord, F., Gaeta, E., Gallego Montejo, A., Geli, S., Gümüş Ağca, Y., Güneş Peschke, S., Yüksel, A. G., Gyftopoulos, S., Kaloudi, E., Kapusuzoğlu, A., Karinsalo, A., Koskela, P., Oğuz, Ö., Ollikainen, V., & Seyfafjehi. S. (2021) Review about good practices of quadruple helix collaboration processes and developments of COVID-19 tracking apps and platforms. Retrieved from https://www.pandevita.eu/images/D3-1_GoodPractices-CTAs.pdf
22. Robert Koch Institute (2021). Kennzahlen zur Corona-Warn-App. Retrieved from https://www.rki.de/DE/ Content/InfAZ/N/Neuartiges_Coronavirus/WarnApp/Archiv_Kennzahlen/Kennzahlen_18022021. pdf?__blob=publicationFile
23. Servick, K. (2020). COVID-19 contact tracing apps are coming to a phone near you. How will we know whether they work? Retrieved from https://www.sciencemag.org/news/2020/05/countries-around-world-arerolling- out-contact-tracing-apps-contain-coronavirus-how. doi:10.1126/science.abc9379.
24. Silvennoinen, J., Vogel, M., & Kujala, S. (2014). Experiencing visual usability and aesthetics in two mobile application contexts. Journal of Usability Studies 10(1), 46-62.
25. Theile, G. (2020). Teure Werbekampagne. Wie die App jetzt populär werden soll. Retrieved from https://www. faz.net/aktuell/wirtschaft/digitec/teure-werbekampagne-wie-die-corona-app-jetzt-populaer-werdensoll- 16817510.html.
26. Terhorst, Y., Philippi, P., Sander, L. B., Schultchen, D., Paganini, S., Bardus, M., Santo, K., Knitza, J., Carvalho Machado, G., Schoeppe, S., Bauereiß, N., Portenhauser, A., Domhardt, M., Walter, B., Krusche, M., Baumeister, H., & Messner, E. M. (2020). Validation of the mobile application rating scale (MARS). PLOS ONE, 15(11), e0241480.
27. Wang, H., & Sun, C.-T. (2011). Game Reward Systems: Gaming Experiences and Social Meanings. Proceedings of DiGRA 2011 Conference: Think Design Play. Retrieved from http://www.digra.org/wp-content/ uploads/digital-library/11310.20247.pdf