skip to main content
10.1145/3341162.3349311acmconferencesArticle/Chapter ViewAbstractPublication PagesubicompConference Proceedingsconference-collections
research-article

Social help: developing methods to support older adults in mobile privacy and security

Published:09 September 2019Publication History

ABSTRACT

Older people experience difficulties when managing their security and privacy in mobile environments. However, support from the older adult's social network, and especially from close-tie relations such as family and close friends, is known to be an effective source of help in coping with technological tasks. On the basis of this existing phenomena, I investigate how new methods can increase the availability of social support to older adults and enhance learning in tackling privacy and security challenges. I will develop and evaluate several technological interventions in the support process within social networks for older adults: finding methods that increase seekers' technology learning and methods that increase help availability and quality.

In my Ph.D., I suggest conducting three studies: the first study aims to analyze existing approaches and scenarios of social support to older adults. The initial results suggest that people have a significant willingness to help their older relatives (specifically, their parents), but the actual instances in which they do so is much rarer. We conclude that the potential for social help is far from being exploited. In the second study, I plan to explore social support as a system to increase older adults' self-efficacy and collective efficacy to overcome privacy and security problems. The final study will investigate physiological signals to identify when an older adult required help with mobile security and privacy issues. A successful outcome will be a theoretical model of social support, focused on the domain of privacy and security, and based on vulnerable populations such as older adults. From a practical standpoint, the thesis will offer and evaluate a set of technologies that enable and encourage social support for older adults on mobile platforms.

References

  1. Monica Anderson and Andrew Perrin. 2017. Tech adoption climbs among older adults. Pew Research Center May (2017), 1--22. Retrieved from http://www.pewinternet.org/2017/05/17/technology-use-among-seniors/Google ScholarGoogle Scholar
  2. A Bandura. 1982. Self-efficacy mechanism in human agency. Amer Psych 37, 2 (1982), 122--147.Google ScholarGoogle ScholarCross RefCross Ref
  3. Albert Bandura. 1977. Self-efficacy: Toward a unifying theory of behavioral change. Psychological Review 84, 191--215.Google ScholarGoogle ScholarCross RefCross Ref
  4. Albert Bandura. 1997. Self-efficacy: The Exercise of Control.Google ScholarGoogle Scholar
  5. Albert Bandura. 2000. Exercise of Human Agency Through Collective Efficacy. (2000), 75--78.Google ScholarGoogle Scholar
  6. Ana Correia De Barros, Roxanne Leitão, and Jorge Ribeiro. 2013. Design and evaluation of a mobile user interface for older adults: Navigation, interaction and visual design recommendations. Procedia Computer Science 27, Dsai 2013 (2013), 369--378.Google ScholarGoogle Scholar
  7. Elizabeth A. Beverly and Linda A. Wray. 2010. The role of collective efficacy in exercise adherence: A qualitative study of spousal support and Type 2 diabetes management. Health Education Research 25, 2 (2010), 211--223.Google ScholarGoogle ScholarCross RefCross Ref
  8. Linda Boise, Katherine Wild, Nora Mattek, Mary Ruhl, Hiroko H. Dodge, and Jeffrey Kaye. 2013. Willingness of older adults to share data and privacy concerns after exposure to unobtrusive in-home monitoring. 11, 3 (2013), 428--435.Google ScholarGoogle Scholar
  9. Ke Chen and Alan Hoi Shou Chan. 2013. Use or non-use of gerontechnology-A qualitative study. International Journal of Environmental Research and Public Health 10, 10 (2013), 4645--4666.Google ScholarGoogle ScholarCross RefCross Ref
  10. Aline Chevalier, Aurélie Dommes, and Jean Claude Marquié. 2015. Strategy and accuracy during information search on the Web: Effects of age and complexity of the search questions. Computers in Human Behavior 53, (2015), 305--315. Google ScholarGoogle ScholarDigital LibraryDigital Library
  11. Wen Hui Chou, Yu Ting Lai, and Kuang Hsia Liu. 2010. Decent digital social media for senior life: A practical design approach. Proceedings - 2010 3rd IEEE International Conference on Computer Science and Information Technology, ICCSIT 2010 4, (2010), 249--253.Google ScholarGoogle Scholar
  12. Regina Juchun Chu and Anita Zichun Chu. 2010. Multi-level analysis of peer support, Internet self-efficacy and e-learning outcomes - The contextual effects of collectivism and group potency. Computers and Education 55, 1 (2010), 145--154. Google ScholarGoogle ScholarDigital LibraryDigital Library
  13. Sara J. Czaja, Neil Charness, Arthur D. Fisk, Christopher Hertzog, Sankaran N. Nair, Wendy A. Rogers, and Joseph Sharit. 2006. Factors predicting the use of technology: Findings from the Center for Research and Education on Aging and Technology Enhancement (CREATE). Psychology and Aging 21, 2 (2006), 333--352.Google ScholarGoogle ScholarCross RefCross Ref
  14. L. Damodaran, C. W. Olphert, and J. Sandhu. 2014. Falling off the bandwagon? Exploring the challenges to sustained digital engagement by older people. Gerontology 60, 2 (2014), 163--173.Google ScholarGoogle ScholarCross RefCross Ref
  15. Sauvik Das, Tiffany Hyun-Jin Kim, Laura A Dabbish, and Jason I Hong. 2014. The Effect of Social Influence on Security Sensitivity. SOUPS '14: Proceedings of the Tenth Symposium On Usable Privacy and Security (2014), 143--157. Google ScholarGoogle ScholarDigital LibraryDigital Library
  16. George Demiris, Marilyn J. Rantz, Myra A. Aud, Karen D. Marek, Harry W. Tyrer, Marjorie Skubic, and Ali A. Hussam. 2004. Older adults attitudes towards and perceptions of 'smart home technologies: A pilot study. Informatics for Health and Social Care 29, 2 (2004), 87--94.Google ScholarGoogle Scholar
  17. Evelina Dimopoulou. 2012. Self Efficacy and Collective Efficacy Beliefs of Teachers for Children with Autism. Literacy Information and Computer Education Journal (LICEJ) 3, 1 (2012), 509--520.Google ScholarGoogle Scholar
  18. Paul Andor Farkas. 2010. Senior Social Platform - An application aimed to reduce the social and digital isolation of seniors. REAL CORP 2010: Cities for everyone. Liveable, Healthy, Prosperous May (2010), 1247--1252.Google ScholarGoogle Scholar
  19. Aurora Harley. 2014. Instructional Overlays and Coach Marks for Mobile Apps. Nielsen Norman Group,. Retrieved October 10, 2018 from https://www.nngroup.com/articles/mobile-instructional-overlay/Google ScholarGoogle Scholar
  20. Chris Hoofnagle, Jennifer King, Su Li, and Joseph Turow. 2010. How Different are Young Adults from Older Adults When it Comes to Information Privacy Attitudes and Policies? New York 4, 19 (2010), 10.Google ScholarGoogle Scholar
  21. Qatrunnada Ismail, Tousif Ahmed, Apu Kapadia, and Michael K. Reiter. 2015. Crowdsourced Exploration of Security Configurations. Proceedings of the 33rd Annual ACM Conference on Human Factors in Computing Systems - CHI '15 (2015), 467--476. Google ScholarGoogle ScholarDigital LibraryDigital Library
  22. Alexis Kuerbis, Adina Mulliken, Frederick Muench, Alison A. Moore, and Daniel Gardner. 2017. Older adults and mobile technology: Factors that enhance and inhibit utilization in the context of behavioral health. Mental Health and Addiction Research 2, 2 (2017).Google ScholarGoogle Scholar
  23. Jiunn Woei Lian and David C. Yen. 2014. Online shopping drivers and barriers for older adults: Age and gender differences. Computers in Human Behavior 37, (2014), 133--143. Google ScholarGoogle ScholarDigital LibraryDigital Library
  24. Jialiu Lin, Norman M Sadeh, Shahriyar Amini, Janne Lindqvist, Jason I Hong, and Joy Zhang. 2012. Expectation and purpose: understanding users' mental models of mobile app privacy through crowdsourcing. The 2012 {ACM} Conference on Ubiquitous Computing, Ubicomp '12, Pittsburgh, PA, USA, September 5--8, 2012 (2012), 501--510. Google ScholarGoogle ScholarDigital LibraryDigital Library
  25. Andrew R. McNeill, Lynne Coventry, Jake Pywell, and Pam Briggs. 2017. Privacy Considerations when Designing Social Network Systems to Support Successful Ageing. Proceedings of the 2017 CHI Conference on Human Factors in Computing Systems - CHI '17 (2017), 6425--6437. Google ScholarGoogle ScholarDigital LibraryDigital Library
  26. T Mendel and E Toch. 2017. Susceptibility to social influence of privacy behaviors: Peer versus authoritative sources. Proceedings of the 2017 ACM Conference on Computer Supported Cooperative Work and Social Computing (2017), 581--593. Google ScholarGoogle ScholarDigital LibraryDigital Library
  27. Tracy L Mitzner, Julie B Boron, Cara Bailey Fausset, Anne E Adams, Sara J Czaja, Katinka Dijkstra, Arthur D Fisk, Wendy A Rogers, and Joseph Sharit. 2010. Older Adults Talk Technology: Technology Usage and Attitudes. Computers in Human Behavior 26, 6 (2010), 1710--1721. Google ScholarGoogle ScholarDigital LibraryDigital Library
  28. Tobias Nef, Raluca L. Ganea, René M. Müri, and Urs P. Mosimann. 2013. Social networking sites and older users - A systematic review. International Psychogeriatrics 25, 7 (2013), 1041--1053.Google ScholarGoogle ScholarCross RefCross Ref
  29. Tom Page. 2014. Touchscreen mobile devices and older adults: a usability study. International Journal of Human Factors and Ergonomics 3, 1 (2014), 65.Google ScholarGoogle ScholarCross RefCross Ref
  30. Samantha J Parker, Sonal Jessel, Joshua E Richardson, and M Cary Reid. 2013. Older adults are mobile too! Identifying the barriers and facilitators to older adults' use of mHealth for pain management. BMC geriatrics 13, (2013), 43.Google ScholarGoogle Scholar
  31. H.a Pensas, T.a Kivimäki, A.-M.a Vainio, S.b Konakas, S.b Costicoglou, P.c Kölndorfer, K.a Summanen, H.a Moisio, and J.a Vanhala. 2013. Building a client-server social network application for elders and safety net. Proceedings of the 17th International Academic MindTrek Conference: "Making Sense of Converging Media", MindTrek 2013 (2013), 310--312. Google ScholarGoogle ScholarDigital LibraryDigital Library
  32. E.S. Poole, M. Chetty, T. Morgan, R.E. Grinter, and W.K. Edwards. 2009. Computer help at home: Methods and motivations for informal technical support. Conference on Human Factors in Computing Systems - Proceedings (2009), 739--748. Google ScholarGoogle ScholarDigital LibraryDigital Library
  33. Bahman Rashidi, Carol Fung, and Tam Vu. 2016. Android fine-grained permission control system with real-time expert recommendations. Pervasive and Mobile Computing 32, (2016), 62--77.Google ScholarGoogle ScholarCross RefCross Ref
  34. Elissa M Redmiles, Sean Kross, and Michelle L Mazurek. 2016. How I Learned to Be Secure: A Census-Representative Survey of Security Advice Sources and Behavior. Proceedings of the ACM SIGSAC Conference on Computer and Communications Security (CCS) (2016), 666--677. Google ScholarGoogle ScholarDigital LibraryDigital Library
  35. Elissa M Redmiles, Amelia R. Malone, and Michelle L. Mazurek. 2016. I Think They're Trying to Tell Me Something: Advice Sources and Selection for Digital Security. Proceedings - 2016 IEEE Symposium on Security and Privacy, SP 2016 (2016), 272--288.Google ScholarGoogle Scholar
  36. Yekta Said, Bert Arnrich, and Cem Ersoy. 2019. Stress detection in daily life scenarios using smart phones and wearable sensors: A survey. Journal of Biomedical Informatics 92, August 2018 (2019), 103139.Google ScholarGoogle Scholar
  37. R Sampson, S Raudenbush, and F Earls. 1997. Neighborhoods and violent crime: a multilevel study of collective efficacy. Science (New York, NY) 277, 5328 (1997), 918--924.Google ScholarGoogle Scholar
  38. Eran Toch. 2014. Crowdsourcing privacy preferences in context-aware applications. Personal and Ubiquitous Computing 18, 1 (2014), 129--141. Google ScholarGoogle ScholarDigital LibraryDigital Library
  39. Population Division U.S. Census Bureau. 2015. Annual Estimates of the Resident Population for Selected Age Groups by Sex for the United States, States, Counties, and Puerto Rico Commonwealth and Municipios: April 1, 2010 to July 1, 2014. Retrieved from https://factfinder.census.gov/faces/tableservices/jsf/pages/productview.xhtml?src=bkmkGoogle ScholarGoogle Scholar
  40. Bo Xie and Julie M. Bugg. 2009. Public library computer training for older adults to access high-quality Internet health information. Library and Information Science Research 31, 3 (2009), 155--162.Google ScholarGoogle ScholarCross RefCross Ref
  41. Bo Xie, Ivan Watkins, Jen Golbeck, and Man Huang. 2012. Understanding and Changing Older Adults' Perceptions and Learning of Social Media. Educational Gerontology 38, 4 (2012), 282--296.Google ScholarGoogle ScholarCross RefCross Ref
  42. Jiahuan Zheng, Xin Peng, Jiacheng Yang, Huaqian Cai, Gang Huang, Ying Zhang, and Wenyun Zhao. 2017. CollaDroid: Automatic Augmentation of Android Application with Lightweight Interactive Collaboration. Proceedings of the 2017 ACM Conference on Computer Supported Cooperative Work and Social Computing (2017), 2462--2474. Google ScholarGoogle ScholarDigital LibraryDigital Library
  43. Jia Zhou, Pei Luen Patrick Rau, and Gavriel Salvendy. 2014. Age-related difference in the use of mobile phones. Universal Access in the Information Society 13, 4 (2014), 401--413. Google ScholarGoogle ScholarDigital LibraryDigital Library

Index Terms

  1. Social help: developing methods to support older adults in mobile privacy and security

          Recommendations

          Comments

          Login options

          Check if you have access through your login credentials or your institution to get full access on this article.

          Sign in
          • Published in

            cover image ACM Conferences
            UbiComp/ISWC '19 Adjunct: Adjunct Proceedings of the 2019 ACM International Joint Conference on Pervasive and Ubiquitous Computing and Proceedings of the 2019 ACM International Symposium on Wearable Computers
            September 2019
            1234 pages
            ISBN:9781450368698
            DOI:10.1145/3341162

            Copyright © 2019 ACM

            Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

            Publisher

            Association for Computing Machinery

            New York, NY, United States

            Publication History

            • Published: 9 September 2019

            Permissions

            Request permissions about this article.

            Request Permissions

            Check for updates

            Qualifiers

            • research-article

            Acceptance Rates

            Overall Acceptance Rate764of2,912submissions,26%

            Upcoming Conference

          PDF Format

          View or Download as a PDF file.

          PDF

          eReader

          View online with eReader.

          eReader