Navigating Privacy and Data Safety: The Implications of Increased Online Activity among Older Adults Post-COVID-19 Induced Isolation
Abstract
:1. Introduction
2. Background
2.1. Information and Communication Technology (ICT) Adoption among Older Adults
2.2. Online Privacy Risks for Older Adults and the Privacy–Security Trade-Off
2.3. Unexplored Privacy Risks of Quarantine Technology Initiates (QTIs)
2.4. Online Risks and Stakes of Privacy and Data Safety Violations
2.5. Fraud Trends among Older Adults: An Analysis Based on Federal Trade Commission (FTC) Data
2.6. Types of Privacy and Data Safety Violations Most Relevant to Older Adults
2.6.1. Romance Scams
2.6.2. Technical Support Impersonation Scams
2.6.3. Friends and Family Impersonation Scams
2.6.4. Business Impersonation Scams
2.6.5. Prize and Sweepstakes Scams
3. Methodology
3.1. Literature Search
3.2. Expert Consultation
4. Discussion
4.1. Expert Consultation and the Implications of Technology Adoption for Older Adults
4.2. COVID-19: A Catalyst for Technology Adoption and the Associated Risks in Older Adults
4.3. Characterization of Quarantine Technology Initiates and Their Online Privacy and Data Safety Risk Profiles
4.4. Strategies to Mitigate Privacy and Data Safety Risks among Older Adults in the Context of COVID-19
4.5. Reflections and Contributions
4.6. Limitations
5. Future Directions
Author Contributions
Funding
Data Availability Statement
Acknowledgments
Conflicts of Interest
References
- Greenwood-Hickman, M.A.; Dahlquist, J.; Cooper, J.; Holden, E.; McClure, J.B.; Mettert, K.D.; Perry, S.R.; Rosenberg, D.E. “They’re going to zoom it”: A qualitative investigation of impacts and coping strategies during the COVID-19 pandemic among older adults. Front. Public Health 2021, 9, 679976. [Google Scholar] [CrossRef]
- Xie, B.; Charness, N.; Fingerman, K.; Kaye, J.; Kim, M.T.; Khurshid, A. When going digital becomes a necessity: Ensuring older adults’ needs for information, services, and social inclusion during COVID-19. J. Aging Soc. Policy 2020, 32, 460–470. [Google Scholar] [CrossRef]
- Haase, K.R.; Cosco, T.; Kervin, L.; Riadi, I.; O’Connell, M.E. Older Adults’ experiences of technology use for socialization during the COVID-19 pandemic: A regionally representative cross-sectional survey. JMIR Aging 2021, 4, e28010. [Google Scholar] [CrossRef]
- Sen, K.; Prybutok, G.; Prybutok, V. The use of digital technology for social wellbeing reduces social isolation in older adults: A systematic review. SSM Popul. Health 2022, 17, 101020. [Google Scholar] [CrossRef] [PubMed]
- Smith, M.L.; Steinman, L.E.; Casey, E.A. Combatting social isolation among older adults in a time of physical distancing: The COVID-19 social connectivity paradox. Front. Public Health 2020, 8, 403. [Google Scholar] [CrossRef] [PubMed]
- Wahid, S.D.M.; Buja, A.G.; Jono, M.N.H.H.; Aziz, A.A. Assessing the influential factors of cybersecurity awareness in Malaysia during the pandemic outbreak: A structural equation modeling. IJATEE 2021, 8, 73–81. [Google Scholar] [CrossRef]
- Teaster, P.B.; Roberto, K.A.; Savla, J.; Du, C.; Du, Z.; Atkinson, E.; Shealy, E.C.; Beach, S.; Charness, N.; Lichtenberg, P.A. Financial fraud of older adults during the early months of the COVID-19 pandemic. Gerontologist 2022, gnac188. [Google Scholar] [CrossRef]
- Zanchetta, C.; Schiff, H.; Novo, C.; Cruz, S.; Vaz de Carvalho, C. Generational inclusion: Getting older adults ready to own safe online identities. Educ. Sci. 2022, 12, 715. [Google Scholar] [CrossRef]
- FBI. 2022 Internet Crime Report; FBI IC3 Internet Crime Complaint Center: Washington, DC, USA, 2023.
- FTC. Consumer Sentinel Network Data Book 2022; Federal Trade Commission: Washington, DC, USA, 2023.
- Nolte, J.; Hanoch, Y.; Wood, S.; Hengerer, D. Susceptibility to COVID-19 scams: The roles of age, individual difference measures, and scam-related perceptions. Front. Psychol. 2021, 12, 789883. [Google Scholar] [CrossRef]
- Agarwal, S.; Chomsisengphet, S.; Liu, C.; Souleles, N.S. Do consumers choose the right credit contracts? Rev. Corp. Financ. Stud. 2015, 4, 239–257. [Google Scholar] [CrossRef] [Green Version]
- Adams, W.; Einav, L.; Levin, J. Liquidity constraints and imperfect information in subprime lending. Am. Econ. Rev. 2009, 99, 49–84. [Google Scholar] [CrossRef] [Green Version]
- Niu, B.; Ren, J.; Li, X. Credit scoring using machine learning by combing social network information: Evidence from peer-to-peer lending. Information 2019, 10, 397. [Google Scholar] [CrossRef] [Green Version]
- Orlova, E.V. Decision-making techniques for credit resource management using machine learning and optimization. Information 2020, 11, 144. [Google Scholar] [CrossRef] [Green Version]
- Ładyżyński, P.; Żbikowski, K.; Gawrysiak, P. Direct Marketing campaigns in retail banking with the use of deep learning and random forests. Expert Syst. Appl. 2019, 134, 28–35. [Google Scholar] [CrossRef]
- Anderson, M.; Perrin, A. Technology Adoption Climbs among Older Adults; Pew Research Center: Washington, DC, USA, 2017. [Google Scholar]
- Grimes, G.A.; Hough, M.G.; Mazur, E.; Signorella, M.L. Older adults’ knowledge of internet hazards. Educ. Gerontol. 2010, 36, 173–192. [Google Scholar] [CrossRef]
- Perrin, A.; Atske, S. 7% of Americans Don’t Use the Internet. Who Are They? Pew Research Center: Washington, DC, USA, 2021. [Google Scholar]
- Pew Research Center Internet/Broadband Fact Sheet; Pew Research Center: Washington, DC, USA, 2021.
- Choi, N.G.; Hammaker, S.; DiNitto, D.M.; Marti, C.N. COVID-19 and loneliness among older adults: Associations with mode of family/friend contacts and social participation. Clin. Gerontol. 2022, 45, 390–402. [Google Scholar] [CrossRef]
- Ray, H. Towards Understanding Usable Privacy Concerns Among Older Adults. Ph.D. Thesis, University of Maryland, College Park, MD, USA, 2022. [Google Scholar]
- FBI. 2019 Internet Crime Report; FBI IC3 Internet Crime Complaint Center: Washington, DC, USA, 2020.
- Mortenson, W.B.; Sixsmith, A.; Woolrych, R. The power(s) of observation: Theoretical perspectives on surveillance technologies and older people. Ageing Soc. 2015, 35, 512–530. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Oh, S.S.; Kim, K.-A.; Kim, M.; Oh, J.; Chu, S.H.; Choi, J. Measurement of digital literacy among older adults: Systematic review. J. Med. Internet Res. 2021, 23, e26145. [Google Scholar] [CrossRef]
- Sheahan, J.; Hjorth, L.; Figueiredo, B.; Martin, D.M.; Reid, M.; Aleti, T.; Buschgens, M. Co-creating ICT risk strategies with older Australians: A workshop model. IJERPH 2022, 20, 52. [Google Scholar] [CrossRef]
- Buil-Gil, D.; Zeng, Y. Meeting you was a fake: Investigating the increase in romance fraud during COVID-19. JFC 2022, 29, 460–475. [Google Scholar] [CrossRef]
- Parti, K. “Elder Scam” risk profiles: Individual and situational factors of younger and older age groups’ fraud victimization. Int. J. Cybersecur. Intell. Cybercrime 2022, 5, 20–40. [Google Scholar]
- Sugunaraj, N.; Ramchandra, A.R.; Ranganathan, P. Cyber fraud economics, scam types, and potential measures to protect U.S. seniors: A short review. In Proceedings of the 2022 IEEE International Conference on Electro Information Technology (eIT), Mankato, MN, USA, 19–21 May 2022; IEEE: Manhattan, NY, USA, 2022; pp. 623–627. [Google Scholar]
- Phibbs, C.L.; Rahman, S.S.M. A synopsis of “The impact of motivation, price, and habit on intention to use IoT-enabled technology: A correlational study”. JCP 2022, 2, 662–699. [Google Scholar] [CrossRef]
- Bennett Gayle, D.; Yuan, X.; Knight, T. The coronavirus pandemic: Accessible Technology for education, employment, and livelihoods. Assist. Technol. 2021, 1–8. [Google Scholar] [CrossRef] [PubMed]
- Choudrie, J.; Banerjee, S.; Kotecha, K.; Walambe, R.; Karende, H.; Ameta, J. Machine learning techniques and older adults processing of online information and misinformation: A Covid 19 study. Comput. Hum. Behav. 2021, 119, 106716. [Google Scholar] [CrossRef]
- Diehl, C.; Tavares, R.; Abreu, T.; Almeida, A.M.P.; Silva, T.E.; Santinha, G.; Rocha, N.P.; Seidel, K.; MacLachlan, M.; Silva, A.G.; et al. Perceptions on extending the use of technology after the COVID-19 pandemic resolves: A Qualitative study with older adults. Int. J. Environ. Res. Public Health 2022, 19, 14152. [Google Scholar] [CrossRef] [PubMed]
- Andreou, A.; Dhand, A.; Vassilev, I.; Griffiths, C.; Panzarasa, P.; De Simoni, A. Understanding online and offline social networks in illness management of older patients with asthma and chronic obstructive pulmonary disease: Mixed methods study using quantitative social network assessment and qualitative analysis. JMIR Form. Res. 2022, 6, e35244. [Google Scholar] [CrossRef]
- Zhao, Y.C.; Zhao, M.; Song, S. Online health information seeking behaviors among older adults: Systematic scoping review. J. Med. Internet Res. 2022, 24, e34790. [Google Scholar] [CrossRef]
- Burnes, D.; Henderson, C.R.; Sheppard, C.; Zhao, R.; Pillemer, K.; Lachs, M.S. Prevalence of financial fraud and scams among older adults in the United States: A systematic review and meta-analysis. Am. J. Public Health 2017, 107, e13–e21. [Google Scholar] [CrossRef]
- Consumer Sentinel Network. Available online: https://www.ftc.gov/enforcement/consumer-sentinel-network (accessed on 1 April 2023).
- 2022 Age and Fraud Data. Available online: https://public.tableau.com/app/profile/federal.trade.commission/viz/AgeandFraud/Infographic (accessed on 3 April 2023).
- Casey, R.P.; Scott, T. Frauds, Scams and COVID–19: How Con Artists Have Targeted Older Americans During the Pandemic; Hearing, 117th U.S. Senate; US Senate Special Committee on Aging: Washington, DC, USA, 2021.
- Whitty, M.T.; Buchanan, T. The online romance scam: A serious cybercrime. Cyberpsychol. Behav. Soc. Netw. 2012, 15, 181–183. [Google Scholar] [CrossRef] [Green Version]
- Coluccia, A.; Pozza, A.; Ferretti, F.; Carabellese, F.; Masti, A.; Gualtieri, G. Online romance scams: Relational dynamics and psychological characteristics of the victims and scammers. A scoping review. CPEMH 2020, 16, 24–35. [Google Scholar] [CrossRef] [PubMed]
- Okereafor, K.; Adebola, O. Tackling the cybersecurity impacts of the coronavirus outbreak as a challenge to internet safety. SSRN Electron. J. 2020, 8, 1–14. [Google Scholar]
- FBI. 2021 Elder Fraud Report; FBI IC3 Internet Crime Complaint Center: Washington, DC, USA, 2021.
- Miramirkhani, N.; Starov, O.; Nikiforakis, N. Dial one for scam: A large-scale analysis of technical support scams. In Proceedings of the 2017 Network and Distributed System Security Symposium, San Diego, CA, USA, 26 February–1 March 2017. [Google Scholar]
- Shao, J.; Zhang, Q.; Ren, Y.; Li, X.; Lin, T. Why are older adults victims of fraud? Current knowledge and prospects regarding older adults’ vulnerability to fraud. J. Elder Abus. Negl. 2019, 31, 225–243. [Google Scholar] [CrossRef] [PubMed]
- Schneider, A. How could they know that? Behind the data that facilitates scams against vulnerable Americans. Va. J. Law Technol. 2015, 19, 225–243. [Google Scholar]
- Beals, M.; Deevy, M.; Deem, D. Framework for a Taxonomy of Fraud; Stanford Center on Longevity: Stanford, CA, USA, 2015. [Google Scholar]
- Page, M.J.; McKenzie, J.E.; Bossuyt, P.M.; Boutron, I.; Hoffmann, T.C.; Mulrow, C.D.; Shamseer, L.; Tetzlaff, J.M.; Akl, E.A.; Brennan, S.E.; et al. The PRISMA 2020 statement: An updated guideline for reporting systematic reviews. Syst. Rev. 2021, 10, 89. [Google Scholar] [CrossRef]
- Brown, C.; Aksan, N.; Muir, A.J. MELD-Na accurately predicts 6-month mortality in patients with decompensated cirrhosis: Potential trigger for hospice referral. J. Clin. Gastroenterol. 2022, 56, 902. [Google Scholar] [CrossRef]
- Lee, S.B.; Oh, J.H.; Park, J.H.; Choi, S.P.; Wee, J.H. Differences in youngest-old, middle-old, and oldest-old patients who visit the emergency department. Clin. Exp. Emerg. Med. 2018, 5, 249–255. [Google Scholar] [CrossRef] [PubMed]
- Moore, R.C.; Hancock, J.T. Older adults, social technologies, and the coronavirus pandemic: Challenges, strengths, and strategies for support. Soc. Media Soc. 2020, 6, 205630512094816. [Google Scholar] [CrossRef]
- Bakshi, T.; Bhattacharyya, A. Socially distanced or socially connected? Well-being through ICT usage among the Indian elderly during COVID-19. Millenn. Asia 2021, 12, 190–208. [Google Scholar] [CrossRef]
- Xie, B.; He, D.; Mercer, T.; Wang, Y.; Wu, D.; Fleischmann, K.R.; Zhang, Y.; Yoder, L.H.; Stephens, K.K.; Mackert, M.; et al. Global health crises are also information crises: A call to action. J. Assoc. Inf. Sci. Technol. 2020, 71, 1419–1423. [Google Scholar] [CrossRef] [Green Version]
- Li, W.; Ornstein, K.A.; Li, Y.; Liu, B. Barriers to learning a new technology to go online among older adults during the COVID-19 pandemic. J. Am. Geriatr. Soc. 2021, 69, 3051–3057. [Google Scholar] [CrossRef] [PubMed]
- Seifert, A. The digital exclusion of older adults during the COVID-19 pandemic. J. Gerontol. Soc. Work 2020, 63, 674–676. [Google Scholar] [CrossRef] [PubMed]
- Frik, A.; Nurgalieva, L.; Bernd, J.; Lee, J.S.; Schaub, F.; Egelman, S. Privacy and security threat models and mitigation strategies of older adults. In Proceedings of the Fifteenth Symposium on Usable Privacy and Security, Santa Clara, CA, USA, 12–13 August 2019. [Google Scholar]
- Anderson, M.; Perrin, A.; Kumar, M. 10% of Americans Don’t Use the Internet. Who Are They? Pew Research Center: Washington, DC, USA, 2019; p. 4. [Google Scholar]
- Javelin. Identity Fraud in Three Acts: A Consumer Guide; AARP: Washington, DC, USA, 2020. [Google Scholar]
- AARP Identity Theft. Available online: https://www.aarp.org/money/scams-fraud/info-2019/identity-theft.html (accessed on 6 April 2023).
- COVID-19 Brings New Scams for Senior Citizens; Nebraska Department of Health and Human Services: Lincoln, NE, USA, 2021.
- Newlands, G.; Lutz, C.; Tamò-Larrieux, A.; Villaronga, E.F.; Harasgama, R.; Scheitlin, G. Innovation under pressure: Implications for data privacy during the Covid-19 pandemic. Big Data Soc. 2020, 7, 205395172097668. [Google Scholar] [CrossRef]
- Lim, H.A.; Lee, J.S.W.; Lim, M.H.; Teo, L.P.Z.; Sin, N.S.W.; Lim, R.W.; Chua, S.M.; Yeo, J.Q.; Ngiam, N.H.W.; Tey, A.J.-Y.; et al. Bridging connectivity issues in digital access and literacy: Reflections on empowering vulnerable older adults in Singapore. JMIR Aging 2022, 5, e34764. [Google Scholar] [CrossRef]
- Saha, P.; Kiran, K.B. What insisted baby boomers adopt unified payment interface as a payment mechanism? An exploration of drivers of behavioral intention. JAMR 2022, 19, 792–809. [Google Scholar] [CrossRef]
- Casanova, G.; Abbondanza, S.; Rolandi, E.; Vaccaro, R.; Pettinato, L.; Colombo, M.; Guaita, A. New Older users’ attitudes toward social networking sites and loneliness: The case of the oldest-old residents in a small Italian city. Soc. Media Soc. 2021, 7, 205630512110529. [Google Scholar] [CrossRef]
- Castillo-Villar, F.R.; Castillo-Villar, R.G. Mobile banking affordances and constraints by the elderly. MIP 2023, 41, 124–137. [Google Scholar] [CrossRef]
- Cham, T.-H.; Cheah, J.-H.; Cheng, B.-L.; Lim, X.-J. I am too old for this! Barriers contributing to the non-adoption of mobile payment. IJBM 2022, 40, 1017–1050. [Google Scholar] [CrossRef]
- Recupero, P.R. Mitigating the risk of digital financial exploitation. J. Am. Acad. Psychiatry Law 2023, 51, 181–189. [Google Scholar] [PubMed]
- Szathmari, G. Are Technical Support Scams Getting More Advanced? Charles Sturt University: Sydney, Australia, 2022. [Google Scholar]
- Wong, F.H.C.; Leung, D.K.Y.; Wong, E.L.Y.; Liu, T.; Lu, S.; Chan, O.F.; Wong, G.H.Y.; Lum, T.Y.S. The moderating role of community capacity for age-friendly communication in mitigating anxiety of older adults during the COVID-19 infodemic: Cross-sectional survey. JMIR Infodemiol. 2022, 2, e33029. [Google Scholar] [CrossRef] [PubMed]
- Wild, K.; Marcoe, J.; Mattek, N.; Sharma, N.; Loewy, E.; Tischler, H.; Kaye, J.; Karlawish, J. Online monitoring of financial capacity in older adults: Feasibility and initial findings. Alzheimer’s Dementia Diagn. Assess. Dis. Monit. 2022, 14, e12282. [Google Scholar] [CrossRef]
- Bernstein, J.P.K.; Dorociak, K.E.; Mattek, N.; Leese, M.; Beattie, Z.T.; Kaye, J.A.; Hughes, A. Passively-measured routine home computer activity and application use can detect mild cognitive impairment and correlate with important cognitive functions in older adulthood. JAD 2021, 81, 1053–1064. [Google Scholar] [CrossRef]
- Baik, J.S. Data privacy against innovation or against discrimination? The case of the California consumer privacy act (CCPA). Telemat. Inform. 2020, 52, 101431. [Google Scholar] [CrossRef]
- Fredriksson, M. Information commons between enclosure and exposure: Regulating piracy and privacy in the EU. Int. J. Commons 2020, 14, 494–507. [Google Scholar] [CrossRef]
- Prasad, A.; Immel, M.; Fisher, A.; Hale, T.M.; Jethwani, K.; Centi, A.J.; Linscott, B.; Boerner, K. Understanding the role of virtual outreach and programming for LGBT individuals in later life. J. Gerontol. Soc. Work. 2022, 65, 766–781. [Google Scholar] [CrossRef] [PubMed]
- Casselden, B. Not like riding a bike: How public libraries facilitate older people’s digital inclusion during the COVID-19 pandemic. J. Librariansh. Inf. Sci. 2022, 096100062211018. [Google Scholar] [CrossRef]
Concept | Boolean Relationship 1 | Terms |
---|---|---|
Older adults | AND | “older adult*” OR “older pe*” OR “old age” OR “seniors” OR “senior citizen*” OR “elderly” |
Data privacy and safety | AND | “priv*” OR “online safety” OR “cybersecurity” OR “data protection” OR “digital literacy” OR “fraud*” OR “scam*” OR “theft*” OR “financial abuse” |
Online activity | AND | “internet” OR “online” OR “digital” OR “social media” OR “ICT” OR “information and communications technology” |
COVID-19 pandemic | AND | “COVID*” OR “coronavirus*” OR “SARS-CoV-2” OR “2019-nCoV” OR “pandemic” |
Expertise | Older Adult Cohort 1 | Technology Adoption Implications of COVID-19 |
---|---|---|
Senior living (placement agency owner) | Independent living and assisted living residents; community-resident older adults considering senior living (middle-old, oldest-old). | Community-resident older adults introduced to technology by family or aging-in-place organizations, such as senior centers. Best positioned for online privacy and safety education. |
Medical home health (regional director) | Patients recovering following injury or illness (middle-old, oldest-old). | Quarantine isolation compounded by injury or illness-driven isolation, increasing incentives to adopt ICT. Physical injury or illness frequently exacerbates cognitive challenges. |
Hospice (program and operations director) | Last 6 months of life (oldest-old) [49]. | Greatest support required for adoption/use of new technology; lowest awareness of online safety. |
ICT Adoption and Use Topics | Description |
---|---|
Adoption pressures | Influence of quarantine isolation on ICT adoption. |
Adoption barriers | Factors driving or exacerbating adoption resistance by older adults. |
Risks | Most common and highest cost types of privacy and data safety risks for older adults. |
Vulnerabilities | Factors driving or exacerbating privacy and data safety violations against older adults. |
Solutions | Approaches or systems mitigating the likelihood or cost of privacy and data safety violations against older adults. |
Characterization of Privacy and Data Safety Risks | Number of Included Articles | Percentage of Included Articles |
---|---|---|
Risk profile of older adults distinguished from younger persons | 21 | 100% |
QTIs not recognized | 13 | 57.1% |
QTIs recognized | 9 | 42.9% |
Risk profile of QTIs distinguished from other older adult ICT adoptees | 0 | 0.0% |
Disclaimer/Publisher’s Note: The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of MDPI and/or the editor(s). MDPI and/or the editor(s) disclaim responsibility for any injury to people or property resulting from any ideas, methods, instructions or products referred to in the content. |
© 2023 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
Share and Cite
Alagood, J.; Prybutok, G.; Prybutok, V.R. Navigating Privacy and Data Safety: The Implications of Increased Online Activity among Older Adults Post-COVID-19 Induced Isolation. Information 2023, 14, 346. https://doi.org/10.3390/info14060346
Alagood J, Prybutok G, Prybutok VR. Navigating Privacy and Data Safety: The Implications of Increased Online Activity among Older Adults Post-COVID-19 Induced Isolation. Information. 2023; 14(6):346. https://doi.org/10.3390/info14060346
Chicago/Turabian StyleAlagood, John, Gayle Prybutok, and Victor R. Prybutok. 2023. "Navigating Privacy and Data Safety: The Implications of Increased Online Activity among Older Adults Post-COVID-19 Induced Isolation" Information 14, no. 6: 346. https://doi.org/10.3390/info14060346
APA StyleAlagood, J., Prybutok, G., & Prybutok, V. R. (2023). Navigating Privacy and Data Safety: The Implications of Increased Online Activity among Older Adults Post-COVID-19 Induced Isolation. Information, 14(6), 346. https://doi.org/10.3390/info14060346