Advertisement

Smartphone Usage Diversity among Older People

  • Andrea RosalesEmail author
  • Mireia Fernández-Ardèvol
Chapter
Part of the Human–Computer Interaction Series book series (HCIS)

Abstract

Older people are a minority in digital media, in terms of both access and use. While the divide in access has decreased, this is not the case with the divide in use. In this chapter, we go deeper into the divide in use, by studying the diversity of smartphone usage among older people. We have used three complementary perspectives: tracked use, reported use, and reflections on use. According to our study, between 2014 and 2016 the divide in smartphone use increased between younger individuals and older people. Moreover, older smartphone users in Spain are a diverse user group, which includes basic, proficient and advanced users. Proficient users are the most common group. Basic users are often new users with little experience of digital technologies who usually achieve their communication goals by other means. We used a triangulation of qualitative and quantitative methods. This approach allowed us to show the limited and at the same time diverse use of smartphones by older people. These results question the stereotypes that only associate older people with a limited use of digital technologies. They also help to raise awareness of the importance of taking the particular characteristics of older proficient smartphone users into account in the design of intelligent systems, in order to fight structural ageism.

Notes

Acknowledgements

We are indebted to all the participants in our study. This research project has been partially funded by the Spanish Ministry of Economy and Competitiveness (FJCI-2015-24120) and the Social Sciences and Humanities Research Council of Canada through the Ageing + Communication + Technologies project (895-2013-1018).

References

  1. Alvarez-Lozano J, Osmani V, Mayora O et al (2014) Tell me your apps and I will tell you your mood: correlation of apps usage with bipolar disorder state. In: Proceedings of the international conference on pervasive technologies related to assistive environments (Petra 2014). Association for Computing Machinery (ACM), pp 1–7Google Scholar
  2. Banovic N, Brant C, Mankoff J et al (2014) Proactive tasks: the short of mobile device use sessions. In: Proceedings of the SIGCHI conference on human-computer interaction with mobile devices and services (MobileHCI 2014). ACM, pp 243–252Google Scholar
  3. Böhmer M, Hecht B, Schöning J et al (2011) Falling asleep with Angry Birds, Facebook and Kindle: a large scale study on mobile application usage. In: Proceedings of the international conference on human computer interaction with mobile devices and services (MobileHCI 2011). ACM, Nueva York, NY, pp 47–56Google Scholar
  4. Bonchi F, Hajian S, Mishra B, Ramazzotti D (2017) Exposing the probabilistic causal structure of discrimination. Int J Data Sci Anal 3:1–21.  https://doi.org/10.1007/s41060-016-0040-zCrossRefGoogle Scholar
  5. Castells M, Fernández-Ardèvol M, Linchuan Qiu J et al (2006) Mobile communication and society: a global perspective. The MIT Press, Cambridge, MACrossRefGoogle Scholar
  6. Charness N, Parks DC, Sabel BA (eds) (2001) Communication, technology and aging: opportunities and challenges for the future. Springer, New York, NYGoogle Scholar
  7. Coupland N, Coupland J (1993) Discourses of ageism and anti-ageism. J Aging Stud 7:279–301.  https://doi.org/10.1016/0890-4065(93)90016-DCrossRefGoogle Scholar
  8. De Montjoye Y-A, Quoidbach J, Robic F et al (2013) Predicting personality using novel mobile phone-based metrics. In: Greenberg A, Kennedy W, Bos N (eds) Social computing, behavioral-cultural modeling and prediction. SBP 2013, pp 48–55Google Scholar
  9. Durick J, Robertson T, Brereton M et al (2013) Dispelling ageing myths in technology design. In: Proceedings of the Australian computer-human interaction conference (OzCHI 2013), pp 467–476Google Scholar
  10. Eurostat (2017) Digital economy and society in the EU: a browse through our online world in figures. In: Digital economy and society http://ec.europa.eu/eurostat/cache/infographs/ict/index.html
  11. Eurostat (2018) Individuals internet use. Last internet use in the last 3 months. Table [isoc_ci_ifp_iu]. http://ec.europa.eu/eurostat/web/products-datasets/-/isoc_ci_ifp_iu. Accessed 1 Mar 2018
  12. Ferdous R, Osmani V, Mayora O (2015) Smartphone app usage as a predictor of perceived stress levels at workplace. In: Proceedings of international conference on pervasive computing technologies for healthcare, pp 225–228.  https://doi.org/10.4108/icst.pervasivehealth.2015.260192
  13. Fernández-Ardèvol M, Arroyo L (2012) Mobile telephony and older people: exploring use and rejection. Interact Stud Commun Cult 3:9–24.  https://doi.org/10.1386/iscc.3.1.9_1CrossRefGoogle Scholar
  14. Fernández-Ardèvol M, Sawchuk K, Grenier L (2017) Maintaining connections: octo- and nonagenarians on digital “use and non-use”. Nord Rev 38:39–51.  https://doi.org/10.1515/nor-2017-0396CrossRefGoogle Scholar
  15. Ferreira D, Dey AK, Kostakos V (2011) Understanding human-smartphone concerns: a study of battery life. In: Proceedings of the conference on pervasive computing (Pervasive 2011), pp 19–33Google Scholar
  16. Ferreira D, Goncalves J, Kostakos V et al (2014) Contextual experience sampling of mobile application micro-usage. In: Proceedings of the international conference on human-computer interaction with mobile devices and services, pp 91–100.  https://doi.org/10.1145/2628363.2628367
  17. Friemel TN (2016) The digital divide has grown old: determinants of a digital divide among seniors. New Media Soc 18:313–331.  https://doi.org/10.1177/1461444814538648CrossRefGoogle Scholar
  18. Fundación Telefónica (2017) Sociedad Digital en España 2017Google Scholar
  19. Gilleard C, Jones I, Higgs P (2015) Connectivity in later life: the declining age divide in mobile cell phone ownership. Sociol Res Online 20:3.  https://doi.org/10.5153/sro.3552CrossRefGoogle Scholar
  20. Hajian S, Bonchi F, Castillo C (2016) Algorithmic bias: from discrimination discovery to fairness-aware data mining Sara. In: Proceedings of the international conference on knowledge discovery and data mining (KDD 2016), pp 2125–2126Google Scholar
  21. Hajian S, Domingo-Ferrer J, Martinez-Balleste A (2011) Discrimination prevention in data mining for intrusion and crime detection. In: Symposium on computational intelligence in cyber security (IEEE SSCI 2011), pp 47–54.  https://doi.org/10.1109/cicybs.2011.5949405
  22. Helsper EJ, Reisdorf BC (2016) The emergence of a “digital underclass” in Great Britain and Sweden: changing reasons for digital exclusion. New Media Soc, 1–18.  https://doi.org/10.1177/1461444816634676CrossRefGoogle Scholar
  23. Higgs P, Gilleard CJ (2015) Rethinking old age: theorising the fourth age. Palgrave Macmillan, London, United KingdomCrossRefGoogle Scholar
  24. Huangfu J, Cao J, Liu C (2015) A context-aware usage prediction approach for smartphone applications. In: Yao L, Xie X, Zhang Q et al. (eds) Advances in services computing (APSCC 2015). Springer Verlag, pp 3–16Google Scholar
  25. Ikebe Y, Katagiri M, Takemura H (2012) Friendship prediction using semi-supervised learning of latent features in smartphone usage data. In: Proceedings of the international conference on knowledge discovery and information retrieval (KDIR 2012)Google Scholar
  26. Jacobetty P, Fernández-Ardèvol M (2017) Older audiences and digital media: Spain, 2016. Preliminary resultsGoogle Scholar
  27. Kitchin R (2014) Big data, new epistemologies and paradigm shifts. Big Data Soc 1:1–12.  https://doi.org/10.1177/2053951714528481CrossRefGoogle Scholar
  28. Leme RR, Zaina LAM, Casadei V (2014) Interaction with mobile devices by elderly people: the Brazilian scenario. In: Proceedings of the international conference on advances in computer-human interactions interaction (ACHI 2014), pp 21–26Google Scholar
  29. Ling R, Bertel TF, Sundsøy PR (2012) The socio-demographics of texting: an analysis of traffic data. New Media Soc 14:281–298.  https://doi.org/10.1177/1461444811412711CrossRefGoogle Scholar
  30. Litt E (2013) Measuring users’ internet skills: a review of past assessments and a look toward the future. New Media Soc 15:612–630.  https://doi.org/10.1177/1461444813475424CrossRefGoogle Scholar
  31. Loos E, Haddon L, Mante-Meijer EA (eds) (2012) Generational use of new media. Ashgate, Farnham, UKGoogle Scholar
  32. Maggiore G, Santos C, Plaat A (2014) Smarter smartphones: Understanding and predicting user habits from gps sensor data. In: Shakshuki EM (ed) International conference on future networks and communications (FNC 2014). Elsevier B.V., pp 297–304Google Scholar
  33. Mascheroni G, Ólafsson K (2016) The mobile internet: access, use, opportunities and divides among European children. New Media Soc 18:1657–1679.  https://doi.org/10.1177/1461444814567986CrossRefGoogle Scholar
  34. Mooi E, Sarstedt M (2011) Cluster analysis. In: A concise guide to market research. Springer, Berlin, HeidelbergGoogle Scholar
  35. Morris A, Goodman J, Brading H (2007) Internet use and non-use: views of older users. Univers Access Inf Soc 6:43–57.  https://doi.org/10.1007/s10209-006-0057-5CrossRefGoogle Scholar
  36. Naab T, Schwarzenegger C (2017) Why ageing is more important than being old: understanding the elderly in a mediatized world. Nord Rev 38:93–107.  https://doi.org/10.1515/nor-2017-0400CrossRefGoogle Scholar
  37. ONTSI (2017) Las TIC en los hogares españoles: Estudio de demanda y uso de servicios de telecomunicaciones y sociedad de la informaciónGoogle Scholar
  38. Park YJ (2015) My whole world’s in my palm! The second-level divide of teenagers’ mobile use and skill. New Media Soc 17:977–995.  https://doi.org/10.1177/1461444813520302CrossRefGoogle Scholar
  39. Peacock SE, Künemund H (2007) Senior citizens and internet technology: reasons and correlates of access versus non-access in a European comparative perspective. Eur J Ageing 4:191–200.  https://doi.org/10.1007/s10433-007-0067-zCrossRefGoogle Scholar
  40. Pearce KE, Rice RE (2013) Digital divides from access to activities: comparing mobile and personal computer internet users. J Commun 63:721–744.  https://doi.org/10.1111/jcom.12045CrossRefGoogle Scholar
  41. Pew Research Center (2017) Tech adoption climbs among older adults. Washington, DCGoogle Scholar
  42. Rogers EM (2003) The digital divide. Convergence 7:96–111CrossRefGoogle Scholar
  43. Rosales A, Fernández-Ardèvol M (2016a) Smartphones, apps and older people’s interests: from a generational perspective. In: Proceedings of the conference on human-computer interaction with mobile devices and services (Mobile HCI 2016). Association for Computing Machinery, Inc, New York, NY, pp 491–503Google Scholar
  44. Rosales A, Fernández-Ardèvol M (2016b) Beyond WhatsApp: older people and smartphones. Rom J Commun Public Relations 18:27–47. doi: https://doi.org/10.21018/rjcpr.2016.1.200CrossRefGoogle Scholar
  45. Sawchuk K, Crow B (2011) Into the grey zone: seniors, cell phones and milieus that matter. WI J Mob Media 5Google Scholar
  46. Schäfer MT, Van Es K (2017) The datafied society: studying culture through data. Amsterdam University PressGoogle Scholar
  47. Singh VK, Freeman L, Lepri B, Pentland A (2013) Predicting spending behavior using socio-mobile features. In: Proceedings on the international conference on social computing, pp 174–179Google Scholar
  48. Taipale S (2016) Do the mobile-rich get richer? Internet use, travelling and social differentiations in Finland. New Media Soc 18:44–61.  https://doi.org/10.1177/1461444814536574CrossRefGoogle Scholar
  49. Van Dijk J (2006) Digital divide research, achievements and shortcomings. Poetics 34:221–235.  https://doi.org/10.1016/j.poetic.2006.05.004CrossRefGoogle Scholar
  50. Van Dijk J, Hacker K (2000) The digital divide as a complex and dynamic phenomenon. Annu Conf Int Commun Assoc 1–20.  https://doi.org/10.1016/s0360-1315(00)00035-xCrossRefGoogle Scholar
  51. Yan T, Chu D, Ganesan D et al (2012) Fast app launching for mobile devices using predictive user context. In: Proceedings of the conference on mobile systems, applications, and services (MobiSys 2012). pp 113–126Google Scholar

Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  1. 1.IN3—Universitat Oberta de CatalunyaBarcelonaSpain

Personalised recommendations