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Exploring iPhone usage: the influence of socioeconomic differences on smartphone adoption, usage and usability

Authors:

Clayton Shepard,

Lin ZhongAuthors Info & Claims

MobileHCI '12: Proceedings of the 14th international conference on Human-computer interaction with mobile devices and services

Pages 11 - 20

https://doi.org/10.1145/2371574.2371577

Published: 21 September 2012 Publication History

Abstract

Previous studies have found that smartphone users differ by orders of magnitude. We explore this variability to understand how users install and use native applications in ecologically-valid environments. A quasi-experimental approach is applied to compare how users in different socio-economic status (SES) groups adopt new smartphone technology along with how applications are installed and used. We present a longitudinal study of 34 iPhone 3GS users. 24 of these participants were chosen from two carefully selected SES groups who were otherwise similar and balanced. Usage data collected through an in-device programmable logger, as well as several structured interviews, identify similarities, differences, and trends, and highlight systematic differences in smartphone usage. A group of 10 lower SES participants were later recruited and confirm the influence of SES diversity on device usage. Among our findings are that a large number of applications were uninstalled, lower SES groups spent more money on applications and installed more applications overall, and the lowest SES group perceived the usability of their iPhones poorly in comparison to the other groups. We further discuss the primary reasons behind this low score, and suggest design implications to better support users across SES brackets.

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Cited By

Paolillo ECasaletto KClark ATaylor JHeuer HWise ADhanam SSanderson-Cimino MSaloner RKramer JKornak JKremers WForsberg LAppleby BBayram EBozoki ABrushaber DDarby RDay GDickerson BDomoto-Reilly KElahi FFields JGhoshal NGraff-Radford NG H Hall MHonig LHuey ELapid MLitvan IMackenzie IMasdeu JMendez MMester CMiyagawa TNaasan GPascual BPressman PRamos ERankin KRexach JRojas JVandeVrede LWong BWszolek ZBoeve BRosen HBoxer AStaffaroni A(2024)Examining Associations Between Smartphone Use and Clinical Severity in Frontotemporal Dementia: Proof-of-Concept StudyJMIR Aging10.2196/528317(e52831)Online publication date: 26-Jun-2024
https://doi.org/10.2196/52831
Munzer TMiller AWeeks HKaciroti NRadesky J(2024)Greater mobile device‐prompted phone pickups are associated with daily parent stressActa Paediatrica10.1111/apa.17260113:8(1868-1875)Online publication date: 2-May-2024
https://doi.org/10.1111/apa.17260
Thompson JWoods SWebber TMedina LPodell KYoshida HEvans DRidgely NBabicz MGomez EMustafa A(2024)Development of the Telephone-based Daily Instrumental Activities of Living (T-DIAL) to assess financial management remotely in older adultsAging, Neuropsychology, and Cognition10.1080/13825585.2024.2352900(1-24)Online publication date: 10-May-2024
https://doi.org/10.1080/13825585.2024.2352900
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Index Terms

Exploring iPhone usage: the influence of socioeconomic differences on smartphone adoption, usage and usability
1. Human-centered computing
  1. Human computer interaction (HCI)

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Published In

cover image ACM Conferences

MobileHCI '12: Proceedings of the 14th international conference on Human-computer interaction with mobile devices and services

September 2012

468 pages

ISBN:9781450311052

DOI:10.1145/2371574

General Chairs:
Elizabeth Churchill
Designing Associates, USA
,
Sriram Subramanian
University of Bristol, UK
,
Program Chairs:
Patrick Baudisch
Hasso Plattner Institute, Germany
,
Kenton O'Hara
Microsoft Research, Cambridge, UK

Copyright © 2012 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]

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SIGCHI: ACM Special Interest Group on Computer-Human Interaction

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 21 September 2012

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MobileHCI '12

Sponsor:

SIGCHI

MobileHCI '12: 14th International Conference on Human Computer Interaction with Mobile Devices and Services

September 21 - 24, 2012

California, San Francisco, USA

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Overall Acceptance Rate 202 of 906 submissions, 22%

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Cited By

Paolillo ECasaletto KClark ATaylor JHeuer HWise ADhanam SSanderson-Cimino MSaloner RKramer JKornak JKremers WForsberg LAppleby BBayram EBozoki ABrushaber DDarby RDay GDickerson BDomoto-Reilly KElahi FFields JGhoshal NGraff-Radford NG H Hall MHonig LHuey ELapid MLitvan IMackenzie IMasdeu JMendez MMester CMiyagawa TNaasan GPascual BPressman PRamos ERankin KRexach JRojas JVandeVrede LWong BWszolek ZBoeve BRosen HBoxer AStaffaroni A(2024)Examining Associations Between Smartphone Use and Clinical Severity in Frontotemporal Dementia: Proof-of-Concept StudyJMIR Aging10.2196/528317(e52831)Online publication date: 26-Jun-2024
https://doi.org/10.2196/52831
Munzer TMiller AWeeks HKaciroti NRadesky J(2024)Greater mobile device‐prompted phone pickups are associated with daily parent stressActa Paediatrica10.1111/apa.17260113:8(1868-1875)Online publication date: 2-May-2024
https://doi.org/10.1111/apa.17260
Thompson JWoods SWebber TMedina LPodell KYoshida HEvans DRidgely NBabicz MGomez EMustafa A(2024)Development of the Telephone-based Daily Instrumental Activities of Living (T-DIAL) to assess financial management remotely in older adultsAging, Neuropsychology, and Cognition10.1080/13825585.2024.2352900(1-24)Online publication date: 10-May-2024
https://doi.org/10.1080/13825585.2024.2352900
Higgins JIrwin S(2023)IntroductionSmartphone Apps for Health and Wellness10.1016/B978-0-323-99271-8.00004-8(1-10)Online publication date: 2023
https://doi.org/10.1016/B978-0-323-99271-8.00004-8
van Berkel NShalawadi SEvans MVisuri AHosio S(2023)A Longitudinal Analysis of Real-World Self-report DataHuman-Computer Interaction – INTERACT 202310.1007/978-3-031-42286-7_34(611-632)Online publication date: 28-Aug-2023
https://dl.acm.org/doi/10.1007/978-3-031-42286-7_34
Bulak MSezgin H(2022)Data-Driven Usability Assessment Model for Smartphones: A Causal Analytic ApproachInternational Journal of Innovation and Technology Management10.1142/S021987702250028619:07Online publication date: 25-May-2022
https://doi.org/10.1142/S0219877022500286
Hartanto ALee KChua YQuek FMajeed N(2022)Smartphone use and daily cognitive failures: A critical examination using a daily diary approach with objective smartphone measuresBritish Journal of Psychology10.1111/bjop.12597114:1(70-85)Online publication date: 14-Sep-2022
https://doi.org/10.1111/bjop.12597
Li TXia TWang HTu ZTarkoma SHan ZHui P(2022)Smartphone App Usage Analysis: Datasets, Methods, and ApplicationsIEEE Communications Surveys & Tutorials10.1109/COMST.2022.316317624:2(937-966)Online publication date: Oct-2023
https://doi.org/10.1109/COMST.2022.3163176
Cummings PPetitclerc AMoskowitz JTandon DZhang YMacNeill LAlshurafa NKrogh-Jespersen SHamil JNili ABerken JGrobman WRangarajan AWakschlag L(2022)Feasibility of Passive ECG Bio-sensing and EMA Emotion Reporting Technologies and Acceptability of Just-in-Time Content in a Well-being Intervention, Considerations for Scalability and Improved UptakeAffective Science10.1007/s42761-022-00147-03:4(849-861)Online publication date: 18-Oct-2022
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Hunter SBlocker LGutworth MAllen J(2022)Why we Support some Original Ideas but Reject Others: An Application of Signaling TheoryThe Journal of Creative Behavior10.1002/jocb.57057:2(199-220)Online publication date: 31-Oct-2022
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