Literature DB >> 26851465

Personal and other factors affecting acceptance of smartphone technology by older Chinese adults.

Qi Ma1, Alan H S Chan2, Ke Chen3.   

Abstract

It has been well documented that in the 21st century, there will be relatively more older people around the world than in the past. Also, it seems that technology will expand in this era at an unprecedented rate. Therefore, it is of critical importance to understand the factors that influence the acceptance of technology by older people. The positive impact that the use of mobile applications can have for older people was confirmed by a previous study (Plaza et al., 2011). The study reported here aimed to explore and confirm, for older adults in China, the key influential factors of smartphone acceptance, and to describe the personal circumstances of Chinese older adults who use smartphone. A structured questionnaire and face to face individual interviews were used with 120 Chinese older adults (over 55). Structural Equation Modeling was used to confirm a proposed smartphone acceptance model based on Technology Acceptance Model (TAM), and the Unified Theory of Acceptance and Use of Technology (UTAUT). The results showed that those who were younger, with higher education, non-widowed, with better economic condition related to salary or family support were more likely to use smartphone. Also, cost was found to be a critical factor influencing behavior intention. Self-satisfaction and facilitating conditions were proved to be important factors influencing perceived usefulness and perceived ease of use.
Copyright © 2015 Elsevier Ltd and The Ergonomics Society. All rights reserved.

Entities:  

Keywords:  Chinese older adults; Mobile apps; Personal factors; Smartphone; Technology acceptance

Mesh:

Year:  2015        PMID: 26851465     DOI: 10.1016/j.apergo.2015.11.015

Source DB:  PubMed          Journal:  Appl Ergon        ISSN: 0003-6870            Impact factor:   3.661


  25 in total

1.  Use of Mobile Health Applications for Health-Seeking Behavior Among US Adults.

Authors:  Soumitra S Bhuyan; Ning Lu; Aastha Chandak; Hyunmin Kim; David Wyant; Jay Bhatt; Satish Kedia; Cyril F Chang
Journal:  J Med Syst       Date:  2016-05-04       Impact factor: 4.460

2.  Research on the use intention of potential designers of unmanned cars based on technology acceptance model.

Authors:  Tianyang Huang
Journal:  PLoS One       Date:  2021-08-20       Impact factor: 3.240

3.  Factors Influencing Sustained Engagement with ECG Self-Monitoring: Perspectives from Patients and Health Care Providers.

Authors:  Meghan Reading; Dawon Baik; Melissa Beauchemin; Kathleen T Hickey; Jacqueline A Merrill
Journal:  Appl Clin Inform       Date:  2018-10-10       Impact factor: 2.342

4.  Facilitators of and Barriers to mHealth Adoption in Older Adults With Heart Failure.

Authors:  Maan Isabella Cajita; Nancy A Hodgson; Katherine Wai Lam; Sera Yoo; Hae-Ra Han
Journal:  Comput Inform Nurs       Date:  2018-08       Impact factor: 1.985

5.  Measuring Senior Technology Acceptance: Development of a Brief, 14-Item Scale.

Authors:  Ke Chen; Vivian Wei Qun Lou
Journal:  Innov Aging       Date:  2020-06-27

6.  Health App Possession Among Smartphone or Tablet Owners in Hong Kong: Population-Based Survey.

Authors:  Chen Shen; Man Ping Wang; Joanna Tw Chu; Alice Wan; Kasisomayajula Viswanath; Sophia Siu Chee Chan; Tai Hing Lam
Journal:  JMIR Mhealth Uhealth       Date:  2017-06-05       Impact factor: 4.773

7.  The use of mobile devices for physical activity tracking in older adults' everyday life.

Authors:  Alexander Seifert; Anna Schlomann; Christian Rietz; Hans Rudolf Schelling
Journal:  Digit Health       Date:  2017-11-09

8.  Predictors of Seniors' Interest in Assistive Applications on Smartphones: Evidence from a Population-Based Survey in Slovenia.

Authors:  Andraž Petrovčič; Sebastiaan Peek; Vesna Dolničar
Journal:  Int J Environ Res Public Health       Date:  2019-05-09       Impact factor: 3.390

9.  Exerting Explanatory Accounts of Safety Behavior of Older Construction Workers within the Theory of Planned Behavior.

Authors:  Lu Peng; Alan H S Chan
Journal:  Int J Environ Res Public Health       Date:  2019-09-10       Impact factor: 3.390

10.  Understanding the Role of Mobile Internet-Based Health Services on Patient Satisfaction and Word-of-Mouth.

Authors:  Dongxiao Gu; Xuejie Yang; Xingguo Li; Hemant K Jain; Changyong Liang
Journal:  Int J Environ Res Public Health       Date:  2018-09-10       Impact factor: 3.390

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