Literature DB >> 25850116

Smartphone Text Input Method Performance, Usability, and Preference With Younger and Older Adults.

Amanda L Smith1, Barbara S Chaparro2.   

Abstract

OBJECTIVE: User performance, perceived usability, and preference for five smartphone text input methods were compared with younger and older novice adults.
BACKGROUND: Smartphones are used for a variety of functions other than phone calls, including text messaging, e-mail, and web browsing. Research comparing performance with methods of text input on smartphones reveals a high degree of variability in reported measures, procedures, and results. This study reports on a direct comparison of five of the most common input methods among a population of younger and older adults, who had no experience with any of the methods.
METHOD: Fifty adults (25 younger, 18-35 years; 25 older, 60-84 years) completed a text entry task using five text input methods (physical Qwerty, onscreen Qwerty, tracing, handwriting, and voice). Entry and error rates, perceived usability, and preference were recorded.
RESULTS: Both age groups input text equally fast using voice input, but older adults were slower than younger adults using all other methods. Both age groups had low error rates when using physical Qwerty and voice, but older adults committed more errors with the other three methods. Both younger and older adults preferred voice and physical Qwerty input to the remaining methods. Handwriting consistently performed the worst and was rated lowest by both groups.
CONCLUSION: Voice and physical Qwerty input methods proved to be the most effective for both younger and older adults, and handwriting input was the least effective overall. APPLICATION: These findings have implications to the design of future smartphone text input methods and devices, particularly for older adults.
© 2015, Human Factors and Ergonomics Society.

Entities:  

Keywords:  age; keyboard; mobile devices; shape writing; touch screen; voice recognition

Mesh:

Year:  2015        PMID: 25850116     DOI: 10.1177/0018720815575644

Source DB:  PubMed          Journal:  Hum Factors        ISSN: 0018-7208            Impact factor:   2.888


  5 in total

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Authors:  Gabriel J Cler; Katharine R Kolin; Jacob P Noordzij; Jennifer M Vojtech; Susan K Fager; Cara E Stepp
Journal:  J Speech Lang Hear Res       Date:  2019-07-15       Impact factor: 2.297

2.  Mobile and Connected Health Technology Needs for Older Adults Aging in Place: Cross-Sectional Survey Study.

Authors:  Jing Wang; Yan Du; Deidra Coleman; Michelle Peck; Sahiti Myneni; Hong Kang; Yang Gong
Journal:  JMIR Aging       Date:  2019-05-15

3.  Automatic Assessment of Loneliness in Older Adults Using Speech Analysis on Responses to Daily Life Questions.

Authors:  Yasunori Yamada; Kaoru Shinkawa; Miyuki Nemoto; Tetsuaki Arai
Journal:  Front Psychiatry       Date:  2021-12-13       Impact factor: 4.157

4.  Mobile Phone-Based Measures of Activity, Step Count, and Gait Speed: Results From a Study of Older Ambulatory Adults in a Naturalistic Setting.

Authors:  Cassia Rye Hanton; Yong-Jun Kwon; Thawda Aung; Jackie Whittington; Robin R High; Evan H Goulding; A Katrin Schenk; Stephen J Bonasera
Journal:  JMIR Mhealth Uhealth       Date:  2017-10-03       Impact factor: 4.773

5.  Design and Usability Evaluation of Mobile Voice-Added Food Reporting for Elderly People: Randomized Controlled Trial.

Authors:  Ying-Chieh Liu; Chien-Hung Chen; Yu-Sheng Lin; Hsin-Yun Chen; Denisa Irianti; Ting-Ni Jen; Jou-Yin Yeh; Sherry Yueh-Hsia Chiu
Journal:  JMIR Mhealth Uhealth       Date:  2020-09-28       Impact factor: 4.773

  5 in total

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