Evaluate the Usability of the Mobile Instant Messaging Software in the Elderly
Abstract
Purpose: Instant messaging (IM) is one kind of online chat that provides real-time text transmission over the Internet. It becomes one of the popular communication tools. Even it is currnetly an era of smartphones, it still a great challenge to teach and promote the elderly to use smart phone. Besides, the acceptance of the elderly to use IM remains unknown. This study describes the usability and evaluates the acceptance of the IM in the elderly, who use the smartphone for the first time. This study is a quasi-experimental design study. The study period started from October, 2012 to December, 2013. There were totally 41 elderly recruited in the study. All of them were the first time to use LINE app on the smartphones. The usability was evaluated by using the Technology Acceptance Model which consisted of four constructs: cognitive usability, cognitive ease of use, attitude and willingness to use. Overall, the elderly had the best “attitude” for LINE APP communication software, with the highest rating averaging 4.07 points on four constructs, followed by an average of 4 points on “cognitive usefulness”. The socres of “cognitive ease of use” and “willingness to use” scores were equal which are an average score of 3.86. It can be interpreted that (1) the elders thought that the LINE APP as an excellent communication tool for them; (2) they found the software is useful (3) it was convenient for them to communicate. However, it was necessary to additionally assist and explain the certain functions such as the options. It would play a great role in the “willingness to use”. The positive acceptance of LINE APP in elderly refer to the probable similar acceptance for them to use other communication software. Encouraging the willingness the elderly to explore more technology products and understanding their behavior will be the basic knowledge to develop further software.
Integrity signals
Registry
Cites
Statistics
Claims the paper makes
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
In the literature, older adults are defined from ages 50 and above, 55 and above, and 70 and above.
“In the literature too, older adults are defned from ages 50 and above [15,61,66], 55 and above [2,67] and 70 and above [59,60].”
From "Where is history": Toward Designing a Voice Assistant to help Older Adults locate Interface Features quickly (2023) · cites this paper as [66]
Cited by
Sorted by citations
Yu, J. E., Parde, N., & Chattopadhyay, D. (2023) · Proceedings of the 2023 CHI Conference on Human Factors in Computing Systems · doi:10.1145/3544548.3581447 · Cited by 22 · see citing works
- Authors
- Tzu-Ning, W., Po-Liang, C., & Po-Lun, C.
- Affiliations
- National Yang Ming University (TW)
- Venue
- Studies in Health Technology and Informatics
- Publisher
- IOS Press
- Published
- 2017
- Volume
- 245
- Pages
- 818-822
- ISSN
- 0926-9630 (ISSN-L)
- OpenAlex
- W2786264352
- Cited by
- 12
- References
- 0
- Citations by year
- 2025: 2 · 2024: 4 · 2022: 1 · 2021: 1 · 2020: 3 · 2019: 1
- FWCI
- 8.66
- Type
- book chapter
- Language
- en
- Open access
- closed
- Locations
- Studies in health technology and informatics (publishedVersion)
- PubMed (publishedVersion)
- PubMed
- Topics
- Social Sciences › Demography › Technology Use by Older Adults
- Social Sciences › Decision Sciences › Information Systems and Management › Technology Adoption and User Behaviour
- Physical Sciences › Computer Science › Human-Computer Interaction › Usability and User Interface Design
- Keywords
- instant messaging, older adults, smartphone use, usability, technology acceptance, technology acceptance model, willingness to use, attitudes toward technology
- MeSH terms
- Smartphone, Aged, Communication, Humans, Internet, Text Messaging, Mobile Applications
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review