Longitudinal Assessment of mHealth Continuance: A Task-Technology Fit Perspective

Wilson Ka-shing Leung; Man Kit Chang; Man Lai Cheung; Fiona Sin-yan Tse; Randy Wong; Sally P M Law

Longitudinal Assessment of mHealth Continuance: A Task-Technology Fit Perspective

Wilson Ka-shing Leung^*, Man Kit Chang, Man Lai Cheung, Fiona Sin-yan Tse, Randy Wong, Sally P M Law

^*Corresponding author for this work

Department of Management, Marketing and Information Systems

Research output: Chapter in book/report/conference proceeding › Conference proceeding › peer-review

Abstract

The rapid aging of Asia's population is set to pose unprecedented challenges, with over a third aged 60 or above by 2050, escalating the need for healthcare services. Although mHealth apps have emerged as a promising solution to address this need, its adoption remains low, with frequent discontinuation. Seeking to address knowledge deficiencies in the area of mHealth adoption and continuance, this study extends the task-technology fit (TTF) model, by proposing that app usage is more likely to continue when it aligns with both the health-tasks-related (functional) and health-style-related (psychological) needs of the elderly, based on a longitudinal study. Our findings contribute to the IS literature by demonstrating how the congruence between users' needs (i.e., health-task-related needs and health-style-related needs) and technology functionality affects the ongoing use and future intentions to use mHealth apps among the elderly. In practice, this paper provides meaningful implications for mHealth app developers.

Original language	English
Title of host publication	PACIS 2024 Proceedings
Publisher	Association for Information Systems
Number of pages	17
Publication status	Published - Jul 2024
Event	28th Pacific Asia Conference on Information Systems, PACIS 2024: Preparing the Next Generation for the IT-Driven Future - The Reverie Saigon, Ho Chi Minh City, Viet Nam Duration: 1 Jul 2024 → 5 Jul 2024 https://pacis2024.aisconferences.org/ https://pacis2024.aisconferences.org/program/conference-program/ (Conference programme) https://aisel.aisnet.org/pacis2024/ (Conference proceedings)

Publication series

Name	Pacific Asia Conference on Information Systems

Conference

Conference	28th Pacific Asia Conference on Information Systems, PACIS 2024
Country/Territory	Viet Nam
City	Ho Chi Minh City
Period	1/07/24 → 5/07/24
Internet address	https://pacis2024.aisconferences.org/ https://pacis2024.aisconferences.org/program/conference-program/ (Conference programme) https://aisel.aisnet.org/pacis2024/ (Conference proceedings)

Scopus Subject Areas

Management Information Systems
Health Information Management

User-Defined Keywords

Task Technology Fit
Mobile Health Apps
Longitudinal

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

Access to Document

https://aisel.aisnet.org/cgi/viewcontent.cgi?article=1097&context=pacis2024Licence: Unspecified

Cite this

Leung, W. K., Chang, M. K., Cheung, M. L., Tse, F. S., Wong, R., & Law, S. P. M. (2024). Longitudinal Assessment of mHealth Continuance: A Task-Technology Fit Perspective. In PACIS 2024 Proceedings Article 1411 (Pacific Asia Conference on Information Systems). Association for Information Systems. https://aisel.aisnet.org/cgi/viewcontent.cgi?article=1097&context=pacis2024

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abstract = "The rapid aging of Asia's population is set to pose unprecedented challenges, with over a third aged 60 or above by 2050, escalating the need for healthcare services. Although mHealth apps have emerged as a promising solution to address this need, its adoption remains low, with frequent discontinuation. Seeking to address knowledge deficiencies in the area of mHealth adoption and continuance, this study extends the task-technology fit (TTF) model, by proposing that app usage is more likely to continue when it aligns with both the health-tasks-related (functional) and health-style-related (psychological) needs of the elderly, based on a longitudinal study. Our findings contribute to the IS literature by demonstrating how the congruence between users' needs (i.e., health-task-related needs and health-style-related needs) and technology functionality affects the ongoing use and future intentions to use mHealth apps among the elderly. In practice, this paper provides meaningful implications for mHealth app developers.",

keywords = "Task Technology Fit, Mobile Health Apps, Longitudinal",

author = "Leung, {Wilson Ka-shing} and Chang, {Man Kit} and Cheung, {Man Lai} and Tse, {Fiona Sin-yan} and Randy Wong and Law, {Sally P M}",

note = "The work described in this study was fully supported by a grant from the Research Grants Council of the Hong Kong Special Administrative Region, China (Project No. “UGC/FDS24/B08/21”); 28th Pacific Asia Conference on Information Systems, PACIS 2024 : Preparing the Next Generation for the IT-Driven Future ; Conference date: 01-07-2024 Through 05-07-2024",

year = "2024",

month = jul,

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publisher = "Association for Information Systems",

booktitle = "PACIS 2024 Proceedings",

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Leung, WK, Chang, MK, Cheung, ML, Tse, FS, Wong, R & Law, SPM 2024, Longitudinal Assessment of mHealth Continuance: A Task-Technology Fit Perspective. in PACIS 2024 Proceedings., 1411, Pacific Asia Conference on Information Systems, Association for Information Systems, 28th Pacific Asia Conference on Information Systems, PACIS 2024, Ho Chi Minh City, Viet Nam, 1/07/24. <https://aisel.aisnet.org/cgi/viewcontent.cgi?article=1097&context=pacis2024>

Longitudinal Assessment of mHealth Continuance: A Task-Technology Fit Perspective. / Leung, Wilson Ka-shing; Chang, Man Kit; Cheung, Man Lai et al.
PACIS 2024 Proceedings. Association for Information Systems, 2024. 1411 (Pacific Asia Conference on Information Systems).

Research output: Chapter in book/report/conference proceeding › Conference proceeding › peer-review

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T1 - Longitudinal Assessment of mHealth Continuance: A Task-Technology Fit Perspective

AU - Leung, Wilson Ka-shing

AU - Chang, Man Kit

AU - Cheung, Man Lai

AU - Tse, Fiona Sin-yan

AU - Wong, Randy

AU - Law, Sally P M

N1 - The work described in this study was fully supported by a grant from the Research Grants Council of the Hong Kong Special Administrative Region, China (Project No. “UGC/FDS24/B08/21”)

PY - 2024/7

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N2 - The rapid aging of Asia's population is set to pose unprecedented challenges, with over a third aged 60 or above by 2050, escalating the need for healthcare services. Although mHealth apps have emerged as a promising solution to address this need, its adoption remains low, with frequent discontinuation. Seeking to address knowledge deficiencies in the area of mHealth adoption and continuance, this study extends the task-technology fit (TTF) model, by proposing that app usage is more likely to continue when it aligns with both the health-tasks-related (functional) and health-style-related (psychological) needs of the elderly, based on a longitudinal study. Our findings contribute to the IS literature by demonstrating how the congruence between users' needs (i.e., health-task-related needs and health-style-related needs) and technology functionality affects the ongoing use and future intentions to use mHealth apps among the elderly. In practice, this paper provides meaningful implications for mHealth app developers.

AB - The rapid aging of Asia's population is set to pose unprecedented challenges, with over a third aged 60 or above by 2050, escalating the need for healthcare services. Although mHealth apps have emerged as a promising solution to address this need, its adoption remains low, with frequent discontinuation. Seeking to address knowledge deficiencies in the area of mHealth adoption and continuance, this study extends the task-technology fit (TTF) model, by proposing that app usage is more likely to continue when it aligns with both the health-tasks-related (functional) and health-style-related (psychological) needs of the elderly, based on a longitudinal study. Our findings contribute to the IS literature by demonstrating how the congruence between users' needs (i.e., health-task-related needs and health-style-related needs) and technology functionality affects the ongoing use and future intentions to use mHealth apps among the elderly. In practice, this paper provides meaningful implications for mHealth app developers.

KW - Task Technology Fit

KW - Mobile Health Apps

KW - Longitudinal

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T3 - Pacific Asia Conference on Information Systems

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PB - Association for Information Systems

T2 - 28th Pacific Asia Conference on Information Systems, PACIS 2024

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ER -

Longitudinal Assessment of mHealth Continuance: A Task-Technology Fit Perspective

Abstract

Publication series

Conference

Scopus Subject Areas

User-Defined Keywords

UN SDGs

Access to Document

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Cite this