Open AccessDeterminants of a mobile phone-based Interactive Voice Response (mIVR) system for monitoring childhood illnesses in a rural district of Ghana: Empirical evidence from the UTAUT model
Author(s) -
Timothy Kwabena Adjei,
Aliyu Mohammed,
Princess Ruhama Acheampong,
Emmanuel Acquah-Gyan,
Augustina Angelina Sylverken,
Sampson Twumasi-Ankrah,
Michael Owusu,
Ellis OwusuDabo
Publication year - 2021
Publication title -
plos one
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.99
H-Index - 332
ISSN - 1932-6203
DOI - 10.1371/journal.pone.0248363
Subject(s) - expectancy theory , mobile phone , phone , unified theory of acceptance and use of technology , life expectancy , rural area , medicine , psychology , gerontology , environmental health , computer science , social psychology , telecommunications , population , linguistics , philosophy , pathology
Background The use of a mobile phone-based Interactive Voice Response (mIVR) System for real time monitoring of childhood illnesses provides an opportunity to improve childhood survival and health systems. However, little is known about the factors that facilitate its use. This study sought to identify key determinants and moderators of mIVR system use among caregivers in a rural district of Ghana using the Unified Theory of Acceptance and Use of Technology (UTAUT) model. Methods The mIVR system was designed to provide real-time data on common symptoms of childhood illnesses after answering several questions by caregivers with sick children. A structured questionnaire with closed questions was used to collect data from 354 caregivers of children under-five living in rural communities, four (4) months after introducing the system. Regression analysis was used to identify key determinants and moderating factors that facilitate the use of the system based on the UTAUT model. Results A total of 101 (28.5%) caregivers had used the system and 328 (92.7%) had intention to use the mIVR system. Caregivers’ level of education and household wealth were associated with use of the mIVR systems (p<0.001). Behavioural intention (BI) to use mIVR system was positively influenced by performance expectancy (PE) (β = 0.278, 95% CI: 0.207, 0.349), effort expectancy (EE) (β = 0.242, 95% CI: 0.159, 0.326) and social influence (SI) (β = 0.081, 95% CI: 0.044, 0.120). Facilitating conditions (FC) (β = 0.609, 95% CI: 0.502, 0.715) and behavioural intention (β = 0.426, 95% CI: 0.255, 0.597) had a positive influence on user behaviour (UB). Mobile phone experience and household wealth significantly moderated the effect of PE, EE, SI, and FC on behavioural intention and usage of mIVR systems. Conclusion The perceived usefulness of the mIVR system, ease of use, social influences, and facilitating conditions are key determinants of users’ attitude and use of mIVR system. These relationships are significantly moderated by users’ phone experience and wealth status.