Literature DB >> 33705448

Determinants 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.

Timothy Kwabena Adjei1,2, Aliyu Mohammed3, Princess Ruhama Acheampong1, Emmanuel Acquah-Gyan1, Augustina Sylverken4,5, Sampson Twumasi-Ankrah6, Michael Owusu7, Ellis Owusu-Dabo1.   

Abstract

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.

Entities:  

Year:  2021        PMID: 33705448      PMCID: PMC7951827          DOI: 10.1371/journal.pone.0248363

Source DB:  PubMed          Journal:  PLoS One        ISSN: 1932-6203            Impact factor:   3.240


  9 in total

1.  Understanding factors influencing the adoption of mHealth by the elderly: An extension of the UTAUT model.

Authors:  Rakibul Hoque; Golam Sorwar
Journal:  Int J Med Inform       Date:  2017-02-10       Impact factor: 4.046

2.  An investigation of users' attitudes, requirements and willingness to use mobile phone-based interactive voice response systems for seeking healthcare in Ghana: a qualitative study.

Authors:  J Brinkel; P Dako-Gyeke; A Krämer; J May; J N Fobil
Journal:  Public Health       Date:  2017-01-19       Impact factor: 2.427

3.  Assessment of mobile health technology for maternal and child health services in rural Upper West Region of Ghana.

Authors:  A S Laar; E Bekyieriya; S Isang; B Baguune
Journal:  Public Health       Date:  2019-01-17       Impact factor: 2.427

4.  Quantifying usability: an evaluation of a diabetes mHealth system on effectiveness, efficiency, and satisfaction metrics with associated user characteristics.

Authors:  Mattias Georgsson; Nancy Staggers
Journal:  J Am Med Inform Assoc       Date:  2015-09-15       Impact factor: 4.497

5.  Gender differentials in readiness and use of mHealth services in a rural area of Bangladesh.

Authors:  Fatema Khatun; Anita E Heywood; Syed Manzoor Ahmed Hanifi; M Shafiqur Rahman; Pradeep K Ray; Siaw-Teng Liaw; Abbas Bhuiya
Journal:  BMC Health Serv Res       Date:  2017-08-18       Impact factor: 2.655

6.  Mobile-health tool to improve maternal and neonatal health care in Bangladesh: a cluster randomized controlled trial.

Authors:  Ruoyan Gai Tobe; Syed Emdadul Haque; Kiyoko Ikegami; Rintaro Mori
Journal:  BMC Pregnancy Childbirth       Date:  2018-04-16       Impact factor: 3.007

7.  Feasibility of Electronic Health Information and Surveillance System (eHISS) for disease symptom monitoring: A case of rural Ghana.

Authors:  Aliyu Mohammed; Konstantin Franke; Portia Boakye Okyere; Johanna Brinkel; Axel Bonačić Marinovic; Benno Kreuels; Ralf Krumkamp; Julius Fobil; Jürgen May; Ellis Owusu-Dabo
Journal:  PLoS One       Date:  2018-05-24       Impact factor: 3.240

8.  Mobile phone short message service (SMS) as a malaria control tool: a quasi-experimental study.

Authors:  Aliyu Mohammed; Princess Ruhama Acheampong; Easmon Otupiri; Francis Adjei Osei; Roderick Larson-Reindorf; Ellis Owusu-Dabo
Journal:  BMC Public Health       Date:  2019-08-29       Impact factor: 3.295

Review 9.  Social Factors Influencing Child Health in Ghana.

Authors:  Emmanuel Quansah; Lilian Akorfa Ohene; Linda Norman; Michael Osei Mireku; Thomas K Karikari
Journal:  PLoS One       Date:  2016-01-08       Impact factor: 3.240

  9 in total

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