Exploring the Biases in the Decision to Download mHealth Apps: A Discrete Choice Experimental Analysis of Nigerian Healthcare App Users

Globally, mobile health (mHealth) tools are becoming more widely available. This provides great benefits for both patients and healthcare providers. However, mHealth adoption is still comparatively low. Furthermore, few studies have examined people's intentions to download mHealth apps. The purpose of this study is to investigate people's propensity to use mobile health apps. The discrete choice experiment method was employed to investigate healthcare application users in Nigeria. Two main features (attributes) of the mHealth applications, subscription cost and data protection, were presented to the 1600 participants in the study. Each feature had two levels: ‘free subscription’ and ‘$20 subscription’ for cost, and ‘data protection’ and ‘no data protection’ for data privacy. The pricing for data protection is $20, equivalent to N39, 058.76 (at the rate of $1 = N1, 502.26), while the free subscription option does not include data protection. A total of 1,600 participants were randomly selected through a web-based survey employing a proportionate stratified sampling technique. Data were analyzed using a conditional logistic regression model in R (Clogit), yielding 43,200 observations (1600 participants’× 18 available choices× 3 alternatives). The results revealed that cost and data protection significantly influenced users’ willingness to download mHealth apps. Specifically, the odds ratio (OR) for paid apps ($20) was 0.498 (95% CI: 0.468–0.530), indicating a reduced likelihood of download compared to free apps, while the OR for data protection was 0.25 (95% CI: 0.232–0.270), suggesting that participants strongly preferred apps that ensured privacy of health data. The model yielded a log-likelihood of –23,165.48 and an R² of 0.113, confirming a good model fit. The findings imply that users are significantly more inclined to adopt mHealth apps that are free and guarantee data protection. Reducing cost barriers and strengthening privacy measures are, therefore, essential strategies for enhancing mHealth adoption in Nigeria and similar contexts.

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Journal
ABUAD Journal of Engineering Research and Development (AJERD)
Published
2025-10-25
DOI
https://doi.org/10.53982/ajerd.2025.0803.12-j
Primary Topic
Technology Adoption and User Behaviour
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article
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article

Exploring the Biases in the Decision to Download mHealth Apps: A Discrete Choice Experimental Analysis of Nigerian Healthcare App Users

Ignatius Nwoyibe Ogbaga, Christiana Uchenna Ezeanya, Henry Friday Nweke, Gabriel Evo Ugwu
ABUAD Journal of Engineering Research and Development (AJERD)
Technology Adoption and User Behaviour
article

Exploring the Biases in the Decision to Download mHealth Apps: A Discrete Choice Experimental Analysis of Nigerian Healthcare App Users

Ignatius Nwoyibe Ogbaga, Christiana Uchenna Ezeanya, Henry Friday Nweke, Gabriel Evo Ugwu
article en

Abstract

Globally, mobile health (mHealth) tools are becoming more widely available. This provides great benefits for both patients and healthcare providers. However, mHealth adoption is still comparatively low. Furthermore, few studies have examined people's intentions to download mHealth apps. The purpose of this study is to investigate people's propensity to use mobile health apps. The discrete choice experiment method was employed to investigate healthcare application users in Nigeria. Two main features (attributes) of the mHealth applications, subscription cost and data protection, were presented to the 1600 participants in the study. Each feature had two levels: ‘free subscription’ and ‘$20 subscription’ for cost, and ‘data protection’ and ‘no data protection’ for data privacy. The pricing for data protection is $20, equivalent to N39, 058.76 (at the rate of $1 = N1, 502.26), while the free subscription option does not include data protection. A total of 1,600 participants were randomly selected through a web-based survey employing a proportionate stratified sampling technique. Data were analyzed using a conditional logistic regression model in R (Clogit), yielding 43,200 observations (1600 participants’× 18 available choices× 3 alternatives). The results revealed that cost and data protection significantly influenced users’ willingness to download mHealth apps. Specifically, the odds ratio (OR) for paid apps ($20) was 0.498 (95% CI: 0.468–0.530), indicating a reduced likelihood of download compared to free apps, while the OR for data protection was 0.25 (95% CI: 0.232–0.270), suggesting that participants strongly preferred apps that ensured privacy of health data. The model yielded a log-likelihood of –23,165.48 and an R² of 0.113, confirming a good model fit. The findings imply that users are significantly more inclined to adopt mHealth apps that are free and guarantee data protection. Reducing cost barriers and strengthening privacy measures are, therefore, essential strategies for enhancing mHealth adoption in Nigeria and similar contexts.

ABUAD Journal of Engineering Research and Development (AJERD)Vol. 8(3)
National Open University of Nigeria (NG), Ebonyi State University (NG)
Openalex Percentile: Top 71%
Technology Adoption and User Behaviour
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