User-Centric Requirements Prioritization in mHealth Applications: Insights from a Discrete Choice Experiment

Fuente: arXiv
Saved in:
Bibliographic Details
Main Authors: Wang, Wei, Khalajzadeh, Hourieh, Grundy, John, Madugalla, Anuradha, Obie, Humphrey O.
Format: Preprint
Published: 2025
Subjects:
Online Access:
Tags: Add Tag
No Tags, Be the first to tag this record!
_version_ 1866912810544398336
author Wang, Wei
Khalajzadeh, Hourieh
Grundy, John
Madugalla, Anuradha
Obie, Humphrey O.
author_facet Wang, Wei
Khalajzadeh, Hourieh
Grundy, John
Madugalla, Anuradha
Obie, Humphrey O.
contents Mobile health (mHealth) applications are widely used for chronic disease management, but usability and accessibility challenges persist due to the diverse needs of users. Adaptive User Interfaces (AUIs) offer a personalized solution to enhance user experience, yet barriers to adoption remain. Understanding user preferences and trade-offs is essential to ensure widespread acceptance of adaptation designs. This study identifies key factors influencing user preferences and trade-offs in mHealth adaptation design. A Discrete Choice Experiment (DCE) was conducted with 186 participants who have chronic diseases and use mHealth applications. Participants were asked to select preferred adaptation designs from choices featuring six attributes with varying levels. A mixed logit model was used to analyze preference heterogeneity and determine the factors most likely influencing adoption. Additionally, subgroup analyses were performed to explore differences by age, gender, health conditions, and coping mechanisms. Maintaining usability while ensuring controllability over adaptations, infrequent adaptations, and small-scale changes are key factors that facilitate the adoption of adaptive mHealth app designs. In contrast, frequently used functions and caregiver involvement can diminish the perceived value of such adaptations. This study employs a data-driven approach to quantify user preferences, identify key trade-offs, and reveal variations across demographic and behavioral subgroups through preference heterogeneity modeling. Furthermore, our results offer valuable guidance for developing future adaptive mHealth applications and lay the groundwork for continued exploration into requirements prioritization within the field of software engineering.
format Preprint
id arxiv_https___arxiv_org_abs_2511_18625
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle User-Centric Requirements Prioritization in mHealth Applications: Insights from a Discrete Choice Experiment
Wang, Wei
Khalajzadeh, Hourieh
Grundy, John
Madugalla, Anuradha
Obie, Humphrey O.
Software Engineering
Mobile health (mHealth) applications are widely used for chronic disease management, but usability and accessibility challenges persist due to the diverse needs of users. Adaptive User Interfaces (AUIs) offer a personalized solution to enhance user experience, yet barriers to adoption remain. Understanding user preferences and trade-offs is essential to ensure widespread acceptance of adaptation designs. This study identifies key factors influencing user preferences and trade-offs in mHealth adaptation design. A Discrete Choice Experiment (DCE) was conducted with 186 participants who have chronic diseases and use mHealth applications. Participants were asked to select preferred adaptation designs from choices featuring six attributes with varying levels. A mixed logit model was used to analyze preference heterogeneity and determine the factors most likely influencing adoption. Additionally, subgroup analyses were performed to explore differences by age, gender, health conditions, and coping mechanisms. Maintaining usability while ensuring controllability over adaptations, infrequent adaptations, and small-scale changes are key factors that facilitate the adoption of adaptive mHealth app designs. In contrast, frequently used functions and caregiver involvement can diminish the perceived value of such adaptations. This study employs a data-driven approach to quantify user preferences, identify key trade-offs, and reveal variations across demographic and behavioral subgroups through preference heterogeneity modeling. Furthermore, our results offer valuable guidance for developing future adaptive mHealth applications and lay the groundwork for continued exploration into requirements prioritization within the field of software engineering.
title User-Centric Requirements Prioritization in mHealth Applications: Insights from a Discrete Choice Experiment
topic Software Engineering
url https://arxiv.org/abs/2511.18625