Uncontrolled hypertension is a global problem that needs to be addressed. Despite the many mHealth solutions in the market, the nonadherence relative to intended use jeopardizes treatment success. Although investigating user experience is one of the most important mechanisms for understanding mHealth discontinuance, surprisingly, the core determinants of overall user experience (i.e., positive and negative) about mHealth apps for hypertension are unknown. To address the mentioned gap in knowledge, this study adopts the computational grounded theory methodological framework and employs advanced deep learning algorithms to predict core quality criteria that affect overall user experience of hypertension apps published in the Apple App Store. This study contributes to theory and practice of designing evidence-based interventions for hypertension in the form of propositions and provide valuable managerial implications and recommendations for manufacturers.

翻译：未受控制的高血压是全球亟待解决的公共卫生问题。尽管市场上存在众多移动健康解决方案，但用户对预期使用的依从性不足严重威胁着治疗效果。虽然用户体验研究是理解移动健康应用中断使用行为的重要机制之一，然而令人惊讶的是，影响高血压移动健康应用整体用户体验（即正向与负向体验）的核心决定因素尚不明确。为填补这一知识空白，本研究采用计算扎根理论方法论框架，并运用先进深度学习算法，预测影响苹果应用商店中高血压应用整体用户体验的核心质量标准。本研究以命题形式为基于证据的高血压干预方案设计提供了理论与实践贡献，同时为制造商提出了具有管理价值的建议与实践启示。