Yoon Sungwon, Lau Rena, Kwan Yu Heng, Liu Huiyi, Sahrin Razeena, Phang Jie Kie, Zhang Yichi, Graves Nicholas, Low Lian Leng
Health Services and Systems Research, Duke-NUS Medical School, Singapore, Singapore.
Centre for Population Health Research and Implementation, SingHealth Regional Health System, Singapore, Singapore.
Digit Health. 2025 Mar 25;11:20552076251322654. doi: 10.1177/20552076251322654. eCollection 2025 Jan-Dec.
To explore the acceptability of family support through an AI-enabled mobile app and identify preferences for its novel family module features among patients with type 2 diabetes (T2DM) and family members.
Semi-structured interviews were conducted with patients with T2DM and family members. A mock wireframe of the FAMILY module was created to help participants visualize the module features. All interviews were audio-recorded and transcribed verbatim. Inductive thematic analysis using the constant-comparative method was performed to identify and interpret patterns within the data.
A total of 25 patients with T2DM and 25 family members participated in the study. Participants viewed the FAMILY module as a valuable tool for reinforcing patients' self-discipline. However, some patients expressed concerns about family involvement, particularly among those who preferred greater control and autonomy over their self-management plan. Family members also raised concerns about caregiving burden and feelings of self-blame if they were unable to provide adequate support. Regarding module features, participants appreciated algorithm-driven nudges and in-app interactions but emphasized the importance of controlling the frequency of nudges. Features such as collaborative goal setting, report cards, and AI-powered smart logging were found useful. However, family members expressed a need for more personalized in-app advice on patient data and medical terminology to better support patient's self-care. In-app family resources should be tailored to meet the needs of first-time caregivers to enhance the module's usability.
The insights from this study will guide the development of the novel FAMILY module and inform targeted interventions aimed at mitigating risks, managing T2DM-related comorbidities, and enhancing self-care.
通过一款支持人工智能的移动应用程序探索家庭支持的可接受性，并确定2型糖尿病（T2DM）患者及其家庭成员对其新型家庭模块功能的偏好。
对T2DM患者及其家庭成员进行了半结构化访谈。创建了家庭模块的模拟线框，以帮助参与者直观了解模块功能。所有访谈均进行了录音，并逐字转录。采用持续比较法进行归纳主题分析，以识别和解释数据中的模式。
共有25名T2DM患者和25名家庭成员参与了该研究。参与者将家庭模块视为加强患者自律的宝贵工具。然而，一些患者对家人的参与表示担忧，尤其是那些在自我管理计划方面更喜欢更多控制权和自主权的患者。家庭成员也对照顾负担以及如果他们无法提供足够支持时的自责感表示担忧。关于模块功能，参与者赞赏算法驱动的提醒和应用内互动，但强调控制提醒频率的重要性。协作目标设定、成绩单和人工智能驱动的智能记录等功能被认为很有用。然而，家庭成员表示需要针对患者数据和医学术语提供更个性化的应用内建议，以更好地支持患者的自我护理。应用内家庭资源应进行定制，以满足初次照顾者的需求，从而提高模块的可用性。
本研究的见解将指导新型家庭模块的开发，并为旨在降低风险、管理T2DM相关合并症以及加强自我护理的针对性干预措施提供信息。
