In China, the structural contradiction between surging health management demands and an insufficient high-quality supply has driven the need for smart health management services. By leveraging information and communication technology (ICT) alongside artificial intelligence (AI), these services integrate the entire process of health monitoring, assessment, and intervention, emerging as a critical new area of demand.

To systematically analyze the current usage, demands, and influencing factors of smart health management services and devices among adult residents in China, thereby providing an evidence base and strategic recommendations for their sustainable development.

An explanatory sequential mixed-methods design was employed. Quantitative data were collected from September to December 2023 using a stratified cluster random sampling method. Adults aged 18 and above were surveyed via the Wenjuanxing platform. The questionnaire captured demographic characteristics and utilized standardized scales alongside self-developed items to measure eHealth literacy, media motivation, attitude toward the behavior, subjective norms, perceived behavioral control, as well as the demands, behavioral intentions, and actual usage behaviors regarding smart health management services. Structural equation modeling (SEM) was applied to analyze the influencing factors. Qualitative data were gathered from May 2024 to March 2025 through one-on-one, semi-structured interviews. The interviews explored participants' basic profiles, personalized demands, usage experiences with smart health management monitoring devices, service model preferences, and feedback. Finally, an explanatory sequential mixed-methods framework was utilized to integrate and interpret the quantitative and qualitative results.

A total of 2 900 questionnaires were distributed, yielding 2 786 valid responses (effective recovery rate: 96.1%). Thirteen individuals participated in the qualitative interviews. Findings revealed: (1) The usage rate of smart health management monitoring devices among adult residents in China was 37.7% (1 051/2 786), demonstrating a declining trend with age, with significantly lower usage among the elderly. (2) User demands exhibited multi-level and age-stratified characteristics. Overall demands were concentrated on basic functions such as health monitoring and answering health queries; qualitative research further revealed a progressive demand model ranging from basic life management to empowered self-actualization. Younger groups preferred basic prevention and lifestyle optimization, whereas older groups focused more on practical functions like disease management. (3) The intention to use was at a moderately high level (62.68±20.65). SEM results indicated that attitude toward the behavior (β=0.568, P<0.001) was the strongest predictor of intention, while subjective norms (β=0.103, P<0.001), and media motivation (β=0.089, P<0.001) also had significant positive effects. eHealth literacy indirectly influenced both intention (β=0.045, P<0.001) and usage behavior (β=0.051, P<0.001) through media motivation. Perceived behavioral control indirectly affected intention (β=0.014, P<0.001) and usage behavior (β=0.016, P<0.001). Urban residence independently and positively affected intention (β=0.056, P<0.001) and usage behavior (β=0.125, P<0.001), and having medical insurance significantly promoted intention (β=0.039, P=0.008). Qualitative findings identified that usage barriers included objective factors (e.g., high costs, product quality issues) and perceived obstacles (e.g., discomfort in wearing, privacy concerns). User attitudes were significantly polarized; positive or negative evaluations stemmed directly from usage experience, perceived benefits, and product intelligence, whereas individuals with neutral attitudes were prone to abandonment due to a lack of clear perceived value. Furthermore, personal beliefs and cultural backgrounds profoundly influenced technological decision-making.

This study reveals that smart health management services among Chinese adults are characterized by high intention but low usage, with age-stratified differences in current usage and demand structures. Regarding influencing mechanisms, attitude toward behavior and subjective norms are the core drivers of intention. eHealth literacy and media motivation exert a significant serial mediating effect, while perceived barriers constitute the primary resistance to behavioral transformation. Future promotion of smart health services should emphasize age-friendly design and precision implementation, while leveraging the synergistic role of primary healthcare to bridge the intention-behavior gap. This approach will enhance adults' proactive health management capabilities and facilitate the goal of healthy aging.

我国健康管理面临需求激增与优质供给不足的结构性矛盾，使得依托信息通信与人工智能技术，整合健康监测、评估、干预全流程的智慧健康管理服务成为新需求点。

系统解析我国成年居民智慧健康管理服务与设备的使用现状、需求及影响因素，为智慧健康管理服务长足发展提供证据基础和策略建议。

本研究采用解释性序列混合研究方法整合定量和定性研究结果。2023年9—12月开展定量研究数据收集，采用分层整群随机抽样方法选取18岁以上成年居民，基于问卷星平台实施调查。问卷内容涵盖一般人口学特征，并采用标准化量表及自编条目对电子健康素养、媒介动机、行为态度、主观规范、知觉行为控制，以及智慧健康管理服务的使用需求、意愿与实际使用行为进行测定。应用结构方程模型分析智慧健康管理服务使用意愿和使用行为影响因素。定性研究于2024年5月—2025年3月展开，由访谈员与访谈对象进行一对一、半结构化访谈。访谈内容包括：调研对象基本情况、智慧健康管理服务的个性化需求、智能健康管理监测设备使用情况及体验、智慧健康管理服务模式偏好以及建议反馈。最后，采用解释性序列混合研究方法对定量数据结果与定性访谈结果进行整合解释。

定量研究共计发放问卷2 900份，回收有效问卷2 786份，有效问卷回收率为96.1%。定性研究共13位访谈对象。研究发现：（1）我国成年居民智能健康管理监测设备使用率为37.7%（1 051/2 786），且随年龄增长呈下降趋势，老年群体使用率显著偏低。（2）使用需求呈现多层次与年龄分化的特征，整体需求集中于健康监测与解答健康问题等基础功能；定性研究进一步揭示了从基础生活管理到赋能自我实现的进阶需求。青年群体偏好基础预防和生活方式优化，老年群体更关注疾病管理等实用功能。（3）使用意愿处于中等偏上水平[（62.68±20.65）分]。结构方程模型结果显示，行为态度（β=0.568，P<0.001）是使用意愿的最强预测因子，主观规范（β=0.103，P<0.001）、媒介动机（β=0.089，P<0.001）也有正向作用。电子健康素养通过媒介动机影响使用意愿（β=0.045，P<0.001）和使用行为（β=0.051，P<0.001），知觉行为控制通过媒介动机间接影响使用意愿（β=0.014，P<0.001）和使用行为（β=0.016，P<0.001）。居住地为城镇对使用意愿（β=0.056，P<0.001）和使用行为（β=0.125，P<0.001）均存在独立正向作用，医保显著促进使用意愿（β=0.039，P=0.008）。定性研究发现，成年人智能健康管理监测设备的使用障碍既包括费用高和产品质量问题等客观因素，也包括对佩戴舒适度与隐私安全的担忧。成年人对智能健康管理监测设备的态度呈现显著分化，其积极或消极评价直接源于使用体验、感知获益及产品智能化水平，态度中性者则因未能感受到明确价值而易弃用。此外，个人观念与文化背景也深刻影响技术决策。

本研究揭示了我国成年居民智慧健康管理服务存在高意愿度、低使用率的特征，且使用现状与需求结构具有年龄分层差异。在影响因素方面，行为态度与主观规范是驱动意愿的核心要素，电子健康素养与媒介动机发挥了显著的链式促进作用，感知障碍是限制行为转化的主要阻力。未来智慧健康服务的推广应注重适龄化设计与精准化实施，同时应发挥基层医疗的协同作用，切实弥合技术使用意愿与实际行为之间的差距，从而增强成年人主动健康管理能力，助力实现健康老龄化目标。