Smartwatches are important tools for health management, yet the extent to which Health Motivation (HM) and Health Consciousness (HC) shape user preferences and behaviors is underexplored. This study contributes to the mobile human-computer interaction field by examining how these factors influence smartwatch usage and functional choices. An online survey was analyzed using exploratory factor analysis and structural equation modeling, segmenting users into three categories—Proactive Health Managers (high HM/HC), Adaptive Health Trackers (moderate HM/HC), and Passive Health Participants (low HM/HC). Proactive Health Managers favor advanced functions (e.g., workout analysis, exercise-mode recognition) and demonstrate higher health management intentions. Adaptive Health Trackers use both basic and advanced functions, adjusting engagement as needed, while Passive Health Participants rely on fundamental features (e.g., step counting, heart rate monitoring) and report lower health management involvement. These findings highlight a need for customizable features to support users with stronger motivation and simple, intuitive designs to engage those less inclined. By revealing how HM and HC affect smartwatch behaviors, this study indicates opportunities for innovation and development across industries—informing future product strategies, enhancing user experiences, and improving understanding of diverse user needs.