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The widespread adoption of smartwatch technology has fundamentally transformed how individuals engage with physical activity. However, limited research has examined the psychological implications of intensive smartwatch use during exercise. This study investigated the cross-sectional relationship between smartwatch use intensity and social physique anxiety among adult exercisers in China, and examined whether personality traits moderate this relationship. A cross-sectional survey was conducted with 486 regular exercisers (mean age = 28.73 years, standard deviation = 7.42; 52.1% female) recruited from fitness centres in Hefei, Anhui Province, China. Participants completed validated measures including the Chinese 7-item Social Physique Anxiety Scale (C-SPAS-7), a purpose-developed Smartwatch Use Intensity Scale (SUIS), and the Big Five Inventory. Common method bias was assessed using Harman’s single-factor test. Hierarchical regression and moderation analyses were conducted using the PROCESS macro. Smartwatch use intensity was positively associated with social physique anxiety (β = 0.29, p < .001), controlling for demographic and exercise-related covariates. Neuroticism significantly moderated this association (ΔR² = 0.028, p < .001), with the association being stronger among individuals high in neuroticism. Conscientiousness also moderated the association (ΔR² = 0.012, p = .008), with the association being weaker among individuals high in conscientiousness. These findings highlight the importance of individual differences in understanding the psychological correlates of wearable technology use. Given the cross-sectional design, causality cannot be established; it remains possible that pre-existing anxiety drives more intensive technology use rather than the reverse. Individuals high in neuroticism may be particularly vulnerable to anxiety associated with intensive smartwatch use, while conscientiousness may serve as a protective factor. Although the moderation effect sizes were small (2.8% and 1.2% additional variance), they represent potentially meaningful individual differences that could accumulate over time. These results have implications for personalised fitness technology design and user wellbeing interventions.