ArticleFrontiers in public health2026
Primary healthcare professionals' perspectives on mobility limitation assessment and predictive model optimization for community-dwelling older adults: a qualitative research.
Article in Frontiers in public health, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
Background: Mobility limitation is an important public health challenge faced by ageing populations. However, standardized assessment tools remain lacking in primary care practice in China, and existing predictive models still face substantial implementation gaps in clinical translation. This qualitative study aimed to explore frontline primary healthcare professionals' perceptions of current assessment practices and to provide recommendations for optimizing and clinically translating related predictive models. Methods: A descriptive qualitative study was conducted in January 2026 among 15 frontline primary healthcare professionals in Dongguan City, China. Participants were recruited using maximum variation purposive sampling supplemented by snowball sampling. Semi-structured face-to-face interviews were analyzed using thematic analysis with NVivo 15. Results: Interviews with 15 community healthcare professionals (general practitioners, community nurses, and public health physicians) identified barriers, facilitators, and specific requirements for clinical implementation. Four principal themes emerged: (i) the current practice of assessment and perceived clinical value; (ii) feedback on model optimization and visions for diversified application; (iii) multidimensional barriers to clinical translation of the model; and (iv) creating a closed-loop support system with the older adults at the center. Conclusion: The findings show that primary healthcare professionals highly value assessment of mobility limitation, yet their assessment practices are inconsistent, and multiple barriers impede clinical translation. Future efforts should prioritize development of localized, intelligent, and cost-effective models and the establishment of a closed-loop management pathway spanning risk warning through follow-up.
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