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BMC Public Health (2026) 26:8 BMC Public Health  \n[https://doi.org/10.1186/s12889-025-25732-3](https://doi.org/10.1186/s12889-025-25732-3)  \nSTUDY PROTOCOL Open Access  \nAdaptive engagement within a prospective registry: tracking health, occupation, and social dynamics among female sex workers in Southern Sichuan  \nQucheng Zhang 1†, Jingbo Zhang 1†, Run Chen 1†, Xiaoxue Chen 1, Ticheng Xiao2, Zhi Lei2, Ailing Li 1* and Song Fan 1*  \nAbstract  \nBackground Female sex workers (FSWs) face elevated health risks, including sexually transmitted infections (STIs), mental health challenges, and violence—often exacerbated by stigma and legal constraints in China. Longitudinal research integrating health trajectories, occupational shifts, and social support remains limited but is essential for public health response. This protocol outlines a prospective registry study of FSWs in southern Sichuan, aiming to both monitor longitudinal dynamics and evaluate an adaptive engagement strategy within the registry system. Methods This multi-center, prospective registry will be established in Luzhou, Yibin, Neijiang, and Zigong. FSWs aged 18 and older will be recruited via initial referrals from health institutions/NGOs and subsequent snowball sampling. Upon enrollment and baseline data collection, participants will be randomized (1:1) into one of two groups: (1) Standard Registry Follow-up, involving scheduled contacts (e. g., quarterly brief check-ins, annual comprehensive interviews) focused primarily on data collection; or (2) Adaptive Registry Engagement, incorporating the standard schedule plus proactive, tailored support and contact adjustments based on participant-reported needs or risk indicators identified through registry data (e. g., intensified contact following reported violence, tailored health information messages, facilitated service referrals) . Data collection will encompass field epidemiological surveys (demographics, comprehensive health status including psychological scales, social support, occupational experiences, employment, sexual behavior, narrative accounts) and integration of data from existing health systems where feasible. A modular database (Basic Information, Health Records, Narrative Data, Social Networks, Occupational Dynamics) will ensure secure and organized data management with rigorous quality control. Statistical analyses will include descriptive summaries, correlation analyses, time-series modeling, qualitative thematic analysis, mixed-  \n†Qucheng Zhang, Jingbo Zhang and Run Chen contributed equally to this paper, should be regarded as co-first authors.  \n*Correspondence: Ailing Li [306816481@qq.com](306816481@qq.com)[ ](306816481@qq.com)Song Fan [fansong@swmu.edu.cn](fansong@swmu.edu.cn)  \nFull list of author information is available at the end of the article  \n© The Author(s) 2025. Open Access This article is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License, which permits any non-commercial use, sharing, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if you modified the licensed material. You do not have permission under this licence to share adapted material derived from this article or parts of it. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit [http://creati](http://creati)[vecommons.org/l](vecommons.org/l)icenses/by-nc-nd/4.0/.  \nZhang et al. BMC Public Health (2026) 26:8 Page 2 of 9  \nmethods integra","cbCaiok2CJTAHOKT","https://ap.wps.com/l/cbCaiok2CJTAHOKT","pdf",2959900,"English","# Abstract\n## Background\n## Methods\n## Discussion\n## Keywords","[{\"question\":\"What study population and setting does the protocol target?\",\"answer\":\"The protocol recruits female sex workers aged 18 and older in southern Sichuan, using health institutions/NGOs referrals and subsequent snowball sampling across Luzhou, Yibin, Neijiang, and Zigong.\"},{\"question\":\"How do the Standard Registry Follow-up and Adaptive Registry Engagement differ?\",\"answer\":\"Standard Follow-up uses a scheduled contact approach focused on data collection, while Adaptive Engagement uses the standard schedule plus proactive, tailored support and contact adjustments based on participant-reported needs or registry-identified risk indicators.\"},{\"question\":\"What outcomes and analyses will the study use to evaluate registry performance?\",\"answer\":\"Analyses include descriptive summaries, correlation analyses, time-series modeling, qualitative thematic analysis, mixed-methods integration, path analysis, and comparative evaluations between groups on retention, data completeness, and service utilization, as well as potentially key health indicators.\"}]","Adaptive engagement within a prospective registry - Study protocol | PDF",1790629097,23]