Evidence map›Paper›PMID 41286780›Full record

ArticleBMC public health2025

Adaptive engagement within a prospective registry: tracking health, occupation, and social dynamics among female sex workers in Southern Sichuan.

Qucheng Zhang, Jingbo Zhang, Run Chen, Xiaoxue Chen, Ticheng Xiao, Zhi Lei, Ailing Li, Song Fan

Abstract read
In one paragraph

Article in BMC public health, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

8 authors.

Qucheng Zhang *School of Public Health, Southwest Medical University, Luzhou City, Sichuan Province, 646000, China.
Jingbo Zhang *School of Public Health, Southwest Medical University, Luzhou City, Sichuan Province, 646000, China.
Run Chen *School of Public Health, Southwest Medical University, Luzhou City, Sichuan Province, 646000, China.
Xiaoxue ChenSchool of Public Health, Southwest Medical University, Luzhou City, Sichuan Province, 646000, China.
Ticheng XiaoLuzhou Center for Disease Control and Prevention, Luzhou, China.
Zhi LeiLuzhou Center for Disease Control and Prevention, Luzhou, China.
Ailing LiSchool of Public Health, Southwest Medical University, Luzhou City, Sichuan Province, 646000, China. 306816481@qq.com.
Song FanSchool of Public Health, Southwest Medical University, Luzhou City, Sichuan Province, 646000, China. fansong@swmu.edu.cn.

Funding

the Ministry of Education Humanities and Social Science Project 24XJCZH002
6 · The paper itself

Abstract

backgroundFemale 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.

methodsThis 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-methods integration, path analysis, and comparative analyses between the two engagement groups on outcomes like retention, data completeness, service utilization, and potentially key health indicators. DISCUSSION: This study is the first to implement a prospective registry for FSWs in Southwest China and uniquely embeds an evaluation of engagement models. By comparing standard and adaptive follow-up approaches, the study examines whether personalized contact improves registry performance and participant support. Findings will generate critical longitudinal insights and guide future research, interventions, and policies tailored to vulnerable populations, while addressing the contextual challenges of implementation in China.

Indexed as

Health StatusRegistriesSex WorkersAdultChinaFemaleGroup DynamicsHumansProspective StudiesSocial SupportYoung AdultAdaptive engagementChinaFemale sex workersHealth dynamicsLongitudinal studyOccupational risksProspective cohortRegistry databaseSocial support

Identifiers

PMID41286780
PMCPMC12764112

What OpenQuestion holds

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LicenceCC BY-NC-ND
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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.