Evidence map›Paper›PMID 39604578›Full record

ArticleScientific reports2024

Impact of family doctor contracted services on the health of migrants: a cross-sectional study in China.

Sijia Liu, Jiajing Hu

Abstract read
In one paragraph

Article in Scientific reports, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing 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

4 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
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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

2 authors.

Sijia LiuSchool of Health Management, Inner Mongolia Medical University, Hohhot, 010100, China.
Jiajing HuSchool of Health Management, Inner Mongolia Medical University, Hohhot, 010100, China. hujiajing@immu.edu.cn.

Funding

The Project for Young Scientists Foundation of Inner Mongolia Medical University YKD2021QN038The Youth Natural Science Foundation of Inner Mongolia 2022QN07001
6 · The paper itself

Abstract

This study investigates the impact of the family doctor contracted service system on the health of migrants in China, utilizing data from the 2018 China Migrants Dynamic Survey (CMDS). The study employs a double machine learning model to estimate the effect of family doctor contracted services (FDCS) on migrants' self-rated health (MSRH). The sample consists of 137,851 migrants, with family doctor service contract status, health education, and health records as key variables. To address potential endogeneity issues, an instrumental variable approach using the regional family doctor contracting rate was implemented. Mediation analysis was conducted to examine the roles of health education and health records in this relationship. The findings indicate that FDCS significantly improve MSRH. This positive effect is robust across various machine learning models, including Lassocv, Random Forest, and Gradient Boost. The instrumental variable approach confirms the validity of these results, mitigating concerns about endogeneity. Mediation analysis reveals that the positive impact of FDCS on MSRH is fully mediated by health education and health records, highlighting their critical roles in enhancing health outcomes. The FDCS play a crucial role in improving the health of migrants by providing continuous and comprehensive care. Enhanced health education and effective health records management are significant pathways through which these services exert their positive effects. Policy recommendations include expanding access to family doctor services, enhancing health education programs, and improving health records management to optimize healthcare delivery for migrants. Future research should consider longitudinal studies to further validate these findings and explore their applicability to specific subgroups or regions.

Indexed as

Transients and MigrantsAdolescentAdultChinaContract ServicesCross-Sectional StudiesFemaleHealth EducationHealth StatusHumansMachine LearningMaleMiddle AgedPhysicians, FamilySurveys and QuestionnairesYoung AdultChina migrant dynamic surveyDouble machine learningFamily doctor contracted servicesHealth educationHealth recordsMigrant populationSelf-rated health

Identifiers

PMID39604578
PMCPMC11603316

What OpenQuestion holds

Textmetadata
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.