Evidence map›Paper›PMID 33453725›Full record

ArticleBMC family practice2021

Health education services utilization and its determinants among migrants: a cross-sectional study in urban-rural fringe areas of Beijing, China.

Shuang Shao, Huirong Zhang, Xiaolei Chen, Xiaojingyuan Xu, Yali Zhao, Meirong Wang, Juan Du

Open access · goldAbstract read
In one paragraph

Article in BMC family practice, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 26 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
26citing papers in PubMed, 1 pooled it
6.1field-weighted citation impact, top 3% of its field
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

26 citing papers in PubMed, 1 synthesis or guideline pooled it, 35 citations in OpenAlex.

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  20. The Impact of Public Health Education on Migrant Workers' Medical Service Utilization.International journal of environmental research and public health · 2022
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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

7 authors at 2 institutions in 1 country.

Shuang ShaoSchool of General Practice and Continuing Education, Capital Medical University, Beijing, 100069, China.
Huirong ZhangHospice Care Ward, Beijing geriatric hospital, Beijing, 100095, China.
Xiaolei ChenSchool of General Practice and Continuing Education, Capital Medical University, Beijing, 100069, China.
Xiaojingyuan XuSchool of General Practice and Continuing Education, Capital Medical University, Beijing, 100069, China.
Yali ZhaoSchool of General Practice and Continuing Education, Capital Medical University, Beijing, 100069, China.
Meirong WangSchool of General Practice and Continuing Education, Capital Medical University, Beijing, 100069, China.
Juan DuSchool of General Practice and Continuing Education, Capital Medical University, Beijing, 100069, China. cuckoo@ccmu.edu.cn.
Capital Medical University · CNBeijing Geriatric Hospital · CN

Funding

National Planning Office of Philosophy and Social Science (CN) 15SHC035
6 · The paper itself

Abstract

backgroundDomestic migration poses a challenge for China as migrants have little access to preventive healthcare services and are vulnerable to certain risks and diseases. This research sought to unveil and explore the determinant factors associated with health education utilization as a key aspect in basic public health services for migrants in Beijing, China.

methodsA sample of 863 inter-provincial migrants, 18 years old and above, was selected by three-stage stratified cluster sampling method in urban-rural fringe areas of Beijing during 2016 to 2017. Face-to-face structured interviews were conducted in the questionnaire survey. The effects of the explanatory variables on health education utilization from predisposing, enabling, health behaviors and need variables were used to demonstrate by Anderson health service utilization model.

resultsThe study revealed that 61.6% migrants desired to receive health education, while only 53.8% of them received in the past year. There were differences in the utilization and needs of health education among the migrants in different ages and genders. Many migrants desired to gain access to various types of health education information from the internet. Chi-square independence test lists such major determinant factors in migrants whole health education as age, "Hukou" registration system, marital status, education level, long-term residence plan in Beijing, one or more children in Beijing, employment status, housing source, average daily working time, exercises, health knowledge, smoking, self-rated health. The binary logistic regression indicates that the migrants with younger age, high education level, one or more children in Beijing, exercises and good self-rated health were more likely to receive whole health education. The results also show that average daily working time of enabling variables and exercise of health behavior variables were the strong and consistent determinants of three types of health education utilization, including communicable, non-communicable and occupational diseases.

conclusionGaps exist between the needs and utilization in health education and more attention should be given to the migrants with heavy workload and low education level. Feasible policies and measures, such as multiple health information channels, should be vigorously implemented to ensure equitable and easy access to health education for migrants.

Indexed as

Transients and MigrantsBeijingChinaCross-Sectional StudiesFacilities and Services UtilizationFemaleHealth EducationHumansMaleRural PopulationAnderson health service utilization behavioral modelDeterminant factorsHealth education utilizationMigrants

Identifiers

PMID33453725
PMCPMC7811350
OpenAlexW3121494155

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.