Evidence map›Paper›PMID 37887160›Full record

ArticleEuropean journal of investigation in health, psychology and education2023

Factors in Immigrant Children's Use of Physician and Dentist Visits, Hospital Care, and Prescribed Medication in the United States.

Tyrone C Cheng, Celia C Lo

Abstract read
In one paragraph

Article in European journal of investigation in health, psychology and education, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. Article
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.

Tyrone C ChengSchool of Social Work, University of Alabama, Little Hall, Tuscaloosa, AL 35401, USA.ORCID 0000-0002-2335-1677
Celia C LoPeraton, Defense Personnel and Security Research Center, Seaside, CA 93955, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Applying the behavioral model of health services utilization to data from the United States, this study examined immigrant children's use of physician and dentist visits, hospital care, and prescribed medication. We employed data describing 9759 immigrant parents and children who participated in 2021's National Survey of Children's Health. Logistic regression results negatively linked physician visits to child health, child age, Asian children, fathers, lower parent education, lower family income, uninsured children, and parent's U.S. residence under 5 years. Dentist visits were positively associated with child age, girls, Hispanic children, parent education, family income, public/private health insurance coverage, and U.S.-born children, but such use was associated negatively with Asian children. Hospital use was positively associated with poor child health, Black children, children of "other" race/ethnicity, younger parent age, enrolled in health insurance, and parent's U.S. residence under 5 years. The use of prescribed medication was negatively associated with Asian children, younger child age, lower parent education, uninsured child, and lack of English proficiency. The paper's conclusion suggests policymakers expand Medicaid and CHIP eligibility among immigrant children and suggests community education to foster awareness of children's physical and oral health needs and of Medicaid, CHIP, and prescription assistance programs. The conclusion calls for healthcare providers and social workers to accommodate and respect immigrants' traditional health-related beliefs, showing cultural competence.

Indexed as

dentist visitshospital careimmigrant childrenphysician visitsprescribed medication

Identifiers

PMID37887160
PMCPMC10606864

What OpenQuestion holds

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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.