International research hotspots and trend on immigrant health from 2017 to 2022
Notice bibliographique
Résumé
BackgroundImmigrant health is an key node in achieving the goal of universal health coverage proposed by 2030 Agenda for Sustainable Development. The shock of severe public health emergency may exacerbate the original health-related contradictions of this group and bring more negative health effects. ObjectiveTo identify academic research hotspots and directions of immigrant health, and to examine trends in research hotspots before and after the public health emergency, so as to provide references to study immigrant health and response to public health emergency in the future. MethodsArticles (document type) included in Web of Science core collection from 2017-01-01 to 2022-12-31 were retrieved. Microsoft Excel 2019 was used for descriptive analysis of included papers. VOSviewer 1.6.19 and CiteSpace 6.1.R6 were combined to draw cooperation maps of authors, institutions, and countries/areas to understand their cooperation and communication, and to draw keywords co-occurrence map, keywords clusters map, and keywords burst map to examine the hotspots and trends of immigrant health research before and after public health emergency. ResultsA total of 5997 papers pertaining to immigrant health from 2017 to 2022 were included, and the number of publications every year were overall on the rise generating a group of productive core authors. Institutions from the United States, Canada, and Northern Europe not only tightly cooperated within their countries/areas, but also cooperated frequently among countries/areas, forming an international cooperation network with the United States as its core. The keywords co-occurrence map showed that from 2017 to 2022, the research hotspots of immigrant health mainly focused on target groups of women, children, and refugees, and the study topics of mental health, acculturation, and care. The results of cluster analysis and further extraction found that the research topics in this field were divided into five categories: maternal and child health care, acculturation and mental health, health services, health equity, and chronic disease. The keywords burst map revealed that the research hotspots shifted from ethnic group, risk behavior, and sexes to COVID-19, health equity, social isolation, and victimization under the impact of public health emergency. ConclusionThe cooperation and communication among study teams, institutions, and countries/areas have promoted the development of immigrant health study. Public health emergency has exacerbated the existing vulnerability of immigrants, and the topics related to health equity and social isolation of immigrants have raised attention becoming the research forefront. It is suggested that under the impact of public health emergency, corresponding public health policies are needed to mitigate health inequities and social support is also required for immigrants to ensure their physical and mental health.
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,008 | 0,027 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,000 |
| Méta-épidémiologie (sens large) | 0,002 | 0,003 |
| Bibliométrie | 0,060 | 0,074 |
| Études des sciences et des technologies | 0,002 | 0,001 |
| Communication savante | 0,007 | 0,006 |
| Science ouverte | 0,001 | 0,004 |
| Intégrité de la recherche | 0,001 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,014 | 0,003 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».