Notice bibliographique
Résumé
Global migration is extensive and ongoing and is today an international process and an international issue affecting every country in the world [1]. As a result of global migration many countries have been transformed into multicultural societies with an increased chance of encountering migrants or those with a migrant history in health care. This can be a challenge for health professionals as disease patterns, health-related beliefs and behaviours, ability to express symptoms and signs of health and illness as well as expectations on health care providers and nursing care may differ significantly. An understanding and knowledge of the relationship between migration and health is limited; however, it is urgently needed all over the world. International migration is increasing and it is estimated that today 190 states in the world are points of origin, transit, or destination for migrants. It is also estimated that the number of migrants has risen from 82 million in 1970 to 175 million in 2000, more than doubling over the course of thirty years [2], and further into 214 million in 2010 [1]. The reasons for the increase of migration are many; in some instances these are linked to better opportunities for work and better life standards, in others to safeguarding one's life from turbulent political situations or environmental disasters. For example, one important reason for the increase of migration in Europe has been disintegration of the Soviet Union [1]. Health can be influenced by migration and several earlier ecological studies have examined health in relation to lifestyle factors and certain diagnoses of cancer in different migrant groups [3]. The increase in international migration also makes it important to study the consequences on different elements and levels of the host countries' society using a variety of research designs. The studies in this edition reflect perspectives from different countries such as Sweden, Canada, the UK, and the United States, countries to which migration is high. Two of the studies are longitudinal epidemiological studies focusing on the situation in Sweden for migrants in a long-term perspective concerning mortality and the utilization of health care (Albin et al.). The other four studies investigate the health situation for particularly vulnerable groups among migrants, women and migrant farmworkers (Babatunde et al., MacDonnell et al., Guruge et al., and Bail et al.). The latter uses a qualitative approach with focus groups interviews, grounded theory, narrative interviews in a case-study, and structured interviews. Women's mental health is highlighted in three of the studies; in one it is related to postnatal depression, in another it is discussed in relation to a history of violence and the third one is in relation to health promotion and empowerment. The fourth qualitative study illustrates how isolation from family and community, as well as perceived invisibility within institutions, for example, in health care and social service, affect health and well-being of migrant farm workers. Although the variety of migrant populations and study designs is limited, we hope that this compilation provides readers and researchers with an overview of contemporary and relevant research activity and helps them find new information in the area of migration and health. We also hope we can inspire others to use different migrant groups and research methods appropriate to the research question and further broaden the existing knowledge base so that health care professionals have the possibility to adapt their care to the needs of migrant populations. Katarina Hjelm Bjorn Albin Rosa Benato Panayota Sourtzi
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 distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,005 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 0,000 |
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 tête enseignante, 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 ».