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Record W2168501553 · doi:10.1155/2012/621914

Migration and Health

2012· article· en· W2168501553 on OpenAlexaboutno aff
Katarina Hjelm, Björn Albin, Rosa Benato, Panayota Sourtzi

Bibliographic record

VenueNursing Research and Practice · 2012
Typearticle
Languageen
FieldPsychology
TopicMigration, Health and Trauma
Canadian institutionsnot available
Fundersnot available
KeywordsSafeguardingHealth careMedicineGlobal healthEconomic growthPublic healthNursing

Abstract

fetched live from OpenAlex

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

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.005
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.571
Threshold uncertainty score0.336

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0050.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.279
GPT teacher head0.580
Teacher spread0.301 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations2
Published2012
Admission routes1
Has abstractyes

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