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Enregistrement W2254051982 · doi:10.2471/blt.14.142315

Including migrant populations in health impact assessments

2015· article· en· W2254051982 sur OpenAlexafffundabout
Lara Miramontes, Kevin Pottie, Maria Benkhalti Jandu, Vivian Welch, Keith E. Miller, Megan James, Janet Hatcher Roberts

Notice bibliographique

RevueBulletin of the World Health Organization · 2015
Typearticle
Langueen
DomainePsychology
ThématiqueMigration, Health and Trauma
Établissements canadiensInstitute of Population and Public HealthBruyèreUniversity of OttawaSimon Fraser University
Organismes subventionnairesCanadian Institutes of Health Research
Mots-clésEnvironmental healthMedicineGeography

Résumé

récupéré en direct d'OpenAlex

In 2010, there were 214 million international migrants worldwide, a number that is projected to double by 2050. (1) Migrants' motives for leaving their countries of origin include employment and education opportunities, escape from conflict and discrimination and the desire to raise families in economically and politically stable environments. New migrants are often healthier than the general population on arrival, but their health may deteriorate after settlement, (2) due to unfamiliar social conditions, infectious diseases, or restricted access to health services. Cultural and linguistic barriers may contribute to poor delivery of health services. The 61st World Health Assembly called on all Member States to promote migrant-sensitive health (3) Some subgroups--especially refugees--have a greater burden of infectious diseases and mental disorders than the indigenous population. (4) Guidelines have been developed to assist health workers in the clinical management of migrating populations. (4) However, there are no explicit decision-support tools for policy-makers to ensure health equity for migrants. Here we discuss how health impact assessment can account for the needs of migrant populations. Health impact assessment Health impact assessment can improve health equity by mitigating unintended harms and maximizing the benefits of programmes or policies. This approach supports decision-makers by suggesting actionable recommendations for emerging policies and programmes. (5) A number of health impact assessment tools have been developed (6) several of which have emphasized the need to consider disadvantaged population groups. However, a recent review found that only 14% of health impact assessments mentioned migrants in the evaluation and only 2% included them in their recommendations. (7) A recent consultation held at the WHO Collaborating Centre for Knowledge Translation and Health Technology Assessment in Health Equity identified four challenges to the inclusion of migrants in health impact assessment: (i) including migrants in the scope of the assessment; (ii) obtaining data on migrants; (iii) engaging migrant communities; and (iv) successfully appealing to decision-makers. Addressing the challenges Based on our own experience from developing migrant-focused guidelines in Canada, we discuss how these four challenges can be addressed. The first challenge is to include migrants in the scope of the assessment. Ideally, scoping should be deliberate and involve health researchers and community experts. In practice, however, the scope of health impact assessment is limited by timelines, political agendas and resources. Those who perform health impact assessments may only have the capacity to consider accessible populations and this may leave out migrants and other vulnerable populations. When appropriate, irregular migrants and/or refugee populations should be included in health impact assessments to maximize the value of the assessment and its recommendations. Appropriate scenarios for inclusion would include existing or future risk for inequities in migrant populations. Equity considerations should be consistent and well-defined. For example, some studies may erroneously consider ethnicity and migrant status as interchangeable. Migration, in itself, may be a unique social determinant of health distinct from ethnicity, language, culture or religion. Vulnerable subgroups of the population should be integrated within health system policies and programmes, with consideration given to historical contexts and local capacity, such as universal access to basic health care. Without explicit mention of migrants during the scoping stage, migrant populations may be forgotten in the assessment and recommendations. The second challenge is to source migrant-specific data. Migrants are heterogeneous, in terms of countries of origin, migration experiences, status, needs and abilities. …

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 enseignants

Ni 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.

score de la tête « metaresearch » (Codex)0,002
score de la tête « metaresearch » (Gemma)0,000
Version: codex-gemma-dda1882f352aStatut de validation: machine_predicted_unvalidated
Catégories candidatesCharge utile insuffisante (le modèle a refusé de juger)
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Observationnel · Signal consensuel: Observationnel
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,258
Score d'incertitude au seuil1,000

Scores Codex et Gemma par catégorie

CatégorieCodexGemma
Métarecherche0,0020,000
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0000,000
Bibliométrie0,0000,001
Études des sciences et des technologies0,0000,000
Communication savante0,0000,000
Science ouverte0,0000,000
Intégrité de la recherche0,0000,000
Charge utile insuffisante (le modèle a refusé de juger)0,0010,000

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.

Tête enseignante Opus0,103
Tête enseignante GPT0,438
Écart entre enseignants0,335 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_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 découle

Classification

machine, non validée

Prédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.

Devis d'étudeObservationnel
Domainenon disponible
GenreEmpirique

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations10
Publié2015
Routes d'admission3
Résumé présentoui

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