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Enregistrement W7028404802

Exploration of the Relationship Between Social Support and Healthcare Utilization Among Adult Immigrants to Canada

2023· dissertation· en· W7028404802 sur OpenAlexaboutno aff

Notice bibliographique

RevueScholarship at UWindsor (University of Windsor) · 2023
Typedissertation
Langueen
DomaineEngineering
ThématiquePhysics and Engineering Research Articles
Établissements canadiensnon disponible
Organismes subventionnairesnon disponible
Mots-clésHealth careImmigrationSocial supportSocial capitalPopulationSocial determinants of healthHealth services research
DOInon disponible

Résumé

récupéré en direct d'OpenAlex

Healthcare is only a protective factor regarding health outcomes if it is used. While differences exist across various populations regarding healthcare utilization, this study focuses on people born outside of Canada, specifically landed immigrants (permanent residents), using the Canadian Community Health Survey 2017/2018 (CCHS). Those born outside of Canada are an increasingly large segment of the Canadian population. Therefore, their healthcare use represents an increasing portion of healthcare utilization. For a variety of sociodemographic and systemic reasons, utilization rates for this population are likely to vary. This study explores two potentially protective factors and their interaction in predicting healthcare access, and ultimately utilization: social support and length of time in country. An exploration of the predictive power of social support was undertaken the lenses of social cognitive and social capital theories. These theories come together to help understand motivations for and supports of healthcare utilization.\nThe three hypotheses in this study were: social support and the length of time in country both protectively predict health care utilization (i.e., new(er) comers were at relative risk of low healthcare utilization), and social support and time in country interact such that the protective effect of social support is larger among more potentially vulnerable or at-risk people who landed more recently (i.e., new(er)comers). Each hypothesis was systematically tested across three outcome indicators of healthcare utilization: has a regular healthcare provider, has a place to go for a minor health problem, has an unmet healthcare need. Outcome descriptions suggested that 10% to 20% of landed immigrants (permanent residents) may not be utilizing healthcare as per the variables chosen in this study.\nThe unique, diverse and potentially underserviced (but with noted strengths and resiliencies), study sample of 3,977 adult landed Canadian immigrants was observed to be demographically vulnerable (prevalent racialized people and those speaking other than an official language), yet relatively well educated and healthy with relatively strong social supports compared with other Canadian residents. Furthermore, within this unique and diverse sample, more recent immigrants (landed less than 10 years ago) were even more demographically vulnerable, and additionally socioeconomically vulnerable, yet still relatively healthy and reporting high levels of social supports. Among relative newcomers, those with strong social supports were 56% more likely than those less well supported to have ready healthcare access. However, this protective association was not observed among those who landed more than 10 years ago.\nFindings suggest that social support has implications for healthcare utilization, and even more implications for the most vulnerable, more recently arrived immigrants to Canada. Subsequently, harnessing social support for increased healthcare utilization can be a powerful in the support of healthy communities. This study culminates in recommendations for social work research, practice, and education, allowing for current and future social workers and educators to best understand how to connect to clients at the intersections of these critical issues. In finding creative solutions, like increased social support, to better access and utilize healthcare, social workers can approach clients from strength based, anti-oppressive approaches that are at the core of our profession.

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)0,000
score de la tête « metaresearch » (Gemma)0,000
Version: codex-gemma-dda1882f352aStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
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 enseignants0,548
Score d'incertitude au seuil0,962

Scores Codex et Gemma par catégorie

CatégorieCodexGemma
Métarecherche0,0000,000
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)0,0000,000

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 Opus0,055
Tête enseignante GPT0,261
Écart entre enseignants0,206 · 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.

Les modèles n’ont appliqué aucune catégorie : rien dans la taxonomie ne correspondait à ce travail.
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

Citations0
Publié2023
Routes d'admission1
Résumé présentoui

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