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Record W3110349749 · doi:10.3390/ijerph17238724

Patient-Reported Experiences in Accessing Primary Healthcare among Immigrant Population in Canada: A Rapid Literature Review

2020· review· en· W3110349749 on OpenAlexafffundabout
Bishnu Bahadur Bajgain, Kalpana Thapa Bajgain, Sujan Badal, Fariba Aghajafari, Jeanette Jackson, Maria Santana

Bibliographic record

VenueInternational Journal of Environmental Research and Public Health · 2020
Typereview
Languageen
FieldPsychology
TopicMigration, Health and Trauma
Canadian institutionsUniversity of Calgary
FundersCumming School of Medicine, University of Calgary
KeywordsImmigrationPrimary carePrimary health careHealth careMedicineFamily medicinePopulationNursingPsychologyPolitical scienceEnvironmental health

Abstract

fetched live from OpenAlex

(1) Background: Immigrants represent around 21.9% of the total population in Canada and encounter multifaceted obstacles in accessing and receiving primary healthcare. This literature review explores patient experiences in primary care from the perspective of immigrants and identifies areas for further research and improvement. (2) Methods: A comprehensive search was performed on PubMed, MEDLINE, Embase, SCOPUS, and Google scholar to identify studies published from 2010 to July 2020. Relevant articles were peer-reviewed, in English language, and reported patient experiences in primary healthcare in Canada. (3) Results: Of the 1566 searched articles, 19 articles were included in this review. Overall, the finding from articles were summarized into four major themes: cultural and linguistic differences; socioeconomic challenges; health system factors; patient-provider relationship. (4) Conclusion: Understanding the gaps to accessing and receiving appropriate healthcare is important to shape policies, enhance the quality of services, and deliver more equitable healthcare services. It is therefore pertinent that primary healthcare providers play an active role in bridging these gaps with strong support from policymakers. Understanding and respecting diversity in culture, language, experiences, and systems is crucial in reducing health inequalities and improving access to quality care in a respectful and responsive manner.

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)0.002
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: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.977
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.002
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 head0.106
GPT teacher head0.432
Teacher spread0.327 · 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 designOther design
Domainnot available
GenreReview

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

Citations41
Published2020
Admission routes3
Has abstractyes

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