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Record W3059616839 · doi:10.1186/s12875-022-01682-2

Utilization of healthcare by immigrants in Canada: a cross-sectional analysis of the Canadian Community Health Survey

2022· article· en· W3059616839 on OpenAlex
Nisanthini Ravichandiran, Maria Mathews, Bridget Ryan

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueBMC Primary Care · 2022
Typearticle
Languageen
FieldPsychology
TopicMigration, Health and Trauma
Canadian institutionsUniversity of TorontoWestern University
Fundersnot available
KeywordsImmigrationHealth careMedicineCommunity healthLogistic regressionDemographyPublic healthNursingGeographySociologyPolitical science

Abstract

fetched live from OpenAlex

BACKGROUND: Immigrants to Canada face unique barriers to health care, which leads to inequities in health care utilization. Lower utilization of health care by immigrants to Canada is associated with the deteriorating health of individual immigrants as well as increased costs to the health care system. The existing literature suggests that time since immigration is an important predictor for utilization of health care for Canadian immigrants; however, few studies have included this variable in their analysis. This study aims to examine the relationships between having a regular health care provider and time since immigration, and number of medical consultations in the past year and time since immigration. METHODS: A secondary cross-sectional data analysis using Andersen and Newman's Framework of Health Service Utilization and data from the 2015-2016 Canadian Community Health Survey (CCHS) was conducted to examine health care utilization among immigrants in Canada. We used multiple logistic regression to examine the relationship between time since immigration and having a regular physician and negative binomial regression to compare the number of consultations of recent (less than 10 years since immigration) and established (10 or more years since immigration) immigrants. RESULTS: Eighty four percent of immigrant respondents to CCHS 2015-2016 had a regular health care provider. After controlling for other independent variables, established immigrants were 1.75 (95% confidence interval: 1.45-2.10) times more likely to have a regular health care provider compared to recent immigrants. Immigrants had a mean of 3.37 (standard deviation 4.53) medical consultations in the preceding year. There was no difference in the mean number of medical consultations by recent and established immigrants. CONCLUSIONS: After controlling for other independent variables, this study found that time since immigration had a significant effect on having a regular provider but not on number of consultations. Differences in health care utilization for recent and for established immigrants observed in this study may be partially explained by Canada's evolving immigration policy and the economic and social integration of immigrants over time.

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.

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)0.001
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.012
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.002
Science and technology studies0.0010.000
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 head0.070
GPT teacher head0.350
Teacher spread0.279 · 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