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Record W7072237079

UNDERSTANDING HEALTH LITERACY REGARDING THE CANADIAN HEALTH CARE SYSTEM UPON SETTLEMENT OF ISMAILI MUSLIM CANADIANS: A NARRATIVE STUDY

2011· article· en· W7072237079 on OpenAlexaboutno aff

Bibliographic record

VenueScholarship@Western (Western University) · 2011
Typearticle
Languageen
FieldPsychology
TopicMigration, Health and Trauma
Canadian institutionsnot available
Fundersnot available
KeywordsHealth literacySettlement (finance)Health careNarrativeImmigrationLiteracyPopulationPsychological interventionQualitative research
DOInot available

Abstract

fetched live from OpenAlex

Health literacy is an individual's ability to read, understand, and use health care information to make\ninformed health decisions for treatment (Kwan, Frankish, & Rootman, 2006). Health literacy studies worldwide have increased dramatically within the past decade in response to concerns about the populations that are at risk and the need to target effective interventions for them. Canadian censuses have utilized the International Adult Literacy and Life Skills Survey (IALLS) to examine Canadian health literacy rates and found that the most high-risk populations are older adults, immigrants, and the chronically unemployed. However, when researching the topic of health literacy, there was little information from the high-risk population themselves, few longitudinal studies, little research about possible interventions, nor was there consistent use of a single definition of health literacy. Being an Ismaili Muslim and understanding their history of migration, I wanted to ground my study through my family's experiences of having to move from East Africa to Canada in 1972. My goal was to gain a better understanding of the post-immigration experiences of the Canadian health care system in comparison to the pre-immigration expectations among older Ismaili Muslim adults, to discover how health literacy affected health seeking behaviours during immigrant settlement in Canada for this group, and to explore the effects of cultural capital, or the non-financial resources that assist in social and economic means, to determine how it assisted or hindered the successful settlement process of Ismaili Muslims within Canada.\nThe research was a narrative inquiry using in-depth, semi-structured interviews to get thick descriptions of the experiences of four Ismaili Muslim older adults who moved to Canada in 1972, their experiences of using the Canadian health care system for the first time, and their thoughts on the topic of health literacy. Their experiences and suggestions, detailed in their stories to live by, expanded the knowledge on the topic of health literacy by explaining possible interventions that have yet to be mentioned in research.\niii\nAs a result of the study, four key considerations emerged: communication strategies applied in health literacy are not successfully targeting the immigrant population; there was confusion about the Canadian health care system, especially relating to the tiers of health care and the limits of OHIP coverage; the Ismaili population utilized the resource of cultural capital to assist in their settlement experiences and stressed the importance of comfort, trust, and sensitivity when taking advice from individuals about the health care system; and knowledge exchange about health literacy is vital for health professionals and patients, as well as other groups, to understand the importance of this topic.\nThe key considerations from the study have important implications for newly arrived immigrants and the Canadian health care system. The study suggests supplementing the typical quantitative surveys with rich, qualitative literature and targeting interventions particularly to the groups that require immediate attention. This study displays the importance of providing the immigrant population with a voice and an opportunity to describe their experiences about the health care system and the topic of health literacy.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.003
metaresearch head score (Gemma)0.006
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.064
Threshold uncertainty score0.465

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.006
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.003
Science and technology studies0.0320.009
Scholarly communication0.0060.002
Open science0.0020.005
Research integrity0.0020.005
Insufficient payload (model declined to judge)0.0040.000

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 head0.229
GPT teacher head0.373
Teacher spread0.144 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designQualitative
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

Citations0
Published2011
Admission routes1
Has abstractyes

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