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Record W4362471619 · doi:10.5430/ijh.v9n1p38

Immigrant women cancer survivors’ perceptions of healthcare services in Canada: A phenomenological study

2023· article· en· W4362471619 on OpenAlexaffabout
Enam Alsrayheen, Khaldoun Aldiabat, Catherine Aquino‐Russell

Bibliographic record

VenueInternational Journal of Healthcare · 2023
Typearticle
Languageen
FieldMedicine
TopicCancer survivorship and care
Canadian institutionsCape Breton UniversityNova Scotia Health AuthorityUniversity of New BrunswickCape Breton Regional Hospital
Fundersnot available
KeywordsPsychosocialHealth careSurvivorship curveEmpowermentImmigrationMeaning (existential)Qualitative researchNursingPsychologyInterpretative phenomenological analysisMedicineGerontologyCancerSociologyPsychotherapistPolitical science

Abstract

fetched live from OpenAlex

Middle Eastern immigrant women (MEIW) living in Canada have significantly increased. However, this group of women is under-represented in health research, and there is a gap in knowledge about their experiences when they access healthcare services for cancer care in Canada. This qualitative approach was conducted to uncover the meaning of the lived experiences of MEIW with healthcare services in Canada during their cancer survivorship (CS). Data were collected through unstructured interviews and one written description from three MEIW. Data were analyzed using a descriptive phenomenological approach developed by Giorgi. Four themes emerged to represent the essence (or meaning) of the participants’ lived experiences. Their healthcare was accompanied with delays and unmet needs. Yet, they found it helpful when they were provided with knowledge and information. The ability to communicate in English was equal to empowerment for each of them, while they faced cultural stigmatization of mental health issues. Thus, healthcare professionals need to identify immigrant women’s unmet support needs and psychosocial responses during their cancer survivorship. Language-specific and culturally competent cancer-care intervention programs must be developed within the Canadian healthcare system.

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)0.001
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 score0.160
Threshold uncertainty score0.696

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
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 head0.029
GPT teacher head0.348
Teacher spread0.319 · 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 designObservational
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
Published2023
Admission routes2
Has abstractyes

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