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Record W4292648205 · doi:10.46743/2160-3715/2022.5513

The Lived Experiences of Middle Eastern Immigrant Women During Their Cancer Survivorship Journey: A Phenomenological Study

2022· article· en· W4292648205 on OpenAlexaffabout
Enam Alsrayheen, Khaldoun Aldiabat, Catherine Aquino‐Russell

Bibliographic record

VenueThe Qualitative Report · 2022
Typearticle
Languageen
FieldSocial Sciences
TopicFamily Support in Illness
Canadian institutionsUniversité de MonctonCape Breton UniversityNova Scotia Health AuthorityUniversity of New BrunswickCape Breton Regional Hospital
Fundersnot available
KeywordsPsychosocialSurvivorship curveQualitative researchImmigrationInterpretative phenomenological analysisPsychologySocial supportHealth careGerontologyCancerMedicineSocial psychologySociologyPsychotherapist

Abstract

fetched live from OpenAlex

The number of Middle Eastern immigrant women (MEIW) living in Canada has significantly increased. However, this group of women is underrepresented in health research and there is a gap in knowledge of their cancer survivorship experiences in Canada. This phenomenological qualitative approach was employed to uncover the meaning of the lived experiences of MEIW during their cancer survivorship journey (CSJ). Data were collected through unstructured interviews and one written description from three MEIW. The participants' perspectives of cancer risk factors were believed to be the cause of their cancer, and their CSJ was fear-inducing and anxiety-provoking. There appears to be similar and homogenous lived experiences among the participants. Participants showed that their own cancer survivorship experiences were shaped by mutual contributions from different factors and circumstances. Importantly, when they talked about their experiences, they related their personal, familial, cultural and immigrational, gender, economics, social support, self-image, and other associated factors that contributed to their illness and wellness. Healthcare professionals need to identify immigrant women's unmet needs of support and psychosocial responses during their CSJ. Language-specific and culturally competent cancer-care intervention programs need development 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)0.015
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.017
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0150.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0030.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.223
GPT teacher head0.443
Teacher spread0.219 · 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.

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
Published2022
Admission routes2
Has abstractyes

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