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Record W4417517186 · doi:10.1163/2161007x-bja10036

Faith-Inclusive Care in Canada During covid-19: A Qualitative Study of Mental Health Professionals’ Perspectives and Immigrant Clients’ Experiences

2025· article· W4417517186 on OpenAlexaboutno aff
Sandra Dixon, Juliane Bell

Bibliographic record

VenueCounseling and Values · 2025
Typearticle
Language
FieldSocial Sciences
TopicReligion, Spirituality, and Psychology
Canadian institutionsnot available
Fundersnot available
KeywordsImmigrationFaithAcculturationQualitative researchMental healthCultural competenceCompetence (human resources)Health careCoping (psychology)

Abstract

fetched live from OpenAlex

Abstract Canada’s diverse cultural landscape, shaped by immigration, presents a complex array of mental health concerns, including anxiety, depression, trauma, and acculturative stress, which were further exacerbated by the covid -19 pandemic. For many immigrants in Canada, faith is a vital source of comfort, meaning-making, community, and spiritual support. Yet, spiritual beliefs and practices are often overlooked in therapeutic contexts. This descriptive qualitative research study explores the experiences of immigrant clients of faith in counseling in Alberta, Canada through semi-structured interviews with 10 immigrant clients and 10 mental health professionals ( mhp s). These insights revealed the complex interplay between migration challenges and spiritual beliefs, underscoring the need for faith-inclusive care for immigrant clients and enhancing the faith competence of mhp s.

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)0.004
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 score0.140
Threshold uncertainty score0.344

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.006
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.002
Science and technology studies0.0220.011
Scholarly communication0.0050.001
Open science0.0020.005
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0020.000

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 head0.026
GPT teacher head0.429
Teacher spread0.403 · 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
Published2025
Admission routes1
Has abstractyes

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