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Record W4412918206 · doi:10.1080/10508619.2025.2536921

Resilience Processes Through Religiosity/Spirituality and Coping in a Sample of Black, Indigenous, and People of Color

2025· article· en· W4412918206 on OpenAlexaffabout
Claire J. Starrs, Vera Békés, J. Christopher Perry

Bibliographic record

VenueInternational Journal for the Psychology of Religion · 2025
Typearticle
Languageen
FieldPsychology
TopicResilience and Mental Health
Canadian institutionsMcGill UniversityUniversité du Québec à Montréal
FundersMarcus Foundation
KeywordsReligiositySpiritualityIndigenousCoping (psychology)PsychologyResilience (materials science)Sample (material)Social psychologyClinical psychologyMedicine

Abstract

fetched live from OpenAlex

Religiosity/Spirituality (RS) has been shown to be related to reduced distress following life threatening and stressful events. However, the study of RS and mental health has been confounded by its overlap with positive coping and well-being. The current study sought to extend current knowledge by examining the impact of RS on depressive and somatic symptoms and post-traumatic growth (PTG) through positive and negative coping in a sample of Black, Indigenous and People of Color (BIPOC). Online cross-sectional data were collected from 912 participants, primarily in Canada & the United States. Parallel mediation findings showed that RS predicted decreased negative coping which in turn predicted decreased symptoms. For PTG, findings supported partial mediation, with RS predicting increased positive coping and subsequent increased PTG, whilst RS continued to directly predict PTG after mediation. Findings suggest multiple-resilience processes through which RS contributes to improved mental health in BIPOC communities.

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 score0.131
Threshold uncertainty score0.245

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
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 head0.027
GPT teacher head0.442
Teacher spread0.415 · 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
Published2025
Admission routes2
Has abstractyes

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