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Record W2981533660 · doi:10.22329/csw.v10i1.5802

Exploring Spirituality in Mental Health

2019· article· en· W2981533660 on OpenAlexaffvenue
Jan-Stella Metheany, Diana Coholic

Bibliographic record

VenueCritical Social Work · 2019
Typearticle
Languageen
FieldSocial Sciences
TopicReligion, Spirituality, and Psychology
Canadian institutionsLaurentian University
Fundersnot available
KeywordsSpiritualityConceptualizationViewpointsMental healthPsychologyQualitative researchMental illnessPsychotherapistMedicineSociologyAlternative medicineSocial science

Abstract

fetched live from OpenAlex

This paper discusses the viewpoints of four psychiatrists and four social workers practicing in mental health. These participants were individually interviewed for the purposes of understanding how spirituality was being incorporated into helping/health practice with people who have serious mental illnesses. Overall, the qualitative analysis demonstrated that the participants’ perspectives were consistent with the literature in social work and spirituality. For example, participants advocated for a diverse conceptualization of spirituality and believed that an incorporation of spirituality into helping/health practices led to more effective processes. One finding that may be specific to mental health practice was the usefulness of understanding a client’s spiritual beliefs and practices in order to better understand their mental illness. Given many mental health consumers/survivors’ desire for a greater integration of their spirituality in their recovery process, practitioners and researchers are encouraged to consider how the incorporation of spirituality into mental health practices may be fostered.

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)0.008
metaresearch head score (Gemma)0.008
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 score0.008
Threshold uncertainty score0.042

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0080.008
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.001
Science and technology studies0.0080.019
Scholarly communication0.0050.003
Open science0.0010.009
Research integrity0.0020.004
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 head0.172
GPT teacher head0.437
Teacher spread0.265 · 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
Published2019
Admission routes2
Has abstractyes

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