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Record W2166014048 · doi:10.1192/pb.bp.108.019430

Religion and mental health: what should psychiatrists do?

2008· article· en· W2166014048 on OpenAlexaboutno aff
Harold G. Koenig

Bibliographic record

VenuePsychiatric Bulletin · 2008
Typearticle
Languageen
FieldSocial Sciences
TopicReligion, Spirituality, and Psychology
Canadian institutionsnot available
Fundersnot available
KeywordsMental illnessMental healthPsychological interventionPsychopathologyReferralPrejudice (legal term)PsychiatryPsychologyPsychotherapistMedicineClinical psychologySocial psychologyNursing

Abstract

fetched live from OpenAlex

Religious beliefs and practices of patients have long been thought to have a pathological basis and psychiatrists for over a century have understood them in this light. Recent research, however, has uncovered findings which suggest that to some patients religion may also be a resource that helps them to cope with the stress of their illness or with dismal life circumstances. What are psychiatrists doing with this new information? How is it affecting their clinical practices? Studies of psychiatrists in the UK, Canada and the USA suggest that there remains widespread prejudice against religion and little integration of it into the assessment or care of patients. In this paper I discuss a range of interventions that psychiatrists should consider when treating patients, including taking a spiritual history, supporting healthy religious beliefs, challenging unhealthy beliefs, praying with patients (in highly selected cases) and consultation with, referral to, or joint therapy with trained clergy (Koenig, 2007). Religion is an important psychological and social factor that may serve either as a powerful resource for healing or be intricately intertwined with psychopathology.

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)0.007
metaresearch head score (Gemma)0.027
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.016
Threshold uncertainty score0.037

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0070.027
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.001
Science and technology studies0.0040.010
Scholarly communication0.0060.008
Open science0.0010.004
Research integrity0.0090.010
Insufficient payload (model declined to judge)0.0050.001

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 head0.034
GPT teacher head0.343
Teacher spread0.308 · 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 designTheoretical or conceptual
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

Citations121
Published2008
Admission routes1
Has abstractyes

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