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Record W1997107631 · doi:10.1177/1049909110385917

The Frequency and Correlates of Spiritual Distress Among Patients With Advanced Cancer Admitted to an Acute Palliative Care Unit

2010· article· en· W1997107631 on OpenAlexaboutno aff
David Hui, Maxine de la Cruz, Steve Thorney, Henrique A. Parsons, Marvin Omar Delgado-Guay, Éduardo Bruera

Bibliographic record

VenueAmerican Journal of Hospice and Palliative Medicine® · 2010
Typearticle
Languageen
FieldSocial Sciences
TopicReligion, Spirituality, and Psychology
Canadian institutionsnot available
FundersNational Institute of Nursing ResearchNational Cancer Institute
KeywordsDistressMedicinePalliative careEmotional distressDepression (economics)Multivariate analysisUnivariate analysisOdds ratioClinical psychologyPsychiatryPsychologyInternal medicineAnxietyNursing

Abstract

fetched live from OpenAlex

Limited research is available on the frequency of spiritual distress and its relationship with physical and emotional distress. We reviewed patients admitted to our acute palliative care unit (APCU) and determined the association between patient characteristics, symptom severity using the Edmonton Symptom Assessment scale (ESAS), and spiritual distress as reported by a chaplain on initial visit. In all, 50 (44%) of 113 patients had spiritual distress. In univariate analysis, patients with spiritual distress were more likely to be younger (odds ratio [OR] = 0.96, P = .004), to have pain (OR = 1.2, P = .010) and depression (OR = 1.24, P = .018) compared to those without spiritual distress. Spiritual distress was associated with age (OR = 0.96, P = .012) and depression (OR = 1.27, P = .020) in multivariate analysis. Our findings support regular spiritual assessment as part of the interdisciplinary approach to optimize symptom control.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.025
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.003
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 head0.016
GPT teacher head0.356
Teacher spread0.341 · 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 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

Citations133
Published2010
Admission routes1
Has abstractyes

Explore more

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