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Record W3165685290 · doi:10.1136/bmjspcare-2021-003090

Spiritual distress: symptoms, quality of life and hospital utilisation in home-based palliative care

2021· article· en· W3165685290 on OpenAlexaboutno aff
Andre Cipta, Bethany Turner, Eric C. Haupt, Henry Werch, Lynn F. Reinke, Richard A. Mularski, Huong Q. Nguyen

Bibliographic record

VenueBMJ Supportive & Palliative Care · 2021
Typearticle
Languageen
FieldSocial Sciences
TopicReligion, Spirituality, and Psychology
Canadian institutionsnot available
FundersPatient-Centered Outcomes Research Institute
KeywordsPalliative careDistressQuality of life (healthcare)MedicineNursingSpiritual carePsychologyAlternative medicineClinical psychologySpirituality

Abstract

fetched live from OpenAlex

OBJECTIVES: The purpose of this study was to use a spiritual screening question to quantify the prevalence of spiritual distress (SD) in a large cohort of seriously ill patients at admission to home-based palliative care (HBPC) and to examine the associations between SD with symptom burden, quality of life and hospital-based utilisation up to 6 months after admission to HBPC. METHODS: Data for this cohort study (n=658) were drawn from a pragmatic comparative-effectiveness trial testing two models of HBPC. At admission to HBPC, SD was measured using a global question (0-10-point scale: none=0; mild=1-4; moderate-to-severe=5+); symptoms and quality of life were measured with the Edmonton Symptom Assessment Scale (ESAS) and PROMIS-10. Hospital utilisation was captured using electronic records and claims. Median regression and proportional hazard competing risk models assessed the association between SD with symptoms and quality of life, and hospital utilisation, respectively. RESULTS: Nearly half of the patients/proxies reported some level of SD. Increasing SD was significantly associated with higher symptom burden (increase of 7-14 points on ESAS) and worse mental well-being (decrease of 2.7 to 4.6 points on PROMIS-10-mental) in adjusted models. Compared with patients/proxies who reported no SD, those with at least some level of SD were not at increased risk for hospital-based utilisation over a median follow-up period of 2 months. CONCLUSION: While SD is cross-sectionally associated with worse symptoms and mental well-being, it did not predict downstream hospital-based utilisation. Our results highlight the importance of assessing for and managing SD in patients with serious illness.

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)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.117
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
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 head0.059
GPT teacher head0.405
Teacher spread0.346 · 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

Citations6
Published2021
Admission routes1
Has abstractyes

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