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Record W4399324808 · doi:10.1136/spcare-2024-004940

Psychological distress and physical symptoms in advanced cancer: cross-sectional study

2024· article· en· W4399324808 on OpenAlexaboutno aff
Bridget Podbury, Taylan Gurgenci, Georgie Huggett, Ristan M. Greer, Janet Hardy, Phillip Good

Bibliographic record

VenueBMJ Supportive & Palliative Care · 2024
Typearticle
Languageen
FieldMedicine
TopicCancer survivorship and care
Canadian institutionsnot available
Fundersnot available
KeywordsAnxietyDepression (economics)NauseaMedicineQuality of life (healthcare)DASSPopulationDistressCancerPhysical therapyPsychiatryClinical psychologyInternal medicine

Abstract

fetched live from OpenAlex

OBJECTIVES: Patients with advanced cancer experience varying physical and psychological symptoms throughout the course of their illness. Depression, anxiety and stress affect overall well-being. This study investigates the correlation between emotional distress and physical symptoms in a cohort of patients with advanced cancer. METHODS: There were 238 patients included in this study. Data from participants in two medicinal cannabis randomised controlled trials were analysed. Patients were aged over 18 years and had advanced cancer. Edmonton Symptom Assessment System, and Depression, Anxiety and Stress Scale (DASS-21) were assessed for all patients at baseline. RESULTS: Moderate-severe depression was reported in 29.8% and moderate-severe anxiety was reported in 47.9% of patients. The emotional subscales of DASS-21 (depression, anxiety, stress) correlated with total symptom distress score (p<0.001) and overall well-being (p<0.001). Depression was correlated with physical symptoms of fatigue, nausea, poor appetite and dyspnoea. Anxiety was correlated with fatigue and dyspnoea. Stress was correlated with fatigue, nausea and dyspnoea. CONCLUSIONS: Depression, anxiety and stress were common in this population. The relationship between physical and psychological well-being is complex. A holistic approach to symptom management is required to improve quality of life in patients with advanced cancer.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.014
Threshold uncertainty score0.873

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 studies0.0000.000
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 head0.040
GPT teacher head0.443
Teacher spread0.403 · 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

Citations15
Published2024
Admission routes1
Has abstractyes

Explore more

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