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Record W4387966768 · doi:10.1017/s1478951523001530

Assessment of emotional distress in palliative care: Edmonton Symptom Assessment System-revised (ESAS-r) vs Distress Thermometer

2023· article· en· W4387966768 on OpenAlexaboutno aff
Leticia Ascencio Huertas, Silvia Allende‐Pérez, Adriana Peña‐Nieves

Bibliographic record

VenuePalliative & Supportive Care · 2023
Typearticle
Languageen
FieldMedicine
TopicCancer survivorship and care
Canadian institutionsnot available
Fundersnot available
KeywordsMedicinePalliative careSadnessDistressGold standard (test)Family medicineInternal medicineClinical psychologyNursing

Abstract

fetched live from OpenAlex

OBJECTIVES: To evaluate the sensitivity and specificity of the Distress Thermometer (DT) as a screening tool for emotional distress in oncological palliative care patients and to compare the DT with the Edmonton Symptom Assessment System-revised (ESAS-r) and the gold standard to determine the most appropriate assessment method in palliative psychological care. METHODS: Data were collected from psychological screening tests (ESAS-r and DT), and clinical interviews (gold standard) were conducted by a clinical psychologist specialist in palliative oncology from January 2021 to January 2022 in an oncology palliative care service. RESULTS: = 206; 57.9%), 60.4% were married/with a partner, 55.4% had between 6 and 9 years of schooling, and a median age of 57 (range, 46-65) years. The cutoff of the DT was 5, with a sensitivity of 75.88% and specificity of 54.3%. Emotional problems (sadness and nervousness) had a greater area under the curve (AUC) when measured using the DT than the ESAS-r; however, only in the case of the comparative sadness and discouragement was the difference between the AUC marginally significant. SIGNIFICANCE OF RESULTS: The use of the DT as a screening tool in oncological palliative care is more effective in the evaluation of psychological needs than the ESAS-r. The DT, in addition to evaluation by an expert psychologist, allows for a more comprehensive identification of signs and symptoms to yield an accurate mental health diagnosis based on the International Classification of Diseases-11th Revision and/or Diagnostic and Statistical Manual of Mental Disorders-Fifth Edition.

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 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 score0.065
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.025
GPT teacher head0.352
Teacher spread0.327 · 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

Citations3
Published2023
Admission routes1
Has abstractyes

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