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Record W2281873631 · doi:10.1188/12.cjon.625-632

Information Needs of Patients With Melanoma

2012· article· en· W2281873631 on OpenAlexaboutno aff
Silvia Passalacqua, Zorika Christiana Di Rocco, Cristina Di Pietro, A. Mozzetta, Stefano Tabolli, Alessandro Scoppola, Paolo Marchetti, Damiano Abeni

Bibliographic record

VenueClinical journal of oncology nursing · 2012
Typearticle
Languageen
FieldHealth Professions
TopicPatient-Provider Communication in Healthcare
Canadian institutionsnot available
Fundersnot available
KeywordsMedicinePsychosocialMelanomaDiseaseCancerIntensive care medicineClinical PracticeOncologyFamily medicineInternal medicinePsychiatry

Abstract

fetched live from OpenAlex

Evidence continues to suggest that patients with cancer require more information about their disease and its consequences. To evaluate the information needs of patients with advanced melanoma compared to patients with other malignancies, a cross-sectional study was conducted on 221 unselected patients from the oncology department of a dermatologic hospital In Italy. Patients completed the Edmonton Symptom Assessment System and the Need Evaluation Questionnaire, two standardized tools for symptoms and psychosocial needs assessment. Results highlight that patients with advanced melanoma have, in general, a higher need for information compared to patients with other cancers, even if they report fewer symptoms. Future studies on the needs of patients with melanoma may contribute to tailored and more satisfactory patient-centered care. Recommendations for clinical practice include that particular attention should be paid by the oncology team to the need for a strong therapeutic relationship.

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)0.001
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 score0.067
Threshold uncertainty score0.548

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
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 head0.249
GPT teacher head0.522
Teacher spread0.273 · 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

Citations21
Published2012
Admission routes1
Has abstractyes

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