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Record W2042428633 · doi:10.1017/s1478951509990745

Reducing the potential for suffering in older adults with advanced cancer

2010· review· en· W2042428633 on OpenAlexaff
Genevieve Thompson, Harvey Max Chochinov

Bibliographic record

VenuePalliative & Supportive Care · 2010
Typereview
Languageen
FieldMedicine
TopicPatient Dignity and Privacy
Canadian institutionsUniversity of ManitobaCancerCare Manitoba
Fundersnot available
KeywordsDignityGerontologyPalliative carePsychological interventionDistressQuality of life (healthcare)Older peopleCancerPsychological distressMedicinePsychologyEnd-of-life careSocial supportNursingPsychiatryClinical psychologyPsychotherapistMental health

Abstract

fetched live from OpenAlex

OBJECTIVE: To deliver quality care at the end of life, understanding the impact of various changes and life transitions that occur in older age is essential. This review seeks to uncover potential sources of distress in an elder's physical, psychological, social, and spiritual well-being to shed light on the unique challenges and needs facing this age group. METHODS: Papers relating to older adults (aged 65 years and older or a mean age of 65 years and older) with advanced/terminal cancer receiving palliative, hospice, or end-of-life care published after 1998 were reviewed. RESULTS: Older adults with advanced cancer have unique needs related to changes in their physical, psychological, social, and spiritual well-being. Changes in each of these domains offer not only the risk of causing distress but also the potential for growth and development during the final stages of advanced cancer. SIGNIFICANCE OF RESULTS: Being aware of the various changes that occur with aging will help health care professionals tailor interventions to promote dignity-conserving care and greatly reduce the potential for suffering at the end of life.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.002
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.046
GPT teacher head0.380
Teacher spread0.333 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreReview

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

Citations24
Published2010
Admission routes1
Has abstractyes

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