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Record W3207373488 · doi:10.1188/21.onf.613-622

Engaging Older Adults With Cancer and Their Caregivers to Set Research Priorities Through Cancer and Aging Research Discussion Sessions

2021· article· en· W3207373488 on OpenAlexaff
Kristen R. Haase, Margaret Tompson, Steven Hall, Schroder Sattar, Shahid Ahmed

Bibliographic record

VenueOncology nursing forum · 2021
Typearticle
Languageen
FieldMedicine
TopicFrailty in Older Adults
Canadian institutionsUniversity of SaskatchewanUniversity of British Columbia
Fundersnot available
KeywordsMedicineCancerGerontologySet (abstract data type)MEDLINEFamily medicineInternal medicine

Abstract

fetched live from OpenAlex

PURPOSE: To report on the perspectives of older adults (aged older than 65 years) with cancer and their caregivers who participated in patient-oriented research priority-setting activities called the Cancer and Aging Research Discussion Sessions. PARTICIPANTS & SETTING: 35 older adults and caregivers participated in three public meetings and follow-up interviews. METHODOLOGIC APPROACH: Qualitative descriptive. FINDINGS: There was clear consensus from participants on research priorities related to two key areas. IMPLICATIONS FOR NURSING: Future research should focus on addressing age-related disparities in cancer care communication and support. By capitalizing on older adults' interest in research engagement, effective solutions can be cocreated to improve cancer experiences for older adults and their caregivers.

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)0.066
metaresearch head score (Gemma)0.072
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.066
Threshold uncertainty score0.346

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0660.072
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0090.004
Scholarly communication0.0040.005
Open science0.0020.012
Research integrity0.0030.004
Insufficient payload (model declined to judge)0.0040.001

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 head0.081
GPT teacher head0.454
Teacher spread0.373 · 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 designQualitative
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

Citations11
Published2021
Admission routes1
Has abstractyes

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