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Record W3208112145 · doi:10.5737/23688076314451456

Standardized versus personalized survivorship care plans for breast cancer survivors: A program evaluation

2021· article· en· W3208112145 on OpenAlexaffvenue
Nicole Rutkowski, Carrie MacDonald-Liska, Kelly-Anne Baines, Vicky Samuel, Cheryl Harris, Sophie Lebel

Bibliographic record

VenueCanadian Oncology Nursing Journal · 2021
Typearticle
Languageen
FieldMedicine
TopicCancer survivorship and care
Canadian institutionsOttawa HospitalUniversity of Ottawa
Fundersnot available
KeywordsSurvivorship curveBreast cancerMedicineStandardized testCancerFamily medicinePersonalized medicineCancer survivorCancer survivorshipOncologyGerontologyPsychologyInternal medicineBioinformatics

Abstract

fetched live from OpenAlex

The Wellness Beyond Cancer Program provides survivorship care plans (SCPs) to cancer survivors, as they transition from cancer centres back to their primary care provider (PCP) upon treatment completion. A program evaluation examined whether standardized SCPs resulted in comparable outcomes on perceived knowledge and patient activation as personalized SCPs. Breast cancer survivors who received either standardized or personalized SCPs completed pre- and post-surveys during their discharge appointment, which included an in-house measure on perceived knowledge, The Perceived Efficacy in Patient-Physician Interactions, and The Patient Activation Measure. Eighty-seven breast cancer survivors completed the surveys (personalized SCP n = 43; standardized SCP n = 44). Standardized SCPs resulted in comparable knowledge and activation outcomes as personalized SCPs. Cost-efficient standardized SCPs may help alleviate human resource constraints and may be considered for further evaluation and implementation in cancer centres.

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)0.007
metaresearch head score (Gemma)0.013
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.008
Threshold uncertainty score0.037

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0070.013
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0050.000

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 head0.063
GPT teacher head0.405
Teacher spread0.342 · 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 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

Citations7
Published2021
Admission routes2
Has abstractyes

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