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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 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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.962
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.063
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 teacher head, not a consensus.

Study designOther design
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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